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Rao S, Verrill C, Cerundolo L, Alham NK, Kaya Z, O'Hanlon M, Hayes A, Lambert A, James M, Tullis IDC, Niederer J, Lovell S, Omer A, Lopez F, Leslie T, Buffa F, Bryant RJ, Lamb AD, Vojnovic B, Wedge DC, Mills IG, Woodcock DJ, Tomlinson I, Hamdy FC. Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole-genome sequencing with histopathological features. Genome Med 2024; 16:35. [PMID: 38374116 PMCID: PMC10877771 DOI: 10.1186/s13073-024-01302-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 02/06/2024] [Indexed: 02/21/2024] Open
Abstract
BACKGROUND Extension of prostate cancer beyond the primary site by local invasion or nodal metastasis is associated with poor prognosis. Despite significant research on tumour evolution in prostate cancer metastasis, the emergence and evolution of cancer clones at this early stage of expansion and spread are poorly understood. We aimed to delineate the routes of evolution and cancer spread within the prostate and to seminal vesicles and lymph nodes, linking these to histological features that are used in diagnostic risk stratification. METHODS We performed whole-genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and lymph nodes of five treatment-naive patients with locally advanced disease. We spatially mapped the clonal composition of cancer across the prostate and the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes in each individual by analysing a total of > 19,000 copy number corrected single nucleotide variants. RESULTS In each patient, we identified sample locations corresponding to the earliest part of the malignancy. In patient 10, we mapped the spread of cancer from the apex of the prostate to the seminal vesicles and identified specific genomic changes associated with the transformation of adenocarcinoma to amphicrine morphology during this spread. Furthermore, we show that the lymph node metastases in this patient arose from specific cancer clones found at the base of the prostate and the seminal vesicles. In patient 15, we observed increased mutational burden, altered mutational signatures and histological changes associated with whole genome duplication. In all patients in whom histological heterogeneity was observed (4/5), we found that the distinct morphologies were located on separate branches of their respective evolutionary trees. CONCLUSIONS Our results link histological transformation with specific genomic alterations and phylogenetic branching. These findings have implications for diagnosis and risk stratification, in addition to providing a rationale for further studies to characterise the genetic changes causally linked to morphological transformation. Our study demonstrates the value of integrating multi-region sequencing with histopathological data to understand tumour evolution and identify mechanisms of prostate cancer spread.
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Affiliation(s)
- Srinivasa Rao
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.
- Botnar Research Centre, Windmill Road, Oxford, OX3 7LD, UK.
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Lucia Cerundolo
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | | | - Zeynep Kaya
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Miriam O'Hanlon
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Alicia Hayes
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Adam Lambert
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Martha James
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | | | - Jane Niederer
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Shelagh Lovell
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Altan Omer
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Francisco Lopez
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Tom Leslie
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | | | - Richard J Bryant
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Alastair D Lamb
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Boris Vojnovic
- Department of Oncology, University of Oxford, Oxford, UK
| | - David C Wedge
- Manchester Cancer Research Centre, University of Manchester, Manchester, UK
| | - Ian G Mills
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Dan J Woodcock
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Ian Tomlinson
- Department of Oncology, University of Oxford, Oxford, UK
| | - Freddie C Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
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2
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Liu JTC, Chow SSL, Colling R, Downes MR, Farré X, Humphrey P, Janowczyk A, Mirtti T, Verrill C, Zlobec I, True LD. Engineering the future of 3D pathology. J Pathol Clin Res 2024; 10:e347. [PMID: 37919231 PMCID: PMC10807588 DOI: 10.1002/cjp2.347] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 10/06/2023] [Accepted: 10/15/2023] [Indexed: 11/04/2023]
Abstract
In recent years, technological advances in tissue preparation, high-throughput volumetric microscopy, and computational infrastructure have enabled rapid developments in nondestructive 3D pathology, in which high-resolution histologic datasets are obtained from thick tissue specimens, such as whole biopsies, without the need for physical sectioning onto glass slides. While 3D pathology generates massive datasets that are attractive for automated computational analysis, there is also a desire to use 3D pathology to improve the visual assessment of tissue histology. In this perspective, we discuss and provide examples of potential advantages of 3D pathology for the visual assessment of clinical specimens and the challenges of dealing with large 3D datasets (of individual or multiple specimens) that pathologists have not been trained to interpret. We discuss the need for artificial intelligence triaging algorithms and explainable analysis methods to assist pathologists or other domain experts in the interpretation of these novel, often complex, large datasets.
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Affiliation(s)
- Jonathan TC Liu
- Department of Mechanical EngineeringUniversity of WashingtonSeattleWAUSA
- Department of Laboratory Medicine & PathologyUniversity of Washington School of MedicineSeattleUSA
- Department of BioengineeringUniversity of WashingtonSeattleUSA
| | - Sarah SL Chow
- Department of Mechanical EngineeringUniversity of WashingtonSeattleWAUSA
| | | | | | | | - Peter Humphrey
- Department of UrologyYale School of MedicineNew HavenCTUSA
| | - Andrew Janowczyk
- Wallace H Coulter Department of Biomedical EngineeringEmory University and Georgia Institute of TechnologyAtlantaGAUSA
- Geneva University HospitalsGenevaSwitzerland
| | - Tuomas Mirtti
- Helsinki University Hospital and University of HelsinkiHelsinkiFinland
- Emory University School of MedicineAtlantaGAUSA
| | - Clare Verrill
- John Radcliffe HospitalUniversity of OxfordOxfordUK
- NIHR Oxford Biomedical Research CentreOxford University Hospitals NHS Foundation TrustOxfordUK
| | - Inti Zlobec
- Institute for Tissue Medicine and PathologyUniversity of BernBernSwitzerland
| | - Lawrence D True
- Department of Laboratory Medicine & PathologyUniversity of Washington School of MedicineSeattleUSA
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3
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Figiel S, Yin W, Doultsinos D, Erickson A, Poulose N, Singh R, Magnussen A, Anbarasan T, Teague R, He M, Lundeberg J, Loda M, Verrill C, Colling R, Gill PS, Bryant RJ, Hamdy FC, Woodcock DJ, Mills IG, Cussenot O, Lamb AD. Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures. Mol Cancer 2023; 22:162. [PMID: 37789377 PMCID: PMC10546768 DOI: 10.1186/s12943-023-01863-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 09/18/2023] [Indexed: 10/05/2023] Open
Abstract
Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx®, Decipher®, Prostadiag®) using a step-wise approach with increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses.
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Affiliation(s)
- Sandy Figiel
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Wencheng Yin
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Dimitrios Doultsinos
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Andrew Erickson
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Ninu Poulose
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Reema Singh
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Anette Magnussen
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Thineskrishna Anbarasan
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Renuka Teague
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Mengxiao He
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Solna, Sweden
| | - Joakim Lundeberg
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Solna, Sweden
| | - Massimo Loda
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Richard Colling
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Pelvender S Gill
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Richard J Bryant
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Freddie C Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Dan J Woodcock
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Ian G Mills
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Olivier Cussenot
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Alastair D Lamb
- Nuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
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4
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Browning L, Winter L, Cooper RA, Ghosh A, Dytor T, Colling R, Fryer E, Rittscher J, Verrill C. Impact of the transition to digital pathology in a clinical setting on histopathologists in training: experiences and perceived challenges within a UK training region. J Clin Pathol 2023; 76:712-718. [PMID: 35906044 PMCID: PMC10511979 DOI: 10.1136/jcp-2022-208416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 07/08/2022] [Indexed: 11/03/2022]
Abstract
AIMS With increasing utility of digital pathology (DP), it is important to consider the experiences of histopathologists in training, particularly in view of the varied access to DP across a training region and the consequent need to remain competent in reporting on glass slides (GS), which is also relevant for the Fellowship of the Royal College of Pathologists part 2 examination. Understanding the impact of DP on training is limited but could aid development of guidance to support the transition. We sought to investigate the perceptions of histopathologists in training around the introduction of DP for clinical diagnosis within a training region, and the potential training benefits and challenges. METHODS An anonymous online survey was circulated to 24 histopathologists in training within a UK training region, including a hospital which has been fully digitised since summer 2020. RESULTS 19 of 24 histopathologists in training responded (79%). The results indicate that DP offers many benefits to training, including ease of access to cases to enhance individual learning and teaching in general. Utilisation of DP for diagnosis appears variable; almost half of the (10 of 19) respondents with DP experience using it only for ancillary purposes such as measurements, reporting varying levels of confidence in using DP clinically. For those yet to undergo the transition, there was a perceived anxiety regarding digital reporting despite experience with DP in other contexts. CONCLUSIONS The survey evidences the need for provision of training and support for histopathologists in training during the transition to DP, and for consideration of their need to maintain competence and confidence with GS reporting.
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Affiliation(s)
- Lisa Browning
- NIHR Oxford Biomedical Research Centre, Oxford, UK
- Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Lucinda Winter
- Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | | | - Abhisek Ghosh
- Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Nuffield Department of Clinical Laboratory Sciences, University of Oxford, Oxford, UK
| | - Thomas Dytor
- Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Richard Colling
- Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Eve Fryer
- Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Jens Rittscher
- NIHR Oxford Biomedical Research Centre, Oxford, UK
- Department of Engineering Science, University of Oxford, Oxford, UK
- Big Data Institute, University of Oxford, Oxford, UK
| | - Clare Verrill
- NIHR Oxford Biomedical Research Centre, Oxford, UK
- Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
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5
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Rao SR, Protheroe A, Cerundolo L, Maldonado-Perez D, Browning L, Lamb AD, Bryant RJ, Mills IG, Woodcock DJ, Hamdy FC, Tomlinson IPM, Verrill C. Genomic Evolution and Transcriptional Changes in the Evolution of Prostate Cancer into Neuroendocrine and Ductal Carcinoma Types. Int J Mol Sci 2023; 24:12722. [PMID: 37628903 PMCID: PMC10454593 DOI: 10.3390/ijms241612722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/08/2023] [Accepted: 08/09/2023] [Indexed: 08/27/2023] Open
Abstract
Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuroendocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease, and the former often arises on a background of androgen deprivation therapy, although it can also arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tissue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with three longitudinal samples over 5 years. Case 2 was a single time point after the development of treatment-related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all samples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, and 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small-cell neuroendocrine and ductal prostatic carcinoma can have a common ancestry. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.
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Affiliation(s)
- Srinivasa R. Rao
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK; (S.R.R.)
| | - Andrew Protheroe
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK; (S.R.R.)
| | - Lucia Cerundolo
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK; (S.R.R.)
| | | | - Lisa Browning
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK; (S.R.R.)
| | - Alastair D. Lamb
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK; (S.R.R.)
| | - Richard J. Bryant
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK; (S.R.R.)
| | - Ian G. Mills
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK; (S.R.R.)
| | - Dan J. Woodcock
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK; (S.R.R.)
| | - Freddie C. Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK; (S.R.R.)
| | | | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK; (S.R.R.)
- NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford OX3 9DU, UK
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6
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Kelleher M, Colling R, Browning L, Roskell D, Roberts-Gant S, Shah KA, Hemsworth H, White K, Rees G, Dolton M, Soares MF, Verrill C. Department Wide Validation in Digital Pathology-Experience from an Academic Teaching Hospital Using the UK Royal College of Pathologists' Guidance. Diagnostics (Basel) 2023; 13:2144. [PMID: 37443538 DOI: 10.3390/diagnostics13132144] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 06/08/2023] [Accepted: 06/14/2023] [Indexed: 07/15/2023] Open
Abstract
AIM we describe our experience of validating departmental pathologists for digital pathology reporting, based on the UK Royal College of Pathologists (RCPath) "Best Practice Recommendations for Implementing Digital Pathology (DP)," at a large academic teaching hospital that scans 100% of its surgical workload. We focus on Stage 2 of validation (prospective experience) prior to full validation sign-off. METHODS AND RESULTS twenty histopathologists completed Stage 1 of the validation process and subsequently completed Stage 2 validation, prospectively reporting a total of 3777 cases covering eight specialities. All cases were initially viewed on digital whole slide images (WSI) with relevant parameters checked on glass slides, and discordances were reconciled before the case was signed out. Pathologists kept an electronic log of the cases, the preferred reporting modality used, and their experiences. At the end of each validation, a summary was compiled and reviewed with a mentor. This was submitted to the DP Steering Group who assessed the scope of cases and experience before sign-off for full validation. A total of 1.3% (49/3777) of the cases had a discordance between WSI and glass slides. A total of 61% (30/49) of the discordances were categorised as a minor error in a supplementary parameter without clinical impact. The most common reasons for diagnostic discordances across specialities included identification and grading of dysplasia, assessment of tumour invasion, identification of small prognostic or diagnostic objects, interpretation of immunohistochemistry/special stains, and mitotic count assessment. Pathologists showed similar mean diagnostic confidences (on Likert scale from 0 to 7) with a mean of 6.8 on digital and 6.9 on glass slide reporting. CONCLUSION we describe one of the first real-world experiences of a department-wide effort to implement, validate, and roll out digital pathology reporting by applying the RCPath Recommendations for Implementing DP. We have shown a very low rate of discordance between WSI and glass slides.
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Affiliation(s)
- Mai Kelleher
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Richard Colling
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
- Nuffield Department of Surgical Sciences, Oxford University, Oxford OX3 9DU, UK
| | - Lisa Browning
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Derek Roskell
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Sharon Roberts-Gant
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Ketan A Shah
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Helen Hemsworth
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Kieron White
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Gabrielle Rees
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Monica Dolton
- Nuffield Department of Surgical Sciences, Oxford University, Oxford OX3 9DU, UK
| | - Maria Fernanda Soares
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Clare Verrill
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
- Nuffield Department of Surgical Sciences, Oxford University, Oxford OX3 9DU, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
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7
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Bryant RJ, Yamamoto H, Eddy B, Kommu S, Narahari K, Omer A, Leslie T, Catto JWF, Rosario DJ, Good DW, Gray R, Liew MPC, Lopez JF, Campbell T, Reynard JM, Tuck S, Barber VS, Medeghri N, Davies L, Parkes M, Hewitt A, Landeiro F, Wolstenholme J, Macpherson R, Verrill C, Marian IR, Williams R, Hamdy FC, Lamb AD. Protocol for the TRANSLATE prospective, multicentre, randomised clinical trial of prostate biopsy technique. BJU Int 2023; 131:694-704. [PMID: 36695816 DOI: 10.1111/bju.15978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
OBJECTIVES Primary objectives: to determine whether local anaesthetic transperineal prostate (LATP) biopsy improves the detection of clinically significant prostate cancer (csPCa), defined as International Society of Urological Pathology (ISUP) Grade Group ≥2 disease (i.e., any Gleason pattern 4 disease), compared to transrectal ultrasound-guided (TRUS) prostate biopsy, in biopsy-naïve men undergoing biopsy based on suspicion of csPCa. SECONDARY OBJECTIVES to compare (i) infection rates, (ii) health-related quality of life, (iii) patient-reported procedure tolerability, (iv) patient-reported biopsy-related complications (including bleeding, bruising, pain, loss of erectile function), (v) number of subsequent prostate biopsy procedures required, (vi) cost-effectiveness, (vii) other histological parameters, and (viii) burden and rate of detection of clinically insignificant PCa (ISUP Grade Group 1 disease) in men undergoing these two types of prostate biopsy. PATIENTS AND METHODS The TRANSLATE trial is a UK-wide, multicentre, randomised clinical trial that meets the criteria for level-one evidence in diagnostic test evaluation. TRANSLATE is investigating whether LATP biopsy leads to a higher rate of detection of csPCa compared to TRUS prostate biopsy. Both biopsies are being performed with an average of 12 systematic cores in six sectors (depending on prostate size), plus three to five target cores per multiparametric/bi-parametric magnetic resonance imaging lesion. LATP biopsy is performed using an ultrasound probe-mounted needle-guidance device (either the 'Precision-Point' or BK UA1232 system). TRUS biopsy is performed according to each hospital's standard practice. The study is 90% powered to detect a 10% difference (LATP biopsy hypothesised at 55% detection rate for csPCa vs 45% for TRUS biopsy). A total of 1042 biopsy-naïve men referred with suspected PCa need to be recruited. CONCLUSIONS This trial will provide robust prospective data to determine the diagnostic ability of LATP biopsy vs TRUS biopsy in the primary diagnostic setting.
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Affiliation(s)
- Richard J Bryant
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Hide Yamamoto
- Department of Urology, Maidstone and Tunbridge Wells NHS Trust, Maidstone Hospital, Maidstone, UK
| | - Ben Eddy
- Department of Urology, East Kent Hospitals University NHS Foundation Trust, Kent and Canterbury Hospital, Canterbury, UK
| | - Sashi Kommu
- Department of Urology, East Kent Hospitals University NHS Foundation Trust, Kent and Canterbury Hospital, Canterbury, UK
| | - Krishna Narahari
- Department of Urology, Cardiff and Vale University Health Board, University Hospital of Wales, Cardiff, UK
| | - Altan Omer
- Department of Urology, University Hospitals Coventry and Warwickshire NHS Trust, University Hospital, Coventry, UK
| | - Tom Leslie
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
- Department of Urology, Milton Keynes University Hospital NHS Foundation Trust, Milton Keynes Hospital, Milton Keynes, UK
| | - James W F Catto
- Academic Urology Unit, University of Sheffield and Department of Urology, Sheffield University Hospitals NHS Foundation Trust, Royal Hallamshire Hospital, Sheffield, UK
| | - Derek J Rosario
- Academic Urology Unit, University of Sheffield and Department of Urology, Sheffield University Hospitals NHS Foundation Trust, Royal Hallamshire Hospital, Sheffield, UK
| | - Daniel W Good
- Department of Urology, NHS Lothian, Western General Hospital, Edinburgh, UK
| | - Rob Gray
- Department of Urology, Buckinghamshire Healthcare NHS Trust, Wycombe Hospital, High Wycombe, UK
| | - Matthew P C Liew
- Department of Urology, Wrightington, Wigan and Leigh Teaching Hospitals NHS Foundation Trust, Wigan, UK
| | - J Francisco Lopez
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
| | - Teresa Campbell
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
| | - John M Reynard
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
| | - Steve Tuck
- Oxfordshire Prostate Cancer Support Group, Oxford, UK
| | - Vicki S Barber
- Oxford Clinical Trials Research Unit, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Nadjat Medeghri
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Lucy Davies
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Matthew Parkes
- Oxford Clinical Trials Research Unit, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Aimi Hewitt
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Filipa Landeiro
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jane Wolstenholme
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ruth Macpherson
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Ioana R Marian
- Oxford Clinical Trials Research Unit, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Roxanne Williams
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Freddie C Hamdy
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Alastair D Lamb
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford, UK
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
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Abd Hamid M, Colin-york H, Khalid-alham N, Browne M, Cerundolo L, Chen J, Yao X, Rosendo-machado S, Waugh C, Maldonado-perez D, Bowes E, Verrill C, Cerundolo V, Conlon CP, Fritzsche M, Peng Y, Dong T. Supplementary Movie Titles and Legends from Self-Maintaining CD103<sup>+</sup> Cancer-Specific T Cells Are Highly Energetic with Rapid Cytotoxic and Effector Responses.. [DOI: 10.1158/2326-6066.22543759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
<p>Titles and Legends for Movies 1-4</p>
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Lam BM, Verrill C. Clinical Significance of Tumour-Infiltrating B Lymphocytes (TIL-Bs) in Breast Cancer: A Systematic Literature Review. Cancers (Basel) 2023; 15:cancers15041164. [PMID: 36831506 PMCID: PMC9953777 DOI: 10.3390/cancers15041164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/03/2023] [Accepted: 02/09/2023] [Indexed: 02/17/2023] Open
Abstract
Although T lymphocytes have been considered the major players in the tumour microenvironment to induce tumour regression and contribute to anti-tumour immunity, much less is known about the role of tumour-infiltrating B lymphocytes (TIL-Bs) in solid malignancies, particularly in breast cancer, which has been regarded as heterogeneous and much less immunogenic compared to other common tumours like melanoma, colorectal cancer and non-small cell lung cancer. Such paucity of research could translate to limited opportunities for this most common type of cancer in the UK to join the immunotherapy efforts in this era of precision medicine. Here, we provide a systematic literature review assessing the clinical significance of TIL-Bs in breast cancer. Articles published between January 2000 and April 2022 were retrieved via an electronic search of two databases (PubMed and Embase) and screened against pre-specified eligibility criteria. The majority of studies reported favourable prognostic and predictive roles of TIL-Bs, indicating that they could have a profound impact on the clinical outcome of breast cancer. Further studies are, however, needed to better define the functional role of B cell subpopulations and to discover ways to harness this intrinsic mechanism in the fight against breast cancer.
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Affiliation(s)
- Brian M. Lam
- Department of Oncology, University of Oxford, Oxford OX3 9DU, UK
- Correspondence:
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK
- Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford OX3 9DU, UK
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK
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Gerstung M, Jolly C, Leshchiner I, Dentro SC, Gonzalez S, Rosebrock D, Mitchell TJ, Rubanova Y, Anur P, Yu K, Tarabichi M, Deshwar A, Wintersinger J, Kleinheinz K, Vázquez-García I, Haase K, Jerman L, Sengupta S, Macintyre G, Malikic S, Donmez N, Livitz DG, Cmero M, Demeulemeester J, Schumacher S, Fan Y, Yao X, Lee J, Schlesner M, Boutros PC, Bowtell DD, Zhu H, Getz G, Imielinski M, Beroukhim R, Sahinalp SC, Ji Y, Peifer M, Markowetz F, Mustonen V, Yuan K, Wang W, Morris QD, Spellman PT, Wedge DC, Van Loo P, Tarabichi M, Wintersinger J, Deshwar AG, Yu K, Gonzalez S, Rubanova Y, Macintyre G, Adams DJ, Anur P, Beroukhim R, Boutros PC, Bowtell DD, Campbell PJ, Cao S, Christie EL, Cmero M, Cun Y, Dawson KJ, Demeulemeester J, Donmez N, Drews RM, Eils R, Fan Y, Fittall M, Garsed DW, Getz G, Ha G, Imielinski M, Jerman L, Ji Y, Kleinheinz K, Lee J, Lee-Six H, Livitz DG, Malikic S, Markowetz F, Martincorena I, Mitchell TJ, Mustonen V, Oesper L, Peifer M, Peto M, Raphael BJ, Rosebrock D, Sahinalp SC, Salcedo A, Schlesner M, Schumacher S, Sengupta S, Shi R, Shin SJ, Spiro O, Pitkänen E, Pivot X, Piñeiro-Yáñez E, Planko L, Plass C, Polak P, Pons T, Popescu I, Potapova O, Prasad A, Stein LD, Preston SR, Prinz M, Pritchard AL, Prokopec SD, Provenzano E, Puente XS, Puig S, Puiggròs M, Pulido-Tamayo S, Pupo GM, Vázquez-García I, Purdie CA, Quinn MC, Rabionet R, Rader JS, Radlwimmer B, Radovic P, Raeder B, Raine KM, Ramakrishna M, Ramakrishnan K, Vembu S, Ramalingam S, Raphael BJ, Rathmell WK, Rausch T, Reifenberger G, Reimand J, Reis-Filho J, Reuter V, Reyes-Salazar I, Reyna MA, Wheeler DA, Reynolds SM, Rheinbay E, Riazalhosseini Y, Richardson AL, Richter J, Ringel M, Ringnér M, Rino Y, Rippe K, Roach J, Yang TP, Roberts LR, Roberts ND, Roberts SA, Robertson AG, Robertson AJ, Rodriguez JB, Rodriguez-Martin B, Rodríguez-González FG, Roehrl MHA, Rohde M, Yao X, Rokutan H, Romieu G, Rooman I, Roques T, Rosebrock D, Rosenberg M, Rosenstiel PC, Rosenwald A, Rowe EW, Royo R, Yuan K, Rozen SG, Rubanova Y, Rubin MA, Rubio-Perez C, Rudneva VA, Rusev BC, Ruzzenente A, Rätsch G, Sabarinathan R, Sabelnykova VY, Zhu H, Sadeghi S, Sahinalp SC, Saini N, Saito-Adachi M, Saksena G, Salcedo A, Salgado R, Salichos L, Sallari R, Saller C, Wang W, Salvia R, Sam M, Samra JS, Sanchez-Vega F, Sander C, Sanders G, Sarin R, Sarrafi I, Sasaki-Oku A, Sauer T, Morris QD, Sauter G, Saw RPM, Scardoni M, Scarlett CJ, Scarpa A, Scelo G, Schadendorf D, Schein JE, Schilhabel MB, Schlesner M, Spellman PT, Schlomm T, Schmidt HK, Schramm SJ, Schreiber S, Schultz N, Schumacher SE, Schwarz RF, Scolyer RA, Scott D, Scully R, Wedge DC, Seethala R, Segre AV, Selander I, Semple CA, Senbabaoglu Y, Sengupta S, Sereni E, Serra S, Sgroi DC, Shackleton M, Van Loo P, Shah NC, Shahabi S, Shang CA, Shang P, Shapira O, Shelton T, Shen C, Shen H, Shepherd R, Shi R, Spellman PT, Shi Y, Shiah YJ, Shibata T, Shih J, Shimizu E, Shimizu K, Shin SJ, Shiraishi Y, Shmaya T, Shmulevich I, Wedge DC, Shorser SI, Short C, Shrestha R, Shringarpure SS, Shriver C, Shuai S, Sidiropoulos N, Siebert R, Sieuwerts AM, Sieverling L, Van Loo P, Signoretti S, Sikora KO, Simbolo M, Simon R, Simons JV, Simpson JT, Simpson PT, Singer S, Sinnott-Armstrong N, Sipahimalani P, Aaltonen LA, Skelly TJ, Smid M, Smith J, Smith-McCune K, Socci ND, Sofia HJ, Soloway MG, Song L, Sood AK, Sothi S, Abascal F, Sotiriou C, Soulette CM, Span PN, Spellman PT, Sperandio N, Spillane AJ, Spiro O, Spring J, Staaf J, Stadler PF, Abeshouse A, Staib P, Stark SG, Stebbings L, Stefánsson ÓA, Stegle O, Stein LD, Stenhouse A, Stewart C, Stilgenbauer S, Stobbe MD, Aburatani H, Stratton MR, Stretch JR, Struck AJ, Stuart JM, Stunnenberg HG, Su H, Su X, Sun RX, Sungalee S, Susak H, Adams DJ, Suzuki A, Sweep F, Szczepanowski M, Sültmann H, Yugawa T, Tam A, Tamborero D, Tan BKT, Tan D, Tan P, Agrawal N, Tanaka H, Taniguchi H, Tanskanen TJ, Tarabichi M, Tarnuzzer R, Tarpey P, Taschuk ML, Tatsuno K, Tavaré S, Taylor DF, Ahn KS, Taylor-Weiner A, 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Yuen D, Yung CK, Zaikova O, Zamora J, Zapatka M, Zenklusen JC, Ammerpohl O, Zenz T, Zeps N, Zhang CZ, Zhang F, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Anderson MJ, Zhang X, Zhang X, Zhang Y, Zhang Z, Zhao Z, Zheng L, Zheng X, Zhou W, Zhou Y, Zhu B, Ang Y, Zhu H, Zhu J, Zhu S, Zou L, Zou X, deFazio A, van As N, van Deurzen CHM, van de Vijver MJ, van’t Veer L, Antonello D, von Mering C, Anur P, Aparicio S, Appelbaum EL, Arai Y, Aretz A, Arihiro K, Ariizumi SI, Armenia J, Arnould L, Asa S, Assenov Y, Atwal G, Aukema S, Auman JT, Aure MRR, Awadalla P, Aymerich M, Bader GD, Baez-Ortega A, Bailey MH, Bailey PJ, Balasundaram M, Balu S, Bandopadhayay P, Banks RE, Barbi S, Barbour AP, Barenboim J, Barnholtz-Sloan J, Barr H, Barrera E, Bartlett J, Bartolome J, Bassi C, Bathe OF, Baumhoer D, Bavi P, Baylin SB, Bazant W, Beardsmore D, Beck TA, Behjati S, Behren A, Niu B, Bell C, Beltran S, Benz C, Berchuck A, Bergmann AK, Bergstrom EN, Berman BP, Berney DM, Bernhart SH, Beroukhim R, Berrios M, Bersani S, Bertl J, Betancourt M, Bhandari V, Bhosle SG, Biankin AV, Bieg M, Bigner D, Binder H, Birney E, Birrer M, Biswas NK, Bjerkehagen B, Bodenheimer T, Boice L, Bonizzato G, De Bono JS, Boot A, Bootwalla MS, Borg A, Borkhardt A, Boroevich KA, Borozan I, Borst C, Bosenberg M, Bosio M, Boultwood J, Bourque G, Boutros PC, Bova GS, Bowen DT, Bowlby R, Bowtell DDL, Boyault S, Boyce R, Boyd J, Brazma A, Brennan P, Brewer DS, Brinkman AB, Bristow RG, Broaddus RR, Brock JE, Brock M, Broeks A, Brooks AN, Brooks D, Brors B, Brunak S, Bruxner TJC, Bruzos AL, Buchanan A, Buchhalter I, Buchholz C, Bullman S, Burke H, Burkhardt B, Burns KH, Busanovich J, Bustamante CD, Butler AP, Butte AJ, Byrne NJ, Børresen-Dale AL, Caesar-Johnson SJ, Cafferkey A, Cahill D, Calabrese C, Caldas C, Calvo F, Camacho N, Campbell PJ, Campo E, Cantù C, Cao S, Carey TE, Carlevaro-Fita J, Carlsen R, Cataldo I, Cazzola M, Cebon J, Cerfolio R, Chadwick DE, Chakravarty D, Chalmers D, Chan CWY, Chan K, 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Doddapaneni H, Donmez N, Dow MT, Drapkin R, Drechsel O, Drews RM, Serge S, Dudderidge T, Dueso-Barroso A, Dunford AJ, Dunn M, Dursi LJ, Duthie FR, Dutton-Regester K, Eagles J, Easton DF, Edmonds S, Edwards PA, Edwards SE, Eeles RA, Ehinger A, Eils J, Eils R, El-Naggar A, Eldridge M, Ellrott K, Erkek S, Escaramis G, Espiritu SMG, Estivill X, Etemadmoghadam D, Eyfjord JE, Faltas BM, Fan D, Fan Y, Faquin WC, Farcas C, Fassan M, Fatima A, Favero F, Fayzullaev N, Felau I, Fereday S, Ferguson ML, Ferretti V, Feuerbach L, Field MA, Fink JL, Finocchiaro G, Fisher C, Fittall MW, Fitzgerald A, Fitzgerald RC, Flanagan AM, Fleshner NE, Flicek P, Foekens JA, Fong KM, Fonseca NA, Foster CS, Fox NS, Fraser M, Frazer S, Frenkel-Morgenstern M, Friedman W, Frigola J, Fronick CC, Fujimoto A, Fujita M, Fukayama M, Fulton LA, Fulton RS, Furuta M, Futreal PA, Füllgrabe A, Gabriel SB, Gallinger S, Gambacorti-Passerini C, Gao J, Gao S, Garraway L, Garred Ø, Garrison E, Garsed DW, Gehlenborg N, Gelpi JLL, 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Hilmarsdottir H, Hinton J, Hirano S, Hiraoka N, Hoadley KA, Hobolth A, Hodzic E, Hoell JI, Hoffmann S, Hofmann O, Holbrook A, Holik AZ, Hollingsworth MA, Holmes O, Holt RA, Hong C, Hong EP, Hong JH, Hooijer GK, Hornshøj H, Hosoda F, Hou Y, Hovestadt V, Howat W, Hoyle AP, Hruban RH, Hu J, Hu T, Hua X, Huang KL, Huang M, Huang MN, Huang V, Huang Y, Huber W, Hudson TJ, Hummel M, Hung JA, Huntsman D, Hupp TR, Huse J, Huska MR, Hutter B, Hutter CM, Hübschmann D, Iacobuzio-Donahue CA, Imbusch CD, Imielinski M, Imoto S, Isaacs WB, Isaev K, Ishikawa S, Iskar M, Islam SMA, Ittmann M, Ivkovic S, Izarzugaza JMG, Jacquemier J, Jakrot V, Jamieson NB, Jang GH, Jang SJ, Jayaseelan JC, Jayasinghe R, Jefferys SR, Jegalian K, Jennings JL, Jeon SH, Jerman L, Ji Y, Jiao W, Johansson PA, Johns AL, Johns J, Johnson R, Johnson TA, Jolly C, Joly Y, Jonasson JG, Jones CD, Jones DR, Jones DTW, Jones N, Jones SJM, Jonkers J, Ju YS, Juhl H, Jung J, Juul M, Juul RI, Juul S, Jäger N, Kabbe R, Kahles A, Kahraman A, Kaiser VB, Kakavand H, Kalimuthu S, von Kalle C, Kang KJ, Karaszi K, Karlan B, Karlić R, Karsch D, Kasaian K, Kassahn KS, Katai H, Kato M, Katoh H, Kawakami Y, Kay JD, Kazakoff SH, Kazanov MD, Keays M, Kebebew E, Kefford RF, Kellis M, Kench JG, Kennedy CJ, Kerssemakers JNA, Khoo D, Khoo V, Khuntikeo N, Khurana E, Kilpinen H, Kim HK, Kim HL, Kim HY, Kim H, Kim J, Kim J, Kim JK, Kim Y, King TA, Klapper W, Kleinheinz K, Klimczak LJ, Knappskog S, Kneba M, Knoppers BM, Koh Y, Komorowski J, Komura D, Komura M, Kong G, Kool M, Korbel JO, Korchina V, Korshunov A, Koscher M, Koster R, Kote-Jarai Z, Koures A, Kovacevic M, Kremeyer B, Kretzmer H, Kreuz M, Krishnamurthy S, Kube D, Kumar K, Kumar P, Kumar S, Kumar Y, Kundra R, Kübler K, Küppers R, Lagergren J, Lai PH, Laird PW, Lakhani SR, Lalansingh CM, Lalonde E, Lamaze FC, Lambert A, Lander E, Landgraf P, Landoni L, Langerød A, Lanzós A, Larsimont D, Larsson E, Lathrop M, Lau LMS, Lawerenz C, Lawlor RT, Lawrence MS, Lazar AJ, Lazic AM, Le X, Lee D, Lee D, Lee EA, Lee HJ, Lee JJK, Lee JY, Lee J, Lee MTM, Lee-Six H, Lehmann KV, Lehrach H, Lenze D, Leonard CR, Leongamornlert DA, Leshchiner I, Letourneau L, Letunic I, Levine DA, Lewis L, Ley T, Li C, Li CH, Li HI, Li J, Li L, Li S, Li S, Li X, Li X, Li X, Li Y, Liang H, Liang SB, Lichter P, Lin P, Lin Z, Linehan WM, Lingjærde OC, Liu D, Liu EM, Liu FFF, Liu F, Liu J, Liu X, Livingstone J, Livitz D, Livni N, Lochovsky L, Loeffler M, Long GV, Lopez-Guillermo A, Lou S, Louis DN, Lovat LB, Lu Y, Lu YJ, Lu Y, Luchini C, Lungu I, Luo X, Luxton HJ, Lynch AG, Lype L, López C, López-Otín C, Ma EZ, Ma Y, MacGrogan G, MacRae S, Macintyre G, Madsen T, Maejima K, Mafficini A, Maglinte DT, Maitra A, Majumder PP, Malcovati L, Malikic S, Malleo G, Mann GJ, Mantovani-Löffler L, Marchal K, Marchegiani G, Mardis ER, Margolin AA, Marin MG, Markowetz F, Markowski J, Marks J, Marques-Bonet T, Marra MA, Marsden L, Martens JWM, Martin S, Martin-Subero JI, Martincorena I, Martinez-Fundichely A, Maruvka YE, Mashl RJ, Massie CE, Matthew TJ, Matthews L, Mayer E, Mayes S, Mayo M, Mbabaali F, McCune K, McDermott U, McGillivray PD, McLellan MD, McPherson JD, McPherson JR, McPherson TA, Meier SR, Meng A, Meng S, Menzies A, Merrett ND, Merson S, Meyerson M, Meyerson W, Mieczkowski PA, Mihaiescu GL, Mijalkovic S, Mikkelsen T, Milella M, Mileshkin L, Miller CA, Miller DK, Miller JK, Mills GB, Milovanovic A, Minner S, Miotto M, Arnau GM, Mirabello L, Mitchell C, Mitchell TJ, Miyano S, Miyoshi N, Mizuno S, Molnár-Gábor F, Moore MJ, Moore RA, Morganella S, Morris QD, Morrison C, Mose LE, Moser CD, Muiños F, Mularoni L, Mungall AJ, Mungall K, Musgrove EA, Mustonen V, Mutch D, Muyas F, Muzny DM, Muñoz A, Myers J, Myklebost O, Möller P, Nagae G, Nagrial AM, Nahal-Bose HK, Nakagama H, Nakagawa H, Nakamura H, Nakamura T, Nakano K, Nandi T, Nangalia J, Nastic M, Navarro A, Navarro FCP, Neal DE, Nettekoven G, Newell F, Newhouse SJ, Newton Y, Ng AWT, Ng A, Nicholson J, Nicol D, Nie Y, Nielsen GP, Nielsen MM, Nik-Zainal S, Noble MS, Nones K, Northcott PA, Notta F, O’Connor BD, O’Donnell P, O’Donovan M, O’Meara S, O’Neill BP, O’Neill JR, Ocana D, Ochoa A, Oesper L, Ogden C, Ohdan H, Ohi K, Ohno-Machado L, Oien KA, Ojesina AI, Ojima H, Okusaka T, Omberg L, Ong CK, Ossowski S, Ott G, Ouellette BFF, P’ng C, Paczkowska M, Paiella S, Pairojkul C, Pajic M, Pan-Hammarström Q, Papaemmanuil E, Papatheodorou I, Paramasivam N, Park JW, Park JW, Park K, Park K, Park PJ, Parker JS, Parsons SL, Pass H, Pasternack D, Pastore A, Patch AM, Pauporté I, Pea A, Pearson JV, Pedamallu CS, Pedersen JS, Pederzoli P, Peifer M, Pennell NA, Perou CM, Perry MD, Petersen GM, Peto M, Petrelli N, Petryszak R, Pfister SM, Phillips M, Pich O, Pickett HA, Pihl TD, Pillay N, Pinder S, Pinese M, Pinho AV. Author Correction: The evolutionary history of 2,658 cancers. Nature 2023; 614:E42. [PMID: 36697833 PMCID: PMC9931577 DOI: 10.1038/s41586-022-05601-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Moritz Gerstung
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK. .,European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany. .,Wellcome Sanger Institute, Cambridge, UK.
| | - Clemency Jolly
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Ignaty Leshchiner
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Stefan C. Dentro
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK ,grid.4991.50000 0004 1936 8948Big Data Institute, University of Oxford, Oxford, UK
| | - Santiago Gonzalez
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Daniel Rosebrock
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Thomas J. Mitchell
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934University of Cambridge, Cambridge, UK
| | - Yulia Rubanova
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Pavana Anur
- grid.5288.70000 0000 9758 5690Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR USA
| | - Kaixian Yu
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Maxime Tarabichi
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Amit Deshwar
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Jeff Wintersinger
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Kortine Kleinheinz
- grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.7700.00000 0001 2190 4373Heidelberg University, Heidelberg, Germany
| | - Ignacio Vázquez-García
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934University of Cambridge, Cambridge, UK
| | - Kerstin Haase
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Lara Jerman
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK ,grid.8954.00000 0001 0721 6013University of Ljubljana, Ljubljana, Slovenia
| | - Subhajit Sengupta
- grid.240372.00000 0004 0400 4439NorthShore University HealthSystem, Evanston, IL USA
| | - Geoff Macintyre
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Salem Malikic
- grid.61971.380000 0004 1936 7494Simon Fraser University, Burnaby, British Columbia Canada ,grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada
| | - Nilgun Donmez
- grid.61971.380000 0004 1936 7494Simon Fraser University, Burnaby, British Columbia Canada ,grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada
| | - Dimitri G. Livitz
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Marek Cmero
- grid.1008.90000 0001 2179 088XUniversity of Melbourne, Melbourne, Victoria Australia ,grid.1042.70000 0004 0432 4889Walter and Eliza Hall Institute, Melbourne, Victoria Australia
| | - Jonas Demeulemeester
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK ,grid.5596.f0000 0001 0668 7884University of Leuven, Leuven, Belgium
| | - Steven Schumacher
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Yu Fan
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Xiaotong Yao
- grid.5386.8000000041936877XWeill Cornell Medicine, New York, NY USA ,grid.429884.b0000 0004 1791 0895New York Genome Center, New York, NY USA
| | - Juhee Lee
- grid.205975.c0000 0001 0740 6917University of California Santa Cruz, Santa Cruz, CA USA
| | - Matthias Schlesner
- grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Paul C. Boutros
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.419890.d0000 0004 0626 690XOntario Institute for Cancer Research, Toronto, Ontario Canada ,grid.19006.3e0000 0000 9632 6718University of California, Los Angeles, CA USA
| | - David D. Bowtell
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, Melbourne, Victoria Australia
| | - Hongtu Zhu
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Gad Getz
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA USA ,grid.32224.350000 0004 0386 9924Department of Pathology, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Marcin Imielinski
- grid.5386.8000000041936877XWeill Cornell Medicine, New York, NY USA ,grid.429884.b0000 0004 1791 0895New York Genome Center, New York, NY USA
| | - Rameen Beroukhim
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA
| | - S. Cenk Sahinalp
- grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada ,grid.411377.70000 0001 0790 959XIndiana University, Bloomington, IN USA
| | - Yuan Ji
- grid.240372.00000 0004 0400 4439NorthShore University HealthSystem, Evanston, IL USA ,grid.170205.10000 0004 1936 7822The University of Chicago, Chicago, IL USA
| | - Martin Peifer
- grid.6190.e0000 0000 8580 3777University of Cologne, Cologne, Germany
| | - Florian Markowetz
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Ville Mustonen
- grid.7737.40000 0004 0410 2071University of Helsinki, Helsinki, Finland
| | - Ke Yuan
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK ,grid.8756.c0000 0001 2193 314XUniversity of Glasgow, Glasgow, UK
| | - Wenyi Wang
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Quaid D. Morris
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | | | - Paul T. Spellman
- grid.5288.70000 0000 9758 5690Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR USA
| | - David C. Wedge
- grid.4991.50000 0004 1936 8948Big Data Institute, University of Oxford, Oxford, UK ,grid.454382.c0000 0004 7871 7212Oxford NIHR Biomedical Research Centre, Oxford, UK
| | - Peter Van Loo
- The Francis Crick Institute, London, UK. .,University of Leuven, Leuven, Belgium.
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Calabrese C, Davidson NR, Demircioğlu D, Fonseca NA, He Y, Kahles A, Lehmann KV, Liu F, Shiraishi Y, Soulette CM, Urban L, Greger L, Li S, Liu D, Perry MD, Xiang Q, Zhang F, Zhang J, Bailey P, Erkek S, Hoadley KA, Hou Y, Huska MR, Kilpinen H, Korbel JO, Marin MG, Markowski J, Nandi T, Pan-Hammarström Q, Pedamallu CS, Siebert R, Stark SG, Su H, Tan P, Waszak SM, Yung C, Zhu S, Awadalla P, Creighton CJ, Meyerson M, Ouellette BFF, Wu K, Yang H, Brazma A, Brooks AN, Göke J, Rätsch G, Schwarz RF, Stegle O, Zhang Z, Wu K, Yang H, Fonseca NA, Kahles A, Lehmann KV, Urban L, Soulette CM, Shiraishi Y, Liu F, He Y, Demircioğlu D, Davidson NR, Calabrese C, Zhang J, Perry MD, Xiang Q, Greger L, Li S, Liu D, Stark SG, Zhang F, Amin SB, Bailey P, Chateigner A, Cortés-Ciriano I, Craft B, Erkek S, Frenkel-Morgenstern M, Goldman M, Hoadley KA, Hou Y, Huska MR, Khurana E, Kilpinen H, Korbel JO, Lamaze FC, Li C, Li X, Li X, Liu X, Marin MG, Markowski J, Nandi T, Nielsen MM, Ojesina AI, Pan-Hammarström Q, Park PJ, Pedamallu CS, Pedersen JS, Pederzoli P, Peifer M, Pennell NA, Perou CM, Perry MD, Petersen GM, Peto M, Petrelli N, Pedamallu CS, Petryszak R, Pfister SM, Phillips M, Pich O, Pickett HA, Pihl TD, Pillay N, Pinder S, Pinese M, Pinho AV, Pedersen JS, Pitkänen E, Pivot X, Piñeiro-Yáñez E, Planko L, Plass C, Polak P, Pons T, Popescu I, Potapova O, Prasad A, Siebert R, Preston SR, Prinz M, Pritchard AL, Prokopec SD, Provenzano E, Puente XS, Puig S, Puiggròs M, Pulido-Tamayo S, Pupo GM, Su H, Purdie CA, Quinn MC, Rabionet R, Rader JS, Radlwimmer B, Radovic P, Raeder B, Raine KM, Ramakrishna M, Ramakrishnan K, Tan P, Ramalingam S, Raphael BJ, Rathmell WK, Rausch T, Reifenberger G, Reimand J, Reis-Filho J, Reuter V, Reyes-Salazar I, Reyna MA, Teh BT, Reynolds SM, Rheinbay E, Riazalhosseini Y, Richardson AL, Richter J, Ringel M, Ringnér M, Rino Y, Rippe K, Roach J, Wang J, Roberts LR, Roberts ND, Roberts SA, Robertson AG, Robertson AJ, Rodriguez JB, Rodriguez-Martin B, Rodríguez-González FG, Roehrl MHA, Rohde M, Waszak SM, Rokutan H, Romieu G, Rooman I, Roques T, Rosebrock D, Rosenberg M, Rosenstiel PC, Rosenwald A, Rowe EW, Royo R, Xiong H, Rozen SG, Rubanova Y, Rubin MA, Rubio-Perez C, Rudneva VA, Rusev BC, Ruzzenente A, Rätsch G, Sabarinathan R, Sabelnykova VY, Yakneen S, Sadeghi S, Sahinalp SC, Saini N, Saito-Adachi M, Saksena G, Salcedo A, Salgado R, Salichos L, Sallari R, Saller C, Ye C, Salvia R, Sam M, Samra JS, Sanchez-Vega F, Sander C, Sanders G, Sarin R, Sarrafi I, Sasaki-Oku A, Sauer T, Yung C, Sauter G, Saw RPM, Scardoni M, Scarlett CJ, Scarpa A, Scelo G, Schadendorf D, Schein JE, Schilhabel MB, Schlesner M, Zhang X, Schlomm T, Schmidt HK, Schramm SJ, Schreiber S, Schultz N, Schumacher SE, Schwarz RF, Scolyer RA, Scott D, Scully R, Zheng L, Seethala R, Segre AV, Selander I, Semple CA, Senbabaoglu Y, Sengupta S, Sereni E, Serra S, Sgroi DC, Shackleton M, Zhu J, Shah NC, Shahabi S, Shang CA, Shang P, Shapira O, Shelton T, Shen C, Shen H, Shepherd R, Shi R, Zhu S, Shi Y, Shiah YJ, Shibata T, Shih J, Shimizu E, Shimizu K, Shin SJ, Shiraishi Y, Shmaya T, Shmulevich I, Awadalla P, Shorser SI, Short C, Shrestha R, Shringarpure SS, Shriver C, Shuai S, Sidiropoulos N, Siebert R, Sieuwerts AM, Sieverling L, Creighton CJ, Signoretti S, Sikora KO, Simbolo M, Simon R, Simons JV, Simpson JT, Simpson PT, Singer S, Sinnott-Armstrong N, Sipahimalani P, Meyerson M, Skelly TJ, Smid M, Smith J, Smith-McCune K, Socci ND, Sofia HJ, Soloway MG, Song L, Sood AK, Sothi S, Ouellette BFF, Sotiriou C, Soulette CM, Span PN, Spellman PT, Sperandio N, Spillane AJ, Spiro O, Spring J, Staaf J, Stadler PF, Wu K, Staib P, Stark SG, Stebbings L, Stefánsson ÓA, Stegle O, Stein LD, Stenhouse A, Stewart C, Stilgenbauer S, Stobbe MD, Yang H, Stratton MR, Stretch JR, Struck AJ, Stuart JM, Stunnenberg HG, Su H, Su X, Sun RX, Sungalee S, Susak H, Göke J, Suzuki A, Sweep F, Szczepanowski M, Sültmann H, Yugawa T, Tam A, Tamborero D, Tan BKT, Tan D, Tan P, Schwarz RF, Tanaka H, Taniguchi H, Tanskanen TJ, Tarabichi M, Tarnuzzer R, Tarpey P, Taschuk ML, Tatsuno K, Tavaré S, Taylor DF, Stegle O, Taylor-Weiner A, Teague JW, Teh BT, Tembe V, Temes J, Thai K, Thayer SP, Thiessen N, Thomas G, Thomas S, Zhang Z, Thompson A, Thompson AM, Thompson JFF, Thompson RH, Thorne H, Thorne LB, Thorogood A, Tiao G, Tijanic N, Timms LE, Brazma A, Tirabosco R, Tojo M, Tommasi S, Toon CW, Toprak UH, Torrents D, Tortora G, Tost J, Totoki Y, Townend D, Rätsch G, Traficante N, Treilleux I, Trotta JR, Trümper LHP, Tsao M, Tsunoda T, Tubio JMC, Tucker O, Turkington R, Turner DJ, Brooks AN, Tutt A, Ueno M, Ueno NT, Umbricht C, Umer HM, Underwood TJ, Urban L, Urushidate T, Ushiku T, Uusküla-Reimand L, Brazma A, Valencia A, Van Den Berg DJ, Van Laere S, Van Loo P, Van Meir EG, Van den Eynden GG, Van der Kwast T, Vasudev N, Vazquez M, Vedururu R, Brooks AN, Veluvolu U, Vembu S, Verbeke LPC, Vermeulen P, Verrill C, Viari A, Vicente D, Vicentini C, VijayRaghavan K, Viksna J, Göke J, Vilain RE, Villasante I, Vincent-Salomon A, Visakorpi T, Voet D, Vyas P, Vázquez-García I, Waddell NM, Waddell N, Wadelius C, Rätsch G, Wadi L, Wagener R, Wala JA, Wang J, Wang J, Wang L, Wang Q, Wang W, Wang Y, Wang Z, Schwarz RF, Waring PM, Warnatz HJ, Warrell J, Warren AY, Waszak SM, Wedge DC, Weichenhan D, Weinberger P, Weinstein JN, Weischenfeldt J, Stegle O, Weisenberger DJ, Welch I, Wendl MC, Werner J, Whalley JP, Wheeler DA, Whitaker HC, Wigle D, Wilkerson MD, Williams A, Zhang Z, Wilmott JS, Wilson GW, Wilson JM, Wilson RK, Winterhoff B, Wintersinger JA, Wiznerowicz M, Wolf S, Wong BH, Wong T, Aaltonen LA, Wong W, Woo Y, Wood S, Wouters BG, Wright AJ, Wright DW, Wright MH, Wu CL, Wu DY, Wu G, Abascal F, Wu J, Wu K, Wu Y, Wu Z, Xi L, Xia T, Xiang Q, Xiao X, Xing R, Xiong H, Abeshouse A, Xu Q, Xu Y, Xue H, Yachida S, Yakneen S, Yamaguchi R, Yamaguchi TN, Yamamoto M, Yamamoto S, Yamaue H, Aburatani H, Yang F, Yang H, Yang JY, Yang L, Yang L, Yang S, Yang TP, Yang Y, Yao X, Yaspo ML, Adams DJ, Yates L, Yau C, Ye C, Ye K, Yellapantula VD, Yoon CJ, Yoon SS, Yousif F, Yu J, Yu K, Agrawal N, Yu W, Yu Y, Yuan K, Yuan Y, Yuen D, Yung CK, Zaikova O, Zamora J, Zapatka M, Zenklusen JC, Ahn KS, Zenz T, Zeps N, Zhang CZ, Zhang F, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Ahn SM, Zhang X, Zhang X, Zhang Y, Zhang Z, Zhao Z, Zheng L, Zheng X, Zhou W, Zhou Y, Zhu B, Aikata H, Zhu H, Zhu J, Zhu S, Zou L, Zou X, deFazio A, van As N, van Deurzen CHM, van de Vijver MJ, van’t Veer L, Akbani R, von Mering C, Akdemir KC, Al-Ahmadie H, Al-Sedairy ST, Al-Shahrour F, Alawi M, Albert M, Aldape K, Alexandrov LB, Ally A, Alsop K, Alvarez EG, Amary F, Amin SB, Aminou B, Ammerpohl O, Anderson MJ, Ang Y, Antonello D, Anur P, Aparicio S, Appelbaum EL, Arai Y, Aretz A, Arihiro K, Ariizumi SI, Armenia J, Arnould L, Asa S, Assenov Y, Atwal G, Aukema S, Auman JT, Aure MRR, Awadalla P, Aymerich M, Bader GD, Baez-Ortega A, Bailey MH, Bailey PJ, Balasundaram M, Balu S, Bandopadhayay P, Banks RE, Barbi S, Barbour AP, Barenboim J, Barnholtz-Sloan J, Barr H, Barrera E, Bartlett J, Bartolome J, Bassi C, Bathe OF, Baumhoer D, Bavi P, Baylin SB, Bazant W, Beardsmore D, Beck TA, Behjati S, Behren A, Niu B, Bell C, Beltran S, Benz C, Berchuck A, Bergmann AK, Bergstrom EN, Berman BP, Berney DM, Bernhart SH, Beroukhim R, Berrios M, Bersani S, Bertl J, Betancourt M, Bhandari V, Bhosle SG, Biankin AV, Bieg M, Bigner D, Binder H, Birney E, Birrer M, Biswas NK, Bjerkehagen B, Bodenheimer T, Boice L, Bonizzato G, De Bono JS, Boot A, Bootwalla MS, Borg A, Borkhardt A, Boroevich KA, Borozan I, Borst C, Bosenberg M, Bosio M, Boultwood J, Bourque G, Boutros PC, Bova GS, Bowen DT, Bowlby R, Bowtell DDL, Boyault S, Boyce R, Boyd J, Brazma A, Brennan P, Brewer DS, Brinkman AB, Bristow RG, Broaddus RR, Brock JE, Brock M, Broeks A, Brooks AN, Brooks D, Brors B, Brunak S, Bruxner TJC, Bruzos AL, Buchanan A, Buchhalter I, Buchholz C, Bullman S, Burke H, Burkhardt B, Burns KH, Busanovich J, Bustamante CD, Butler AP, Butte AJ, Byrne NJ, Børresen-Dale AL, Caesar-Johnson SJ, Cafferkey A, Cahill D, Calabrese C, Caldas C, Calvo F, Camacho N, Campbell PJ, Campo E, Cantù C, Cao S, Carey TE, Carlevaro-Fita J, Carlsen R, Cataldo I, Cazzola M, Cebon J, Cerfolio R, Chadwick DE, Chakravarty D, Chalmers D, Chan CWY, Chan K, Chan-Seng-Yue M, Chandan VS, Chang DK, Chanock SJ, Chantrill LA, Chateigner A, Chatterjee N, Chayama K, Chen HW, Chen J, Chen K, Chen Y, Chen Z, Cherniack AD, Chien J, Chiew YE, Chin SF, Cho J, Cho S, Choi JK, Choi W, Chomienne C, Chong Z, Choo SP, Chou A, Christ AN, Christie EL, Chuah E, Cibulskis C, Cibulskis K, Cingarlini S, Clapham P, Claviez A, Cleary S, Cloonan N, Cmero M, Collins CC, Connor AA, Cooke SL, Cooper CS, Cope L, Corbo V, Cordes MG, Cordner SM, Cortés-Ciriano I, Covington K, Cowin PA, Craft B, Craft D, Creighton CJ, Cun Y, Curley E, Cutcutache I, Czajka K, Czerniak B, Dagg RA, Danilova L, Davi MV, Davidson NR, Davies H, Davis IJ, 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Harliwong I, Harmanci AO, Harrington E, Hasegawa T, Haussler D, Hawkins S, Hayami S, Hayashi S, Hayes DN, Hayes SJ, Hayward NK, Hazell S, He Y, Heath AP, Heath SC, Hedley D, Hegde AM, Heiman DI, Heinold MC, Heins Z, Heisler LE, Hellstrom-Lindberg E, Helmy M, Heo SG, Hepperla AJ, Heredia-Genestar JM, Herrmann C, Hersey P, Hess JM, Hilmarsdottir H, Hinton J, Hirano S, Hiraoka N, Hoadley KA, Hobolth A, Hodzic E, Hoell JI, Hoffmann S, Hofmann O, Holbrook A, Holik AZ, Hollingsworth MA, Holmes O, Holt RA, Hong C, Hong EP, Hong JH, Hooijer GK, Hornshøj H, Hosoda F, Hou Y, Hovestadt V, Howat W, Hoyle AP, Hruban RH, Hu J, Hu T, Hua X, Huang KL, Huang M, Huang MN, Huang V, Huang Y, Huber W, Hudson TJ, Hummel M, Hung JA, Huntsman D, Hupp TR, Huse J, Huska MR, Hutter B, Hutter CM, Hübschmann D, Iacobuzio-Donahue CA, Imbusch CD, Imielinski M, Imoto S, Isaacs WB, Isaev K, Ishikawa S, Iskar M, Islam SMA, Ittmann M, Ivkovic S, Izarzugaza JMG, Jacquemier J, Jakrot V, Jamieson NB, Jang GH, Jang SJ, Jayaseelan JC, Jayasinghe R, Jefferys SR, Jegalian K, Jennings JL, Jeon SH, Jerman L, Ji Y, Jiao W, Johansson PA, Johns AL, Johns J, Johnson R, Johnson TA, Jolly C, Joly Y, Jonasson JG, Jones CD, Jones DR, Jones DTW, Jones N, Jones SJM, Jonkers J, Ju YS, Juhl H, Jung J, Juul M, Juul RI, Juul S, Jäger N, Kabbe R, Kahles A, Kahraman A, Kaiser VB, Kakavand H, Kalimuthu S, von Kalle C, Kang KJ, Karaszi K, Karlan B, Karlić R, Karsch D, Kasaian K, Kassahn KS, Katai H, Kato M, Katoh H, Kawakami Y, Kay JD, Kazakoff SH, Kazanov MD, Keays M, Kebebew E, Kefford RF, Kellis M, Kench JG, Kennedy CJ, Kerssemakers JNA, Khoo D, Khoo V, Khuntikeo N, Khurana E, Kilpinen H, Kim HK, Kim HL, Kim HY, Kim H, Kim J, Kim J, Kim JK, Kim Y, King TA, Klapper W, Kleinheinz K, Klimczak LJ, Knappskog S, Kneba M, Knoppers BM, Koh Y, Komorowski J, Komura D, Komura M, Kong G, Kool M, Korbel JO, Korchina V, Korshunov A, Koscher M, Koster R, Kote-Jarai Z, Koures A, Kovacevic M, Kremeyer B, Kretzmer H, Kreuz M, Krishnamurthy S, Kube D, Kumar K, Kumar P, Kumar S, Kumar Y, Kundra R, Kübler K, Küppers R, Lagergren J, Lai PH, Laird PW, Lakhani SR, Lalansingh CM, Lalonde E, Lamaze FC, Lambert A, Lander E, Landgraf P, Landoni L, Langerød A, Lanzós A, Larsimont D, Larsson E, Lathrop M, Lau LMS, Lawerenz C, Lawlor RT, Lawrence MS, Lazar AJ, Lazic AM, Le X, Lee D, Lee D, Lee EA, Lee HJ, Lee JJK, Lee JY, Lee J, Lee MTM, Lee-Six H, Lehmann KV, Lehrach H, Lenze D, Leonard CR, Leongamornlert DA, Leshchiner I, Letourneau L, Letunic I, Levine DA, Lewis L, Ley T, Li C, Li CH, Li HI, Li J, Li L, Li S, Li S, Li X, Li X, Li X, Li Y, Liang H, Liang SB, Lichter P, Lin P, Lin Z, Linehan WM, Lingjærde OC, Liu D, Liu EM, Liu FFF, Liu F, Liu J, Liu X, Livingstone J, Livitz D, Livni N, Lochovsky L, Loeffler M, Long GV, Lopez-Guillermo A, Lou S, Louis DN, Lovat LB, Lu Y, Lu YJ, Lu Y, Luchini C, Lungu I, Luo X, Luxton HJ, Lynch AG, Lype L, López C, López-Otín C, Ma EZ, Ma Y, MacGrogan G, MacRae S, Macintyre G, Madsen T, 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Mustonen V, Mutch D, Muyas F, Muzny DM, Muñoz A, Myers J, Myklebost O, Möller P, Nagae G, Nagrial AM, Nahal-Bose HK, Nakagama H, Nakagawa H, Nakamura H, Nakamura T, Nakano K, Nandi T, Nangalia J, Nastic M, Navarro A, Navarro FCP, Neal DE, Nettekoven G, Newell F, Newhouse SJ, Newton Y, Ng AWT, Ng A, Nicholson J, Nicol D, Nie Y, Nielsen GP, Nielsen MM, Nik-Zainal S, Noble MS, Nones K, Northcott PA, Notta F, O’Connor BD, O’Donnell P, O’Donovan M, O’Meara S, O’Neill BP, O’Neill JR, Ocana D, Ochoa A, Oesper L, Ogden C, Ohdan H, Ohi K, Ohno-Machado L, Oien KA, Ojesina AI, Ojima H, Okusaka T, Omberg L, Ong CK, Ossowski S, Ott G, Ouellette BFF, P’ng C, Paczkowska M, Paiella S, Pairojkul C, Pajic M, Pan-Hammarström Q, Papaemmanuil E, Papatheodorou I, Paramasivam N, Park JW, Park JW, Park K, Park K, Park PJ, Parker JS, Parsons SL, Pass H, Pasternack D, Pastore A, Patch AM, Pauporté I, Pea A, Pearson JV. Author Correction: Genomic basis for RNA alterations in cancer. Nature 2023; 614:E37. [PMID: 36697831 PMCID: PMC9931574 DOI: 10.1038/s41586-022-05596-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
| | - Claudia Calabrese
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Natalie R. Davidson
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.5386.8000000041936877XWeill Cornell Medical College, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Deniz Demircioğlu
- grid.4280.e0000 0001 2180 6431National University of Singapore, Singapore, Singapore ,grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore
| | - Nuno A. Fonseca
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Yao He
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - André Kahles
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Kjong-Van Lehmann
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Fenglin Liu
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - Yuichi Shiraishi
- grid.26999.3d0000 0001 2151 536XThe University of Tokyo, Minato-ku, Japan
| | - Cameron M. Soulette
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA
| | - Lara Urban
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Liliana Greger
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Siliang Li
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Dongbing Liu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Marc D. Perry
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada ,grid.266102.10000 0001 2297 6811University of California, San Francisco, San Francisco, CA USA
| | - Qian Xiang
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Fan Zhang
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - Junjun Zhang
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Peter Bailey
- grid.8756.c0000 0001 2193 314XUniversity of Glasgow, Glasgow, UK
| | - Serap Erkek
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Katherine A. Hoadley
- grid.10698.360000000122483208The University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Yong Hou
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Matthew R. Huska
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Helena Kilpinen
- grid.83440.3b0000000121901201University College London, London, UK
| | - Jan O. Korbel
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Maximillian G. Marin
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA
| | - Julia Markowski
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Tannistha Nandi
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore
| | - Qiang Pan-Hammarström
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.4714.60000 0004 1937 0626Karolinska Institutet, Stockholm, Sweden
| | - Chandra Sekhar Pedamallu
- grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Reiner Siebert
- grid.410712.10000 0004 0473 882XUlm University and Ulm University Medical Center, Ulm, Germany
| | - Stefan G. Stark
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Hong Su
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Patrick Tan
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore ,grid.428397.30000 0004 0385 0924Duke-NUS Medical School, Singapore, Singapore
| | - Sebastian M. Waszak
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Christina Yung
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Shida Zhu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Philip Awadalla
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada ,grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada
| | - Chad J. Creighton
- grid.39382.330000 0001 2160 926XBaylor College of Medicine, Houston, TX USA
| | - Matthew Meyerson
- grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | | | - Kui Wu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Huanming Yang
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China
| | | | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
| | - Angela N. Brooks
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA ,grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA
| | - Jonathan Göke
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore ,grid.410724.40000 0004 0620 9745National Cancer Centre Singapore, Singapore, Singapore
| | - Gunnar Rätsch
- ETH Zurich, Zurich, Switzerland. .,Memorial Sloan Kettering Cancer Center, New York, NY, USA. .,Weill Cornell Medical College, New York, NY, USA. .,SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,University Hospital Zurich, Zurich, Switzerland.
| | - Roland F. Schwarz
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), partner site Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oliver Stegle
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Zemin Zhang
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
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12
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Browning L, White K, Siiankoski D, Colling R, Roskell D, Fryer E, Hemsworth H, Roberts-Gant S, Roelofsen R, Rittscher J, Verrill C. RFID analysis of the complexity of cellular pathology workflow—An opportunity for digital pathology. Front Med (Lausanne) 2022; 9:933933. [PMID: 35979219 PMCID: PMC9377528 DOI: 10.3389/fmed.2022.933933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 07/07/2022] [Indexed: 12/02/2022] Open
Abstract
Digital pathology (DP) offers potential for time efficiency gains over an analog workflow however, to date, evidence supporting this claim is relatively lacking. Studies available concentrate on specific workflow points such as diagnostic reporting time, rather than overall efficiencies in slide logistics that might be expected. This is in part a result of the complexity and variation in analog working, and the challenge therefore in capturing this. We have utilized RFID technology to conduct a novel study capturing the movement of diagnostic cases within the analog pathway in a large teaching hospital setting, thus providing benchmark data for potential efficiency gains with DP. This technology overcomes the need to manually record data items and has facilitated the capture of both the physical journey of a case and the time associated with relevant components of the analog pathway predicted to be redundant in the digital setting. RFID tracking of 1,173 surgical pathology cases and over 30 staff in an analog cellular pathology workflow illustrates the complexity of the physical movement of slides within the department, which impacts on case traceability within the system. Detailed analysis of over 400 case journeys highlights redundant periods created by batching of slides at workflow points, including potentially 2–3 h for a case to become available for reporting after release from the lab, and variable lag-times prior to collection for reporting, and provides an illustration of patterns of lab and pathologist working within the analog setting. This study supports the challenge in evidencing efficiency gains to be anticipated with DP in the context of the variation and complexity of the analog pathway, but also evidences the efficiency gains that may be expected through a greater understanding of patterns of working and movement of cases. Such data may benefit other departments building a business case for DP.
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Affiliation(s)
- Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, United Kingdom
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
- *Correspondence: Lisa Browning
| | - Kieron White
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, United Kingdom
| | - Darrin Siiankoski
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, United Kingdom
| | - Richard Colling
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, United Kingdom
- Nuffield Department of Surgical Sciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Derek Roskell
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, United Kingdom
| | - Eve Fryer
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, United Kingdom
| | - Helen Hemsworth
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, United Kingdom
| | - Sharon Roberts-Gant
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, United Kingdom
| | - Ruud Roelofsen
- Philips Digital and Computational Pathology, Precision Diagnosis Solutions, Best, Netherlands
| | - Jens Rittscher
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Clare Verrill
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, United Kingdom
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
- Nuffield Department of Surgical Sciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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13
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Martin NG, Malacrino S, Wojciechowska M, Campo L, Jones H, Wedge DC, Holmes C, Sirinukunwattana K, Sailem H, Verrill C, Rittscher J. A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples. Annu Int Conf IEEE Eng Med Biol Soc 2022; 2022:3063-3067. [PMID: 36085678 DOI: 10.1109/embc48229.2022.9871251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Multiplexed immunofluorescence provides an un-precedented opportunity for studying specific cell-to-cell and cell microenvironment interactions. We employ graph neural networks to combine features obtained from tissue morphology with measurements of protein expression to profile the tumour microenvironment associated with different tumour stages. Our framework presents a new approach to analysing and processing these complex multi-dimensional datasets that overcomes some of the key challenges in analysing these data and opens up the opportunity to abstract biologically meaningful interactions.
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14
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Jewsbury R, Pell R, Bhalerao A, Raza SEA, Wilkins A, James ND, Verrill C, Snead D, Rajpoot N. Digital score of lymphocytic infiltration in tumor-associated stroma in relation to overall survival in bladder cancer. J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.16_suppl.4576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
4576 Background: Bladder Urothelial Carcinoma (BLCA) is the most common type of bladder cancer and the sixth most frequent cancer in the US. High numbers of lymphocytes colocated with tumour-associated stromal (TAS) tissue has demonstrated prognostic significance for overall survival in multiple cancers. Our goal in this study was to explore the prognostic significance of an automated score to quantify the colocalisation of lymphocytes and TAS for overall survival (OS) in BLCA patients from Haematoxylin & Eosin (H&E) stained Whole Slide Images (WSIs). Methods: Two cohorts of BLCA patients were included in this study. From the UK, a cohort of 67 BLCA patients constituted cohort A. We also evaluated our method on The Cancer Genome Atlas (TCGA) bladder cancer cohort of 453 cases, which we refer to as cohort B. We developed a two-stage method for digital quantification of lymphocytic infiltrates in TAS. First, we employed an AI algorithm to recognise and classify different regions as areas of high concentration of tumour, lymphocytes and stroma for each WSI creating a segmentation map of the different tissue types. For patients with multiple WSIs, we used the slide with the highest percentage of tumour to predict survival. This algorithm had been pre-trained on a cohort of Oral cancer and was fine-tuned using annotations from 4 BLCA WSIs, 3 from cohort A and 1 from cohort B. These WSIs were excluded from the final survival analysis. Using the segmentation maps, a statistical measure for the colocalisation of TAS and lymphocytes termed the tumour-associated stroma infiltrating lymphocytes or (TASIL) score was computed. Finally, for each cohort, data was right-censored at 10 years and the digital BLCA-TASIL (BT) score’s prognostic significance for OS was investigated by fitting a Kaplan-Meier estimator and Cox proportional hazard (PH) analysis, stratifying patients into two groups based on the BT score. In each cohort, two thirds of the data was used as the discovery set to determine the best cut-off for the TASIL Score and the remaining third was used as the validation set. Results: Our classification algorithm achieved high average F1-score of 0.88 on a held-out set of unseen data for the classification of tumour, lymphocytic and stromal regions. In cohort A, higher BT score was strongly associated with better OS ( P= 0.00906) on the unseen validation data. This significant association was also found in the validation data of cohort B ( P< 0.001). Using the BT score as the only covariate, a Cox PH model for the validation data resulted in a C-index of 0.73 for cohort A and 0.57 for cohort B, respectively. Conclusions: The digital BT score showed significant prognostic value for overall survival in both BLCA cohorts, reinforcing the findings of prior work. We intend to further validate these findings on another cohort. To the best of our knowledge, this is the first attempt to predict survival solely from H&E slides in BLCA.
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Affiliation(s)
| | - Robert Pell
- University of Oxford, Oxford, United Kingdom
| | | | | | - Anna Wilkins
- The Institute of Cancer Research & The Crick Institute, London, United Kingdom
| | | | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - David Snead
- University Hospitals Coventry and Warwickshire, Coventry, United Kingdom
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15
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Rakovic K, Colling R, Browning L, Dolton M, Horton MR, Protheroe A, Lamb AD, Bryant RJ, Scheffer R, Crofts J, Stanislaus E, Verrill C. The Use of Digital Pathology and Artificial Intelligence in Histopathological Diagnostic Assessment of Prostate Cancer: A Survey of Prostate Cancer UK Supporters. Diagnostics (Basel) 2022; 12:1225. [PMID: 35626380 PMCID: PMC9141178 DOI: 10.3390/diagnostics12051225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 05/09/2022] [Accepted: 05/11/2022] [Indexed: 12/03/2022] Open
Abstract
There has been particular interest in the deployment of digital pathology (DP) and artificial intelligence (AI) in the diagnosis of prostate cancer, but little is known about the views of the public on their use. Prostate Cancer UK supporters were invited to an online survey which included quantitative and qualitative questions exploring views on the use of DP and AI in histopathological assessment. A total of 1276 responses to the survey were analysed (response rate 12.5%). Most respondents were supportive of DP (87%, 1113/1276) and of testing AI in clinical practice as a diagnostic adjunct (83%, 1058/1276). Respondents saw DP as potentially increasing workflow efficiency, facilitating research, education/training and fostering clinical discussions between clinician and patient. Some respondents raised concerns regarding data security, reliability and the need for human oversight. Among those who were unsure about AI, information was requested regarding its performance and others wanted to defer the decision to use it to an expert. Although most are in favour of its use, some are unsure, and their concerns could be addressed with more information or better communication. A small minority (<1%) are not in favour of the testing of the use of AI in histopathology for reasons which are not easily addressed.
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Affiliation(s)
- Kai Rakovic
- Institute of Cancer Sciences, University of Glasgow, Switchback Road, Glasgow G61 1QH, UK
- Department of Pathology, Queen Elizabeth University Hospital, Govan Road, Glasgow G51 4TF, UK
| | - Richard Colling
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (R.C.); (L.B.); (C.V.)
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (M.D.); (A.D.L.); (R.J.B.); (R.S.); (J.C.); (E.S.)
| | - Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (R.C.); (L.B.); (C.V.)
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK
| | - Monica Dolton
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (M.D.); (A.D.L.); (R.J.B.); (R.S.); (J.C.); (E.S.)
| | | | - Andrew Protheroe
- Department of Oncology, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ, UK;
- Oxford Cancer & Haematology Centre, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford OX3 7LE, UK
| | - Alastair D. Lamb
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (M.D.); (A.D.L.); (R.J.B.); (R.S.); (J.C.); (E.S.)
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford OX3 7LE, UK
| | - Richard J. Bryant
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (M.D.); (A.D.L.); (R.J.B.); (R.S.); (J.C.); (E.S.)
- Department of Urology, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford OX3 7LE, UK
| | - Richard Scheffer
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (M.D.); (A.D.L.); (R.J.B.); (R.S.); (J.C.); (E.S.)
| | - James Crofts
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (M.D.); (A.D.L.); (R.J.B.); (R.S.); (J.C.); (E.S.)
| | - Ewart Stanislaus
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (M.D.); (A.D.L.); (R.J.B.); (R.S.); (J.C.); (E.S.)
| | - Clare Verrill
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (R.C.); (L.B.); (C.V.)
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK; (M.D.); (A.D.L.); (R.J.B.); (R.S.); (J.C.); (E.S.)
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headley Way, Oxford OX3 9DU, UK
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16
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Sorell T, Rajpoot N, Verrill C. Ethical issues in computational pathology. J Med Ethics 2022; 48:278-284. [PMID: 33658334 DOI: 10.1136/medethics-2020-107024] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 02/02/2021] [Accepted: 02/05/2021] [Indexed: 06/12/2023]
Abstract
This paper explores ethical issues raised by whole slide image-based computational pathology. After briefly giving examples drawn from some recent literature of advances in this field, we consider some ethical problems it might be thought to pose. These arise from (1) the tension between artificial intelligence (AI) research-with its hunger for more and more data-and the default preference in data ethics and data protection law for the minimisation of personal data collection and processing; (2) the fact that computational pathology lends itself to kinds of data fusion that go against data ethics norms and some norms of biobanking; (3) the fact that AI methods are esoteric and produce results that are sometimes unexplainable (the so-called 'black box'problem) and (4) the fact that computational pathology is particularly dependent on scanning technology manufacturers with interests of their own in profit-making from data collection. We shall suggest that most of these issues are resolvable.
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Affiliation(s)
- Tom Sorell
- PAIS, University of Warwick, Coventry, UK
| | - Nasir Rajpoot
- Computer Science, University of Warwick, Coventry, UK
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, Oxford University, Oxford, UK
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17
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Haghighat M, Browning L, Sirinukunwattana K, Malacrino S, Khalid Alham N, Colling R, Cui Y, Rakha E, Hamdy FC, Verrill C, Rittscher J. Automated quality assessment of large digitised histology cohorts by artificial intelligence. Sci Rep 2022; 12:5002. [PMID: 35322056 PMCID: PMC8943120 DOI: 10.1038/s41598-022-08351-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 03/03/2022] [Indexed: 02/07/2023] Open
Abstract
Research using whole slide images (WSIs) of histopathology slides has increased exponentially over recent years. Glass slides from retrospective cohorts, some with patient follow-up data are digitised for the development and validation of artificial intelligence (AI) tools. Such resources, therefore, become very important, with the need to ensure that their quality is of the standard necessary for downstream AI development. However, manual quality control of large cohorts of WSIs by visual assessment is unfeasible, and whilst quality control AI algorithms exist, these focus on bespoke aspects of image quality, e.g. focus, or use traditional machine-learning methods, which are unable to classify the range of potential image artefacts that should be considered. In this study, we have trained and validated a multi-task deep neural network to automate the process of quality control of a large retrospective cohort of prostate cases from which glass slides have been scanned several years after production, to determine both the usability of the images at the diagnostic level (considered in this study to be the minimal standard for research) and the common image artefacts present. Using a two-layer approach, quality overlays of WSIs were generated from a quality assessment (QA) undertaken at patch-level at \documentclass[12pt]{minimal}
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\begin{document}$$5\times$$\end{document}5× magnification. From these quality overlays the slide-level quality scores were predicted and then compared to those generated by three specialist urological pathologists, with a Pearson correlation of 0.89 for overall ‘usability’ (at a diagnostic level), and 0.87 and 0.82 for focus and H&E staining quality scores respectively. To demonstrate its wider potential utility, we subsequently applied our QA pipeline to the TCGA prostate cancer cohort and to a colorectal cancer cohort, for comparison. Our model, designated as PathProfiler, indicates comparable predicted usability of images from the cohorts assessed (86–90% of WSIs predicted to be usable), and perhaps more significantly is able to predict WSIs that could benefit from an intervention such as re-scanning or re-staining for quality improvement. We have shown in this study that AI can be used to automate the process of quality control of large retrospective WSI cohorts to maximise their utility for research.
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Affiliation(s)
- Maryam Haghighat
- Department of Engineering Science, Institute of Biomedical Engineering (IBME), University of Oxford, Oxford, UK. .,CSIRO, Brisbane, QLD, Australia.
| | - Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK
| | - Korsuk Sirinukunwattana
- Department of Engineering Science, Institute of Biomedical Engineering (IBME), University of Oxford, Oxford, UK
| | - Stefano Malacrino
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Nasullah Khalid Alham
- Department of Engineering Science, Institute of Biomedical Engineering (IBME), University of Oxford, Oxford, UK
| | - Richard Colling
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK.,Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Ying Cui
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Emad Rakha
- School of Medicine, University of Nottingham, Nottingham, UK
| | - Freddie C Hamdy
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK.,Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Clare Verrill
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK.,Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Jens Rittscher
- Department of Engineering Science, Institute of Biomedical Engineering (IBME), University of Oxford, Oxford, UK. .,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK.
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18
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Coulter C, McKay F, Hallowell N, Browning L, Colling R, Macklin P, Sorell T, Aslam M, Bryson G, Treanor D, Verrill C. Understanding the ethical and legal considerations of Digital Pathology. J Pathol Clin Res 2022; 8:101-115. [PMID: 34796679 PMCID: PMC8822384 DOI: 10.1002/cjp2.251] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 09/12/2021] [Accepted: 10/12/2021] [Indexed: 12/21/2022]
Abstract
Digital Pathology (DP) is a platform which has the potential to develop a truly integrated and global pathology community. The generation of DP data at scale creates novel challenges for the histopathology community in managing, processing, and governing the use of these data. The current understanding of, and confidence in, the legal and ethical aspects of DP by pathologists is unknown. We developed an electronic survey (e-survey), comprising 22 questions, with input from the Royal College of Pathologists (RCPath) Digital Pathology Working Group. The e-survey was circulated via e-mail and social media (Twitter) through the RCPath Digital Pathology Working Group network, RCPath Trainee Committee network, the Pathology image data Lake for Analytics, Knowledge and Education (PathLAKE) digital pathology consortium, National Pathology Imaging Co-operative (NPIC), local contacts, and to the membership of both The Pathological Society of Great Britain and Ireland and the British Division of the International Academy of Pathology (BDIAP). Between 14 July 2020 and 6 September 2020, we collected 198 responses representing a cross section of histopathologists, including individuals with experience of DP research. We ascertained that, in the UK, DP is being used for diagnosis, research, and teaching, and that the platform is enabling data sharing. Our survey demonstrated that there is often a lack of confidence and understanding of the key issues of consent, legislation, and ethical guidelines. Of 198 respondents, 82 (41%) did not know when the use of digital scanned slide images would fall under the relevant legislation and 93 (47%) were 'Not confident at all' in their interpretation of consent for scanned slide images in research. With increasing uptake of DP, a working knowledge of these areas is essential but histopathologists often express a lack of confidence in these topics. The need for specific training in these areas is highlighted by the findings of this study.
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Affiliation(s)
- Cheryl Coulter
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK.,Nuffield Division of Clinical Laboratory Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Francis McKay
- The Wellcome Centre for Ethics and Humanities and the Ethox Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Nina Hallowell
- The Wellcome Centre for Ethics and Humanities and the Ethox Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Richard Colling
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK.,Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Philip Macklin
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Tom Sorell
- Department of Politics and International Studies, University of Warwick, Coventry, UK
| | - Muhammad Aslam
- Department of Histopathology, Glangwilli Hospital, Hywel Dda University Health Board, Carmarthen, Wales, UK
| | - Gareth Bryson
- Department of Pathology, Queen Elizabeth University Hospital, NHS Greater Glasgow and Clyde, Glasgow, Scotland, UK
| | - Darren Treanor
- Department of Pathology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Clare Verrill
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK.,Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
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19
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Atallah NM, Toss MS, Verrill C, Salto-Tellez M, Snead D, Rakha EA. Potential quality pitfalls of digitalized whole slide image of breast pathology in routine practice. Mod Pathol 2022; 35:903-910. [PMID: 34961765 PMCID: PMC8711290 DOI: 10.1038/s41379-021-01000-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 12/11/2021] [Accepted: 12/12/2021] [Indexed: 12/26/2022]
Abstract
Using digitalized whole slide images (WSI) in routine histopathology practice is a revolutionary technology. This study aims to assess the clinical impacts of WSI quality and representation of the corresponding glass slides. 40,160 breast WSIs were examined and compared with their corresponding glass slides. The presence, frequency, location, tissue type, and the clinical impacts of missing tissue were assessed. Scanning time, type of the specimens, time to WSIs implementation, and quality control (QC) measures were also considered. The frequency of missing tissue ranged from 2% to 19%. The area size of the missed tissue ranged from 1-70%. In most cases (>75%), the missing tissue area size was <10% and peripherally located. In all cases the missed tissue was fat with or without small entrapped normal breast parenchyma. No missing tissue was identified in WSIs of the core biopsy specimens. QC measures improved images quality and reduced WSI failure rates by seven-fold. A negative linear correlation between the frequency of missing tissue and both the scanning time and the image file size was observed (p < 0.05). None of the WSI with missing tissues resulted in a change in the final diagnosis. Missing tissue on breast WSI is observed but with variable frequency and little diagnostic consequence. Balancing between WSI quality and scanning time/image file size should be considered and pathology laboratories should undertake their own assessments of risk and provide the relevant mitigations with the appropriate level of caution.
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Affiliation(s)
- Nehal M. Atallah
- grid.4563.40000 0004 1936 8868Department of Histopathology, School of Medicine, the University of Nottingham and Nottingham University Hospitals NHS Trust, Nottingham, UK ,grid.411775.10000 0004 0621 4712Department of Pathology, Faculty of Medicine, Menoufia University, Shebin Elkom, Al-Menoufia, Egypt
| | - Michael S. Toss
- grid.4563.40000 0004 1936 8868Department of Histopathology, School of Medicine, the University of Nottingham and Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Clare Verrill
- grid.4991.50000 0004 1936 8948Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK ,grid.4991.50000 0004 1936 8948NIHR Oxford Biomedical Research Centre, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Manuel Salto-Tellez
- grid.4777.30000 0004 0374 7521Precision Medicine Centre of Excellence, The Patrick G Johnston Centre for Cancer Research, Queen’s University, Belfast, UK
| | - David Snead
- grid.15628.380000 0004 0393 1193Cellular Pathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, Coventry, UK
| | - Emad A. Rakha
- grid.4563.40000 0004 1936 8868Department of Histopathology, School of Medicine, the University of Nottingham and Nottingham University Hospitals NHS Trust, Nottingham, UK ,grid.411775.10000 0004 0621 4712Department of Pathology, Faculty of Medicine, Menoufia University, Shebin Elkom, Al-Menoufia, Egypt
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20
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Colling R, Colling H, Browning L, Verrill C. Validation of grading of non-invasive urothelial carcinoma by digital pathology for routine diagnosis. BMC Cancer 2021; 21:995. [PMID: 34488682 PMCID: PMC8420048 DOI: 10.1186/s12885-021-08698-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 08/13/2021] [Indexed: 11/30/2022] Open
Abstract
Background Pathological grading of non-invasive urothelial carcinoma has a direct impact upon management. This study evaluates the reproducibility of grading these tumours on glass slides and digital pathology. Methods Forty eight non-invasive urothelial bladder carcinomas were graded by three uropathologists on glass and on a digital platform using the 1973 WHO and 2004 ISUP/WHO systems. Results Consensus grades for glass and digital grading gave Cohen’s kappa scores of 0.78 (2004) and 0.82 (1973). Of 142 decisions made on the key therapeutic borderline of low grade versus high grade urothelial carcinoma (2004) by the three pathologists, 85% were in agreement. For the 1973 grading system, agreement overall was 90%. Conclusions Agreement on grading on glass slide and digital screen assessment is similar or in some cases improved, suggesting at least non-inferiority of DP for grading of non-invasive urothelial carcinoma.
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Affiliation(s)
- Richard Colling
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK. .,Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
| | - Hayleigh Colling
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, OX3 9DU, UK.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK.,Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Oxford, OX3 9DU, UK.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK
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21
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Browning L, Colling R, Verrill C. WHO/ISUP grading of clear cell renal cell carcinoma and papillary renal cell carcinoma; validation of grading on the digital pathology platform and perspectives on reproducibility of grade. Diagn Pathol 2021; 16:75. [PMID: 34419085 PMCID: PMC8380382 DOI: 10.1186/s13000-021-01130-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 07/12/2021] [Indexed: 11/10/2022] Open
Abstract
Background There are recognised potential pitfalls in digital diagnosis in urological pathology, including the grading of dysplasia. The World Health Organisation/International Society of Urological Pathology (WHO/ISUP) grading system for renal cell carcinoma (RCC) is prognostically important in clear cell RCC (CCRCC) and papillary RCC (PRCC), and is included in risk stratification scores for CCRCC, thus impacting on patient management. To date there are no systematic studies examining the concordance of WHO/ISUP grading between digital pathology (DP) and glass slide (GS) images. We present a validation study examining intraobserver agreement in WHO/ISUP grade of CCRCC and PRCC. Methods Fifty CCRCCs and 10 PRCCs were graded (WHO/ISUP system) by three specialist uropathologists on three separate occasions (DP once then two GS assessments; GS1 and GS2) separated by wash-out periods of at least two-weeks. The grade was recorded for each assessment, and compared using Cohen’s and Fleiss’s kappa. Results There was 65 to 78% concordance of WHO/ISUP grading on DP and GS1. Furthermore, for the individual pathologists, the comparative kappa scores for DP versus GS1, and GS1 versus GS2, were 0.70 and 0.70, 0.57 and 0.73, and 0.71 and 0.74, and with no apparent tendency to upgrade or downgrade on DP versus GS. The interobserver kappa agreement was less, at 0.58 on DP and 0.45 on GS. Conclusion Our results demonstrate that the assessment of WHO/ISUP grade on DP is noninferior to that on GS. There is an apparent slight improvement in agreement between pathologists on RCC grade when assessed on DP, which may warrant further study.
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Affiliation(s)
- Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Headley Way, OX3 9DU, Oxford, UK. .,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK.
| | - Richard Colling
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Headley Way, OX3 9DU, Oxford, UK.,Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, OX3 9DU, Oxford, UK
| | - Clare Verrill
- Department of Cellular Pathology, Oxford University Hospitals NHS Trust, John Radcliffe Hospital, Headley Way, OX3 9DU, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK.,Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, OX3 9DU, Oxford, UK
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22
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Eyres M, Lanfredini S, Xu H, Burns A, Blake A, Willenbrock F, Goldin R, Hughes D, Hughes S, Thapa A, Vavoulis D, Hubert A, D'Costa Z, Sabbagh A, Abraham AG, Blancher C, Jones S, Verrill C, Silva M, Soonawalla Z, Maughan T, Schuh A, Mukherjee S, O'Neill E. TET2 Drives 5hmc Marking of GATA6 and Epigenetically Defines Pancreatic Ductal Adenocarcinoma Transcriptional Subtypes. Gastroenterology 2021; 161:653-668.e16. [PMID: 33915173 DOI: 10.1053/j.gastro.2021.04.044] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 03/12/2021] [Accepted: 04/07/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND & AIMS Pancreatic ductal adenocarcinoma (PDAC) is characterized by advanced disease stage at presentation, aggressive disease biology, and resistance to therapy, resulting in an extremely poor 5-year survival rate of <10%. PDAC is classified into transcriptional subtypes with distinct survival characteristics, although how these arise is not known. Epigenetic deregulation, rather than genetics, has been proposed to underpin progression, but exactly why is unclear and is hindered by the technical limitations of analyzing clinical samples. METHODS We performed genome-wide epigenetic mapping of DNA modifications 5-methylcytosine and 5-hydroxymethylcytosine (5hmc) using oxidative bisulfite sequencing from formalin-embedded sections. We identified overlap with transcriptional signatures in formalin-fixed, paraffin-embedded tissue from resected patients, via bioinformatics using iCluster and mutational profiling and confirmed them in vivo. RESULTS We found that aggressive squamous-like PDAC subtypes result from epigenetic inactivation of loci, including GATA6, which promote differentiated classical pancreatic subtypes. We showed that squamous-like PDAC transcriptional subtypes are associated with greater loss of 5hmc due to reduced expression of the 5-methylcytosine hydroxylase TET2. Furthermore, we found that SMAD4 directly supports TET2 levels in classical pancreatic tumors, and loss of SMAD4 expression was associated with reduced 5hmc, GATA6, and squamous-like tumors. Importantly, enhancing TET2 stability using metformin and vitamin C/ascorbic acid restores 5hmc and GATA6 levels, reverting squamous-like tumor phenotypes and WNT-dependence in vitro and in vivo. CONCLUSIONS We identified epigenetic deregulation of pancreatic differentiation as an underpinning event behind the emergence of transcriptomic subtypes in PDAC. Our data showed that restoring epigenetic control increases biomarkers of classical pancreatic tumors that are associated with improved therapeutic responses and survival.
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MESH Headings
- 5-Methylcytosine/analogs & derivatives
- 5-Methylcytosine/metabolism
- Animals
- Antineoplastic Combined Chemotherapy Protocols/pharmacology
- Ascorbic Acid/pharmacology
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Carcinoma, Pancreatic Ductal/drug therapy
- Carcinoma, Pancreatic Ductal/enzymology
- Carcinoma, Pancreatic Ductal/genetics
- Carcinoma, Pancreatic Ductal/pathology
- Cell Differentiation
- Cell Line, Tumor
- DNA Methylation/drug effects
- DNA-Binding Proteins/genetics
- DNA-Binding Proteins/metabolism
- Dioxygenases/genetics
- Dioxygenases/metabolism
- Epigenesis, Genetic/drug effects
- Epigenome
- Epigenomics
- GATA6 Transcription Factor/genetics
- GATA6 Transcription Factor/metabolism
- Gene Expression Profiling
- Gene Expression Regulation, Neoplastic
- Humans
- Metformin/pharmacology
- Mice, Nude
- Mice, Transgenic
- Pancreatic Neoplasms/drug therapy
- Pancreatic Neoplasms/enzymology
- Pancreatic Neoplasms/genetics
- Pancreatic Neoplasms/pathology
- Retrospective Studies
- Smad4 Protein/genetics
- Smad4 Protein/metabolism
- Transcription, Genetic/drug effects
- Transcriptome
- Wnt Signaling Pathway/genetics
- Xenograft Model Antitumor Assays
- Mice
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Affiliation(s)
- Michael Eyres
- Department of Oncology, University of Oxford, Oxford, UK
| | | | - Haonan Xu
- Department of Oncology, University of Oxford, Oxford, UK
| | - Adam Burns
- Department of Oncology, University of Oxford, Oxford, UK
| | - Andrew Blake
- Department of Oncology, University of Oxford, Oxford, UK
| | | | - Robert Goldin
- Centre for Pathology, Imperial College, London, United Kingdom
| | - Daniel Hughes
- Department of Oncology, University of Oxford, Oxford, UK; Department of Hepatobiliary and Pancreatic Surgery, Oxford University Hospitals National Health Service Foundation Trust, Oxford, United Kingdom
| | - Sophie Hughes
- Department of Oncology, University of Oxford, Oxford, UK
| | - Asmita Thapa
- Department of Oncology, University of Oxford, Oxford, UK
| | | | - Aline Hubert
- Department of Oncology, University of Oxford, Oxford, UK
| | | | - Ahmad Sabbagh
- Department of Oncology, University of Oxford, Oxford, UK
| | | | - Christine Blancher
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Stephanie Jones
- Oxford Radcliffe Biobank, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Clare Verrill
- Nuffield Department of Surgical Sciences and Oxford National Institute for Health Research Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
| | - Michael Silva
- Department of Hepatobiliary and Pancreatic Surgery, Oxford University Hospitals National Health Service Foundation Trust, Oxford, United Kingdom
| | - Zahir Soonawalla
- Department of Hepatobiliary and Pancreatic Surgery, Oxford University Hospitals National Health Service Foundation Trust, Oxford, United Kingdom
| | | | - Anna Schuh
- Department of Oncology, University of Oxford, Oxford, UK
| | | | - Eric O'Neill
- Department of Oncology, University of Oxford, Oxford, UK.
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23
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Erickson A, Hayes A, Rajakumar T, Verrill C, Bryant RJ, Hamdy FC, Wedge DC, Woodcock DJ, Mills IG, Lamb AD. A Systematic Review of Prostate Cancer Heterogeneity: Understanding the Clonal Ancestry of Multifocal Disease. Eur Urol Oncol 2021; 4:358-369. [PMID: 33888445 DOI: 10.1016/j.euo.2021.02.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 01/31/2021] [Accepted: 02/26/2021] [Indexed: 11/24/2022]
Abstract
CONTEXT Studies characterising genomic changes in prostate cancer (PCa) during natural progression have greatly increased our understanding of the disease. A better understanding of the evolutionary history of PCa would allow advances in diagnostics, prognostication, and novel therapies that together will improve patient outcomes. OBJECTIVE To review the molecular heterogeneity of PCa and assess recent efforts to profile intratumoural heterogeneity and clonal evolution. EVIDENCE ACQUISITION We screened a total of 1313 abstracts from PubMed published between 2009 and 2020, of which we reviewed 84 full-text articles. We excluded 49, resulting in 35 studies for qualitative analysis. EVIDENCE SYNTHESIS In studies of primary disease (16 studies, 4793 specimens), there is a lack of consensus regarding the monoclonal or polyclonal origin of primary PCa. There is no consistent mutation giving rise to primary PCa. Detailed clonal analysis of primary PCa has been limited by current techniques. By contrast, clonal relationships between PCa metastases and a potentiating clone have been consistently identified (19 studies, 732 specimens). Metastatic specimens demonstrate consistent truncal genomic aberrations that suggest monoclonal metastatic progenitors. CONCLUSIONS The relationship between the clonal dynamics of PCa and clinical outcomes needs further investigation. It is likely that this will provide a biological rationale for whether radical treatment of the primary tumour benefits patients with oligometastatic PCa. Future studies on the mutational burden in primary disease at single-cell resolution should permit the identification of clonal patterns underpinning the origin of lethal PCa. PATIENT SUMMARY Prostate cancers arise in different parts of the prostate because of DNA mutations that occur by chance at different times. These cancer cells and their origin can be tracked by DNA mapping. In this review we summarise the state of the art and outline what further science is needed to provide the missing answers.
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Affiliation(s)
- Andrew Erickson
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Alicia Hayes
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK
| | - Timothy Rajakumar
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK
| | - Richard J Bryant
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK
| | - Freddie C Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK
| | - David C Wedge
- Manchester Cancer Research Centre, University of Manchester, Manchester, UK
| | - Dan J Woodcock
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Oxford Big Data Institute, University of Oxford, Oxford, UK
| | - Ian G Mills
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK
| | - Alastair D Lamb
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK.
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24
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Ghosh A, Sirinukunwattana K, Khalid Alham N, Browning L, Colling R, Protheroe A, Protheroe E, Jones S, Aberdeen A, Rittscher J, Verrill C. The Potential of Artificial Intelligence to Detect Lymphovascular Invasion in Testicular Cancer. Cancers (Basel) 2021; 13:cancers13061325. [PMID: 33809521 PMCID: PMC7998792 DOI: 10.3390/cancers13061325] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 03/08/2021] [Accepted: 03/12/2021] [Indexed: 11/16/2022] Open
Abstract
Testicular cancer is the most common cancer in men aged from 15 to 34 years. Lymphovascular invasion refers to the presence of tumours within endothelial-lined lymphatic or vascular channels, and has been shown to have prognostic significance in testicular germ cell tumours. In non-seminomatous tumours, lymphovascular invasion is the most powerful prognostic factor for stage 1 disease. For the pathologist, searching multiple slides for lymphovascular invasion can be highly time-consuming. The aim of this retrospective study was to develop and assess an artificial intelligence algorithm that can identify areas suspicious for lymphovascular invasion in histological digital whole slide images. Areas of possible lymphovascular invasion were annotated in a total of 184 whole slide images of haematoxylin and eosin (H&E) stained tissue from 19 patients with testicular germ cell tumours, including a mixture of seminoma and non-seminomatous cases. Following consensus review by specialist uropathologists, we trained a deep learning classifier for automatic segmentation of areas suspicious for lymphovascular invasion. The classifier identified 34 areas within a validation set of 118 whole slide images from 10 patients, each of which was reviewed by three expert pathologists to form a majority consensus. The precision was 0.68 for areas which were considered to be appropriate to flag, and 0.56 for areas considered to be definite lymphovascular invasion. An artificial intelligence tool which highlights areas of possible lymphovascular invasion to reporting pathologists, who then make a final judgement on its presence or absence, has been demonstrated as feasible in this proof-of-concept study. Further development is required before clinical deployment.
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Affiliation(s)
- Abhisek Ghosh
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK; (L.B.); (R.C.); (C.V.)
- Nuffield Department of Clinical and Laboratory Sciences, Oxford University, John Radcliffe Hospital, Oxford OX3 9DU, UK
- Correspondence:
| | - Korsuk Sirinukunwattana
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK; (K.S.); (N.K.A.); (J.R.)
- Oxford NIHR Biomedical Research Centre, Oxford University, Oxford OX3 9DU, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford OX3 7DQ, UK
- Ground Truth Labs, Oxford OX4 2HN, UK;
| | - Nasullah Khalid Alham
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK; (K.S.); (N.K.A.); (J.R.)
- Oxford NIHR Biomedical Research Centre, Oxford University, Oxford OX3 9DU, UK
| | - Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK; (L.B.); (R.C.); (C.V.)
- Oxford NIHR Biomedical Research Centre, Oxford University, Oxford OX3 9DU, UK
| | - Richard Colling
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK; (L.B.); (R.C.); (C.V.)
- Nuffield Department of Surgical Sciences, Oxford University, Oxford OX3 9DU, UK;
| | - Andrew Protheroe
- Department of Oncology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK; (A.P.); (E.P.)
| | - Emily Protheroe
- Department of Oncology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK; (A.P.); (E.P.)
| | - Stephanie Jones
- Nuffield Department of Surgical Sciences, Oxford University, Oxford OX3 9DU, UK;
| | | | - Jens Rittscher
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK; (K.S.); (N.K.A.); (J.R.)
- Oxford NIHR Biomedical Research Centre, Oxford University, Oxford OX3 9DU, UK
| | - Clare Verrill
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford OX3 9DU, UK; (L.B.); (R.C.); (C.V.)
- Oxford NIHR Biomedical Research Centre, Oxford University, Oxford OX3 9DU, UK
- Nuffield Department of Surgical Sciences, Oxford University, Oxford OX3 9DU, UK;
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25
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Sirinukunwattana K, Domingo E, Richman SD, Redmond KL, Blake A, Verrill C, Leedham SJ, Chatzipli A, Hardy C, Whalley CM, Wu CH, Beggs AD, McDermott U, Dunne PD, Meade A, Walker SM, Murray GI, Samuel L, Seymour M, Tomlinson I, Quirke P, Maughan T, Rittscher J, Koelzer VH. Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning. Gut 2021; 70:544-554. [PMID: 32690604 PMCID: PMC7873419 DOI: 10.1136/gutjnl-2019-319866] [Citation(s) in RCA: 105] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 05/19/2020] [Accepted: 06/08/2020] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning. DESIGN Training and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier. RESULTS Image-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS. CONCLUSION This study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows.
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Affiliation(s)
- Korsuk Sirinukunwattana
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Oxford, UK
- Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Enric Domingo
- Department of Oncology, University of Oxford, Oxford, UK
| | - Susan D Richman
- Department of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, Leeds, UK
| | - Keara L Redmond
- Centre for Cancer Research and Cell Biology, Faculty of Medicine, Health and Life Sciences, Queen's University Belfast, Belfast, UK
| | - Andrew Blake
- Department of Oncology, University of Oxford, Oxford, UK
| | - Clare Verrill
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Nuffield Department of Surgical Sciences and NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Simon J Leedham
- Gastrointestinal Stem-cell Biology Laboratory, Oxford Centre for Cancer Gene Research, Wellcome Trust Centre for Human Genetics, Oxford, UK
- Translational Gastroenterology Unit, Experimental Medicine Division, Nuffield Department of Clinical Medicine, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | | | | | - Celina M Whalley
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Chieh-Hsi Wu
- Department of Statistics, University of Oxford, Oxford, UK
| | - Andrew D Beggs
- School of Cancer Sciences, University of Birmingham, Birmingham, UK
| | | | - Philip D Dunne
- Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, UK
| | - Angela Meade
- MRC Clinical Trials Unit at University College London, London, UK
| | | | - Graeme I Murray
- Department of Pathology, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, UK
| | - Leslie Samuel
- Department of Clinical Oncology, Aberdeen Royal Infirmary, Aberdeen, UK
| | - Matthew Seymour
- Department of Oncology, Leeds Institute of Cancer and Pathology, Leeds, UK
| | - Ian Tomlinson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Edinburgh Cancer Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Phil Quirke
- Department of Pathology and Tumour Biology, Leeds Institute of Cancer and Pathology, Leeds, UK
| | - Timothy Maughan
- CRUK/MRC Oxford Institute for Radiation Oncology, University of Oxford, Oxford, UK
| | - Jens Rittscher
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Oxford, UK
- Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Viktor H Koelzer
- Department of Oncology, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Department of Pathology and Molecular Pathology, University of Zurich, Zurich, Switzerland
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26
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Wellington D, Yin Z, Abdel-Haq A, Zhang L, Forbester J, Kite K, Rajapaksa U, Laurenson-Schafer H, Makvandi-Nejad S, Jin B, Bowes E, Manoharan K, Maldonado-Perez D, Verrill C, Humphreys IR, Dong T. IFITM3-specific antibody reveals IFN preferences and slow IFN induction of the antiviral factor IFITM3 in humans. Eur J Immunol 2021; 51:742-745. [PMID: 33125710 PMCID: PMC7983929 DOI: 10.1002/eji.202048706] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 10/01/2020] [Accepted: 10/22/2020] [Indexed: 01/09/2023]
Abstract
Using a specific antibody, we found that expression of the viral restriction factor IFITM3 differs across cell types within the immune compartment with higher expression in myeloid rather than lymphoid cells. IFITM3 expression was increased following IFN stimulation, mostly type I, in immune cells, with the exception of T cells.
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Affiliation(s)
- Dannielle Wellington
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford University, Oxford, UK.,Nuffield Department of Medicine, Chinese Academy of Medical Sciences (CAMS) Oxford Institute, Oxford University, Oxford, UK
| | - Zixi Yin
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford University, Oxford, UK.,Nuffield Department of Medicine, Chinese Academy of Medical Sciences (CAMS) Oxford Institute, Oxford University, Oxford, UK
| | - Adi Abdel-Haq
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford University, Oxford, UK.,Charles Tanford-Proteinzentrum, Martin-Luther-Universität Halle-Wittenberg, Institut für Molekulare Medizin, Kurt-Mothes-Straße 3a, Halle, Germany
| | - Liwei Zhang
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford University, Oxford, UK
| | - Jessica Forbester
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford University, Oxford, UK.,Division of Infection and Immunity/Systems Immunity University Research Institute, Cardiff University, Cardiff, UK
| | - Kerry Kite
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford University, Oxford, UK
| | - Ushani Rajapaksa
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford University, Oxford, UK
| | - Henry Laurenson-Schafer
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford University, Oxford, UK
| | - Shokouh Makvandi-Nejad
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford University, Oxford, UK
| | - Boquan Jin
- Fourth Military Medical University, Xian, China
| | - Emma Bowes
- Oxford Radcliffe Biobank, Nuffield Department of Surgical Sciences, Oxford University, Oxford, UK
| | - Krishnageetha Manoharan
- Oxford Radcliffe Biobank, Nuffield Department of Surgical Sciences, Oxford University, Oxford, UK
| | - David Maldonado-Perez
- Oxford Radcliffe Biobank, Nuffield Department of Surgical Sciences, Oxford University, Oxford, UK
| | - Clare Verrill
- Oxford Radcliffe Biobank, Nuffield Department of Surgical Sciences, Oxford University, Oxford, UK
| | - Ian R Humphreys
- Division of Infection and Immunity/Systems Immunity University Research Institute, Cardiff University, Cardiff, UK
| | - Tao Dong
- MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford University, Oxford, UK.,Nuffield Department of Medicine, Chinese Academy of Medical Sciences (CAMS) Oxford Institute, Oxford University, Oxford, UK
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27
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Awan R, Benes K, Azam A, Song TH, Shaban M, Verrill C, Tsang YW, Snead D, Minhas F, Rajpoot N. Deep learning based digital cell profiles for risk stratification of urine cytology images. Cytometry A 2021; 99:732-742. [PMID: 33486882 DOI: 10.1002/cyto.a.24313] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 12/05/2020] [Accepted: 12/15/2020] [Indexed: 11/06/2022]
Abstract
Urine cytology is a test for the detection of high-grade bladder cancer. In clinical practice, the pathologist would manually scan the sample under the microscope to locate atypical and malignant cells. They would assess the morphology of these cells to make a diagnosis. Accurate identification of atypical and malignant cells in urine cytology is a challenging task and is an essential part of identifying different diagnosis with low-risk and high-risk malignancy. Computer-assisted identification of malignancy in urine cytology can be complementary to the clinicians for treatment management and in providing advice for carrying out further tests. In this study, we presented a method for identifying atypical and malignant cells followed by their profiling to predict the risk of diagnosis automatically. For cell detection and classification, we employed two different deep learning-based approaches. Based on the best performing network predictions at the cell level, we identified low-risk and high-risk cases using the count of atypical cells and the total count of atypical and malignant cells. The area under the receiver operating characteristic (ROC) curve shows that a total count of atypical and malignant cells is comparably better at diagnosis as compared to the count of malignant cells only. We obtained area under the ROC curve with the count of malignant cells and the total count of atypical and malignant cells as 0.81 and 0.83, respectively. Our experiments also demonstrate that the digital risk could be a better predictor of the final histopathology-based diagnosis. We also analyzed the variability in annotations at both cell and whole slide image level and also explored the possible inherent rationales behind this variability.
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Affiliation(s)
- Ruqayya Awan
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Ksenija Benes
- The Royal Wolverhampton NHS Trust, Wolverhampton, UK
| | - Ayesha Azam
- Department of Computer Science, University of Warwick, Coventry, UK.,Department of Pathology, University Hospitals Coventry and Warwickshire, Coventry, UK
| | - Tzu-Hsi Song
- Department of Computer Science, University of Warwick, Coventry, UK.,Laboratory of Quantitative Cellular Imaging, Worcester Polytechnic Institute, Worcester, Massachusetts, USA
| | - Muhammad Shaban
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Clare Verrill
- Nuffield Department of Surgical Sciences and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Yee Wah Tsang
- Department of Pathology, University Hospitals Coventry and Warwickshire, Coventry, UK
| | - David Snead
- Department of Pathology, University Hospitals Coventry and Warwickshire, Coventry, UK
| | - Fayyaz Minhas
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Nasir Rajpoot
- Department of Computer Science, University of Warwick, Coventry, UK.,Department of Pathology, University Hospitals Coventry and Warwickshire, Coventry, UK.,The Alan Turing Institute, London, UK
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28
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Chatrian A, Colling RT, Browning L, Alham NK, Sirinukunwattana K, Malacrino S, Haghighat M, Aberdeen A, Monks A, Moxley-Wyles B, Rakha E, Snead DRJ, Rittscher J, Verrill C. Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies. Mod Pathol 2021; 34:1780-1794. [PMID: 34017063 PMCID: PMC8376647 DOI: 10.1038/s41379-021-00826-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 04/23/2021] [Accepted: 04/27/2021] [Indexed: 12/29/2022]
Abstract
The use of immunohistochemistry in the reporting of prostate biopsies is an important adjunct when the diagnosis is not definite on haematoxylin and eosin (H&E) morphology alone. The process is however inherently inefficient with delays while waiting for pathologist review to make the request and duplicated effort reviewing a case more than once. In this study, we aimed to capture the workflow implications of immunohistochemistry requests and demonstrate a novel artificial intelligence tool to identify cases in which immunohistochemistry (IHC) is required and generate an automated request. We conducted audits of the workflow for prostate biopsies in order to understand the potential implications of automated immunohistochemistry requesting and collected prospective cases to train a deep neural network algorithm to detect tissue regions that presented ambiguous morphology on whole slide images. These ambiguous foci were selected on the basis of the pathologist requesting immunohistochemistry to aid diagnosis. A gradient boosted trees classifier was then used to make a slide-level prediction based on the outputs of the neural network prediction. The algorithm was trained on annotations of 219 immunohistochemistry-requested and 80 control images, and tested by threefold cross-validation. Validation was conducted on a separate validation dataset of 222 images. Non IHC-requested cases were diagnosed in 17.9 min on average, while IHC-requested cases took 33.4 min over multiple reporting sessions. We estimated 11 min could be saved on average per case by automated IHC requesting, by removing duplication of effort. The tool attained 99% accuracy and 0.99 Area Under the Curve (AUC) on the test data. In the validation, the average agreement with pathologists was 0.81, with a mean AUC of 0.80. We demonstrate the proof-of-principle that an AI tool making automated immunohistochemistry requests could create a significantly leaner workflow and result in pathologist time savings.
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Affiliation(s)
- Andrea Chatrian
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK. .,Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK.
| | - Richard T. Colling
- grid.4991.50000 0004 1936 8948Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK ,grid.8348.70000 0001 2306 7492Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK
| | - Lisa Browning
- grid.8348.70000 0001 2306 7492Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK ,grid.8348.70000 0001 2306 7492NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK
| | - Nasullah Khalid Alham
- grid.4991.50000 0004 1936 8948Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK ,grid.4991.50000 0004 1936 8948Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
| | - Korsuk Sirinukunwattana
- grid.4991.50000 0004 1936 8948Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK ,grid.4991.50000 0004 1936 8948Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
| | - Stefano Malacrino
- grid.4991.50000 0004 1936 8948Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK ,grid.4991.50000 0004 1936 8948Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK ,grid.4991.50000 0004 1936 8948Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Maryam Haghighat
- grid.4991.50000 0004 1936 8948Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK ,grid.4991.50000 0004 1936 8948Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
| | - Alan Aberdeen
- Ground Truth Labs, 9400 Garsington Road, Oxford Business Park, Oxford, UK
| | - Amelia Monks
- grid.4991.50000 0004 1936 8948Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK
| | - Benjamin Moxley-Wyles
- grid.439664.a0000 0004 0368 863XDepartment of Cellular Pathology, Buckinghamshire Healthcare NHS Trust, Amersham, UK
| | - Emad Rakha
- grid.4563.40000 0004 1936 8868School of Medicine, University of Nottingham, Nottingham, Nottinghamshire UK
| | - David. R. J. Snead
- grid.15628.38Department of Pathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, West Midlands UK
| | - Jens Rittscher
- Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford, Old Road Campus Research Building Oxford, Oxford, UK. .,Oxford Big Data Institute, University of Oxford, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK. .,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK. .,Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK.
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK. .,Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK. .,NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK.
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29
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Ranasinha N, Omer A, Philippou Y, Harriss E, Davies L, Chow K, Chetta PM, Erickson A, Rajakumar T, Mills IG, Bryant RJ, Hamdy FC, Murphy DG, Loda M, Hovens CM, Corcoran NM, Verrill C, Lamb AD. Ductal adenocarcinoma of the prostate: A systematic review and meta-analysis of incidence, presentation, prognosis, and management. BJUI Compass 2021; 2:13-23. [PMID: 35474657 PMCID: PMC8988764 DOI: 10.1002/bco2.60] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 11/02/2020] [Indexed: 01/22/2023] Open
Abstract
Context Ductal adenocarcinoma (DAC) is relatively rare, but is nonetheless the second most common subtype of prostate cancer. First described in 1967, opinion is still divided regarding its biology, prognosis, and outcome. Objectives To systematically interrogate the literature to clarify the epidemiology, diagnosis, management, progression, and survival statistics of DAC. Materials and methods We conducted a literature search of five medical databases from inception to May 04 2020 according to PRISMA criteria using search terms "prostate ductal adenocarcinoma" OR "endometriod adenocarcinoma of prostate" and variations of each. Results Some 114 studies were eligible for inclusion, presenting 2 907 170 prostate cancer cases, of which 5911 were DAC. [Correction added on 16 January 2021 after the first online publication: the preceding statement has been corrected in this current version.] DAC accounts for 0.17% of prostate cancer on meta-analysis (range 0.0837%-13.4%). The majority of DAC cases were admixed with predominant acinar adenocarcinoma (AAC). Median Prostate Specific Antigen at diagnosis ranged from 4.2 to 9.6 ng/mL in the case series.DAC was more likely to present as T3 (RR1.71; 95%CI 1.53-1.91) and T4 (RR7.56; 95%CI 5.19-11.01) stages, with far higher likelihood of metastatic disease (RR4.62; 95%CI 3.84-5.56; all P-values < .0001), compared to AAC. Common first treatments included surgery (radical prostatectomy (RP) or cystoprostatectomy for select cases) or radiotherapy (RT) for localized disease, and hormonal or chemo-therapy for metastatic disease. Few studies compared RP and RT modalities, and those that did present mixed findings, although cancer-specific survival rates seem worse after RP.Biochemical recurrence rates were increased with DAC compared to AAC. Additionally, DAC metastasized to unusual sites, including penile and peritoneal metastases. Where compared, all studies reported worse survival for DAC compared to AAC. Conclusion When drawing conclusions about DAC it is important to note the heterogenous nature of the data. DAC is often diagnosed incidentally post-treatment, perhaps due to lack of a single, universally applied histopathological definition. As such, DAC is likely underreported in clinical practice and the literature. Poorer prognosis and outcomes for DAC compared to AAC merit further research into genetic composition, evolution, diagnosis, and treatment of this surprisingly common prostate cancer sub-type. Patient summary Ductal prostate cancer is a rare but important form of prostate cancer. This review demonstrates that it tends to be more serious at detection and more likely to spread to unusual parts of the body. Overall survival is worse with this type of prostate cancer and urologists need to be aware of the presence of ductal prostate cancer to alter management decisions and follow-up.
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Affiliation(s)
- Nithesh Ranasinha
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
- Department of UrologyOxford University Hospitals NHS Foundation Trust, Roosevelt DriveOxfordUK
| | - Altan Omer
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
| | - Yiannis Philippou
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
| | - Eli Harriss
- Bodleian Health Care LibrariesUniversity of OxfordOxfordUK
| | - Lucy Davies
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
| | - Ken Chow
- Department of SurgeryRoyal Melbourne HospitalUniversity of MelbourneMelbourneVICAustralia
| | | | - Andrew Erickson
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
| | - Timothy Rajakumar
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
| | - Ian G. Mills
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
| | - Richard J. Bryant
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
- Department of UrologyOxford University Hospitals NHS Foundation Trust, Roosevelt DriveOxfordUK
| | - Freddie C. Hamdy
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
- Department of UrologyOxford University Hospitals NHS Foundation Trust, Roosevelt DriveOxfordUK
| | - Declan G. Murphy
- Division of Cancer SurgeryPeter MacCallum Cancer CentreMelbourneVICAustralia
- Sir Peter MacCallum Department of OncologyUniversity of MelbourneParkvilleVICAustralia
| | - Massimo Loda
- Dana Farber Cancer InstituteHarvardMAUSA
- Weill Cornell Medical SchoolNew YorkNYUSA
| | - Christopher M. Hovens
- Department of SurgeryRoyal Melbourne HospitalUniversity of MelbourneMelbourneVICAustralia
| | - Niall M. Corcoran
- Department of SurgeryRoyal Melbourne HospitalUniversity of MelbourneMelbourneVICAustralia
| | - Clare Verrill
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
- NIHR Oxford Biomedical Research CentreUniversity of Oxford, John Radcliffe HospitalOxfordUK
| | - Alastair D. Lamb
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
- Department of UrologyOxford University Hospitals NHS Foundation Trust, Roosevelt DriveOxfordUK
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31
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Charlton P, O'Reilly D, Philippou Y, Rao S, Lamb A, Higgins G, Hamdy F, Verrill C, Bryant R, Buffa F. PO-1160: A pilot dual-platform transcriptomic analysis of diagnostic prostate biopsies & radical RT response. Radiother Oncol 2020. [DOI: 10.1016/s0167-8140(21)01178-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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32
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Kanellakis NI, Asciak R, Hamid MA, Yao X, McCole M, McGowan S, Seraia E, Hatch S, Hallifax RJ, Mercer RM, Bedawi EO, Jones S, Verrill C, Dobson M, George V, Stathopoulos GT, Peng Y, Ebner D, Dong T, Rahman NM, Psallidas I. Patient-derived malignant pleural mesothelioma cell cultures: a tool to advance biomarker-driven treatments. Thorax 2020; 75:1004-1008. [PMID: 32943495 PMCID: PMC7569377 DOI: 10.1136/thoraxjnl-2020-215027] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 07/03/2020] [Accepted: 07/14/2020] [Indexed: 12/17/2022]
Abstract
Malignant pleural mesothelioma (MPM) is an aggressive cancer, associated with poor prognosis. We assessed the feasibility of patient-derived cell cultures to serve as an ex vivo model of MPM. Patient-derived MPM cell cultures (n=16) exhibited stemness features and reflected intratumour and interpatient heterogeneity. A subset of the cells were subjected to high-throughput drug screening and coculture assays with cancer-specific cytotoxic T cells and showed diverse responses. Some of the biphasic MPM cells were capable of processing and presenting the neoantigen SSX-2 endogenously. In conclusion, patient-derived MPM cell cultures are a promising and faithful ex vivo model of MPM.
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Affiliation(s)
- Nikolaos I Kanellakis
- Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom .,Laboratory of Pleural and Lung Cancer Translational Research, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom.,Oxford Respiratory Trials Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Rachelle Asciak
- Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.,Laboratory of Pleural and Lung Cancer Translational Research, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,Oxford Respiratory Trials Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Megat Abd Hamid
- Chinese Academy of Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Xuan Yao
- Chinese Academy of Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Mark McCole
- Cellular Pathology Department, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Simon McGowan
- Computational Biology Research Group, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Elena Seraia
- Cellular High Throughput Screening Facility, Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, United Kingdom
| | - Stephanie Hatch
- Cellular High Throughput Screening Facility, Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, United Kingdom
| | - Rob J Hallifax
- Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.,Oxford Respiratory Trials Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Rachel M Mercer
- Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.,Oxford Respiratory Trials Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Eihab O Bedawi
- Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.,Oxford Respiratory Trials Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Stephanie Jones
- Oxford Radcliffe Biobank, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Clare Verrill
- Oxford Radcliffe Biobank, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Melissa Dobson
- Oxford Respiratory Trials Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Vineeth George
- Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.,Oxford Respiratory Trials Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Georgios T Stathopoulos
- Molecular Lung Carcinogenesis Group, Comprehensive Pneumology Center and Institute for Lung Biology and Disease, Ludwig-Maximilians University and Helmholtz Center, Munich, Germany.,Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Patras, Greece
| | - Yanchun Peng
- Chinese Academy of Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Daniel Ebner
- Cellular High Throughput Screening Facility, Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, United Kingdom
| | - Tao Dong
- Chinese Academy of Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Najib M Rahman
- Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.,Laboratory of Pleural and Lung Cancer Translational Research, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom.,Oxford Respiratory Trials Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Ioannis Psallidas
- Oxford Centre for Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.,Laboratory of Pleural and Lung Cancer Translational Research, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.,Oxford Respiratory Trials Unit, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
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33
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Cui H, Verrill C, Sullivan M. A new cancer on the block: Tuberous sclerosis-associated renal cell carcinoma. Journal of Clinical Urology 2020. [DOI: 10.1177/2051415820956434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Purpose: The purpose of this article is to present the first reported case of a renal tumour classified as tuberous sclerosis complex-associated renal cell carcinoma in the UK and discuss its clinical implications. Case report: A female, aged 65 years, with tuberous sclerosis complex was found on surveillance imaging to have interval growth of multiple right renal tumours up to 19 mm. Right partial nephrectomy was performed. Histology showed multiple tiny angiomyolipomas and a 20 mm tumour classified as tuberous sclerosis complex-associated renal cell carcinoma. These tumour cells showed abundant clear cytoplasm with a branched elongated arrangement encircled in dense smooth muscle stroma. Literature review: Renal cell carcinoma in patients with tuberous sclerosis complex is rare, occurring in approximately 4% of cases. Tuberous sclerosis complex-associated renal cell carcinoma is a relatively new histological entity, having previously been described as clear cell or chromophobe-like, with only one published case series from the USA. These tumours have three histological entities which are distinct from all other renal cell carcinoma classifications. Based on case series, tuberous sclerosis complex-associated renal cell carcinoma tends to occur more often in females, present at a younger age, have multiple tumours, and tend to show an indolent course, although metastases have been reported. Learning points: Patients with tuberous sclerosis complex can develop renal cell carcinoma, though the risk is thought to be no higher than for sporadic renal cell carcinoma. Given the limited literature, more evidence is required to help predict the future behaviour of these tumours. Level of evidence: 5
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Affiliation(s)
- Helen Cui
- Urology Department, Oxford University Hospitals NHS Foundation Trust, UK
| | - Clare Verrill
- Department of Pathology, Oxford University Hospitals NHS Foundation Trust, UK
| | - Mark Sullivan
- Urology Department, Oxford University Hospitals NHS Foundation Trust, UK
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Tuthill M, Cappuccini F, Carter L, Pollock E, Poulton I, Verrill C, Evans T, Gillessen S, Attard G, Protheroe A, Hamdy F, Hill A, Redchenko I. 682P Results from ADVANCE: A phase I/II open-label non-randomised safety and efficacy study of the viral vectored ChAdOx1-MVA 5T4 (VTP-800) vaccine in combination with PD-1 checkpoint blockade in metastatic prostate cancer. Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.08.2076] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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35
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Browning L, Colling R, Rakha E, Rajpoot N, Rittscher J, James JA, Salto-Tellez M, Snead DRJ, Verrill C. Digital pathology and artificial intelligence will be key to supporting clinical and academic cellular pathology through COVID-19 and future crises: the PathLAKE consortium perspective. J Clin Pathol 2020; 74:443-447. [PMID: 32620678 PMCID: PMC8223667 DOI: 10.1136/jclinpath-2020-206854] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 06/15/2020] [Indexed: 12/19/2022]
Abstract
The measures to control the COVID-19 outbreak will likely remain a feature of our working lives until a suitable vaccine or treatment is found. The pandemic has had a substantial impact on clinical services, including cancer pathways. Pathologists are working remotely in many circumstances to protect themselves, colleagues, family members and the delivery of clinical services. The effects of COVID-19 on research and clinical trials have also been significant with changes to protocols, suspensions of studies and redeployment of resources to COVID-19. In this article, we explore the specific impact of COVID-19 on clinical and academic pathology and explore how digital pathology and artificial intelligence can play a key role to safeguarding clinical services and pathology-based research in the current climate and in the future.
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Affiliation(s)
- Lisa Browning
- Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford, Oxfordshire, UK
| | - Richard Colling
- Nuffield Department of Surgical Sciences, Oxford University, Oxford, Oxfordshire, UK
| | - Emad Rakha
- School of Medicine, University of Nottingham, Nottingham, Nottinghamshire, UK
| | - Nasir Rajpoot
- Tissue Image Analytics Laboratory, Department of Computer Science, University of Warwick, Coventry, West Midlands, UK.,Department of Pathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, West Midlands, UK
| | - Jens Rittscher
- NIHR Oxford Biomedical Research Centre, Oxford, Oxfordshire, UK.,Department of Engineering Science and Big Data Institute, Oxford University, Oxford, Oxfordshire, UK
| | - Jacqueline A James
- Precision Medicine Centre of Excellence, Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, Belfast, UK.,Cellular Pathology, Belfast Health and Social Care Trust, Belfast, Belfast, UK
| | - Manuel Salto-Tellez
- Precision Medicine Centre of Excellence, Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, Belfast, UK.,Cellular Pathology, Belfast Health and Social Care Trust, Belfast, Belfast, UK
| | - David R J Snead
- Department of Pathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, West Midlands, UK
| | - Clare Verrill
- NIHR Oxford Biomedical Research Centre, Oxford, Oxfordshire, UK .,Nuffield Department of Surgical Sciences, Oxford University, Oxford, Oxfordshire, UK
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36
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Browning L, Fryer E, Roskell D, White K, Colling R, Rittscher J, Verrill C. Role of digital pathology in diagnostic histopathology in the response to COVID-19: results from a survey of experience in a UK tertiary referral hospital. J Clin Pathol 2020; 74:129-132. [PMID: 32616541 PMCID: PMC7841475 DOI: 10.1136/jclinpath-2020-206786] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 06/05/2020] [Indexed: 12/21/2022]
Abstract
The COVID-19 pandemic has challenged our diagnostic services at a time when many histopathology departments already faced a diminishing workforce and increasing workload. Digital pathology (DP) has been hailed as a potential solution to at least some of the challenges faced. We present a survey of pathologists within a UK National Health Service cellular pathology department with access to DP, in which we ascertain the role of DP in clinical services during this current pandemic and explore challenges encountered. This survey indicates an increase in uptake of diagnostic DP during this period, with increased remote access. Half of respondents agreed that DP had facilitated maintenance of diagnostic practice. While challenges have been encountered, these are remediable, and none have impacted on the uptake of DP during this period. We conclude that in our institution, DP has demonstrated current and future potential to increase resilience in diagnostic practice and have highlighted some of the challenges that need to be considered.
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Affiliation(s)
- Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK .,NIHR Oxford Biomedical Research Centre, Oxford, Oxfordshire, UK
| | - Eve Fryer
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK
| | - Derek Roskell
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK
| | - Kieron White
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK
| | - Richard Colling
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK.,Nuffield Department of Surgical Sciences, University of Oxford, Oxford, Oxfordshire, UK
| | - Jens Rittscher
- NIHR Oxford Biomedical Research Centre, Oxford, Oxfordshire, UK.,Department of Engineering Science, University of Oxford, Oxford, Oxfordshire, UK
| | - Clare Verrill
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, Oxfordshire, UK.,NIHR Oxford Biomedical Research Centre, Oxford, Oxfordshire, UK.,Nuffield Department of Surgical Sciences, University of Oxford, Oxford, Oxfordshire, UK
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37
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Charlton P, O’Reilly D, Philippou Y, Rao S, Lamb A, Higgins G, Hamdy F, Verrill C, Bryant R, Buffa F. A pilot transcriptomic analysis of archival prostate biopsy samples and response to radical radiotherapy. EUR UROL SUPPL 2020. [DOI: 10.1016/s2666-1683(20)32956-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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38
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Cappuccini F, Bryant R, Pollock E, Carter L, Verrill C, Hollidge J, Poulton I, Baker M, Mitton C, Baines A, Meier A, Schmidt G, Harrop R, Protheroe A, MacPherson R, Kennish S, Morgan S, Vigano S, Romero PJ, Evans T, Catto J, Hamdy F, Hill AVS, Redchenko I. Safety and immunogenicity of novel 5T4 viral vectored vaccination regimens in early stage prostate cancer: a phase I clinical trial. J Immunother Cancer 2020; 8:e000928. [PMID: 32591433 PMCID: PMC7319775 DOI: 10.1136/jitc-2020-000928] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/26/2020] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Prostate cancer (PCa) has been under investigation as a target for antigen-specific immunotherapies in metastatic disease settings for the last two decades leading to a licensure of the first therapeutic cancer vaccine, Sipuleucel-T, in 2010. However, neither Sipuleucel-T nor other experimental PCa vaccines that emerged later induce strong T-cell immunity. METHODS In this first-in-man study, VANCE, we evaluated a novel vaccination platform based on two replication-deficient viruses, chimpanzee adenovirus (ChAd) and MVA (Modified Vaccinia Ankara), targeting the oncofetal self-antigen 5T4 in early stage PCa. Forty patients, either newly diagnosed with early-stage PCa and scheduled for radical prostatectomy or patients with stable disease on an active surveillance protocol, were recruited to the study to assess the vaccine safety and T-cell immunogenicity. Secondary and exploratory endpoints included immune infiltration into the prostate, prostate-specific antigen (PSA) change, and assessment of phenotype and functionality of antigen-specific T cells. RESULTS The vaccine had an excellent safety profile. Vaccination-induced 5T4-specific T-cell responses were measured in blood by ex vivo IFN-γ ELISpot and were detected in the majority of patients with a mean level in responders of 198 spot-forming cells per million peripheral blood mononuclear cells. Flow cytometry analysis demonstrated the presence of both CD8+ and CD4+ polyfunctional 5T4-specific T cells in the circulation. 5T4-reactive tumor-infiltrating lymphocytes were isolated from post-treatment prostate tissue. Some of the patients had a transient PSA rise 2-8 weeks following vaccination, possibly indicating an inflammatory response in the target organ. CONCLUSIONS An excellent safety profile and T-cell responses elicited in the circulation and also detected in the prostate gland support the evaluation of the ChAdOx1-MVA 5T4 vaccine in efficacy trials. It remains to be seen if this vaccination strategy generates immune responses of sufficient magnitude to mediate clinical efficacy and whether it can be effective in late-stage PCa settings, as a monotherapy in advanced disease or as part of multi-modality PCa therapy. To address these questions, the phase I/II trial, ADVANCE, is currently recruiting patients with intermediate-risk PCa, and patients with advanced metastatic castration-resistant PCa, to receive this vaccine in combination with nivolumab. TRIAL REGISTRATION The trial was registered with the U.S. National Institutes of Health (NIH) Clinical Trials Registry (ClinicalTrials.gov identifier NCT02390063).
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Affiliation(s)
- Federica Cappuccini
- Nuffield Department of Medicine, The Jenner Institute, Oxford University, Oxford, UK
| | - Richard Bryant
- Nuffield Department of Surgical Sciences, Oxford University, Oxford, UK
- Department of Urology, Churchill Hospital, Oxford, UK
| | - Emily Pollock
- Nuffield Department of Medicine, The Jenner Institute, Oxford University, Oxford, UK
| | - Lucy Carter
- Nuffield Department of Medicine, The Jenner Institute, Oxford University, Oxford, UK
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, Oxford University, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University, Oxford, UK
| | - Julianne Hollidge
- Nuffield Department of Surgical Sciences, Oxford University, Oxford, UK
| | - Ian Poulton
- Nuffield Department of Medicine, The Jenner Institute, Oxford University, Oxford, UK
| | - Megan Baker
- Nuffield Department of Medicine, The Jenner Institute, Oxford University, Oxford, UK
| | - Celia Mitton
- Nuffield Department of Medicine, The Jenner Institute, Oxford University, Oxford, UK
| | - Andrea Baines
- Nuffield Department of Medicine, The Jenner Institute, Oxford University, Oxford, UK
| | | | | | | | - Andrew Protheroe
- Department of Oncology, Oxford Cancer and Haematology Centre, Churchill Hospital, Oxford, UK
| | | | - Steven Kennish
- Department of Radiology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Susan Morgan
- Department of Pathology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Selena Vigano
- Oncology, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pedro J Romero
- Oncology, University Hospital of Lausanne, Lausanne, Switzerland
| | | | - James Catto
- Academic Urology Unit, The University of Sheffield, Sheffield, UK
| | - Freddie Hamdy
- Nuffield Department of Surgical Sciences, Oxford University, Oxford, UK
- Department of Urology, Churchill Hospital, Oxford, UK
| | - Adrian V S Hill
- Nuffield Department of Medicine, The Jenner Institute, Oxford University, Oxford, UK
| | - Irina Redchenko
- Nuffield Department of Medicine, The Jenner Institute, Oxford University, Oxford, UK
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39
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Tuthill M, Cappuccini F, Bryant RJ, Poulton I, Pollock E, Carter L, Verrill C, Meier A, Schmidt G, Catto JWF, Evans T, Gillessen S, Protheroe A, Hamdy F, Hill AV, Redchenko I. Phase I/II open label nonrandomized safety and efficacy study of the viral vectored ChAdOx1-MVA 5T4 immunotherapy in combination with PD-1 checkpoint blockade in intermediate-risk localized or locally advanced prostate cancer and advanced metastatic prostate cancer. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.tps3170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
TPS3170 Background: Antigen-specific immunotherapy (Sipuleucel-T) is licenced for the treatment for castrate resistant prostate cancer, but has modest clinical efficacy and is complex to administer to patients. New therapeutic antigen-specific approaches are required to generate and sustain therapeutic immune responses against tumour specific antigens in men with early and advanced prostate cancer. We have previously reported immunogenicity and efficacy data of a novel viral vectored vaccines-based immunotherapy based on two replication-deficient viruses, chimpanzee adenovirus (ChAdOx1) and MVA, targeting an oncofetal self-antigen 5T4, administered as a single agent and in combination with anti-PD-1 in mouse tumour models. We tested this immunotherapy alone in a first-in-human trial, VANCE (NCT02390063), in intermediate risk prostate cancer patients. Based on encouraging safety and exceptional T cell immunogenicity of the VANCE study, the phase I/II trial, ADVANCE (NCT03815942) is being undertaken to test the immunotherapy safety and efficacy in combination with PD-1 blockade in intermediate risk disease and metastatic prostate cancer. Methods: Study design: ADVANCE, an open label non-randomised phase I/II study, will recruit 12 patients with intermediate-risk prostate cancer patients (Gleason score ≤ 7, local tumour stage ≤T3c, PSA≤ 20 ng/ml) scheduled to undergo radical prostatectomy (Cohort 1) and 24 mCRPC patients with disease progression on anti-androgen therapy with either enzalutamide or abiraterone (Cohort 2). Cohort 1 will receive one cycle of ChAdOx1-MVA 5T4 immunotherapy and a single nivolumab infusion. Cohort 2 will receive 2 cycles of ChAdOx1-MVA 5T4 vaccination and three nivolumab infusions. Primary endpoint: Cohort 1 - PSA change from baseline to surgery, Cohort 2 – composite response rate measured as either ≥50% reduction of circulating tumour DNA or ≥50% serum PSA decrease from baseline at 24-week assessment and the maximal response rate. Secondary and exploratory endpoints include 5T4-specific immune response in the periphery, progression-free and overall survival and reduction of circulating tumour cells. 23 of planned 24 patients have been enrolled in Cohort 2. Enrolment to the Cohort 1 is ongoing. The data analysis is expected to be completed by Q4 2020 for Cohort 2. Clinical trial information: NCT03815942 .
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Affiliation(s)
- Mark Tuthill
- The Jenner Institute, University of Oxford, Oxford, United Kingdom
| | | | - Richard John Bryant
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Ian Poulton
- The Jenner Institute, University of Oxford, Oxford, United Kingdom
| | - Emily Pollock
- Department of Immunobiology, Guy's Hospital, London, United Kingdom
| | - Lucy Carter
- The Jenner Institute, University of Oxford, Oxford, United Kingdom
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | | | | | - James WF Catto
- Academic Urology Unit, University of Sheffield, Sheffield, United Kingdom
| | - Tom Evans
- Vaccitech ltd, Oxford, United Kingdom
| | | | | | - Freddie Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Adrian V.S. Hill
- The Jenner Institute, University of Oxford, Oxford, United Kingdom
| | - Irina Redchenko
- The Jenner Institute, University of Oxford, Oxford, United Kingdom
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40
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Rao SR, Alham NK, Upton E, McIntyre S, Bryant RJ, Cerundolo L, Bowes E, Jones S, Browne M, Mills I, Lamb A, Tomlinson I, Wedge D, Browning L, Sirinukunwattana K, Palles C, Hamdy FC, Rittscher J, Verrill C. Detailed Molecular and Immune Marker Profiling of Archival Prostate Cancer Samples Reveals an Inverse Association between TMPRSS2:ERG Fusion Status and Immune Cell Infiltration. J Mol Diagn 2020; 22:652-669. [PMID: 32229180 DOI: 10.1016/j.jmoldx.2020.02.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 08/28/2019] [Accepted: 02/04/2020] [Indexed: 01/02/2023] Open
Abstract
Prostate cancer is a significant global health issue, and limitations to current patient management pathways often result in overtreatment or undertreatment. New ways to stratify patients are urgently needed. We conducted a feasibility study of such novel assessments, looking for associations between genomic changes and lymphocyte infiltration. An innovative workflow using an in-house targeted sequencing panel, immune cell profiling using an image analysis pipeline, RNA sequencing, and exome sequencing in select cases was tested. Gene fusions were profiled by RNA sequencing in 27 of 27 cases, and a significantly higher tumor-infiltrating lymphocyte (TIL) count was noted in tumors without a TMPRSS2:ERG fusion compared with those with the fusion (P = 0.01). Although this finding was not replicated in a larger validation set (n = 436) of The Cancer Genome Atlas images, there was a trend in the same direction. Differential expression analysis of TIL-high and TIL-low tumors revealed the enrichment of both innate and adaptive immune response pathways. Mutations in mismatch repair genes (MLH1 and MSH6 mutations in 1 of 27 cases) were identified. We describe a potential immune escape mechanism in TMPRSS2:ERG fusion-positive tumors. Detailed profiling, as shown herein, can provide novel insights into tumor biology. Likely differences with findings with other cohorts are related to methods used to define region of interest, but this warrants further study in a larger cohort.
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Affiliation(s)
- Srinivasa R Rao
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Nasullah K Alham
- Big Data Institute, University of Oxford, Old Road Campus, Oxford, United Kingdom; Oxford National Institute for Health Research Oxford Biomedical Research Centre, Oxford, United Kingdom
| | - Elysia Upton
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Stacey McIntyre
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Richard J Bryant
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Lucia Cerundolo
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Emma Bowes
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom; Oxford National Institute for Health Research Oxford Biomedical Research Centre, Oxford, United Kingdom
| | - Stephanie Jones
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Molly Browne
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom; Oxford National Institute for Health Research Oxford Biomedical Research Centre, Oxford, United Kingdom
| | - Ian Mills
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Alastair Lamb
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Ian Tomlinson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - David Wedge
- Big Data Institute, University of Oxford, Old Road Campus, Oxford, United Kingdom; Oxford National Institute for Health Research Oxford Biomedical Research Centre, Oxford, United Kingdom
| | - Lisa Browning
- Oxford National Institute for Health Research Oxford Biomedical Research Centre, Oxford, United Kingdom; Department of Cellular Pathology, Oxford University Hospitals National Health Service Foundation Trust, John Radcliffe Hospital, Oxford, United Kingdom
| | | | - Claire Palles
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Freddie C Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Jens Rittscher
- Big Data Institute, University of Oxford, Old Road Campus, Oxford, United Kingdom
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom; Oxford National Institute for Health Research Oxford Biomedical Research Centre, Oxford, United Kingdom; Department of Cellular Pathology, Oxford University Hospitals National Health Service Foundation Trust, John Radcliffe Hospital, Oxford, United Kingdom.
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Williams BJ, Brettle D, Aslam M, Barrett P, Bryson G, Cross S, Snead D, Verrill C, Clarke E, Wright A, Treanor D. Guidance for Remote Reporting of Digital Pathology Slides During Periods of Exceptional Service Pressure: An Emergency Response from the UK Royal College of Pathologists. J Pathol Inform 2020; 11:12. [PMID: 32477618 PMCID: PMC7245343 DOI: 10.4103/jpi.jpi_23_20] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 03/27/2020] [Accepted: 03/31/2020] [Indexed: 12/12/2022] Open
Abstract
Pathology departments must rise to new staffing challenges caused by the coronavirus disease-19 pandemic and may need to work more flexibly for the foreseeable future. In light of this, many pathologists and departments are considering the merits of remote or home reporting of digital cases. While some individuals have experience of this, little work has been done to determine optimum conditions for home reporting, including technical and training considerations. In this publication produced in response to the pandemic, we provide information regarding risk assessment of home reporting of digital slides, summarize available information on specifications for home reporting computing equipment, and share access to a novel point-of-use quality assurance tool for assessing the suitability of home reporting screens for digital slide diagnosis. We hope this study provides a useful starting point and some practical guidance in a difficult time. This study forms the basis of the guidance issued by the Royal College of Pathologists, available at: https://www.rcpath.org/uploads/assets/626ead77-d7dd-42e1-949988e43dc84c97/RCPath-guidance-for-remote-digital-pathology.pdf.
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Affiliation(s)
| | - David Brettle
- Leeds Teaching Hospitals NHS Trust, Leeds, UK
- University of Leeds, Leeds, UK
| | | | - Paul Barrett
- County Durham and Darlington NHS Foundation Trust, Darlington, UK
| | | | | | - David Snead
- University Hospitals Coventry and Warwickshire, Coventry, UK
- University of Warwick, Warwick, UK
| | - Clare Verrill
- Nuffield Department of Surgical Sciences and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Emily Clarke
- Leeds Teaching Hospitals NHS Trust, Leeds, UK
- University of Leeds, Leeds, UK
| | | | - Darren Treanor
- Leeds Teaching Hospitals NHS Trust, Leeds, UK
- University of Leeds, Leeds, UK
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Chow* K, Ryan A, Agarwal D, Bolton D, Chan Y, Dundee P, Frydenberg M, Furrer M, Goad J, Gyomber D, Hanegbi U, Harewood L, King D, Lawrentschuk N, Lamb A, Liodakis P, Moon D, Murphy D, Peters J, Ruljancich P, Verrill C, Webb D, Wong LM, Zargar H, Costello A, Hovens C, Corcoran N. MP64-09 DUCTAL ADENOCARCINOMA OF THE PROSTATE IS ASSOCIATED WITH SHORTER METASTASIS-FREE SURVIVAL. J Urol 2020. [DOI: 10.1097/ju.0000000000000939.09] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Lakhoo K, Davies J, Chakraborty S, Berg S, Tennyson R, Fowler D, Manek S, Verrill C, Lane S. Correction to: Development of a new reproductive tissue cryopreservation clinical service for children: the Oxford programme. Pediatr Surg Int 2020; 36:537. [PMID: 32030460 PMCID: PMC7645559 DOI: 10.1007/s00383-020-04624-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
In the published version, the Acknowledgements section was missing a funding note of co-author Dr C Verrill. The corrected version should read as follows.
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Affiliation(s)
- K. Lakhoo
- Department of Paediatric Surgery, University of Oxford and Oxford University Hospitals, Oxford, UK ,Nuffield Department of Surgery, Oxford University and Oxford University Hospitals, Headley Way, Oxford, OX39DA UK
| | - J. Davies
- Oxford Tissue Bank, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - S. Chakraborty
- Department of Paediatric Radiology, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - S. Berg
- Department of Paediatric Anaesthesia, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - R. Tennyson
- Department of Psychology, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - D. Fowler
- Department of Cellular Pathology, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - S. Manek
- Department of Cellular Pathology, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - C. Verrill
- Department of Cellular Pathology, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - S. Lane
- Department of Paediatrics and Child Health, University of Oxford and Oxford University Hospitals, Oxford, UK
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Aaltonen LA, Abascal F, Abeshouse A, Aburatani H, Adams DJ, Agrawal N, Ahn KS, Ahn SM, Aikata H, Akbani R, Akdemir KC, Al-Ahmadie H, Al-Sedairy ST, Al-Shahrour F, Alawi M, Albert M, Aldape K, Alexandrov LB, Ally A, Alsop K, Alvarez EG, Amary F, Amin SB, Aminou B, Ammerpohl O, Anderson MJ, Ang Y, Antonello D, Anur P, Aparicio S, Appelbaum EL, Arai Y, Aretz A, Arihiro K, Ariizumi SI, Armenia J, Arnould L, Asa S, Assenov Y, Atwal G, Aukema S, Auman JT, Aure MRR, Awadalla P, Aymerich M, Bader GD, Baez-Ortega A, Bailey MH, Bailey PJ, Balasundaram M, Balu S, Bandopadhayay P, Banks RE, Barbi S, Barbour AP, Barenboim J, Barnholtz-Sloan J, Barr H, Barrera E, Bartlett J, Bartolome J, Bassi C, Bathe OF, Baumhoer D, Bavi P, Baylin SB, Bazant W, Beardsmore D, Beck TA, Behjati S, Behren A, Niu B, Bell C, Beltran S, Benz C, Berchuck A, Bergmann AK, Bergstrom EN, Berman BP, Berney DM, Bernhart SH, Beroukhim R, Berrios M, Bersani S, Bertl J, Betancourt M, Bhandari V, Bhosle SG, Biankin AV, Bieg M, Bigner D, Binder H, Birney E, Birrer M, Biswas NK, Bjerkehagen B, Bodenheimer T, Boice L, Bonizzato G, De Bono JS, Boot A, Bootwalla MS, Borg A, Borkhardt A, Boroevich KA, Borozan I, Borst C, Bosenberg M, Bosio M, Boultwood J, Bourque G, Boutros PC, Bova GS, Bowen DT, Bowlby R, Bowtell DDL, Boyault S, Boyce R, Boyd J, Brazma A, Brennan P, Brewer DS, Brinkman AB, Bristow RG, Broaddus RR, Brock JE, Brock M, Broeks A, Brooks AN, Brooks D, Brors B, Brunak S, Bruxner TJC, Bruzos AL, Buchanan A, Buchhalter I, Buchholz C, Bullman S, Burke H, Burkhardt B, Burns KH, Busanovich J, Bustamante CD, Butler AP, Butte AJ, Byrne NJ, Børresen-Dale AL, Caesar-Johnson SJ, Cafferkey A, Cahill D, Calabrese C, Caldas C, Calvo F, Camacho N, Campbell PJ, Campo E, Cantù C, Cao S, Carey TE, Carlevaro-Fita J, Carlsen R, Cataldo I, Cazzola M, Cebon J, Cerfolio R, Chadwick DE, Chakravarty D, Chalmers D, Chan CWY, Chan K, Chan-Seng-Yue M, Chandan VS, Chang DK, Chanock SJ, Chantrill LA, Chateigner A, Chatterjee N, Chayama K, Chen HW, Chen J, Chen K, Chen Y, Chen Z, Cherniack AD, Chien J, Chiew YE, Chin SF, Cho J, Cho S, Choi JK, Choi W, Chomienne C, Chong Z, Choo SP, Chou A, Christ AN, Christie EL, Chuah E, Cibulskis C, Cibulskis K, Cingarlini S, Clapham P, Claviez A, Cleary S, Cloonan N, Cmero M, Collins CC, Connor AA, Cooke SL, Cooper CS, Cope L, Corbo V, Cordes MG, Cordner SM, Cortés-Ciriano I, Covington K, Cowin PA, Craft B, Craft D, Creighton CJ, Cun Y, Curley E, Cutcutache I, Czajka K, Czerniak B, Dagg RA, Danilova L, Davi MV, Davidson NR, Davies H, Davis IJ, Davis-Dusenbery BN, Dawson KJ, De La Vega FM, De Paoli-Iseppi R, Defreitas T, Tos APD, Delaneau O, Demchok JA, Demeulemeester J, Demidov GM, Demircioğlu D, Dennis NM, Denroche RE, Dentro SC, Desai N, Deshpande V, Deshwar AG, Desmedt C, Deu-Pons J, Dhalla N, Dhani NC, Dhingra P, Dhir R, DiBiase A, Diamanti K, Ding L, Ding S, Dinh HQ, Dirix L, Doddapaneni H, Donmez N, Dow MT, Drapkin R, Drechsel O, Drews RM, Serge S, Dudderidge T, Dueso-Barroso A, Dunford AJ, Dunn M, Dursi LJ, Duthie FR, Dutton-Regester K, Eagles J, Easton DF, Edmonds S, Edwards PA, Edwards SE, Eeles RA, Ehinger A, Eils J, Eils R, El-Naggar A, Eldridge M, Ellrott K, Erkek S, Escaramis G, Espiritu SMG, Estivill X, Etemadmoghadam D, Eyfjord JE, Faltas BM, Fan D, Fan Y, Faquin WC, Farcas C, Fassan M, Fatima A, Favero F, Fayzullaev N, Felau I, Fereday S, Ferguson ML, Ferretti V, Feuerbach L, Field MA, Fink JL, Finocchiaro G, Fisher C, Fittall MW, Fitzgerald A, Fitzgerald RC, Flanagan AM, Fleshner NE, Flicek P, Foekens JA, Fong KM, Fonseca NA, Foster CS, Fox NS, Fraser M, Frazer S, Frenkel-Morgenstern M, Friedman W, Frigola J, Fronick CC, Fujimoto A, Fujita M, Fukayama M, Fulton LA, Fulton RS, Furuta M, Futreal PA, Füllgrabe A, Gabriel SB, Gallinger S, Gambacorti-Passerini C, Gao J, Gao S, Garraway L, Garred Ø, Garrison E, Garsed DW, Gehlenborg N, Gelpi JLL, George J, Gerhard DS, Gerhauser C, Gershenwald JE, Gerstein M, Gerstung M, Getz G, Ghori M, Ghossein R, Giama NH, Gibbs RA, Gibson B, Gill AJ, Gill P, Giri DD, Glodzik D, Gnanapragasam VJ, Goebler ME, Goldman MJ, Gomez C, Gonzalez S, Gonzalez-Perez A, Gordenin DA, Gossage J, Gotoh K, Govindan R, Grabau D, Graham JS, Grant RC, Green AR, Green E, Greger L, Grehan N, Grimaldi S, Grimmond SM, Grossman RL, Grundhoff A, Gundem G, Guo Q, Gupta M, Gupta S, Gut IG, Gut M, Göke J, Ha G, Haake A, Haan D, Haas S, Haase K, Haber JE, Habermann N, Hach F, Haider S, Hama N, Hamdy FC, Hamilton A, Hamilton MP, Han L, Hanna GB, Hansmann M, Haradhvala NJ, Harismendy O, Harliwong I, Harmanci AO, Harrington E, Hasegawa T, Haussler D, Hawkins S, Hayami S, Hayashi S, Hayes DN, Hayes SJ, Hayward NK, Hazell S, He Y, Heath AP, Heath SC, Hedley D, Hegde AM, Heiman DI, Heinold MC, Heins Z, Heisler LE, Hellstrom-Lindberg E, Helmy M, Heo SG, Hepperla AJ, Heredia-Genestar JM, Herrmann C, Hersey P, Hess JM, Hilmarsdottir H, Hinton J, Hirano S, Hiraoka N, Hoadley KA, Hobolth A, Hodzic E, Hoell JI, Hoffmann S, Hofmann O, Holbrook A, Holik AZ, Hollingsworth MA, Holmes O, Holt RA, Hong C, Hong EP, Hong JH, Hooijer GK, Hornshøj H, Hosoda F, Hou Y, Hovestadt V, Howat W, Hoyle AP, Hruban RH, Hu J, Hu T, Hua X, Huang KL, Huang M, Huang MN, Huang V, Huang Y, Huber W, Hudson TJ, Hummel M, Hung JA, Huntsman D, Hupp TR, Huse J, Huska MR, Hutter B, Hutter CM, Hübschmann D, Iacobuzio-Donahue CA, Imbusch CD, Imielinski M, Imoto S, Isaacs WB, Isaev K, Ishikawa S, Iskar M, Islam SMA, Ittmann M, Ivkovic S, Izarzugaza JMG, Jacquemier J, Jakrot V, Jamieson NB, Jang GH, Jang SJ, Jayaseelan JC, Jayasinghe R, Jefferys SR, Jegalian K, Jennings JL, Jeon SH, Jerman L, Ji Y, Jiao W, Johansson PA, Johns AL, Johns J, Johnson R, Johnson TA, Jolly C, Joly Y, Jonasson JG, Jones CD, Jones DR, Jones DTW, Jones N, Jones SJM, Jonkers J, Ju YS, Juhl H, Jung J, Juul M, Juul RI, Juul S, Jäger N, Kabbe R, Kahles A, Kahraman A, Kaiser VB, Kakavand H, Kalimuthu S, von Kalle C, Kang KJ, Karaszi K, Karlan B, Karlić R, Karsch D, Kasaian K, Kassahn KS, Katai H, Kato M, Katoh H, Kawakami Y, Kay JD, Kazakoff SH, Kazanov MD, Keays M, Kebebew E, Kefford RF, Kellis M, Kench JG, Kennedy CJ, Kerssemakers JNA, Khoo D, Khoo V, Khuntikeo N, Khurana E, Kilpinen H, Kim HK, Kim HL, Kim HY, Kim H, Kim J, Kim J, Kim JK, Kim Y, King TA, Klapper W, Kleinheinz K, Klimczak LJ, Knappskog S, Kneba M, Knoppers BM, Koh Y, Komorowski J, Komura D, Komura M, Kong G, Kool M, Korbel JO, Korchina V, Korshunov A, Koscher M, Koster R, Kote-Jarai Z, Koures A, Kovacevic M, Kremeyer B, Kretzmer H, Kreuz M, Krishnamurthy S, Kube D, Kumar K, Kumar P, Kumar S, Kumar Y, Kundra R, Kübler K, Küppers R, Lagergren J, Lai PH, Laird PW, Lakhani SR, Lalansingh CM, Lalonde E, Lamaze FC, Lambert A, Lander E, Landgraf P, Landoni L, Langerød A, Lanzós A, Larsimont D, Larsson E, Lathrop M, Lau LMS, Lawerenz C, Lawlor RT, Lawrence MS, Lazar AJ, Lazic AM, Le X, Lee D, Lee D, Lee EA, Lee HJ, Lee JJK, Lee JY, Lee J, Lee MTM, Lee-Six H, Lehmann KV, Lehrach H, Lenze D, Leonard CR, Leongamornlert DA, Leshchiner I, Letourneau L, Letunic I, Levine DA, Lewis L, Ley T, Li C, Li CH, Li HI, Li J, Li L, Li S, Li S, Li X, Li X, Li X, Li Y, Liang H, Liang SB, Lichter P, Lin P, Lin Z, Linehan WM, Lingjærde OC, Liu D, Liu EM, Liu FFF, Liu F, Liu J, Liu X, Livingstone J, Livitz D, Livni N, Lochovsky L, Loeffler M, Long GV, Lopez-Guillermo A, Lou S, Louis DN, Lovat LB, Lu Y, Lu YJ, Lu Y, Luchini C, Lungu I, Luo X, Luxton HJ, Lynch AG, Lype L, López C, López-Otín C, Ma EZ, Ma Y, MacGrogan G, MacRae S, Macintyre G, Madsen T, Maejima K, Mafficini A, Maglinte DT, Maitra A, Majumder PP, Malcovati L, Malikic S, Malleo G, Mann GJ, Mantovani-Löffler L, Marchal K, Marchegiani G, Mardis ER, Margolin AA, Marin MG, Markowetz F, Markowski J, Marks J, Marques-Bonet T, Marra MA, Marsden L, Martens JWM, Martin S, Martin-Subero JI, Martincorena I, Martinez-Fundichely A, Maruvka YE, Mashl RJ, Massie CE, Matthew TJ, Matthews L, Mayer E, Mayes S, Mayo M, Mbabaali F, McCune K, McDermott U, McGillivray PD, McLellan MD, McPherson JD, McPherson JR, McPherson TA, Meier SR, Meng A, Meng S, Menzies A, Merrett ND, Merson S, Meyerson M, Meyerson W, Mieczkowski PA, Mihaiescu GL, Mijalkovic S, Mikkelsen T, Milella M, Mileshkin L, Miller CA, Miller DK, Miller JK, Mills GB, Milovanovic A, Minner S, Miotto M, Arnau GM, Mirabello L, Mitchell C, Mitchell TJ, Miyano S, Miyoshi N, Mizuno S, Molnár-Gábor F, Moore MJ, Moore RA, Morganella S, Morris QD, Morrison C, Mose LE, Moser CD, Muiños F, Mularoni L, Mungall AJ, Mungall K, Musgrove EA, Mustonen V, Mutch D, Muyas F, Muzny DM, Muñoz A, Myers J, Myklebost O, Möller P, Nagae G, Nagrial AM, Nahal-Bose HK, Nakagama H, Nakagawa H, Nakamura H, Nakamura T, Nakano K, Nandi T, Nangalia J, Nastic M, Navarro A, Navarro FCP, Neal DE, Nettekoven G, Newell F, Newhouse SJ, Newton Y, Ng AWT, Ng A, Nicholson J, Nicol D, Nie Y, Nielsen GP, Nielsen MM, Nik-Zainal S, Noble MS, Nones K, Northcott PA, Notta F, O’Connor BD, O’Donnell P, O’Donovan M, O’Meara S, O’Neill BP, O’Neill JR, Ocana D, Ochoa A, Oesper L, Ogden C, Ohdan H, Ohi K, Ohno-Machado L, Oien KA, Ojesina AI, Ojima H, Okusaka T, Omberg L, Ong CK, Ossowski S, Ott G, Ouellette BFF, P’ng C, Paczkowska M, Paiella S, Pairojkul C, Pajic M, Pan-Hammarström Q, Papaemmanuil E, Papatheodorou I, Paramasivam N, Park JW, Park JW, Park K, Park K, Park PJ, Parker JS, Parsons SL, Pass H, Pasternack D, Pastore A, Patch AM, Pauporté I, Pea A, Pearson JV, Pedamallu CS, Pedersen JS, Pederzoli P, Peifer M, Pennell NA, Perou CM, Perry MD, Petersen GM, Peto M, Petrelli N, Petryszak R, Pfister SM, Phillips M, Pich O, Pickett HA, Pihl TD, Pillay N, Pinder S, Pinese M, Pinho AV, Pitkänen E, Pivot X, Piñeiro-Yáñez E, Planko L, Plass C, Polak P, Pons T, Popescu I, Potapova O, Prasad A, Preston SR, Prinz M, Pritchard AL, Prokopec SD, Provenzano E, Puente XS, Puig S, Puiggròs M, Pulido-Tamayo S, Pupo GM, Purdie CA, Quinn MC, Rabionet R, Rader JS, Radlwimmer B, Radovic P, Raeder B, Raine KM, Ramakrishna M, Ramakrishnan K, Ramalingam S, Raphael BJ, Rathmell WK, Rausch T, Reifenberger G, Reimand J, Reis-Filho J, Reuter V, Reyes-Salazar I, Reyna MA, Reynolds SM, Rheinbay E, Riazalhosseini Y, Richardson AL, Richter J, Ringel M, Ringnér M, Rino Y, Rippe K, Roach J, Roberts LR, Roberts ND, Roberts SA, Robertson AG, Robertson AJ, Rodriguez JB, Rodriguez-Martin B, Rodríguez-González FG, Roehrl MHA, Rohde M, Rokutan H, Romieu G, Rooman I, Roques T, Rosebrock D, Rosenberg M, Rosenstiel PC, Rosenwald A, Rowe EW, Royo R, Rozen SG, Rubanova Y, Rubin MA, Rubio-Perez C, Rudneva VA, Rusev BC, Ruzzenente A, Rätsch G, Sabarinathan R, Sabelnykova VY, Sadeghi S, Sahinalp SC, Saini N, Saito-Adachi M, Saksena G, Salcedo A, Salgado R, Salichos L, Sallari R, Saller C, Salvia R, Sam M, Samra JS, Sanchez-Vega F, Sander C, Sanders G, Sarin R, Sarrafi I, Sasaki-Oku A, Sauer T, Sauter G, Saw RPM, Scardoni M, Scarlett CJ, Scarpa A, Scelo G, Schadendorf D, Schein JE, Schilhabel MB, Schlesner M, Schlomm T, Schmidt HK, Schramm SJ, Schreiber S, Schultz N, Schumacher SE, Schwarz RF, Scolyer RA, Scott D, Scully R, Seethala R, Segre AV, Selander I, Semple CA, Senbabaoglu Y, Sengupta S, Sereni E, Serra S, Sgroi DC, Shackleton M, Shah NC, Shahabi S, Shang CA, Shang P, Shapira O, Shelton T, Shen C, Shen H, Shepherd R, Shi R, Shi Y, Shiah YJ, Shibata T, Shih J, Shimizu E, Shimizu K, Shin SJ, Shiraishi Y, Shmaya T, Shmulevich I, Shorser SI, Short C, Shrestha R, Shringarpure SS, Shriver C, Shuai S, Sidiropoulos N, Siebert R, Sieuwerts AM, Sieverling L, Signoretti S, Sikora KO, Simbolo M, Simon R, Simons JV, Simpson JT, Simpson PT, Singer S, Sinnott-Armstrong N, Sipahimalani P, Skelly TJ, Smid M, Smith J, Smith-McCune K, Socci ND, Sofia HJ, Soloway MG, Song L, Sood AK, Sothi S, Sotiriou C, Soulette CM, Span PN, Spellman PT, Sperandio N, Spillane AJ, Spiro O, Spring J, Staaf J, Stadler PF, Staib P, Stark SG, Stebbings L, Stefánsson ÓA, Stegle O, Stein LD, Stenhouse A, Stewart C, Stilgenbauer S, Stobbe MD, Stratton MR, Stretch JR, Struck AJ, Stuart JM, Stunnenberg HG, Su H, Su X, Sun RX, Sungalee S, Susak H, Suzuki A, Sweep F, Szczepanowski M, Sültmann H, Yugawa T, Tam A, Tamborero D, Tan BKT, Tan D, Tan P, Tanaka H, Taniguchi H, Tanskanen TJ, Tarabichi M, Tarnuzzer R, Tarpey P, Taschuk ML, Tatsuno K, Tavaré S, Taylor DF, Taylor-Weiner A, Teague JW, Teh BT, Tembe V, Temes J, Thai K, Thayer SP, Thiessen N, Thomas G, Thomas S, Thompson A, Thompson AM, Thompson JFF, Thompson RH, Thorne H, Thorne LB, Thorogood A, Tiao G, Tijanic N, Timms LE, Tirabosco R, Tojo M, Tommasi S, Toon CW, Toprak UH, Torrents D, Tortora G, Tost J, Totoki Y, Townend D, Traficante N, Treilleux I, Trotta JR, Trümper LHP, Tsao M, Tsunoda T, Tubio JMC, Tucker O, Turkington R, Turner DJ, Tutt A, Ueno M, Ueno NT, Umbricht C, Umer HM, Underwood TJ, Urban L, Urushidate T, Ushiku T, Uusküla-Reimand L, Valencia A, Van Den Berg DJ, Van Laere S, Van Loo P, Van Meir EG, Van den Eynden GG, Van der Kwast T, Vasudev N, Vazquez M, Vedururu R, Veluvolu U, Vembu S, Verbeke LPC, Vermeulen P, Verrill C, Viari A, Vicente D, Vicentini C, VijayRaghavan K, Viksna J, Vilain RE, Villasante I, Vincent-Salomon A, Visakorpi T, Voet D, Vyas P, Vázquez-García I, Waddell NM, Waddell N, Wadelius C, Wadi L, Wagener R, Wala JA, Wang J, Wang J, Wang L, Wang Q, Wang W, Wang Y, Wang Z, Waring PM, Warnatz HJ, Warrell J, Warren AY, Waszak SM, Wedge DC, Weichenhan D, Weinberger P, Weinstein JN, Weischenfeldt J, Weisenberger DJ, Welch I, Wendl MC, Werner J, Whalley JP, Wheeler DA, Whitaker HC, Wigle D, Wilkerson MD, Williams A, Wilmott JS, Wilson GW, Wilson JM, Wilson RK, Winterhoff B, Wintersinger JA, Wiznerowicz M, Wolf S, Wong BH, Wong T, Wong W, Woo Y, Wood S, Wouters BG, Wright AJ, Wright DW, Wright MH, Wu CL, Wu DY, Wu G, Wu J, Wu K, Wu Y, Wu Z, Xi L, Xia T, Xiang Q, Xiao X, Xing R, Xiong H, Xu Q, Xu Y, Xue H, Yachida S, Yakneen S, Yamaguchi R, Yamaguchi TN, Yamamoto M, Yamamoto S, Yamaue H, Yang F, Yang H, Yang JY, Yang L, Yang L, Yang S, Yang TP, Yang Y, Yao X, Yaspo ML, Yates L, Yau C, Ye C, Ye K, Yellapantula VD, Yoon CJ, Yoon SS, Yousif F, Yu J, Yu K, Yu W, Yu Y, Yuan K, Yuan Y, Yuen D, Yung CK, Zaikova O, Zamora J, Zapatka M, Zenklusen JC, Zenz T, Zeps N, Zhang CZ, Zhang F, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Zhang X, Zhang X, Zhang Y, Zhang Z, Zhao Z, Zheng L, Zheng X, Zhou W, Zhou Y, Zhu B, Zhu H, Zhu J, Zhu S, Zou L, Zou X, deFazio A, van As N, van Deurzen CHM, van de Vijver MJ, van’t Veer L, von Mering C. Pan-cancer analysis of whole genomes. Nature 2020; 578:82-93. [PMID: 32025007 PMCID: PMC7025898 DOI: 10.1038/s41586-020-1969-6] [Citation(s) in RCA: 1435] [Impact Index Per Article: 358.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Accepted: 12/11/2019] [Indexed: 02/07/2023]
Abstract
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.
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Abd Hamid M, Colin-York H, Khalid-Alham N, Browne M, Cerundolo L, Chen JL, Yao X, Rosendo-Machado S, Waugh C, Maldonado-Perez D, Bowes E, Verrill C, Cerundolo V, Conlon CP, Fritzsche M, Peng Y, Dong T. Self-Maintaining CD103 + Cancer-Specific T Cells Are Highly Energetic with Rapid Cytotoxic and Effector Responses. Cancer Immunol Res 2020; 8:203-216. [PMID: 31771983 PMCID: PMC7611226 DOI: 10.1158/2326-6066.cir-19-0554] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 09/19/2019] [Accepted: 11/15/2019] [Indexed: 11/16/2022]
Abstract
Enrichment of CD103+ tumor-infiltrating T lymphocytes (TIL) is associated with improved outcomes in patients. However, the characteristics of human CD103+ cytotoxic CD8+ T cells (CTL) and their role in tumor control remain unclear. We investigated the features and antitumor mechanisms of CD103+ CTLs by assessing T-cell receptor (TCR)-matched CD103+ and CD103- cancer-specific CTL immunity in vitro and its immunophenotype ex vivo Interestingly, we found that differentiated CD103+ cancer-specific CTLs expressed the active form of TGFβ1 to continually self-regulate CD103 expression, without relying on external TGFβ1-producing cells. The presence of CD103 on CTLs improved TCR antigen sensitivity, which enabled faster cancer recognition and rapid antitumor cytotoxicity. These CD103+ CTLs had elevated energetic potential and faster migration capacity. However, they had increased inhibitory receptor coexpression and elevated T-cell apoptosis following prolonged cancer exposure. Our data provide fundamental insights into the properties of matured human CD103+ cancer-specific CTLs, which could have important implications for future designs of tissue-localized cancer immunotherapy strategies.
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Affiliation(s)
- Megat Abd Hamid
- Chinese Academy of Medical Sciences (CAMS) Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Medical Research Council (MRC) Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Huw Colin-York
- Medical Research Council (MRC) Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Nasullah Khalid-Alham
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
- Oxford National Institute of Health Research (NIHR) Biomedical Research Centre, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Molly Browne
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Lucia Cerundolo
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Ji-Li Chen
- Medical Research Council (MRC) Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Xuan Yao
- Chinese Academy of Medical Sciences (CAMS) Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Medical Research Council (MRC) Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Samara Rosendo-Machado
- Medical Research Council (MRC) Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Craig Waugh
- Flow Cytometry Facility, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - David Maldonado-Perez
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Emma Bowes
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Clare Verrill
- Oxford National Institute of Health Research (NIHR) Biomedical Research Centre, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Vincenzo Cerundolo
- Chinese Academy of Medical Sciences (CAMS) Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Medical Research Council (MRC) Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Christopher P Conlon
- Chinese Academy of Medical Sciences (CAMS) Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Marco Fritzsche
- Medical Research Council (MRC) Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, United Kingdom
| | - Yanchun Peng
- Chinese Academy of Medical Sciences (CAMS) Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Medical Research Council (MRC) Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Tao Dong
- Chinese Academy of Medical Sciences (CAMS) Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
- Medical Research Council (MRC) Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
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Turnquist C, Roberts-Gant S, Hemsworth H, White K, Browning L, Rees G, Roskell D, Verrill C. On the Edge of a Digital Pathology Transformation: Views from a Cellular Pathology Laboratory Focus Group. J Pathol Inform 2019; 10:37. [PMID: 31897354 PMCID: PMC6909548 DOI: 10.4103/jpi.jpi_38_19] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 07/08/2019] [Indexed: 01/18/2023] Open
Abstract
Introduction: Digital pathology has the potential to revolutionize the way clinical diagnoses are made while improving safety and quality. With a few notable exceptions in the UK, few National Health Service (NHS) departments have deployed digital pathology platforms. Thus, in the next few years, many departments are anticipated to undergo the transition to digital pathology. In this period of transition, capturing attitudes and experiences can elucidate issues to be addressed and foster collaboration between NHS Trusts. This study aims to qualitatively ascertain the benefits and challenges of transitioning to digital pathology from the perspectives of pathologists and biomedical scientists in a department about to undergo the transition from diagnostic reporting via traditional microscopy to digital pathology. Methods: A focus group discussion was held in the setting of a large NHS teaching hospital's cellular pathology department which was on the brink of transitioning to digital pathology. A set of open questions were developed and posed to a group of pathologists and biomedical scientists in a focus group setting. Notes of the discussion were made along with an audio recording with permission. The discussion was subsequently turned into a series of topic headings and analyzed using content analysis. Results: Identified benefits of digital pathology included enhanced collaboration, teaching, cost savings, research, growth of specialty, multidisciplinary teams, and patient-centered care. Barriers to transitioning to digital pathology included standardization, validation, national implementation, storage and backups, training, logistical implementation, cost-effectiveness, privacy, and legality. Conclusion: Many benefits of digital pathology were identified, but key barriers need to be addressed in order to fully implement digital pathology on a trust and national level.
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Affiliation(s)
- Casmir Turnquist
- University of Oxford Medical School, John Radcliffe Hospital, Oxford, UK
| | - Sharon Roberts-Gant
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Helen Hemsworth
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Kieron White
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Lisa Browning
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Gabrielle Rees
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Derek Roskell
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Clare Verrill
- Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.,Nuffield Department of Surgical Sciences, Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
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47
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Lakhoo K, Davies J, Chakraborty S, Berg S, Tennyson R, Fowler D, Manek S, Verrill C, Lane S. Development of a new reproductive tissue cryopreservation clinical service for children: the Oxford programme. Pediatr Surg Int 2019; 35:1271-1278. [PMID: 31267143 PMCID: PMC6800834 DOI: 10.1007/s00383-019-04503-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/21/2019] [Indexed: 12/04/2022]
Abstract
PURPOSE This article describes the development of a new reproductive tissue cryopreservation clinical service for children at high risk of infertility in the NHS during times of severe financial constraints in the health service. METHOD A development plan with two phases was drawn up. Phase 1 restricted the service to childhood cancer patients referred to the Oxford Paediatric Oncology and Haematology Principle Treatment Centre. It was estimated that there would be 10 patients/year and used existing staff and facilities from paediatric oncology, surgery, anaesthetics radiology, pathology, psychology, teenage-young adult gynaecology, and an existing Human Tissue Authority tissue bank with a licence for storage of tissue under a Human Sector Licence. Phase 2 extended the service to include children and young adults across England, Wales and Ireland-patients from Scotland having access to a research programme in Edinburgh. The main challenge in phase 2 being resources and the need for patients to be able to be treated as close to home as safely as possible. RESULTS The Oxford team developed information resources and eligibility criteria based on published best practice, referral and treatment pathways, multidisciplinary team meetings, a network of third party sites, and a dedicated case management and database. As the programme expanded, the Oxford team was able to justify to management the need for a dedicated theatre list. Patient feedback through questionnaires, qualitative work conducted as part of a Ph.D. thesis as well as direct patient stories and interviews in TV, and radio features underpins the positive impact the programme has on patients and their families. CONCLUSION The Oxford Reproductive Cryopreservation programme delivers fertility preservation treatment to children and young adults at high risk of infertility safely, effectively and as close to home as possible. The onward view is to apply for national funding for this programme for recognition and sustainability.
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Affiliation(s)
- K. Lakhoo
- Department of Paediatric Surgery, University of Oxford and Oxford University Hospitals, Oxford, UK ,Nuffield Department of Surgery, Oxford University and Oxford University Hospitals, Headley Way, Oxford, OX39DA UK
| | - J. Davies
- Oxford Tissue Bank, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - S. Chakraborty
- Department of Paediatric Radiology, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - S. Berg
- Department of Paediatric Anaesthesia, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - R. Tennyson
- Department of Psychology, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - D. Fowler
- Department of Cellular Pathology, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - S. Manek
- Department of Cellular Pathology, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - C. Verrill
- Department of Cellular Pathology, University of Oxford and Oxford University Hospitals, Oxford, UK
| | - S. Lane
- Department of Paediatrics and Child Health, University of Oxford and Oxford University Hospitals, Oxford, UK
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48
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Li X, Wang R, Fan P, Yao X, Qin L, Peng Y, Ma M, Asley N, Chang X, Feng Y, Hu Y, Zhang Y, Li C, Fanning G, Jones S, Verrill C, Maldonado-Perez D, Sopp P, Waugh C, Taylor S, Mcgowan S, Cerundolo V, Conlon C, McMichael A, Lu S, Wang X, Li N, Dong T. A Comprehensive Analysis of Key Immune Checkpoint Receptors on Tumor-Infiltrating T Cells From Multiple Types of Cancer. Front Oncol 2019; 9:1066. [PMID: 31709176 PMCID: PMC6823747 DOI: 10.3389/fonc.2019.01066] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 09/30/2019] [Indexed: 12/27/2022] Open
Abstract
Background: Cancer patients often display dysfunctional antitumor T-cell responses. Because noteworthy benefits of immune checkpoint pathway blockade, such as programmed cell death protein 1 (PD-1) inhibitors, have been achieved in multiple advanced cancers, the next critical question is which mono-blockade or combinatorial blockade regimens may reinvigorate antitumor T-cell immunity in those cancer patients while limiting immune-related adverse effects. Method: This study recruited, in total, 172 primary cancer patients (131 were blood-tumor-matched patients) who were treatment-naïve prior to the surgeries or biopsies covering the eight most prevalent types of cancer. With access to fresh surgical samples, this study simultaneously investigated the ex vivo expression level of eight known immune checkpoint receptors [PD-1, cytotoxic T-lymphocyte antigen-4 [CTLA-4], T-cell immunoglobulin and mucin-domain containing-3 [Tim-3], 2B4, killer cell lectin like receptor G1 [KLRG-1], TIGIT, B- and T-lymphocyte attenuator [BTLA], and CD160] on tumor-infiltrating T cells (TILs) and paired circulating T cells in blood from a 131-patient cohort. Results: We found increased an expression of PD-1 and Tim-3 but a decreased expression of BTLA on TILs when compared with peripheral blood from multiple types of cancer. Moreover, our co-expression analysis of key immune checkpoint receptors delineates "shared" subsets as PD-1+Tim-3+TIGIT+2B4+KLRG-1-CTLA-4- and PD-1+TIGIT+2B4+Tim-3-KLRG-1-CTLA-4- from bulk CD8 TILs. Furthermore, we found that a higher frequency of advanced differentiation stage T cells (CD27-CCR7-CD45RA-) among the "shared" subset (PD-1+Tim-3+TIGIT+2B4+KLRG-1-CTLA-4-) in bulk CD8 TILs was associated with poorly differentiated cancer type in cervical cancer patients. Conclusions: To our knowledge, our study is the first comprehensive analysis of key immune checkpoint receptors on T cells in treatment-naïve, primary cancer patients from the eight most prevalent types of cancer. These findings might provide useful information for future design of mono-blockade/combinatorial blockades and/or genetically modified T-cell immunotherapy.
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Affiliation(s)
- Xi Li
- Key Laboratory of Tumor Immunology and Radiation Therapy, Third Affiliated Hospital, Xinjiang Tumor Hospital, Chinese Academy of Medical Sciences (CAMS), Xinjiang Medical University, Ürümqi, China
- Nuffield Department of Medicine (NDM), Chinese Academy of Medical Sciences Oxford Institute (CAMS Oxford Institute), University of Oxford, Oxford, United Kingdom
- MRC Human Immunology Unit, Radcliffe Department of Medicine, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Rouzheng Wang
- Key Laboratory of Tumor Immunology and Radiation Therapy, Third Affiliated Hospital, Xinjiang Tumor Hospital, Chinese Academy of Medical Sciences (CAMS), Xinjiang Medical University, Ürümqi, China
- Nuffield Department of Medicine (NDM), Chinese Academy of Medical Sciences Oxford Institute (CAMS Oxford Institute), University of Oxford, Oxford, United Kingdom
- Third Affiliated Hospital, Xinjiang Tumor Hospital, Xinjiang Medical University, Ürümqi, China
| | - Peiwen Fan
- Key Laboratory of Tumor Immunology and Radiation Therapy, Third Affiliated Hospital, Xinjiang Tumor Hospital, Chinese Academy of Medical Sciences (CAMS), Xinjiang Medical University, Ürümqi, China
- Third Affiliated Hospital, Xinjiang Tumor Hospital, Xinjiang Medical University, Ürümqi, China
| | - Xuan Yao
- Nuffield Department of Medicine (NDM), Chinese Academy of Medical Sciences Oxford Institute (CAMS Oxford Institute), University of Oxford, Oxford, United Kingdom
- MRC Human Immunology Unit, Radcliffe Department of Medicine, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Ling Qin
- Beijing You'an Hospital, Capital Medical University, Beijing, China
| | - Yanchun Peng
- Nuffield Department of Medicine (NDM), Chinese Academy of Medical Sciences Oxford Institute (CAMS Oxford Institute), University of Oxford, Oxford, United Kingdom
- MRC Human Immunology Unit, Radcliffe Department of Medicine, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Miaomiao Ma
- Key Laboratory of Tumor Immunology and Radiation Therapy, Third Affiliated Hospital, Xinjiang Tumor Hospital, Chinese Academy of Medical Sciences (CAMS), Xinjiang Medical University, Ürümqi, China
- Third Affiliated Hospital, Xinjiang Tumor Hospital, Xinjiang Medical University, Ürümqi, China
| | - Neil Asley
- Single Cell Genomics Facility, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Xuimei Chang
- Key Laboratory of Tumor Immunology and Radiation Therapy, Third Affiliated Hospital, Xinjiang Tumor Hospital, Chinese Academy of Medical Sciences (CAMS), Xinjiang Medical University, Ürümqi, China
- Third Affiliated Hospital, Xinjiang Tumor Hospital, Xinjiang Medical University, Ürümqi, China
| | - Yaning Feng
- Key Laboratory of Tumor Immunology and Radiation Therapy, Third Affiliated Hospital, Xinjiang Tumor Hospital, Chinese Academy of Medical Sciences (CAMS), Xinjiang Medical University, Ürümqi, China
- Third Affiliated Hospital, Xinjiang Tumor Hospital, Xinjiang Medical University, Ürümqi, China
| | - Yunhui Hu
- Key Laboratory of Tumor Immunology and Radiation Therapy, Third Affiliated Hospital, Xinjiang Tumor Hospital, Chinese Academy of Medical Sciences (CAMS), Xinjiang Medical University, Ürümqi, China
- Third Affiliated Hospital, Xinjiang Tumor Hospital, Xinjiang Medical University, Ürümqi, China
| | - Yonghong Zhang
- Beijing You'an Hospital, Capital Medical University, Beijing, China
| | - Chris Li
- China R&D, Janssen Pharmaceuticals, Shanghai, China
| | | | - Stephanie Jones
- Oxford Radcliffe Biobank, Department of Cellular Pathology, Oxford University Hospitals NHS Trust, Oxford, United Kingdom
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
| | - David Maldonado-Perez
- Nuffield Department of Surgical Sciences, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United Kingdom
| | - Paul Sopp
- Flow Cytometry Facility, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Craig Waugh
- Flow Cytometry Facility, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Stephen Taylor
- Bioinformatics Team, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Simon Mcgowan
- Bioinformatics Team, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Vincenzo Cerundolo
- Nuffield Department of Medicine (NDM), Chinese Academy of Medical Sciences Oxford Institute (CAMS Oxford Institute), University of Oxford, Oxford, United Kingdom
- MRC Human Immunology Unit, Radcliffe Department of Medicine, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Christopher Conlon
- Nuffield Department of Medicine (NDM), Chinese Academy of Medical Sciences Oxford Institute (CAMS Oxford Institute), University of Oxford, Oxford, United Kingdom
| | - Andrew McMichael
- Nuffield Department of Medicine (NDM), Chinese Academy of Medical Sciences Oxford Institute (CAMS Oxford Institute), University of Oxford, Oxford, United Kingdom
| | - Shichun Lu
- China Military General Hospital, Beijing, China
| | - Xiyan Wang
- Key Laboratory of Tumor Immunology and Radiation Therapy, Third Affiliated Hospital, Xinjiang Tumor Hospital, Chinese Academy of Medical Sciences (CAMS), Xinjiang Medical University, Ürümqi, China
- Third Affiliated Hospital, Xinjiang Tumor Hospital, Xinjiang Medical University, Ürümqi, China
| | - Ning Li
- Beijing You'an Hospital, Capital Medical University, Beijing, China
| | - Tao Dong
- Nuffield Department of Medicine (NDM), Chinese Academy of Medical Sciences Oxford Institute (CAMS Oxford Institute), University of Oxford, Oxford, United Kingdom
- MRC Human Immunology Unit, Radcliffe Department of Medicine, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
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49
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Browning L, Colling R, Rittscher J, Winter L, McEntyre N, Verrill C. Implementation of digital pathology into diagnostic practice: perceptions and opinions of histopathology trainees and implications for training. J Clin Pathol 2019; 73:223-227. [PMID: 31597682 DOI: 10.1136/jclinpath-2019-206137] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 09/13/2019] [Accepted: 09/19/2019] [Indexed: 11/04/2022]
Abstract
There is increasing interest in the utility of digital pathology in the diagnostic setting. Successful transition requires guidance and training, but additionally an understanding of opinions and attitudes of histopathologists to ensure that potential barriers are addressed. Histopathology trainees as a group are likely to be at the forefront of this revolution, and have specific and as yet largely neglected training needs in this context. We designed an online survey for trainees within our region to capture their opinions and attitudes to digital pathology in the diagnostic setting, and to assess their perceived training needs. This survey indicates overall that these trainees have similar aspirations with regard to the predicted utility of digital pathology and the challenges faced as have been recognised among consultant histopathologists. While their training needs are also largely similar, there are specific additional considerations based around training in multiple centres with varying exposure to digital pathology.
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Affiliation(s)
- Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Richard Colling
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.,Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Jens Rittscher
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.,Big Data Institute, Oxford University, Oxford, UK
| | - Lucinda Winter
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Nicholas McEntyre
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Clare Verrill
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.,Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
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50
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Macklin PS, Pillay N, Lee JL, Pitman H, Scott S, Wang J, Craig C, Jones JL, Oien KA, Colling R, Coupland SE, Verrill C. CM-Path Molecular Diagnostics Forum-consensus statement on the development and implementation of molecular diagnostic tests in the United Kingdom. Br J Cancer 2019; 121:738-743. [PMID: 31575975 PMCID: PMC6889373 DOI: 10.1038/s41416-019-0588-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2019] [Revised: 09/03/2019] [Accepted: 09/06/2019] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Pathology has evolved from a purely morphological description of cellular alterations in disease to our current ability to interrogate tissues with multiple 'omics' technologies. By utilising these techniques and others, 'molecular diagnostics' acts as the cornerstone of precision/personalised medicine by attempting to match the underlying disease mechanisms to the most appropriate targeted therapy. METHODS Despite the promises of molecular diagnostics, significant barriers have impeded its widespread clinical adoption. Thus, the National Cancer Research Institute (NCRI) Cellular Molecular Pathology (CM-Path) initiative convened a national Molecular Diagnostics Forum to facilitate closer collaboration between clinicians, academia, industry, regulators and other key stakeholders in an attempt to overcome these. RESULTS We agreed on a consensus 'roadmap' that should be followed during development and implementation of new molecular diagnostic tests. We identified key barriers to efficient implementation and propose possible solutions to these. In addition, we discussed the recent reconfiguration of molecular diagnostic services in NHS England and its likely impacts. CONCLUSIONS We anticipate that this consensus statement will provide practical advice to those involved in the development of novel molecular diagnostic tests. Although primarily focusing on test adoption within the United Kingdom, we also refer to international guidelines to maximise the applicability of our recommendations.
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Affiliation(s)
- Philip S Macklin
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
| | | | - Jessica L Lee
- Strategy and Initiatives, National Cancer Research Institute, London, UK
| | - Helen Pitman
- CM-Path Programme Manager, National Cancer Research Institute, London, UK
| | - Sophie Scott
- Medical Science Liaison (Europe), Guardant Health, London, UK
| | - Jayson Wang
- Molecular Pathology Lead, Department of Cellular Pathology, St George's University Hospitals NHS Foundation Trust, London, UK
| | | | - J Louise Jones
- Genomics England, London, UK
- Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Karin A Oien
- Department of Pathology, The Queen Elizabeth University Hospital, Glasgow, UK
| | - Richard Colling
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Sarah E Coupland
- North West Cancer Research Centre, University of Liverpool, Liverpool, UK
| | - Clare Verrill
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.
- National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, Oxford, UK.
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