1
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Isago H, Watanabe K, Satoh Y, Kurano M. Correlation between variant call accuracy and quality parameters in comprehensive cancer genomic profiling tests. Pract Lab Med 2024; 39:e00369. [PMID: 38404524 PMCID: PMC10884978 DOI: 10.1016/j.plabm.2024.e00369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 02/04/2024] [Accepted: 02/13/2024] [Indexed: 02/27/2024] Open
Abstract
Background Comprehensive genomic profiling (CGP) tests have been widely utilized in clinical practice. In this test, the variant list automatically output from the data analysis pipeline often contains false-positive variants, although the correlation between the quality parameters and prevalence of false-positive variants remains unclear. Methods We analyzed 125 CGP tests performed in our laboratory. False-positive variants were manually detected via visual inspection. The quality parameters of both wet and dry processes were also analyzed. Results Among the 125 tests, 52 (41.6%) required more than one correction of the called variants, and 21 (16.8%) required multiple corrections. A significant correlation was detected between somatic false-positive variants and quality parameters in the wet (ΔΔCq, pre-capture library peak size, pre-capture library DNA amount, capture library peak size, and capture library concentration) and dry processes (total reads, mapping rates, duplication rates, mean depth, and depth coverage). Capture library concentration and mean depth were strong independent predictors of somatic false-positive variants. Conclusions We demonstrated a correlation between somatic false-positive variants and quality parameters in the CGP test. This study facilitates gaining a better understanding of CGP test quality management.
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Affiliation(s)
- Hideaki Isago
- Department of Clinical Laboratory, The University of Tokyo Hospital, Tokyo, Japan
| | - Kousuke Watanabe
- Department of Clinical Laboratory, The University of Tokyo Hospital, Tokyo, Japan
| | - Yumiko Satoh
- Department of Clinical Laboratory, The University of Tokyo Hospital, Tokyo, Japan
| | - Makoto Kurano
- Department of Clinical Laboratory, The University of Tokyo Hospital, Tokyo, Japan
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2
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Choon YW, Choon YF, Nasarudin NA, Al Jasmi F, Remli MA, Alkayali MH, Mohamad MS. Artificial intelligence and database for NGS-based diagnosis in rare disease. Front Genet 2024; 14:1258083. [PMID: 38371307 PMCID: PMC10870236 DOI: 10.3389/fgene.2023.1258083] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 11/24/2023] [Indexed: 02/20/2024] Open
Abstract
Rare diseases (RDs) are rare complex genetic diseases affecting a conservative estimate of 300 million people worldwide. Recent Next-Generation Sequencing (NGS) studies are unraveling the underlying genetic heterogeneity of this group of diseases. NGS-based methods used in RDs studies have improved the diagnosis and management of RDs. Concomitantly, a suite of bioinformatics tools has been developed to sort through big data generated by NGS to understand RDs better. However, there are concerns regarding the lack of consistency among different methods, primarily linked to factors such as the lack of uniformity in input and output formats, the absence of a standardized measure for predictive accuracy, and the regularity of updates to the annotation database. Today, artificial intelligence (AI), particularly deep learning, is widely used in a variety of biological contexts, changing the healthcare system. AI has demonstrated promising capabilities in boosting variant calling precision, refining variant prediction, and enhancing the user-friendliness of electronic health record (EHR) systems in NGS-based diagnostics. This paper reviews the state of the art of AI in NGS-based genetics, and its future directions and challenges. It also compare several rare disease databases.
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Affiliation(s)
- Yee Wen Choon
- Institute for Artificial Intelligence and Big Data, Universiti Malaysia Kelantan, Kota Bharu, Kelantan, Malaysia
- Faculty of Data Science and Informatics, Universiti Malaysia Kelantan, Kota Bharu, Kelantan, Malaysia
| | - Yee Fan Choon
- Faculty of Dentistry, Lincoln University College, Petaling Jaya, Selangor, Malaysia
| | - Nurul Athirah Nasarudin
- Health Data Science Lab, Department of Genetics and Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Fatma Al Jasmi
- Health Data Science Lab, Department of Genetics and Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Muhamad Akmal Remli
- Institute for Artificial Intelligence and Big Data, Universiti Malaysia Kelantan, Kota Bharu, Kelantan, Malaysia
- Faculty of Data Science and Informatics, Universiti Malaysia Kelantan, Kota Bharu, Kelantan, Malaysia
| | | | - Mohd Saberi Mohamad
- Health Data Science Lab, Department of Genetics and Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
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3
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Eren KK, Çınar E, Karakurt HU, Özgür A. Improving the filtering of false positive single nucleotide variations by combining genomic features with quality metrics. Bioinformatics 2023; 39:btad694. [PMID: 38019945 PMCID: PMC10692869 DOI: 10.1093/bioinformatics/btad694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 10/16/2023] [Accepted: 11/28/2023] [Indexed: 12/01/2023] Open
Abstract
MOTIVATION Technical errors in sequencing or bioinformatics steps and difficulties in alignment at some genomic sites result in false positive (FP) variants. Filtering based on quality metrics is a common method for detecting FP variants, but setting thresholds to reduce FP rates may reduce the number of true positive variants by overlooking the more complex relationships between features. The goal of this study is to develop a machine learning-based model for identifying FPs that integrates quality metrics with genomic features and with the feature interpretability property to provide insights into model results. RESULTS We propose a random forest-based model that utilizes genomic features to improve identification of FPs. Further examination of the features shows that the newly introduced features have an important impact on the prediction of variants misclassified by VEF, GATK-CNN, and GARFIELD, recently introduced FP detection systems. We applied cost-sensitive training to avoid errors in misclassification of true variants and developed a model that provides a robust mechanism against misclassification of true variants while increasing the prediction rate of FP variants. This model can be easily re-trained when factors such as experimental protocols might alter the FP distribution. In addition, it has an interpretability mechanism that allows users to understand the impact of features on the model's predictions. AVAILABILITY AND IMPLEMENTATION The software implementation can be found at https://github.com/ideateknoloji/FPDetect.
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Affiliation(s)
- Kazım Kıvanç Eren
- Department of Computer Engineering, Kocaeli University, Kocaeli 41000, Turkey
| | - Esra Çınar
- R&D Department, Idea Technology Solutions LLC., Istanbul 34396, Turkey
| | - Hamza U Karakurt
- R&D Department, Idea Technology Solutions LLC., Istanbul 34396, Turkey
- Department of Bioengineering, Gebze Technical University, Kocaeli 41400, Turkey
| | - Arzucan Özgür
- Department of Computer Engineering, Boğaziçi University, Istanbul 34342, Turkey
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4
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Choate LA, Koleilat A, Harris K, Vidal-Folch N, Guenzel A, Newman J, Peterson BJ, Peterson SE, Rice CS, Train LJ, Hasadsri L, Marcou CA, Moyer AM, Baudhuin LM. Confirmation of Insertion, Deletion, and Deletion-Insertion Variants Detected by Next-Generation Sequencing. Clin Chem 2023; 69:1155-1162. [PMID: 37566393 DOI: 10.1093/clinchem/hvad110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 07/03/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND Despite clinically demonstrated accuracy in next generation sequencing (NGS) data, many clinical laboratories continue to confirm variants with Sanger sequencing, which increases cost of testing and turnaround time. Several studies have assessed the accuracy of NGS in detecting single nucleotide variants; however, less has been reported about insertion, deletion, and deletion-insertion variants (indels). METHODS We performed a retrospective analysis from 2015-2022 of indel results from a subset of NGS targeted gene panel tests offered through the Mayo Clinic Genomics Laboratories. We compared results from NGS and Sanger sequencing of indels observed in clinical runs and during the intra-assay validation of the tests. RESULTS Results demonstrated 100% concordance between NGS and Sanger sequencing for over 490 indels (217 unique), ranging in size from 1 to 68 basepairs (bp). The majority of indels were deletions (77%) and 1 to 5 bp in length (90%). Variant frequencies ranged from 11.4% to 67.4% and 85.1% to 100% for heterozygous and homozygous variants, respectively, with a median depth of coverage of 2562×. A subset of indels (7%) were located in complex regions of the genome, and these were accurately detected by NGS. We also demonstrated 100% reproducibility of indel detection (n = 179) during intra-assay validation. CONCLUSIONS Together this data demonstrates that reportable indel variants up to 68 bp can be accurately assessed using NGS, even when they occur in complex regions. Depending on the complexity of the region or variant, Sanger sequence confirmation of indels is usually not necessary if the variants meet appropriate coverage and allele frequency thresholds.
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Affiliation(s)
- Lauren A Choate
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Alaa Koleilat
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Kimberley Harris
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Noemi Vidal-Folch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Adam Guenzel
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Jessica Newman
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Brenda J Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Sandra E Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Christopher S Rice
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Laura J Train
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Linda Hasadsri
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Cherisse A Marcou
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Ann M Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Linnea M Baudhuin
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
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5
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Crooks KR, Farwell Hagman KD, Mandelker D, Santani A, Schmidt RJ, Temple-Smolkin RL, Lincoln SE. Recommendations for Next-Generation Sequencing Germline Variant Confirmation: A Joint Report of the Association for Molecular Pathology and National Society of Genetic Counselors. J Mol Diagn 2023; 25:411-427. [PMID: 37207865 DOI: 10.1016/j.jmoldx.2023.03.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/27/2023] [Accepted: 03/30/2023] [Indexed: 05/21/2023] Open
Abstract
Clinical laboratory implementation of next-generation sequencing (NGS)-based constitutional genetic testing has been rapid and widespread. In the absence of widely adopted comprehensive guidance, there remains substantial variability among laboratories in the practice of NGS. One issue of sustained discussion in the field is whether and to what extent orthogonal confirmation of genetic variants identified by NGS is necessary or helpful. The Association for Molecular Pathology Clinical Practice Committee convened the NGS Germline Variant Confirmation Working Group to assess current evidence regarding orthogonal confirmation and to establish recommendations for standardizing orthogonal confirmation practices to support quality patient care. On the basis of the results of a survey of the literature, a survey of laboratory practices, and subject expert matter consensus, eight recommendations are presented, providing a common framework for clinical laboratory professionals to develop or refine individualized laboratory policies and procedures regarding orthogonal confirmation of germline variants detected by NGS.
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Affiliation(s)
- Kristy R Crooks
- NGS Germline Variant Confirmation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, Colorado.
| | - Kelly D Farwell Hagman
- NGS Germline Variant Confirmation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Clinical Diagnostics, Ambry Genetics, Aliso Viejo, California
| | - Diana Mandelker
- NGS Germline Variant Confirmation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Avni Santani
- NGS Germline Variant Confirmation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; LetsGetChecked, PrivaPath Diagnostics, Dublin, Ireland; Veritas Genetics, Danvers, Massachusetts
| | - Ryan J Schmidt
- NGS Germline Variant Confirmation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, California; Department of Pathology, Keck School of Medicine of the University of Southern California, Los Angeles, California
| | | | - Stephen E Lincoln
- NGS Germline Variant Confirmation Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; InVitae, Bethesda, Maryland
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6
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Cechova M, Miga KH. Satellite DNAs and human sex chromosome variation. Semin Cell Dev Biol 2022; 128:15-25. [PMID: 35644878 PMCID: PMC9233459 DOI: 10.1016/j.semcdb.2022.04.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 04/26/2022] [Accepted: 04/27/2022] [Indexed: 11/17/2022]
Abstract
Satellite DNAs are present on every chromosome in the cell and are typically enriched in repetitive, heterochromatic parts of the human genome. Sex chromosomes represent a unique genomic and epigenetic context. In this review, we first report what is known about satellite DNA biology on human X and Y chromosomes, including repeat content and organization, as well as satellite variation in typical euploid individuals. Then, we review sex chromosome aneuploidies that are among the most common types of aneuploidies in the general population, and are better tolerated than autosomal aneuploidies. This is demonstrated also by the fact that aging is associated with the loss of the X, and especially the Y chromosome. In addition, supernumerary sex chromosomes enable us to study general processes in a cell, such as analyzing heterochromatin dosage (i.e. additional Barr bodies and long heterochromatin arrays on Yq) and their downstream consequences. Finally, genomic and epigenetic organization and regulation of satellite DNA could influence chromosome stability and lead to aneuploidy. In this review, we argue that the complete annotation of satellite DNA on sex chromosomes in human, and especially in centromeric regions, will aid in explaining the prevalence and the consequences of sex chromosome aneuploidies.
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Affiliation(s)
- Monika Cechova
- Faculty of Informatics, Masaryk University, Czech Republic
| | - Karen H Miga
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA; UC Santa Cruz Genomics Institute, University of California Santa Cruz, CA 95064, USA
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7
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Wagner U, Wong C, Camenisch U, Zimmermann K, Rechsteiner M, Valtcheva N, Theocharides A, Widmer CC, Manz MG, Moch H, Wild PJ, Balabanov S. Comprehensive Validation of Diagnostic Next-Generation Sequencing Panels for Acute Myeloid Leukemia Patients. J Mol Diagn 2022; 24:935-954. [PMID: 35718092 DOI: 10.1016/j.jmoldx.2022.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 03/11/2022] [Accepted: 05/06/2022] [Indexed: 11/28/2022] Open
Abstract
Next-generation sequencing has greatly advanced the molecular diagnostics of malignant hematological diseases and provides useful information for clinical decision making. Studies have shown that certain mutations are associated with prognosis and have a direct impact on treatment of affected patients. Therefore, reliable detection of pathogenic variants is critically important. In this study, we aimed to compare four sequencing panels with different characteristics, from number of genes covered to technical aspects of library preparation and data analysis workflows, to find the panel with the best clinical utility for myeloid neoplasms with a special focus on acute myeloid leukemia. Using the Acrometrix Oncology Hotspot Control DNA and DNA from acute myeloid leukemia patients, we evaluated panel performance in terms of coverage, precision, recall, and reproducibility and tested different bioinformatics tools that can be used for the evaluation of any next-generation sequencing panel. Taken together, our results support the reliability of the Acrometrix Oncology Hotspot Control to validate and compare sequencing panels for hematological diseases and show which panel-software combination (platform) has the best performance.
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Affiliation(s)
- Ulrich Wagner
- Department of Pathology and Molecular Pathology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Christine Wong
- Department of Pathology and Molecular Pathology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Ulrike Camenisch
- Department of Pathology and Molecular Pathology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Kathrin Zimmermann
- Division of Medical Oncology and Hematology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Markus Rechsteiner
- Department of Pathology and Molecular Pathology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Nadejda Valtcheva
- Department of Pathology and Molecular Pathology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Alexandre Theocharides
- Division of Medical Oncology and Hematology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Corinne C Widmer
- Division of Medical Oncology and Hematology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Markus G Manz
- Division of Medical Oncology and Hematology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Holger Moch
- Department of Pathology and Molecular Pathology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Peter J Wild
- Dr. Senckenberg Institute of Pathology, University Hospital Frankfurt, Frankfurt am Main, Germany; Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany; Wildlab, University Hospital Frankfurt MVZ GmbH, Frankfurt am Main, Germany.
| | - Stefan Balabanov
- Division of Medical Oncology and Hematology, University Hospital and University of Zurich, Zurich, Switzerland.
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8
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Watson CM, Crinnion LA, Simmonds J, Camm N, Adlard J, Bonthron DT. Long-read nanopore sequencing enables accurate confirmation of a recurrent PMS2 insertion-deletion variant located in a region of complex genomic architecture. Cancer Genet 2021; 256-257:122-126. [PMID: 34116445 DOI: 10.1016/j.cancergen.2021.05.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 04/08/2021] [Accepted: 05/24/2021] [Indexed: 10/21/2022]
Abstract
Targeted next generation sequencing (NGS) is the predominant methodology for the molecular genetic diagnosis of inherited conditions. In many laboratories, NGS-identified variants are routinely validated using a different method, to minimize the risk of a false-positive diagnosis. This can be particularly important when pathogenic variants are located in complex genomic regions. In this situation, new long-read sequencing technologies have potential advantages over existing alternatives. However, practical examples of their utility for diagnostic purposes remain scant. Here, we report the use of nanopore sequencing to validate a PMS2 mutation refractory to conventional methods. In a patient who presented with colorectal cancer and loss of PMS2 immunostaining, short-read NGS of Lynch syndrome-associated genes identified the recurrent PMS2 insertion-deletion variant, c.736_741delinsTGTGTGTGAAG (p.Pro246Cysfs*3). Confirmation of this variant using bidirectional Sanger sequencing was impeded by an upstream intron 6 poly(T) tract. Using a locus-specific amplicon template, we undertook nanopore long-read sequencing in order to assess the diagnostic accuracy of this platform. Pairwise comparison between a curated benchmark allele (derived from short-read NGS and unidirectional Sanger sequencing) and the consensus nanopore dataset revealed 100% sequence identity. Our experience provides insight into the robustness and ease of deployment of "third-generation" sequencing for accurate characterisation of pathogenic variants.
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Affiliation(s)
- Christopher M Watson
- Yorkshire and North East Genomic Laboratory Hub, Central Lab, St. James's University Hospital, Leeds LS9 7TF, United Kingdom; Leeds Institute of Medical Research, University of Leeds, St. James's University Hospital, Leeds LS9 7TF, United Kingdom.
| | - Laura A Crinnion
- Yorkshire and North East Genomic Laboratory Hub, Central Lab, St. James's University Hospital, Leeds LS9 7TF, United Kingdom; Leeds Institute of Medical Research, University of Leeds, St. James's University Hospital, Leeds LS9 7TF, United Kingdom
| | - Jennifer Simmonds
- Yorkshire and North East Genomic Laboratory Hub, Central Lab, St. James's University Hospital, Leeds LS9 7TF, United Kingdom
| | - Nick Camm
- Yorkshire and North East Genomic Laboratory Hub, Central Lab, St. James's University Hospital, Leeds LS9 7TF, United Kingdom
| | - Julian Adlard
- The Clinical Genetics Department, Chapel Allerton Hospital, Leeds LS7 4SA, United Kingdom
| | - David T Bonthron
- Leeds Institute of Medical Research, University of Leeds, St. James's University Hospital, Leeds LS9 7TF, United Kingdom; The Clinical Genetics Department, Chapel Allerton Hospital, Leeds LS7 4SA, United Kingdom
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9
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Prasad A, Bhargava H, Gupta A, Shukla N, Rajagopal S, Gupta S, Sharma A, Valadi J, Nigam V, Suravajhala P. Next Generation Sequencing. Adv Bioinformatics 2021. [DOI: 10.1007/978-981-33-6191-1_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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10
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Adedokun B, Zheng Y, Ndom P, Gakwaya A, Makumbi T, Zhou AY, Yoshimatsu TF, Rodriguez A, Madduri RK, Foster IT, Sallam A, Olopade OI, Huo D. Prevalence of Inherited Mutations in Breast Cancer Predisposition Genes among Women in Uganda and Cameroon. Cancer Epidemiol Biomarkers Prev 2019; 29:359-367. [PMID: 31871109 DOI: 10.1158/1055-9965.epi-19-0506] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2019] [Revised: 07/23/2019] [Accepted: 12/09/2019] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Sub-Saharan Africa (SSA) has a high proportion of premenopausal hormone receptor negative breast cancer. Previous studies reported a strikingly high prevalence of germline mutations in BRCA1 and BRCA2 among Nigerian patients with breast cancer. It is unknown if this exists in other SSA countries. METHODS Breast cancer cases, unselected for age at diagnosis and family history, were recruited from tertiary hospitals in Kampala, Uganda and Yaoundé, Cameroon. Controls were women without breast cancer recruited from the same hospitals and age-matched to cases. A multigene sequencing panel was used to test for germline mutations. RESULTS There were 196 cases and 185 controls with a mean age of 46.2 and 46.6 years for cases and controls, respectively. Among cases, 15.8% carried a pathogenic or likely pathogenic mutation in a breast cancer susceptibility gene: 5.6% in BRCA1, 5.6% in BRCA2, 1.5% in ATM, 1% in PALB2, 0.5% in BARD1, 0.5% in CDH1, and 0.5% in TP53. Among controls, 1.6% carried a mutation in one of these genes. Cases were 11-fold more likely to carry a mutation compared with controls (OR = 11.34; 95% confidence interval, 3.44-59.06; P < 0.001). The mean age of cases with BRCA1 mutations was 38.3 years compared with 46.7 years among other cases without such mutations (P = 0.03). CONCLUSIONS Our findings replicate the earlier report of a high proportion of mutations in BRCA1/2 among patients with symptomatic breast cancer in SSA. IMPACT Given the high burden of inherited breast cancer in SSA countries, genetic risk assessment could be integrated into national cancer control plans.
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Affiliation(s)
- Babatunde Adedokun
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, The University of Chicago, Chicago, Illinois
| | - Yonglan Zheng
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, The University of Chicago, Chicago, Illinois
| | - Paul Ndom
- Hôpital Général Yaoundé, Yaoundé, Cameroon
| | | | | | | | - Toshio F Yoshimatsu
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, The University of Chicago, Chicago, Illinois
| | | | - Ravi K Madduri
- Globus, The University of Chicago, Chicago, Illinois.,Data Science and Learning Division, Argonne National Laboratory, Lemont, Illinois
| | - Ian T Foster
- Globus, The University of Chicago, Chicago, Illinois.,Data Science and Learning Division, Argonne National Laboratory, Lemont, Illinois
| | - Aminah Sallam
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, The University of Chicago, Chicago, Illinois.,Yale School of Medicine, New Haven, Connecticut
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, The University of Chicago, Chicago, Illinois.
| | - Dezheng Huo
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, The University of Chicago, Chicago, Illinois. .,Department of Public Health Sciences, The University of Chicago, Chicago, Illinois
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11
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Methods for Identifying Patients with Tropomyosin Receptor Kinase (TRK) Fusion Cancer. Pathol Oncol Res 2019; 26:1385-1399. [PMID: 31256325 PMCID: PMC7297824 DOI: 10.1007/s12253-019-00685-2] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 06/11/2019] [Indexed: 11/01/2022]
Abstract
NTRK gene fusions affecting the tropomyosin receptor kinase (TRK) protein family have been found to be oncogenic drivers in a broad range of cancers. Small molecule inhibitors targeting TRK activity, such as the recently Food and Drug Administration-approved agent larotrectinib (Vitrakvi®), have shown promising efficacy and safety data in the treatment of patients with TRK fusion cancers. NTRK gene fusions can be detected using several different approaches, including fluorescent in situ hybridization, reverse transcription polymerase chain reaction, immunohistochemistry, next-generation sequencing, and ribonucleic acid-based multiplexed assays. Identifying patients with cancers that harbor NTRK gene fusions will optimize treatment outcomes by providing targeted precision therapy.
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12
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Martinez-Martin N, Magnus D. Privacy and ethical challenges in next-generation sequencing. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2019; 4:95-104. [PMID: 32775691 PMCID: PMC7413244 DOI: 10.1080/23808993.2019.1599685] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 03/22/2019] [Indexed: 02/04/2023]
Abstract
INTRODUCTION Next-generation sequencing (NGS) is expected to revolutionize health care. NGS allows for sequencing of the whole genome more cheaply and quickly than previous techniques. NGS offers opportunities to advance medical diagnostics and treatments, but also raises complicated ethical questions that need to be addressed. AREAS CONSIDERED This article draws from the literature on research and clinical ethics, as well as next-generation sequencing, in order to provide an overview of the ethical challenges involved in next-generation sequencing. This article includes a discussion of the ethics of NGS in research and clinical contexts. EXPERT OPINION The use of NGS in clinical and research contexts has features that pose challenges for traditional ethical frameworks for protecting research participants and patients. NGS generates massive amounts of data and results that vary in terms of known clinical relevance. It is important to determine appropriate processes for protecting, managing and communicating the data. The use of machine learning for sequencing and interpretation of genomic data also raises concerns in terms of the potential for bias and potential implications for fiduciary obligations. NGS poses particular challenges in three main ethical areas: privacy, informed consent, and return of results.
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Affiliation(s)
| | - David Magnus
- Stanford Center for Biomedical Ethics, Stanford University, Stanford, CA, USA
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13
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Muzzey D, Kash S, Johnson JI, Melroy LM, Kaleta P, Pierce KA, Ready K, Kang HP, Haas KR. Software-Assisted Manual Review of Clinical Next-Generation Sequencing Data. J Mol Diagn 2019; 21:296-306. [DOI: 10.1016/j.jmoldx.2018.10.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Revised: 09/24/2018] [Accepted: 10/24/2018] [Indexed: 12/13/2022] Open
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Lincoln SE, Truty R, Lin CF, Zook JM, Paul J, Ramey VH, Salit M, Rehm HL, Nussbaum RL, Lebo MS. A Rigorous Interlaboratory Examination of the Need to Confirm Next-Generation Sequencing-Detected Variants with an Orthogonal Method in Clinical Genetic Testing. J Mol Diagn 2019; 21:318-329. [PMID: 30610921 PMCID: PMC6629256 DOI: 10.1016/j.jmoldx.2018.10.009] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 09/28/2018] [Accepted: 10/24/2018] [Indexed: 12/17/2022] Open
Abstract
Orthogonal confirmation of next-generation sequencing (NGS)-detected germline variants is standard practice, although published studies have suggested that confirmation of the highest-quality calls may not always be necessary. The key question is how laboratories can establish criteria that consistently identify those NGS calls that require confirmation. Most prior studies addressing this question have had limitations: they have been generally of small scale, omitted statistical justification, and explored limited aspects of underlying data. The rigorous definition of criteria that separate high-accuracy NGS calls from those that may or may not be true remains a crucial issue. We analyzed five reference samples and over 80,000 patient specimens from two laboratories. Quality metrics were examined for approximately 200,000 NGS calls with orthogonal data, including 1662 false positives. A classification algorithm used these data to identify a battery of criteria that flag 100% of false positives as requiring confirmation (CI lower bound, 98.5% to 99.8%, depending on variant type) while minimizing the number of flagged true positives. These criteria identify false positives that the previously published criteria miss. Sampling analysis showed that smaller data sets resulted in less effective criteria. Our methodology for determining test- and laboratory-specific criteria can be generalized into a practical approach that can be used by laboratories to reduce the cost and time burdens of confirmation without affecting clinical accuracy.
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Affiliation(s)
| | | | - Chiao-Feng Lin
- Laboratory for Molecular Medicine, Partners HealthCare, Cambridge, Massachusetts; Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Justin M Zook
- National Institute of Standards and Technology, Gaithersburg, Maryland
| | | | | | - Marc Salit
- National Institute of Standards and Technology, Gaithersburg, Maryland; Joint Initiative for Metrology in Biology, Stanford, California
| | - Heidi L Rehm
- Laboratory for Molecular Medicine, Partners HealthCare, Cambridge, Massachusetts; Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts; Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Robert L Nussbaum
- Invitae, San Francisco, California; Department of Medicine, University of California San Francisco, San Francisco, California
| | - Matthew S Lebo
- Laboratory for Molecular Medicine, Partners HealthCare, Cambridge, Massachusetts; Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
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15
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Parikh RB, Gdowski A, Patt DA, Hertler A, Mermel C, Bekelman JE. Using Big Data and Predictive Analytics to Determine Patient Risk in Oncology. Am Soc Clin Oncol Educ Book 2019; 39:e53-e58. [PMID: 31099672 DOI: 10.1200/edbk_238891] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Big data and predictive analytics have immense potential to improve risk stratification, particularly in data-rich fields like oncology. This article reviews the literature published on use cases and challenges in applying predictive analytics to improve risk stratification in oncology. We characterized evidence-based use cases of predictive analytics in oncology into three distinct fields: (1) population health management, (2) radiomics, and (3) pathology. We then highlight promising future use cases of predictive analytics in clinical decision support and genomic risk stratification. We conclude by describing challenges in the future applications of big data in oncology, namely (1) difficulties in acquisition of comprehensive data and endpoints, (2) the lack of prospective validation of predictive tools, and (3) the risk of automating bias in observational datasets. If such challenges can be overcome, computational techniques for clinical risk stratification will in short order improve clinical risk stratification for patients with cancer.
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Affiliation(s)
- Ravi B Parikh
- 1 Penn Center for Cancer Care Innovation at the Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
- 2 Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
| | - Andrew Gdowski
- 3 Dell Medical School at The University of Texas at Austin, Austin, TX
| | - Debra A Patt
- 3 Dell Medical School at The University of Texas at Austin, Austin, TX
- 4 Texas Oncology, Dallas, TX
| | | | | | - Justin E Bekelman
- 1 Penn Center for Cancer Care Innovation at the Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
- 2 Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
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16
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Evaluation for Genetic Disorders in the Absence of a Clinical Indication for Testing. J Mol Diagn 2019; 21:3-12. [DOI: 10.1016/j.jmoldx.2018.09.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 08/29/2018] [Accepted: 09/17/2018] [Indexed: 01/01/2023] Open
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