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Hu X, Zhu B, Vokes N, Fujimoto J, Rojas Alvarez FR, Heeke S, Moreira AL, Solis LM, Haymaker C, Velcheti V, Sterman DH, Pass HI, Cheng C, Lee JJ, Zhang J, Wei Z, Wu J, Le X, Ostrin E, Toumazis I, Gibbons D, Su D, Fukuoka J, Antonoff MB, Gerber DE, Li C, Kadara H, Wang L, Davis M, Heymach JV, Hannash S, Wistuba I, Dubinett S, Alexandrov L, Lippman S, Spira A, Futreal AP, Reuben A, Zhang J. The evolution of lung adenocarcinoma precursors is associated with chromosomal instability and transition from innate to adaptive immune response/evasion. RESEARCH SQUARE 2024:rs.3.rs-4396272. [PMID: 38798564 PMCID: PMC11118701 DOI: 10.21203/rs.3.rs-4396272/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Studying lung adenocarcinoma (LUAD) early carcinogenesis is challenging, primarily due to the lack of LUAD precursors specimens. We amassed multi-omics data from 213 LUAD and LUAD precursors to identify molecular features underlying LUAD precancer evolution. We observed progressively increasing mutations, chromosomal aberrations, whole genome doubling and genomic instability from precancer to invasive LUAD, indicating aggravating chromosomal instability (CIN). Telomere shortening, a crucial genomic alteration linked to CIN, emerged at precancer stage. Moreover, later-stage lesions demonstrated increasing cancer stemness and decreasing alveolar identity, suggesting epithelial de-differentiation during early LUAD carcinogenesis. The innate immune cells progressively diminished from precancer to invasive LUAD, concomitant with a gradual recruitment of adaptive immune cells (except CD8+ and gamma-delta T cells that decreased in later stages) and upregulation of numerous immune checkpoints, suggesting LUAD precancer evolution is associated with a shift from innate to adaptive immune response and immune evasion mediated by various mechanisms.
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Affiliation(s)
- Xin Hu
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Bo Zhu
- Departments of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Natalie Vokes
- Departments of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | | | - Frank R. Rojas Alvarez
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Simon Heeke
- Departments of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Andre L. Moreira
- Department of Pathology, New York University Langone Medical Center, New York, 10012, USA
| | - Luisa M. Solis
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Cara Haymaker
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Vamsidhar Velcheti
- Department of Medical oncology, New York University, New York, 10012, USA
| | | | - Harvey I. Pass
- Department of Cardiothoracic Surgery, New York University Langone Medical Center, New York, 10016, USA
| | - Chao Cheng
- Department of Medicine, Epidemiology and Population Science, Baylor College of Medicine. Houston, TX, 77030, USA
| | - Jack J. Lee
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jianhua Zhang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Zhubo Wei
- Departments of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jia Wu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Xiuning Le
- Departments of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Edwin Ostrin
- Department of General Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Iakovos Toumazis
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Don Gibbons
- Departments of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Dan Su
- Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, 310022, China
- Department of Pathology, Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, 310022, China
| | - Junya Fukuoka
- Department of Pathology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, 8528523, Japan
| | - Mara B. Antonoff
- Department of Thoracic & Cardiovasc Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - David E. Gerber
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Chenyang Li
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Humam Kadara
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Linghua Wang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Mark Davis
- Moores Cancer Center, UC San Diego School of Medicine, San Diego, CA, 92037, USA
| | - John V. Heymach
- Departments of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Samir Hannash
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Ignacio Wistuba
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Steven Dubinett
- Departments of Medicine and Pathology, University of California Los Angeles and Greater Los Angeles Healthcare System, Los Angeles, CA, 90095, USA
| | - Ludmil Alexandrov
- Moores Cancer Center, UC San Diego School of Medicine, San Diego, CA, 92037, USA
| | - Scott Lippman
- Moores Cancer Center, UC San Diego School of Medicine, San Diego, CA, 92037, USA
| | - Avrum Spira
- Pathology & Laboratory Medicine, and Bioinformatics, Boston University, Boston, MA, 02215, USA
| | - Andrew P. Futreal
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Alexandre Reuben
- Departments of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jianjun Zhang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
- Departments of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
- Lead contact
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dos Santos GA, Magdaleno GDV, de Magalhães JP. Evidence of a pan-tissue decline in stemness during human aging. Aging (Albany NY) 2024; 16:5796-5810. [PMID: 38604248 PMCID: PMC11042951 DOI: 10.18632/aging.205717] [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: 10/08/2023] [Accepted: 02/02/2024] [Indexed: 04/13/2024]
Abstract
Despite their biological importance, the role of stem cells in human aging remains to be elucidated. In this work, we applied a machine learning methodology to GTEx transcriptome data and assigned stemness scores to 17,382 healthy samples from 30 human tissues aged between 20 and 79 years. We found that ~60% of the studied tissues exhibit a significant negative correlation between the subject's age and stemness score. The only significant exception was the uterus, where we observed an increased stemness with age. Moreover, we observed that stemness is positively correlated with cell proliferation and negatively correlated with cellular senescence. Finally, we also observed a trend that hematopoietic stem cells derived from older individuals might have higher stemness scores. In conclusion, we assigned stemness scores to human samples and show evidence of a pan-tissue loss of stemness during human aging, which adds weight to the idea that stem cell deterioration may contribute to human aging.
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Affiliation(s)
- Gabriel Arantes dos Santos
- Laboratory of Medical Investigation (LIM55), Urology Department, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo 01246 903, Brazil
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham B15 2WB, United Kingdom
| | | | - João Pedro de Magalhães
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham B15 2WB, United Kingdom
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3
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Altorki NK, Bhinder B, Borczuk AC, Elemento O, Mittal V, McGraw TE. A signature of enhanced proliferation associated with response and survival to anti-PD-L1 therapy in early-stage non-small cell lung cancer. Cell Rep Med 2024; 5:101438. [PMID: 38401548 PMCID: PMC10982989 DOI: 10.1016/j.xcrm.2024.101438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 11/20/2023] [Accepted: 01/30/2024] [Indexed: 02/26/2024]
Abstract
In early-stage non-small cell lung cancer, the combination of neoadjuvant anti-PD-L1 and subablative stereotactic body radiation therapy (SBRT) is associated with higher rates of major pathologic response compared to anti-PD-L1 alone. Here, we identify a 140-gene set, enriched in genes characteristic of highly proliferating cells, associated with response to the dual therapy. Analysis of on-treatment transcriptome data indicate roles for T and B cells in response. The 140-gene set is associated with disease-free survival when applied to the combined trial arms. This 140-gene set identifies a subclass of tumors in all 7 of The Cancer Genome Atlas tumor types examined. Worse survival is associated with the 140-gene signature in 5 of these tumor types. Collectively, our data support that this 140-gene set, discovered in association with response to combined anti-PD-L1 and SBRT, identifies a clinically aggressive subclass of solid tumors that may be more likely to respond to immunotherapies.
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Affiliation(s)
- Nasser K Altorki
- Meyer Cancer Center, Weill Cornell Medicine and New York Presbyterian Hospital, New York, NY 10065, USA; Department of Cardiothoracic Surgery, Weill Cornell Medicine and New York Presbyterian Hospital, New York, NY 10065, USA.
| | - Bhavneet Bhinder
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Alain C Borczuk
- Department of Pathology and Laboratory Medicine, Northwell Health Cancer Institute, Northwell Health, Greenvale, NY 10042, USA
| | - Olivier Elemento
- Meyer Cancer Center, Weill Cornell Medicine and New York Presbyterian Hospital, New York, NY 10065, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Vivek Mittal
- Meyer Cancer Center, Weill Cornell Medicine and New York Presbyterian Hospital, New York, NY 10065, USA; Department of Cardiothoracic Surgery, Weill Cornell Medicine and New York Presbyterian Hospital, New York, NY 10065, USA
| | - Timothy E McGraw
- Meyer Cancer Center, Weill Cornell Medicine and New York Presbyterian Hospital, New York, NY 10065, USA; Department of Cardiothoracic Surgery, Weill Cornell Medicine and New York Presbyterian Hospital, New York, NY 10065, USA; Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA.
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4
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Malla SB, Byrne RM, Lafarge MW, Corry SM, Fisher NC, Tsantoulis PK, Mills ML, Ridgway RA, Lannagan TRM, Najumudeen AK, Gilroy KL, Amirkhah R, Maguire SL, Mulholland EJ, Belnoue-Davis HL, Grassi E, Viviani M, Rogan E, Redmond KL, Sakhnevych S, McCooey AJ, Bull C, Hoey E, Sinevici N, Hall H, Ahmaderaghi B, Domingo E, Blake A, Richman SD, Isella C, Miller C, Bertotti A, Trusolino L, Loughrey MB, Kerr EM, Tejpar S, Maughan TS, Lawler M, Campbell AD, Leedham SJ, Koelzer VH, Sansom OJ, Dunne PD. Pathway level subtyping identifies a slow-cycling biological phenotype associated with poor clinical outcomes in colorectal cancer. Nat Genet 2024; 56:458-472. [PMID: 38351382 PMCID: PMC10937375 DOI: 10.1038/s41588-024-01654-5] [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: 12/04/2022] [Accepted: 01/03/2024] [Indexed: 02/29/2024]
Abstract
Molecular stratification using gene-level transcriptional data has identified subtypes with distinctive genotypic and phenotypic traits, as exemplified by the consensus molecular subtypes (CMS) in colorectal cancer (CRC). Here, rather than gene-level data, we make use of gene ontology and biological activation state information for initial molecular class discovery. In doing so, we defined three pathway-derived subtypes (PDS) in CRC: PDS1 tumors, which are canonical/LGR5+ stem-rich, highly proliferative and display good prognosis; PDS2 tumors, which are regenerative/ANXA1+ stem-rich, with elevated stromal and immune tumor microenvironmental lineages; and PDS3 tumors, which represent a previously overlooked slow-cycling subset of tumors within CMS2 with reduced stem populations and increased differentiated lineages, particularly enterocytes and enteroendocrine cells, yet display the worst prognosis in locally advanced disease. These PDS3 phenotypic traits are evident across numerous bulk and single-cell datasets, and demark a series of subtle biological states that are currently under-represented in pre-clinical models and are not identified using existing subtyping classifiers.
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Affiliation(s)
- Sudhir B Malla
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Ryan M Byrne
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Maxime W Lafarge
- Department of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Shania M Corry
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Natalie C Fisher
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | | | | | | | | | | | | | - Raheleh Amirkhah
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Sarah L Maguire
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | | | | | - Elena Grassi
- Candiolo Cancer Institute, FPO IRCCS, Candiolo, Torino, Italy
- Department of Oncology, University of Torino, Candiolo, Torino, Italy
| | - Marco Viviani
- Candiolo Cancer Institute, FPO IRCCS, Candiolo, Torino, Italy
- Department of Oncology, University of Torino, Candiolo, Torino, Italy
| | - Emily Rogan
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Keara L Redmond
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Svetlana Sakhnevych
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Aoife J McCooey
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Courtney Bull
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Emily Hoey
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Nicoleta Sinevici
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Holly Hall
- Cancer Research UK Scotland Institute, Glasgow, UK
| | - Baharak Ahmaderaghi
- School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast, UK
| | - Enric Domingo
- Department of Oncology, University of Oxford, Oxford, Oxfordshire, UK
| | - Andrew Blake
- Department of Oncology, University of Oxford, Oxford, Oxfordshire, UK
| | - Susan D Richman
- Leeds Institute of Medical Research, University of Leeds, Leeds, UK
| | - Claudio Isella
- Candiolo Cancer Institute, FPO IRCCS, Candiolo, Torino, Italy
- Department of Oncology, University of Torino, Candiolo, Torino, Italy
| | - Crispin Miller
- Cancer Research UK Scotland Institute, Glasgow, UK
- School of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Andrea Bertotti
- Candiolo Cancer Institute, FPO IRCCS, Candiolo, Torino, Italy
- Department of Oncology, University of Torino, Candiolo, Torino, Italy
| | - Livio Trusolino
- Candiolo Cancer Institute, FPO IRCCS, Candiolo, Torino, Italy
- Department of Oncology, University of Torino, Candiolo, Torino, Italy
| | - Maurice B Loughrey
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
- Department of Cellular Pathology, Royal Victoria Hospital, Belfast Health and Social Care Trust, Belfast, UK
| | - Emma M Kerr
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Sabine Tejpar
- Department of Oncology, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Timothy S Maughan
- Department of Oncology, University of Oxford, Oxford, Oxfordshire, UK
| | - Mark Lawler
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | | | | | - Viktor H Koelzer
- Department of Pathology and Molecular Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Oncology, University of Oxford, Oxford, Oxfordshire, UK
| | - Owen J Sansom
- Cancer Research UK Scotland Institute, Glasgow, UK
- School of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Philip D Dunne
- The Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK.
- Cancer Research UK Scotland Institute, Glasgow, UK.
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5
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Zeng L, Chen X, Cui J, Zhang L, Li L, Yin C, Chen X, Sun J. High-resolution transcriptomics analysis of CXCL13 + EPSTI1 + CDK1 + cells with a specific focus on lung adenocarcinoma. J Thorac Dis 2024; 16:201-214. [PMID: 38410612 PMCID: PMC10894425 DOI: 10.21037/jtd-23-1164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/17/2023] [Indexed: 02/28/2024]
Abstract
Background Programmed cell death ligand 1 (PD-L1) blocking therapy has transformed the treatment of lung adenocarcinoma (LUAD), which has significantly changed the landscape of immunotherapy. We aimed to explore specific cell subpopulations to understand tumor progression and identify markers of response to PD-L1 blocking therapy. Methods Bulk, fluorescence-activated cell sorting (FACS), and single-cell RNA (scRNA) sequencing were used to profile CXCL13, EPSTI1, and CDK1. The gene set variation analysis (GSVA) R package was utilized for score calculation, and prognostic analyses included receiver operating characteristic (ROC) curves, Cox proportional hazard models, and meta-analysis. Additionally, we analyzed tumor microenvironment (TME), genomics, compound perturbations, and clinical indicators. The high-dimensional analysis captured the intrinsic characteristics of the subpopulation. Furthermore, subpopulation differential genes were used for enrichment analysis of transcription factors and compounds. Results Literature and website analyses supported the essential role of CXCL13, CDK1, and EPSTI1 in immunotherapy. This led us to focus specifically on LUAD by representing a pan-cancer profile of immune-sensitive genes. Logically, the high-characteristic population may consist of samples positive for CXCL13, EPSTI1, and CDK1. The three-gene signature was a favorable indicator of immunotherapy response in the Stand Up to Cancer-Mark Foundation (SU2C-MARK) LUAD cohort but showed a poor prognosis before treatment in the Lung Cancer Explorer (LCE) database. Further mechanistic exploration revealed specific mutations associated with the three-gene signature in SU2C-MARK LUAD, such as STK11. In The Cancer Genome Atlas (TCGA)-LUAD cohort, the high-scoring group exhibited a higher tumor mutational burden (TMB) and global methylation but a lower fraction genome altered (FGA) and estimated tumor purity. Moreover, dasatinib demonstrated sensitivity in the high-scoring group. The co-localization of the CXCL13, EPSTI1, and CDK1 subpopulation was validated through spatial transcriptome and immunohistochemical databases. Assessment of the subpopulation depicted high-resolution intercellular communication. Maintenance of specific pathways, such as TNF, CD74, and CD44, contributed to immunotherapy sensitivity. Finally, the subpopulation-enriched targets and drugs were confirmed through ConnectivityMap (CMAP) analysis and multi-omics, respectively. Conclusions In this study, positive samples for CXCL13, EPSTI1, and CDK1 exhibited poor prognostic significance in treatment-naïve LUAD cases but demonstrated benefits from PD-L1 blockade and dasatinib therapies.
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Affiliation(s)
- Longjin Zeng
- College of Basic Medicine, Army Medical University, Chongqing, China
| | - Xu Chen
- Department of Medical Affairs, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Jianxiong Cui
- Cancer Institute, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Longyao Zhang
- Cancer Institute, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Lingchen Li
- Cancer Institute, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Chenrui Yin
- Cancer Institute, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Xiewan Chen
- College of Basic Medicine, Army Medical University, Chongqing, China
- Cancer Institute, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Jianguo Sun
- Cancer Institute, Xinqiao Hospital, Army Medical University, Chongqing, China
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6
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Parga-Pazos M, Cusimano N, Rábano M, Akhmatskaya E, Vivanco MDM. A Novel Mathematical Approach for Analysis of Integrated Cell-Patient Data Uncovers a 6-Gene Signature Linked to Endocrine Therapy Resistance. J Transl Med 2024; 104:100286. [PMID: 37951307 DOI: 10.1016/j.labinv.2023.100286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 10/17/2023] [Accepted: 11/03/2023] [Indexed: 11/13/2023] Open
Abstract
A significant number of breast cancers develop resistance to hormone therapy. This progression, while posing a major clinical challenge, is difficult to predict. Despite important contributions made by cell models and clinical studies to tackle this problem, both present limitations when taken individually. Experiments with cell models are highly reproducible but do not reflect the indubitable heterogenous landscape of breast cancer. On the other hand, clinical studies account for this complexity but introduce uncontrolled noise due to external factors. Here, we propose a new approach for biomarker discovery that is based on a combined analysis of sequencing data from controlled MCF7 cell experiments and heterogenous clinical samples that include clinical and sequencing information from The Cancer Genome Atlas. Using data from differential gene expression analysis and a Bayesian logistic regression model coupled with an original simulated annealing-type algorithm, we discovered a novel 6-gene signature for stratifying patient response to hormone therapy. The experimental observations and computational analysis built on independent cohorts indicated the superior predictive performance of this gene set over previously known signatures of similar scope. Together, these findings revealed a new gene signature to identify patients with breast cancer with an increased risk of developing resistance to endocrine therapy.
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Affiliation(s)
- Martin Parga-Pazos
- Modelling and Simulation in Life and Materials Sciences, Basque Center for Applied Mathematics, Spain; Cancer Heterogeneity Lab, CIC bioGUNE, Basque Research and Technology Alliance, Derio, Spain
| | - Nicole Cusimano
- Modelling and Simulation in Life and Materials Sciences, Basque Center for Applied Mathematics, Spain
| | - Miriam Rábano
- Cancer Heterogeneity Lab, CIC bioGUNE, Basque Research and Technology Alliance, Derio, Spain
| | - Elena Akhmatskaya
- Modelling and Simulation in Life and Materials Sciences, Basque Center for Applied Mathematics, Spain; IKERBASQUE, Basque Foundation for Science, Bilbao, Spain.
| | - Maria dM Vivanco
- Cancer Heterogeneity Lab, CIC bioGUNE, Basque Research and Technology Alliance, Derio, Spain.
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7
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Perez MF, Sarkies P. Histone methyltransferase activity affects metabolism in human cells independently of transcriptional regulation. PLoS Biol 2023; 21:e3002354. [PMID: 37883365 PMCID: PMC10602318 DOI: 10.1371/journal.pbio.3002354] [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: 04/26/2023] [Accepted: 09/27/2023] [Indexed: 10/28/2023] Open
Abstract
The N-terminal tails of eukaryotic histones are frequently posttranslationally modified. The role of these modifications in transcriptional regulation is well-documented. However, the extent to which the enzymatic processes of histone posttranslational modification might affect metabolic regulation is less clear. Here, we investigated how histone methylation might affect metabolism using metabolomics, proteomics, and RNA-seq data from cancer cell lines, primary tumour samples and healthy tissue samples. In cancer, the expression of histone methyltransferases (HMTs) was inversely correlated to the activity of NNMT, an enzyme previously characterised as a methyl sink that disposes of excess methyl groups carried by the universal methyl donor S-adenosyl methionine (SAM or AdoMet). In healthy tissues, histone methylation was inversely correlated to the levels of an alternative methyl sink, PEMT. These associations affected the levels of multiple histone marks on chromatin genome-wide but had no detectable impact on transcriptional regulation. We show that HMTs with a variety of different associations to transcription are co-regulated by the Retinoblastoma (Rb) tumour suppressor in human cells. Rb-mutant cancers show increased total HMT activity and down-regulation of NNMT. Together, our results suggest that the total activity of HMTs affects SAM metabolism, independent of transcriptional regulation.
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Affiliation(s)
- Marcos Francisco Perez
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
- Department of Cells and Tissues, Instituto de Biologia Molecular de Barcelona (IBMB), CSIC, Barcelona, Spain
| | - Peter Sarkies
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
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8
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Fuchs S, Danßmann C, Klironomos F, Winkler A, Fallmann J, Kruetzfeldt LM, Szymansky A, Naderi J, Bernhart SH, Grunewald L, Helmsauer K, Rodriguez-Fos E, Kirchner M, Mertins P, Astrahantseff K, Suenkel C, Toedling J, Meggetto F, Remke M, Stadler PF, Hundsdoerfer P, Deubzer HE, Künkele A, Lang P, Fuchs J, Henssen AG, Eggert A, Rajewsky N, Hertwig F, Schulte JH. Defining the landscape of circular RNAs in neuroblastoma unveils a global suppressive function of MYCN. Nat Commun 2023; 14:3936. [PMID: 37402719 DOI: 10.1038/s41467-023-38747-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 05/12/2023] [Indexed: 07/06/2023] Open
Abstract
Circular RNAs (circRNAs) are a regulatory RNA class. While cancer-driving functions have been identified for single circRNAs, how they modulate gene expression in cancer is not well understood. We investigate circRNA expression in the pediatric malignancy, neuroblastoma, through deep whole-transcriptome sequencing in 104 primary neuroblastomas covering all risk groups. We demonstrate that MYCN amplification, which defines a subset of high-risk cases, causes globally suppressed circRNA biogenesis directly dependent on the DHX9 RNA helicase. We detect similar mechanisms in shaping circRNA expression in the pediatric cancer medulloblastoma implying a general MYCN effect. Comparisons to other cancers identify 25 circRNAs that are specifically upregulated in neuroblastoma, including circARID1A. Transcribed from the ARID1A tumor suppressor gene, circARID1A promotes cell growth and survival, mediated by direct interaction with the KHSRP RNA-binding protein. Our study highlights the importance of MYCN regulating circRNAs in cancer and identifies molecular mechanisms, which explain their contribution to neuroblastoma pathogenesis.
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Affiliation(s)
- Steffen Fuchs
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany.
- The German Cancer Consortium (DKTK), Partner Site Berlin, 10117, Berlin, Germany.
- The German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany.
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, 10178, Berlin, Germany.
- CRCT, Inserm, CNRS, Université Toulouse III-Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Université de Toulouse, 31037, Toulouse, France.
- Laboratoire d'Excellence Toulouse Cancer-TOUCAN, 31037, Toulouse, France.
| | - Clara Danßmann
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
| | - Filippos Klironomos
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
| | - Annika Winkler
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
| | - Jörg Fallmann
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, 04107, Leipzig, Germany
| | - Louisa-Marie Kruetzfeldt
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
| | - Annabell Szymansky
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
| | - Julian Naderi
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, 14195, Berlin, Germany
| | - Stephan H Bernhart
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, 04107, Leipzig, Germany
| | - Laura Grunewald
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
- The German Cancer Consortium (DKTK), Partner Site Berlin, 10117, Berlin, Germany
- The German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Konstantin Helmsauer
- Experimental and Clinical Research Center (ECRC) of the Charité and Max-Delbrück-Center for Molecular Medicine (MDC) in the Helmholtz Association, 13125, Berlin, Germany
| | - Elias Rodriguez-Fos
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
- Experimental and Clinical Research Center (ECRC) of the Charité and Max-Delbrück-Center for Molecular Medicine (MDC) in the Helmholtz Association, 13125, Berlin, Germany
| | - Marieluise Kirchner
- Core Unit Proteomics, Berlin Institute of Health at Charité - Universitätsmedizin Berlin and Max Delbrück Center for Molecular Medicine (MDC), 13125, Berlin, Germany
| | - Philipp Mertins
- Core Unit Proteomics, Berlin Institute of Health at Charité - Universitätsmedizin Berlin and Max Delbrück Center for Molecular Medicine (MDC), 13125, Berlin, Germany
| | - Kathy Astrahantseff
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
| | - Christin Suenkel
- Systems Biology of Gene Regulatory Elements, Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Hannoversche Straße 28, 10115, Berlin, Germany
- Lonza Drug Product Services, 4057, Basel, Switzerland
| | - Joern Toedling
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
- The German Cancer Consortium (DKTK), Partner Site Berlin, 10117, Berlin, Germany
- The German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Fabienne Meggetto
- CRCT, Inserm, CNRS, Université Toulouse III-Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Université de Toulouse, 31037, Toulouse, France
- Laboratoire d'Excellence Toulouse Cancer-TOUCAN, 31037, Toulouse, France
| | - Marc Remke
- Department of Pediatric Oncology, Hematology and Clinical Immunology, Heinrich Heine University Düsseldorf, Medical Faculty, and University Hospital Düsseldorf, 40225, Düsseldorf, Germany
- The German Cancer Consortium (DKTK), Partner Site Essen/Düsseldorf, 40225, Düsseldorf, Germany
- Institute of Neuropathology, Heinrich Heine University Düsseldorf, Medical Faculty, and University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - Peter F Stadler
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, 04107, Leipzig, Germany
| | - Patrick Hundsdoerfer
- Department of Pediatric Oncology, Helios Klinikum Berlin-Buch, 13125, Berlin, Germany
| | - Hedwig E Deubzer
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
- The German Cancer Consortium (DKTK), Partner Site Berlin, 10117, Berlin, Germany
- The German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, 10178, Berlin, Germany
- Experimental and Clinical Research Center (ECRC) of the Charité and Max-Delbrück-Center for Molecular Medicine (MDC) in the Helmholtz Association, 13125, Berlin, Germany
| | - Annette Künkele
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
- The German Cancer Consortium (DKTK), Partner Site Berlin, 10117, Berlin, Germany
- The German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Peter Lang
- Department I - General Pediatrics, Hematology/Oncology, University Children's Hospital, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany
| | - Jörg Fuchs
- Department of Pediatric Surgery and Pediatric Urology, University Children's Hospital, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany
| | - Anton G Henssen
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
- The German Cancer Consortium (DKTK), Partner Site Berlin, 10117, Berlin, Germany
- The German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Experimental and Clinical Research Center (ECRC) of the Charité and Max-Delbrück-Center for Molecular Medicine (MDC) in the Helmholtz Association, 13125, Berlin, Germany
| | - Angelika Eggert
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
- The German Cancer Consortium (DKTK), Partner Site Berlin, 10117, Berlin, Germany
- The German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, 10178, Berlin, Germany
| | - Nikolaus Rajewsky
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
- Systems Biology of Gene Regulatory Elements, Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Hannoversche Straße 28, 10115, Berlin, Germany
| | - Falk Hertwig
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany
- The German Cancer Consortium (DKTK), Partner Site Berlin, 10117, Berlin, Germany
- The German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Johannes H Schulte
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, 13353, Berlin, Germany.
- The German Cancer Consortium (DKTK), Partner Site Berlin, 10117, Berlin, Germany.
- The German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany.
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, 10178, Berlin, Germany.
- Department I - General Pediatrics, Hematology/Oncology, University Children's Hospital, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany.
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9
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Bhukdee D, Nuwongsri P, Israsena N, Sriswasdi S. Improved Delineation of Colorectal Cancer Molecular Subtypes and Functional Profiles with a 62-Gene Panel. Mol Cancer Res 2023; 21:240-252. [PMID: 36490322 DOI: 10.1158/1541-7786.mcr-22-0476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 11/01/2022] [Accepted: 12/07/2022] [Indexed: 12/14/2022]
Abstract
Since its establishment in 2015, the transcriptomics-based consensus molecular subtype (CMS) classification has unified our understanding of colorectal cancer. Each of the four CMS exhibited distinctive high-level molecular signatures that correlated well with prognosis and treatment response. Nonetheless, many key aspects of colorectal cancer progression and intra-subtype heterogeneity remain unresolved. This is partly because the bulk transcriptomic data used to define CMS contain substantial interference from non-tumor cells. Here, we propose a concise panel of 62 genes that not only accurately recapitulates all key characteristics of the four original CMS but also identifies three additional subpopulations with unique molecular signatures. Validation on independent cohorts confirms that the new CMS4 intra-subtypes coincide with single-cell-derived intrinsic subtypes and that the panel consists of many immune cell-type markers that can capture the status of tumor microenvironment. Furthermore, a 2D embedding of CMS structure based on the proposed gene panel provides a high-resolution view of the functional pathways and cell-type markers that underlie each CMS intra-subtype and the continuous progression from CMS2 to CMS4 subtypes. Our gene panel and 2D visualization refined the delineation of colorectal cancer subtypes and could aid further discovery of molecular mechanisms in colorectal cancer. IMPLICATIONS : Well-selected gene panel and representation can capture both the continuum of cancer cell states and tumor microenvironment status.
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Affiliation(s)
- Dhup Bhukdee
- Science Division, Mahidol University International College, Nakhon Pathom, Thailand.,Center of Excellence in Computational Molecular Biology, Faculty of Medicine, Chulalongkorn University, Pathum Wan, Bangkok, Thailand
| | - Pattarin Nuwongsri
- Center of Excellence in Computational Molecular Biology, Faculty of Medicine, Chulalongkorn University, Pathum Wan, Bangkok, Thailand.,Center of Excellence in Stem Cell and Cell Therapy, Faculty of Medicine, Chulalongkorn University, Pathum Wan, Bangkok, Thailand
| | - Nipan Israsena
- Center of Excellence in Stem Cell and Cell Therapy, Faculty of Medicine, Chulalongkorn University, Pathum Wan, Bangkok, Thailand.,Department of Pharmacology, Faculty of Medicine, Chulalongkorn University, Pathum Wan, Bangkok, Thailand
| | - Sira Sriswasdi
- Center of Excellence in Computational Molecular Biology, Faculty of Medicine, Chulalongkorn University, Pathum Wan, Bangkok, Thailand.,Center for Artificial Intelligence in Medicine, Research Affairs, Faculty of Medicine, Chulalongkorn University, Pathum Wan, Bangkok, Thailand
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10
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Zamani-Ahmadmahmudi M, Jajarmi M, Talebipour S. Molecular phenotyping of malignant canine mammary tumours: Detection of high-risk group and its relationship with clinicomolecular characteristics. Vet Comp Oncol 2023; 21:73-81. [PMID: 36251017 DOI: 10.1111/vco.12863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 10/09/2022] [Accepted: 10/10/2022] [Indexed: 11/27/2022]
Abstract
Canine mammary gland tumours (CMTs) constitute the most common cancer in female dogs and comprise approximately 50% of all canine cancers. With the advent of high-throughput technologies such as microarray and next-generation sequencing, the molecular phenotyping (classification) of various cancers has been extensively developed. The present study used a canine RNA-sequencing dataset, namely GSE119810, to classify 113 malignant CMTs and 64 matched normal samples via an unsupervised hierarchical algorithm with a view to evaluating the association between the resulting subtypes (clusters) (n = 4) and clinical and molecular characteristics. Finally, a molecular classifier was developed, and it detected 1 high-risk molecular subtype in the training dataset (GSE119810) and 2 independent validation datasets (GSE20718 and GSE22516). Our results revealed four molecular subtypes (C2-C5) in malignant CMTs. Furthermore, the normal samples constituted a distinct group in the clustering analysis. Marked significant associations were observed between the molecular subtypes (especially C5) and clinical/molecular features, including positive lymphatic invasion, high tumour grades, histopathology diagnoses, short survival and high TP53 mutation rates (ps <.05). The high-risk subtype (C5) was further characterized through the development of a cell cycle-based gene signature, which comprised 37 proliferation-related genes according to the support vector machine algorithm. This signature identified the high-risk group in both training and validation datasets (ps <.001). In the validation analysis, our potential classifier robustly predicted patients with positive lymphatic invasion, metastases and short survival.
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Affiliation(s)
- Mohamad Zamani-Ahmadmahmudi
- Department of Clinical Science, Faculty of Veterinary Medicine, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Maziar Jajarmi
- Department of Pathobiology, Faculty of Veterinary Medicine, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Saeedeh Talebipour
- Department of Clinical Science, Faculty of Veterinary Medicine, Shahid Bahonar University of Kerman, Kerman, Iran
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11
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Luo J, Wu S, Rizvi H, Zhang Q, Egger JV, Osorio JC, Schoenfeld AJ, Plodkowski AJ, Ginsberg MS, Callahan MK, Maher C, Shoushtari AN, Postow MA, Voss MH, Kotecha RR, Gupta A, Raja R, Kris MG, Hellmann MD. Deciphering radiological stable disease to immune checkpoint inhibitors. Ann Oncol 2022; 33:824-835. [PMID: 35533926 PMCID: PMC10001430 DOI: 10.1016/j.annonc.2022.04.450] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 04/17/2022] [Accepted: 04/19/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND 'Stable disease (SD)' as per RECIST is a common but ambiguous outcome in patients receiving immune checkpoint inhibitors (ICIs). This study aimed to characterize SD and identify the subset of patients with SD who are benefiting from treatment. Understanding SD would facilitate drug development and improve precision in correlative research. PATIENTS AND METHODS A systematic review was carried out to characterize SD in ICI trials. SD and objective response were compared to proliferation index using The Cancer Genome Atlas gene expression data. To identify a subgroup of SD with outcomes mirroring responders, we examined a discovery cohort of non-small-cell lung cancer (NSCLC). Serial cutpoints of two variables, % best overall response and progression-free survival (PFS), were tested to define a subgroup of patients with SD with similar survival as responders. Results were then tested in external validation cohorts. RESULTS Among trials of ICIs (59 studies, 14 280 patients), SD ranged from 16% to 42% in different tumor types and was associated with disease-specific proliferation index (ρ = -0.75, P = 0.03), a proxy of tumor kinetics, rather than relative response to ICIs. In a discovery cohort of NSCLC [1220 patients, 313 (26%) with SD to ICIs], PFS ranged widely in SD (0.2-49 months, median 4.9 months). The subset with PFS >6 months and no tumor growth mirrored partial response (PR) minor (overall survival hazard ratio 1.0) and was proposed as the definition of SD responder. This definition was confirmed in two validation cohorts from trials of NSCLC treated with durvalumab and found to apply in tumor types treated with immunotherapy in which depth and duration of benefit were correlated. CONCLUSIONS RECIST-defined SD to immunotherapy is common, heterogeneous, and may largely reflect tumor growth rate rather than ICI response. In patients with NSCLC and SD to ICIs, PFS >6 months and no tumor growth may be considered 'SD responders'. This definition may improve the efficiency of and insight derivable from clinical and translational research.
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Affiliation(s)
- J Luo
- Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA; Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, USA; Department of Medicine, Harvard Medical School, Boston, USA
| | - S Wu
- Translational Medicine Oncology, AstraZeneca, Gaithersburg, USA
| | - H Rizvi
- Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, USA
| | - Q Zhang
- Translational Medicine Oncology, AstraZeneca, Gaithersburg, USA
| | - J V Egger
- Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, USA
| | - J C Osorio
- Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - A J Schoenfeld
- Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA; Department of Medicine, Weill Cornell Medical Center, New York, USA
| | - A J Plodkowski
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, USA
| | - M S Ginsberg
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, USA
| | - M K Callahan
- Department of Medicine, Weill Cornell Medical Center, New York, USA; Parker Institute for Cancer Immunotherapy at Memorial Sloan Kettering Cancer Center, New York, USA; Melanoma Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - C Maher
- Melanoma Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - A N Shoushtari
- Department of Medicine, Weill Cornell Medical Center, New York, USA; Melanoma Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - M A Postow
- Department of Medicine, Weill Cornell Medical Center, New York, USA; Melanoma Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - M H Voss
- Department of Medicine, Weill Cornell Medical Center, New York, USA; Genitourinary Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - R R Kotecha
- Department of Medicine, Weill Cornell Medical Center, New York, USA; Genitourinary Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA
| | - A Gupta
- Global Medicines Development, AstraZeneca, Gaithersburg, USA
| | - R Raja
- Translational Medicine Oncology, AstraZeneca, Gaithersburg, USA
| | - M G Kris
- Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA; Department of Medicine, Weill Cornell Medical Center, New York, USA
| | - M D Hellmann
- Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA; Department of Medicine, Weill Cornell Medical Center, New York, USA; Parker Institute for Cancer Immunotherapy at Memorial Sloan Kettering Cancer Center, New York, USA.
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12
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Nath A, Cohen AL, Bild AH. ENDORSE: a prognostic model for endocrine therapy in estrogen-receptor-positive breast cancers. Mol Syst Biol 2022; 18:e10558. [PMID: 35671075 PMCID: PMC9172932 DOI: 10.15252/msb.202110558] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 05/19/2022] [Accepted: 05/20/2022] [Indexed: 12/14/2022] Open
Abstract
Advanced and metastatic estrogen receptor-positive (ER+ ) breast cancers are often endocrine resistant. However, endocrine therapy remains the primary treatment for all advanced ER+ breast cancers. Treatment options that may benefit resistant cancers, such as add-on drugs that target resistance pathways or switching to chemotherapy, are only available after progression on endocrine therapy. Here we developed an endocrine therapy prognostic model for early and advanced ER+ breast cancers. The endocrine resistance (ENDORSE) model is composed of two components, each based on the empirical cumulative distribution function of ranked expression of gene signatures. These signatures include a feature set associated with long-term survival outcomes on endocrine therapy selected using lasso-regularized Cox regression and a pathway-based curated set of genes expressed in response to estrogen. We extensively validated ENDORSE in multiple ER+ clinical trial datasets and demonstrated superior and consistent performance of the model over clinical covariates, proliferation markers, and multiple published signatures. Finally, genomic and pathway analyses in patient data revealed possible mechanisms that may help develop rational stratification strategies for endocrine-resistant ER+ breast cancer patients.
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Affiliation(s)
- Aritro Nath
- Department of Medical Oncology and TherapeuticsCity of Hope Comprehensive Cancer CenterMonroviaCAUSA
| | - Adam L Cohen
- Neuro Oncology ProgramInova Schar Cancer InstituteFairfaxVAUSA
| | - Andrea H Bild
- Department of Medical Oncology and TherapeuticsCity of Hope Comprehensive Cancer CenterMonroviaCAUSA
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13
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Sharaf R, Montesion M, Hopkins JF, Song J, Frampton GM, Albacker LA. A pan-cancer landscape of telomeric content shows that RAD21 and HGF alterations are associated with longer telomeres. Genome Med 2022; 14:25. [PMID: 35227290 PMCID: PMC8883689 DOI: 10.1186/s13073-022-01029-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 02/11/2022] [Indexed: 01/02/2023] Open
Abstract
Background Cancer cells can proliferate indefinitely through telomere maintenance mechanisms. These mechanisms include telomerase-dependent elongation, mediated by TERT activation, and alternative lengthening of telomeres (ALT), linked to loss of ATRX or DAXX. Methods We analyzed the telomeric content of 89,959 tumor samples within the Foundation Medicine dataset and investigated the genomic determinants of high telomeric content, linking them to clinical outcomes, when available. Results Telomeric content varied widely by disease type with leiomyosarcoma having the highest and Merkel cell carcinoma having the lowest telomeric content. In agreement with previous studies, telomeric content was significantly higher in samples with alterations in TERC, ATRX, and DAXX. We further identified that amplifications in two genes, RAD21 and HGF, were enriched in samples with high telomeric content, which was confirmed using the PCAWG/ICGC dataset. We identified the minimal amplified region associated with high telomeric content for RAD21 (8q23.1–8q24.12), which excludes MYC, and for HGF (7q21.11). Our results demonstrated that RAD21 and HGF exerted an additive telomere lengthening effect on samples with existing alterations in canonical genes previously associated with telomere elongation. Furthermore, patients with breast cancer who harbor RAD21 alterations had poor median overall survival and trended towards higher levels of Ki-67 staining. Conclusions This study highlights the importance of the role played by RAD21 (8q23.1–8q24.12) and HGF (7q21.11) in the lengthening of telomeres, supporting unlimited replication in tumors. These findings open avenues for work aimed at targeting this crucial pathway in tumorigenesis. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-022-01029-7.
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Affiliation(s)
- Radwa Sharaf
- Foundation Medicine Inc, 150 Second Street, Cambridge, MA, 02141, USA
| | - Meagan Montesion
- Foundation Medicine Inc, 150 Second Street, Cambridge, MA, 02141, USA
| | - Julia F Hopkins
- Foundation Medicine Inc, 150 Second Street, Cambridge, MA, 02141, USA
| | - Jiarong Song
- Foundation Medicine Inc, 150 Second Street, Cambridge, MA, 02141, USA
| | | | - Lee A Albacker
- Foundation Medicine Inc, 150 Second Street, Cambridge, MA, 02141, USA.
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14
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Perez MF, Sarkies P. Malignancy and NF-κB signalling strengthen coordination between expression of mitochondrial and nuclear-encoded oxidative phosphorylation genes. Genome Biol 2021; 22:328. [PMID: 34857014 PMCID: PMC8638269 DOI: 10.1186/s13059-021-02541-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 11/11/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Mitochondria are ancient endosymbiotic organelles crucial to eukaryotic growth and metabolism. The mammalian mitochondrial genome encodes for 13 mitochondrial proteins, and the remaining mitochondrial proteins are encoded by the nuclear genome. Little is known about how coordination between the expression of the two sets of genes is achieved. RESULTS Correlation analysis of RNA-seq expression data from large publicly available datasets is a common method to leverage genetic diversity to infer gene co-expression modules. Here we use this method to investigate nuclear-mitochondrial gene expression coordination. We identify a pitfall in correlation analysis that results from the large variation in the proportion of transcripts from the mitochondrial genome in RNA-seq data. Commonly used normalisation techniques based on total read counts, such as FPKM or TPM, produce artefactual negative correlations between mitochondrial- and nuclear-encoded transcripts. This also results in artefactual correlations between pairs of nuclear-encoded genes, with important consequences for inferring co-expression modules beyond mitochondria. We show that these effects can be overcome by normalizing using the median-ratio normalisation (MRN) or trimmed mean of M values (TMM) methods. Using these normalisations, we find only weak and inconsistent correlations between mitochondrial and nuclear-encoded mitochondrial genes in the majority of healthy human tissues from the GTEx database. CONCLUSIONS We show that a subset of healthy tissues with high expression of NF-κB show significant coordination, suggesting a role for NF-κB in ensuring balanced expression between mitochondrial and nuclear genes. Contrastingly, most cancer types show robust coordination of nuclear and mitochondrial OXPHOS gene expression, identifying this as a feature of gene regulation in cancer.
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Affiliation(s)
- Marcos Francisco Perez
- MRC London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK.
- Institute of Clinical Sciences, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK.
| | - Peter Sarkies
- MRC London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK.
- Institute of Clinical Sciences, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK.
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, UK.
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15
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Okajima D, Yasuda S, Maejima T, Karibe T, Sakurai K, Aida T, Toki T, Yamaguchi J, Kitamura M, Kamei R, Fujitani T, Honda T, Shibutani T, Muramatsu S, Nakada T, Goto R, Takahashi S, Yamaguchi M, Hamada H, Noguchi Y, Murakami M, Abe Y, Agatsuma T. Datopotamab Deruxtecan, a Novel TROP2-directed Antibody-drug Conjugate, Demonstrates Potent Antitumor Activity by Efficient Drug Delivery to Tumor Cells. Mol Cancer Ther 2021; 20:2329-2340. [PMID: 34413126 PMCID: PMC9398094 DOI: 10.1158/1535-7163.mct-21-0206] [Citation(s) in RCA: 90] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 06/15/2021] [Accepted: 08/12/2021] [Indexed: 01/07/2023]
Abstract
Trophoblast cell surface antigen 2 (TROP2) is highly expressed on various epithelial tumors and correlates with poor prognosis. We developed the novel TROP2-directed antibody-drug conjugate (ADC), datopotamab deruxtecan (Dato-DXd, DS-1062a), with a potent DNA topoisomerase I inhibitor (DXd), and evaluated its antitumor activity and safety profiles in preclinical models.The pharmacologic activity and mechanism of action of Dato-DXd were investigated in several human cancer cell lines and xenograft mouse models including patient-derived xenograft (PDX) models. Safety profiles were also assessed in rats and cynomolgus monkeys.Dato-DXd bound specifically to TROP2 and was internalized into tumor cells followed by intracellular trafficking to lysosome and DXd release, which induced DNA damage and apoptosis in TROP2-expressing tumor cells in vitro. Dato-DXd exhibited in vivo antitumor activity with DNA damage induced by the accumulated DXd in TROP2-expressing xenograft tumors, but neither isotype control IgG-ADC nor anti-TROP2 antibody had this effect. Dato-DXd also showed potent antitumor activity with tumor regression in several TROP2-expressing xenograft tumors including NSCLC PDX models. Safety profiles of Dato-DXd in rats and cynomolgus monkeys were acceptable.Dato-DXd demonstrated potent antitumor activity against TROP2-expressing tumors by efficient payload delivery into tumors and acceptable safety profiles in preclinical models. These results suggest Dato-DXd could be a valuable treatment option for patients with TROP2-expressing tumors in the clinical setting.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Riki Goto
- Daiichi Sankyo Co., Ltd., Tokyo, Japan
| | - Shu Takahashi
- Daiichi Sankyo Co., Ltd., Tokyo, Japan.,Department of Molecular Medicine, Research Institute for Frontier Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan
| | - Miki Yamaguchi
- Department of Molecular Medicine, Research Institute for Frontier Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan
| | - Hirofumi Hamada
- Department of Molecular Medicine, Research Institute for Frontier Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan
| | | | | | - Yuki Abe
- Daiichi Sankyo Co., Ltd., Tokyo, Japan
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16
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Rocha D, García IA, González Montoro A, Llera A, Prato L, Girotti MR, Soria G, Fernández EA. Pan-Cancer Molecular Patterns and Biological Implications Associated with a Tumor-Specific Molecular Signature. Cells 2020; 10:E45. [PMID: 33396205 PMCID: PMC7823585 DOI: 10.3390/cells10010045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 11/25/2020] [Accepted: 11/26/2020] [Indexed: 12/13/2022] Open
Abstract
Studying tissue-independent components of cancer and defining pan-cancer subtypes could be addressed using tissue-specific molecular signatures if classification errors are controlled. Since PAM50 is a well-known, United States Food and Drug Administration (FDA)-approved and commercially available breast cancer signature, we applied it with uncertainty assessment to classify tumor samples from over 33 cancer types, discarded unassigned samples, and studied the emerging tumor-agnostic molecular patterns. The percentage of unassigned samples ranged between 55.5% and 86.9% in non-breast tissues, and gene set analysis suggested that the remaining samples could be grouped into two classes (named C1 and C2) regardless of the tissue. The C2 class was more dedifferentiated, more proliferative, with higher centrosome amplification, and potentially more TP53 and RB1 mutations. We identified 28 gene sets and 95 genes mainly associated with cell-cycle progression, cell-cycle checkpoints, and DNA damage that were consistently exacerbated in the C2 class. In some cancer types, the C1/C2 classification was associated with survival and drug sensitivity, and modulated the prognostic meaning of the immune infiltrate. Our results suggest that PAM50 could be repurposed for a pan-cancer context when paired with uncertainty assessment, resulting in two classes with molecular, biological, and clinical implications.
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Affiliation(s)
- Darío Rocha
- Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina; (D.R.); (A.G.M.)
| | - Iris A. García
- Centro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas, Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Católica de Córdoba, Córdoba X5016DHK, Argentina;
- Departamento de Bioquímica Clínica, Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina;
| | - Aldana González Montoro
- Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina; (D.R.); (A.G.M.)
- Facultad de Matemática, Astronomía y Física, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina
| | - Andrea Llera
- Laboratorio de Terapia Molecular y Celular—Genocan, Fundación Instituto Leloir, Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires C1405BWE, Argentina;
| | - Laura Prato
- Instituto Académico Pedagógico de Ciencias Básicas y Aplicadas, Universidad Nacional de Villa María, Villa María, Córdoba X5900, Argentina;
| | - María R. Girotti
- Laboratorio de Inmuno Oncología Traslacional, Instituto de Biología y Medicina Experimental, Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires C1428ADN, Argentina;
| | - Gastón Soria
- Departamento de Bioquímica Clínica, Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina;
- Centro de Investigaciones en Bioquímica Clínica e Inmunología, Consejo Nacional de Investigaciones Científicas y Técnicas, Córdoba X5000HUA, Argentina
| | - Elmer A. Fernández
- Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina; (D.R.); (A.G.M.)
- Centro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas, Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Católica de Córdoba, Córdoba X5016DHK, Argentina;
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17
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Schaafsma E, Zhao Y, Zhang L, Li Y, Cheng C. MYC Activity Inference Captures Diverse Mechanisms of Aberrant MYC Pathway Activation in Human Cancers. Mol Cancer Res 2020; 19:414-428. [PMID: 33234576 DOI: 10.1158/1541-7786.mcr-20-0526] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 08/21/2020] [Accepted: 11/20/2020] [Indexed: 11/16/2022]
Abstract
c-MYC (MYC) is deregulated in more than 50% of all cancers. While MYC amplification is the most common MYC-deregulating event, many other alterations can increase MYC activity. We thus systematically investigated MYC pathway activity across different tumor types. Using a logistic regression framework, we established tumor type-specific, transcriptomic-based MYC activity scores that can accurately capture MYC activity. We show that MYC activity scores reflect a variety of MYC-regulating mechanisms, including MYCL and/or MYCN amplification, MYC promoter methylation, MYC mRNA expression, lncRNA PVT1 expression, MYC mutations, and viral integrations near the MYC locus. Our MYC activity score incorporates all of these mechanisms, resulting in better prognostic predictions compared with MYC amplification status, MYC promoter methylation, and MYC mRNA expression in several cancer types. In addition, we show that tumor proliferation and immune evasion are likely contributors to this reduction in survival. Finally, we developed a MYC activity signature for liquid tumors in which MYC translocation is commonly observed, suggesting that our approach can be applied to different types of genomic alterations. In conclusion, we developed a MYC activity score that captures MYC pathway activity and is clinically relevant. IMPLICATIONS: By using cancer type-specific MYC activity profiles, we were able to assess MYC activity across many more tumor types than previously investigated. The range of different MYC-related alterations captured by our MYC activity score can be used to facilitate the application of future MYC inhibitors and aid physicians to preselect patients for targeted therapy.
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Affiliation(s)
- Evelien Schaafsma
- Department of Molecular and Systems Biology, Dartmouth College, Hanover, New Hampshire
| | - Yanding Zhao
- Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Lanjing Zhang
- Department of Biological Sciences, Rutgers University, Newark, New Jersey.,Department of Pathology, Princeton Medical Center, Plainsboro, New Jersey
| | - Yong Li
- Department of Medicine, Section of Epidemiology and Population Sciences, Baylor College of Medicine, Houston, Texas
| | - Chao Cheng
- Department of Medicine, Baylor College of Medicine, Houston, Texas. .,Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas.,Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire.,The Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
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18
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Cardillo TM, Rossi DL, Zalath MB, Liu D, Arrojo R, Sharkey RM, Chang CH, Goldenberg DM. Predictive biomarkers for sacituzumab govitecan efficacy in Trop-2-expressing triple-negative breast cancer. Oncotarget 2020; 11:3849-3862. [PMID: 33196706 PMCID: PMC7597411 DOI: 10.18632/oncotarget.27766] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 09/23/2020] [Indexed: 12/21/2022] Open
Abstract
Sacituzumab govitecan (SG) is an antibody-drug conjugate composed of a humanized anti-Trop-2 IgG antibody conjugated via a hydrolysable linker to SN-38, the topoisomerase I-inhibitory active component of irinotecan. We investigated whether Trop-2-expression and homologous recombination repair (HRR) of SN-38-mediated double-strand DNA (dsDNA) breaks play a role in the sensitivity of triple-negative breast cancer (TNBC) to SG. Activation of HRR pathways, as evidenced by Rad51 expression, was assessed in SG-sensitive cell lines with low and moderate Trop-2-expression (SK-MES-1 squamous cell lung carcinoma and HCC1806 TNBC, respectively), compared to a low Trop-2-expressing, less SG-sensitive TNBC cell line (MDA-MB-231). Further, two Trop-2-transfectants of MDA-MB-231, C13 and C39 (4- and 25-fold higher Trop-2, respectively), were treated in mice with SG to determine whether increasing Trop-2 expression improves SG efficacy. SG mediated >2-fold increase in Rad51 in MDA-MB-231 but had no effect in SK-MES-1 or HCC1806, resulting in lower levels of dsDNA breaks in MDA-MB-231. SG and saline produced similar effects in parental MDA-MB-231 tumor-bearing mice (median survival time (MST) = 21d and 19.5d, respectively). However, in mice bearing higher Trop-2-expressing C13 and C39 tumors after Trop-2 transfection, SG provided a significant survival benefit, even compared to irinotecan (MST = 97d vs. 35d for C13, and 81d vs. 28d for C39, respectively; P < 0.0007). These results suggest that SG could provide better clinical benefit than irinotecan in patients with HRR-proficient tumors expressing high levels of Trop-2, as well as to patients with HRR-deficient tumors expressing low/moderate levels of Trop-2.
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Affiliation(s)
| | | | | | - Donglin Liu
- Immunomedics, Inc., Morris Plains, NJ 07950, USA.,Currently employed with FrontAim Biomedicines Inc., Princeton, NJ 08540, USA
| | | | - Robert M Sharkey
- Immunomedics, Inc., Morris Plains, NJ 07950, USA.,At the time the work was conducted, these authors were employees of Immunomedics, Inc., Morris Plains, NJ 07950, USA
| | - Chien-Hsing Chang
- Immunomedics, Inc., Morris Plains, NJ 07950, USA.,At the time the work was conducted, these authors were employees of Immunomedics, Inc., Morris Plains, NJ 07950, USA
| | - David M Goldenberg
- Immunomedics, Inc., Morris Plains, NJ 07950, USA.,Current address: Center for Molecular Medicine and Immunology, Mendham, NJ 07945, USA.,At the time the work was conducted, this author was Chairman and Chief Scientific Officer of Immunomedics, Inc., Morris Plains, NJ 07950, USA
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19
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Sharma A, Merritt E, Hu X, Cruz A, Jiang C, Sarkodie H, Zhou Z, Malhotra J, Riedlinger GM, De S. Non-Genetic Intra-Tumor Heterogeneity Is a Major Predictor of Phenotypic Heterogeneity and Ongoing Evolutionary Dynamics in Lung Tumors. Cell Rep 2020; 29:2164-2174.e5. [PMID: 31747591 PMCID: PMC6952742 DOI: 10.1016/j.celrep.2019.10.045] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 09/04/2019] [Accepted: 10/10/2019] [Indexed: 12/24/2022] Open
Abstract
Impacts of genetic and non-genetic intra-tumor heterogeneity (ITH) on tumor phenotypes and evolvability remain debated. We analyze ITH in lung squamous cell carcinoma at the levels of genome, transcriptome, and tumor-immune interactions and histopathological characteristics by multi-region bulk and single-cell sequencing. Genomic heterogeneity alone is a weak indicator of intra-tumor non-genetic heterogeneity at immune and transcriptomic levels that impact multiple cancer-related pathways, including those related to proliferation and inflammation, which in turn contribute to intra-tumor regional differences in histopathology and subtype classification. Tumor subclones have substantial differences in proliferation score, suggestive of non-neutral clonal dynamics. Proliferation and other cancer-related pathways also show intra-tumor regional differences, sometimes even within the same subclones. Neo-epitope burden negatively correlates with immune infiltration, indicating immune-mediated purifying selection on somatic mutations. Taken together, our observations suggest that non-genetic heterogeneity is a major determinant of heterogeneity in histopathological characteristics and impacts evolutionary dynamics in lung cancer.
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Affiliation(s)
- Anchal Sharma
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Elise Merritt
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Xiaoju Hu
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ 08901, USA
| | | | - Chuan Jiang
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Halle Sarkodie
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Zhan Zhou
- Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Jyoti Malhotra
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Gregory M Riedlinger
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Subhajyoti De
- Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ 08901, USA.
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20
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Pattwell SS, Arora S, Cimino PJ, Ozawa T, Szulzewsky F, Hoellerbauer P, Bonifert T, Hoffstrom BG, Boiani NE, Bolouri H, Correnti CE, Oldrini B, Silber JR, Squatrito M, Paddison PJ, Holland EC. A kinase-deficient NTRK2 splice variant predominates in glioma and amplifies several oncogenic signaling pathways. Nat Commun 2020; 11:2977. [PMID: 32532995 PMCID: PMC7293284 DOI: 10.1038/s41467-020-16786-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 05/26/2020] [Indexed: 12/17/2022] Open
Abstract
Independent scientific achievements have led to the discovery of aberrant splicing patterns in oncogenesis, while more recent advances have uncovered novel gene fusions involving neurotrophic tyrosine receptor kinases (NTRKs) in gliomas. The exploration of NTRK splice variants in normal and neoplastic brain provides an intersection of these two rapidly evolving fields. Tropomyosin receptor kinase B (TrkB), encoded NTRK2, is known for critical roles in neuronal survival, differentiation, molecular properties associated with memory, and exhibits intricate splicing patterns and post-translational modifications. Here, we show a role for a truncated NTRK2 splice variant, TrkB.T1, in human glioma. TrkB.T1 enhances PDGF-driven gliomas in vivo, augments PDGF-induced Akt and STAT3 signaling in vitro, while next generation sequencing broadly implicates TrkB.T1 in the PI3K signaling cascades in a ligand-independent fashion. These TrkB.T1 findings highlight the importance of expanding upon whole gene and gene fusion analyses to include splice variants in basic and translational neuro-oncology research.
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Affiliation(s)
- Siobhan S Pattwell
- Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mailstop C3-168, Seattle, WA, 98109, USA
| | - Sonali Arora
- Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mailstop C3-168, Seattle, WA, 98109, USA
| | - Patrick J Cimino
- Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mailstop C3-168, Seattle, WA, 98109, USA
- Department of Pathology, University of Washington School of Medicine, 325 9th Avenue, Box 359791, Seattle, WA, 98104, USA
| | - Tatsuya Ozawa
- Division of Brain Tumor Translational Research, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Frank Szulzewsky
- Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mailstop C3-168, Seattle, WA, 98109, USA
| | - Pia Hoellerbauer
- Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mailstop C3-168, Seattle, WA, 98109, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, 98195, USA
| | - Tobias Bonifert
- Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mailstop C3-168, Seattle, WA, 98109, USA
| | - Benjamin G Hoffstrom
- Antibody Technology Resource, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA, 98109, USA
| | - Norman E Boiani
- Antibody Technology Resource, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA, 98109, USA
| | - Hamid Bolouri
- Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mailstop C3-168, Seattle, WA, 98109, USA
- Systems Immunology, Benaroya Research Institute at Virginia Mason, 1201 Ninth Avenue, Seattle, WA, 98101, USA
| | - Colin E Correnti
- Clinical Research Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA, 98109, USA
| | - Barbara Oldrini
- Seve Ballesteros Foundation Brain Tumor Group, Spanish National Cancer Research Centre, 28209, Madrid, Spain
| | - John R Silber
- Department of Neurological Surgery, Alvord Brain Tumor Center, University of Washington School of Medicine, Seattle, WA, 98104, USA
| | - Massimo Squatrito
- Seve Ballesteros Foundation Brain Tumor Group, Spanish National Cancer Research Centre, 28209, Madrid, Spain
| | - Patrick J Paddison
- Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mailstop C3-168, Seattle, WA, 98109, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA, 98195, USA
| | - Eric C Holland
- Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Mailstop C3-168, Seattle, WA, 98109, USA.
- Department of Neurological Surgery, Alvord Brain Tumor Center, University of Washington School of Medicine, Seattle, WA, 98104, USA.
- Seattle Tumor Translational Research Center, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA, 98109, USA.
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21
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Cook DJ, Kallus J, Jörnsten R, Nielsen J. Molecular natural history of breast cancer: Leveraging transcriptomics to predict breast cancer progression and aggressiveness. Cancer Med 2020; 9:3551-3562. [PMID: 32207233 PMCID: PMC7221450 DOI: 10.1002/cam4.2996] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 01/29/2020] [Accepted: 03/01/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Characterizing breast cancer progression and aggressiveness relies on categorical descriptions of tumor stage and grade. Interpreting these categorical descriptions is challenging because stage convolutes the size and spread of the tumor and no consensus exists to define high/low grade tumors. METHODS We address this challenge of heterogeneity in patient-specific cancer samples by adapting and applying several tools originally created for understanding heterogeneity and phenotype development in single cells (specifically, single-cell topological data analysis and Wanderlust) to create a continuous metric describing breast cancer progression using bulk RNA-seq samples from individual patient tumors. We also created a linear regression-based method to predict tumor aggressiveness in vivo from bulk RNA-seq data. RESULTS We found that breast cancer proceeds along three convergent phenotype trajectories: luminal, HER2-enriched, and basal-like. Furthermore, 31 296 genes (for luminal cancers), 17 827 genes (for HER2-enriched), and 18 505 genes (for basal-like) are dynamically differentially expressed during breast cancer progression. Across progression trajectories, our results show that expression of genes related to ADP-ribosylation decreased as tumors progressed (while PARP1 and PARP2 increased or remained stable), suggesting the potential for a differential response to PARP inhibitors based on cancer progression. Additionally, we developed a 132-gene expression regression equation to predict mitotic index and a 23-gene expression regression equation to predict growth rate from a single breast cancer biopsy. CONCLUSION Our results suggest that breast cancer dynamically changes during disease progression, and growth rate of the cancer cells is associated with distinct transcriptional profiles.
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Affiliation(s)
- Daniel J. Cook
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
- Wallenberg Center for Protein ResearchChalmers University of TechnologyGothenburgSweden
| | - Jonatan Kallus
- Department of Mathematical SciencesChalmers University of Technology and University of GothenburgGothenburgSweden
| | - Rebecka Jörnsten
- Department of Mathematical SciencesChalmers University of Technology and University of GothenburgGothenburgSweden
| | - Jens Nielsen
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
- Wallenberg Center for Protein ResearchChalmers University of TechnologyGothenburgSweden
- Novo Nordisk Foundation Center for BiosustainabilityTechnical University of DenmarkLyngbyDenmark
- BioInnovation InstituteCopenhagen NDenmark
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22
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McCarthy DJ, Rostom R, Huang Y, Kunz DJ, Danecek P, Bonder MJ, Hagai T, Lyu R, Wang W, Gaffney DJ, Simons BD, Stegle O, Teichmann SA. Cardelino: computational integration of somatic clonal substructure and single-cell transcriptomes. Nat Methods 2020; 17:414-421. [PMID: 32203388 DOI: 10.1038/s41592-020-0766-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Accepted: 01/31/2020] [Indexed: 02/03/2023]
Abstract
Bulk and single-cell DNA sequencing has enabled reconstructing clonal substructures of somatic tissues from frequency and cooccurrence patterns of somatic variants. However, approaches to characterize phenotypic variations between clones are not established. Here we present cardelino (https://github.com/single-cell-genetics/cardelino), a computational method for inferring the clonal tree configuration and the clone of origin of individual cells assayed using single-cell RNA-seq (scRNA-seq). Cardelino flexibly integrates information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. We apply cardelino to a published cancer dataset and to newly generated matched scRNA-seq and exome-seq data from 32 human dermal fibroblast lines, identifying hundreds of differentially expressed genes between cells from different somatic clones. These genes are frequently enriched for cell cycle and proliferation pathways, indicating a role for cell division genes in somatic evolution in healthy skin.
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Affiliation(s)
- Davis J McCarthy
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.,St Vincent's Institute of Medical Research, Fitzroy, Victoria, Australia.,Melbourne Integrative Genomics, School of Mathematics and Statistics/School of Biosciences, University of Melbourne, Parkville, Victoria, Australia
| | - Raghd Rostom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Yuanhua Huang
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.,Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Daniel J Kunz
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.,Department of Physics, Cavendish Laboratory, Cambridge, UK.,The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK
| | - Petr Danecek
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Marc Jan Bonder
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Tzachi Hagai
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.,School of Molecular Cell Biology and Biotechnology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Ruqian Lyu
- St Vincent's Institute of Medical Research, Fitzroy, Victoria, Australia.,Melbourne Integrative Genomics, School of Mathematics and Statistics/School of Biosciences, University of Melbourne, Parkville, Victoria, Australia
| | | | - Wenyi Wang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Benjamin D Simons
- Department of Physics, Cavendish Laboratory, Cambridge, UK.,The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK.,The Wellcome Trust/Medical Research Council Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Oliver Stegle
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK. .,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK. .,European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany. .,Division of Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany.
| | - Sarah A Teichmann
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK. .,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK. .,Department of Physics, Cavendish Laboratory, Cambridge, UK.
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23
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Lanata CM, Paranjpe I, Nititham J, Taylor KE, Gianfrancesco M, Paranjpe M, Andrews S, Chung SA, Rhead B, Barcellos LF, Trupin L, Katz P, Dall'Era M, Yazdany J, Sirota M, Criswell LA. A phenotypic and genomics approach in a multi-ethnic cohort to subtype systemic lupus erythematosus. Nat Commun 2019; 10:3902. [PMID: 31467281 PMCID: PMC6715644 DOI: 10.1038/s41467-019-11845-y] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 07/13/2019] [Indexed: 01/05/2023] Open
Abstract
Systemic lupus erythematous (SLE) is a heterogeneous autoimmune disease in which outcomes vary among different racial groups. Here, we aim to identify SLE subgroups within a multiethnic cohort using an unsupervised clustering approach based on the American College of Rheumatology (ACR) classification criteria. We identify three patient clusters that vary according to disease severity. Methylation association analysis identifies a set of 256 differentially methylated CpGs across clusters, including 101 CpGs in genes in the Type I Interferon pathway, and we validate these associations in an external cohort. A cis-methylation quantitative trait loci analysis identifies 744 significant CpG-SNP pairs. The methylation signature is enriched for ethnic-associated CpGs suggesting that genetic and non-genetic factors may drive outcomes and ethnic-associated methylation differences. Our computational approach highlights molecular differences associated with clusters rather than single outcome measures. This work demonstrates the utility of applying integrative methods to address clinical heterogeneity in multifactorial multi-ethnic disease settings.
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Affiliation(s)
- Cristina M Lanata
- Russell/Engleman Rheumatology Research Center, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Ishan Paranjpe
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joanne Nititham
- Russell/Engleman Rheumatology Research Center, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Kimberly E Taylor
- Russell/Engleman Rheumatology Research Center, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Milena Gianfrancesco
- Russell/Engleman Rheumatology Research Center, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Manish Paranjpe
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
| | - Shan Andrews
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
| | - Sharon A Chung
- Russell/Engleman Rheumatology Research Center, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | | | | | - Laura Trupin
- Russell/Engleman Rheumatology Research Center, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Patricia Katz
- Russell/Engleman Rheumatology Research Center, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Maria Dall'Era
- Russell/Engleman Rheumatology Research Center, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Jinoos Yazdany
- Russell/Engleman Rheumatology Research Center, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
| | - Lindsey A Criswell
- Russell/Engleman Rheumatology Research Center, Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
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24
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Pabla S, Conroy JM, Nesline MK, Glenn ST, Papanicolau-Sengos A, Burgher B, Hagen J, Giamo V, Andreas J, Lenzo FL, Yirong W, Dy GK, Yau E, Early A, Chen H, Bshara W, Madden KG, Shirai K, Dragnev K, Tafe LJ, Marin D, Zhu J, Clarke J, Labriola M, McCall S, Zhang T, Zibelman M, Ghatalia P, Araujo-Fernandez I, Singavi A, George B, MacKinnon AC, Thompson J, Singh R, Jacob R, Dressler L, Steciuk M, Binns O, Kasuganti D, Shah N, Ernstoff M, Odunsi K, Kurzrock R, Gardner M, Galluzzi L, Morrison C. Proliferative potential and resistance to immune checkpoint blockade in lung cancer patients. J Immunother Cancer 2019; 7:27. [PMID: 30709424 PMCID: PMC6359802 DOI: 10.1186/s40425-019-0506-3] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 01/13/2019] [Indexed: 02/04/2023] Open
Abstract
Background Resistance to immune checkpoint inhibitors (ICIs) has been linked to local immunosuppression independent of major ICI targets (e.g., PD-1). Clinical experience with response prediction based on PD-L1 expression suggests that other factors influence sensitivity to ICIs in non-small cell lung cancer (NSCLC) patients. Methods Tumor specimens from 120 NSCLC patients from 10 institutions were evaluated for PD-L1 expression by immunohistochemistry, and global proliferative profile by targeted RNA-seq. Results Cell proliferation, derived from the mean expression of 10 proliferation-associated genes (namely BUB1, CCNB2, CDK1, CDKN3, FOXM1, KIAA0101, MAD2L1, MELK, MKI67, and TOP2A), was identified as a marker of response to ICIs in NSCLC. Poorly, moderately, and highly proliferative tumors were somewhat equally represented in NSCLC, with tumors with the highest PD-L1 expression being more frequently moderately proliferative as compared to lesser levels of PD-L1 expression. Proliferation status had an impact on survival in patients with both PD-L1 positive and negative tumors. There was a significant survival advantage for moderately proliferative tumors compared to their combined highly/poorly counterparts (p = 0.021). Moderately proliferative PD-L1 positive tumors had a median survival of 14.6 months that was almost twice that of PD-L1 negative highly/poorly proliferative at 7.6 months (p = 0.028). Median survival in moderately proliferative PD-L1 negative tumors at 12.6 months was comparable to that of highly/poorly proliferative PD-L1 positive tumors at 11.5 months, but in both instances less than that of moderately proliferative PD-L1 positive tumors. Similar to survival, proliferation status has impact on disease control (DC) in patients with both PD-L1 positive and negative tumors. Patients with moderately versus those with poorly or highly proliferative tumors have a superior DC rate when combined with any classification schema used to score PD-L1 as a positive result (i.e., TPS ≥ 50% or ≥ 1%), and best displayed by a DC rate for moderately proliferative tumors of no less than 40% for any classification of PD-L1 as a negative result. While there is an over representation of moderately proliferative tumors as PD-L1 expression increases this does not account for the improved survival or higher disease control rates seen in PD-L1 negative tumors. Conclusions Cell proliferation is potentially a new biomarker of response to ICIs in NSCLC and is applicable to PD-L1 negative tumors. Electronic supplementary material The online version of this article (10.1186/s40425-019-0506-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sarabjot Pabla
- OmniSeq, Inc., 700 Ellicott Street, Buffalo, NY, 14203, USA
| | - Jeffrey M Conroy
- OmniSeq, Inc., 700 Ellicott Street, Buffalo, NY, 14203, USA.,Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14206, USA
| | - Mary K Nesline
- OmniSeq, Inc., 700 Ellicott Street, Buffalo, NY, 14203, USA
| | - Sean T Glenn
- OmniSeq, Inc., 700 Ellicott Street, Buffalo, NY, 14203, USA.,Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14206, USA
| | | | - Blake Burgher
- OmniSeq, Inc., 700 Ellicott Street, Buffalo, NY, 14203, USA
| | - Jacob Hagen
- OmniSeq, Inc., 700 Ellicott Street, Buffalo, NY, 14203, USA
| | - Vincent Giamo
- OmniSeq, Inc., 700 Ellicott Street, Buffalo, NY, 14203, USA
| | | | | | - Wang Yirong
- OmniSeq, Inc., 700 Ellicott Street, Buffalo, NY, 14203, USA
| | - Grace K Dy
- Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14206, USA
| | - Edwin Yau
- Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14206, USA
| | - Amy Early
- Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14206, USA
| | - Hongbin Chen
- Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14206, USA
| | - Wiam Bshara
- Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14206, USA
| | | | - Keisuke Shirai
- Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA
| | | | - Laura J Tafe
- Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA
| | | | - Jason Zhu
- Duke University, Durham, NC, 27708, USA
| | | | | | | | | | | | | | | | - Arun Singavi
- Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Ben George
- Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | | | | | - Rajbir Singh
- Meharry Medical College, Nashville, TN, 37208, USA
| | - Robin Jacob
- Meharry Medical College, Nashville, TN, 37208, USA
| | | | - Mark Steciuk
- Mission Health System, Asheville, NC, 28801, USA
| | - Oliver Binns
- Mission Health System, Asheville, NC, 28801, USA
| | | | - Neel Shah
- Community Hospital, Munster, IN, 46321, USA
| | - Marc Ernstoff
- Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14206, USA
| | - Kunle Odunsi
- Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14206, USA
| | - Razelle Kurzrock
- Center for Personalized Cancer Therapy, Moores Cancer Center, La Jolla, CA, 92093, USA
| | - Mark Gardner
- OmniSeq, Inc., 700 Ellicott Street, Buffalo, NY, 14203, USA
| | - Lorenzo Galluzzi
- Department of Radiation Oncology, Weill Cornell Medical College, New York, NY, 10065, USA.,Sandra and Edward Meyer Cancer Center, New York, NY, 10065, USA.,Université Paris Descartes/Paris V, 75006, Paris, France
| | - Carl Morrison
- OmniSeq, Inc., 700 Ellicott Street, Buffalo, NY, 14203, USA. .,Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14206, USA.
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25
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Bielski CM, Zehir A, Penson AV, Donoghue MTA, Chatila W, Armenia J, Chang MT, Schram AM, Jonsson P, Bandlamudi C, Razavi P, Iyer G, Robson ME, Stadler ZK, Schultz N, Baselga J, Solit DB, Hyman DM, Berger MF, Taylor BS. Genome doubling shapes the evolution and prognosis of advanced cancers. Nat Genet 2018; 50:1189-1195. [PMID: 30013179 PMCID: PMC6072608 DOI: 10.1038/s41588-018-0165-1] [Citation(s) in RCA: 338] [Impact Index Per Article: 56.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2017] [Accepted: 05/22/2018] [Indexed: 01/22/2023]
Abstract
Ploidy abnormalities are a hallmark of cancer, but their impact on the evolution and outcomes of cancers is unknown. Here, we identified whole-genome doubling (WGD) in the tumors of nearly 30% of 9,692 prospectively sequenced advanced cancer patients. WGD varied by tumor lineage and molecular subtype, and arose early in carcinogenesis after an antecedent transforming driver mutation. While associated with TP53 mutations, 46% of all WGD arose in TP53-wild-type tumors and in such cases was associated with an E2F-mediated G1 arrest defect, although neither aberration was obligate in WGD tumors. The variability of WGD across cancer types can be explained in part by cancer cell proliferation rates. WGD predicted for increased morbidity across cancer types, including KRAS-mutant colorectal cancers and estrogen receptor-positive breast cancers, independently of established clinical prognostic factors. We conclude that WGD is highly common in cancer and is a macro-evolutionary event associated with poor prognosis across cancer types.
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Affiliation(s)
- Craig M Bielski
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ahmet Zehir
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Alexander V Penson
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Mark T A Donoghue
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Walid Chatila
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Joshua Armenia
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Matthew T Chang
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Genentech, San Francisco, CA, USA
| | - Alison M Schram
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Philip Jonsson
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Chaitanya Bandlamudi
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Pedram Razavi
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Gopa Iyer
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Mark E Robson
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Zsofia K Stadler
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Nikolaus Schultz
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jose Baselga
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - David B Solit
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, NY, USA
| | - David M Hyman
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, NY, USA
| | - Michael F Berger
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Barry S Taylor
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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26
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Schulze M, Violonchi C, Swoboda S, Welz T, Kerkhoff E, Hoja S, Brüggemann S, Simbürger J, Reinders J, Riemenschneider MJ. RELN signaling modulates glioblastoma growth and substrate-dependent migration. Brain Pathol 2018; 28:695-709. [PMID: 29222813 DOI: 10.1111/bpa.12584] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 11/24/2017] [Accepted: 11/30/2017] [Indexed: 12/15/2022] Open
Abstract
Glioblastoma (GBM) represents the most common and most malignant type of primary brain tumor and significantly contributes to cancer morbidity and mortality. Invasion into the healthy brain parenchyma is a major feature of glioblastoma aggressiveness. Reelin (RELN) is a large secreted extracellular matrix glycoprotein that regulates neuronal migration and positioning in the developing brain and sustains functionality in the adult brain. We here show that both RELN and its main downstream effector DAB1 are silenced in glioblastoma as compared to non-neoplastic tissue and mRNA expression is inversely correlated with malignancy grade. Furthermore, RELN expression is positively correlated with patient survival in two large, independent clinically annotated datasets. RELN silencing occurs via promoter hypermethylation as shown by both database mining and bisulfite sequencing of the RELN promoter. Consequently, treatment with 5'-Azacytidine and trichostatin A induced RELN expression in vitro. On the functional level, we found RELN to regulate glioblastoma cell migration both in a DAB1 (tyrosine phosphorylation)-dependent and -independent fashion, depending on the substrate provided. Moreover, stimulation of RELN signaling strongly reduced proliferation in glioblastoma cells. This phenotype depends on DAB1 stimulation by RELN, as a mutant that lacks all RELN induced tyrosine phosphorylation sites (DAB1-5F) failed to induce a growth arrest. Proteomic analyzes revealed that these effects are mediated by a reduction in E2F targets and dephosphorylation of ERK1/2. Taken together, our data establish a relevance of RELN signaling in glioblastoma pathology and thereby might unearth novel, yet unrecognized treatment options.
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Affiliation(s)
- Markus Schulze
- Department of Neuropathology, Regensburg University Hospital, Regensburg, Germany
| | - Christ Violonchi
- Department of Neuropathology, Heinrich-Heine University, Düsseldorf, Germany
| | - Stefan Swoboda
- Department of Neuropathology, Regensburg University Hospital, Regensburg, Germany
| | - Tobias Welz
- Molecular Cell Biology Laboratory, Department of Neurology, Regensburg University Hospital, Regensburg, Germany
| | - Eugen Kerkhoff
- Molecular Cell Biology Laboratory, Department of Neurology, Regensburg University Hospital, Regensburg, Germany
| | - Sabine Hoja
- Department of Neuropathology, Regensburg University Hospital, Regensburg, Germany
| | - Susanne Brüggemann
- Department of Neuropathology, Regensburg University Hospital, Regensburg, Germany
| | - Johann Simbürger
- Institute of Functional Genomics, University of Regensburg, Regensburg, Germany
| | - Jörg Reinders
- Institute of Functional Genomics, University of Regensburg, Regensburg, Germany
| | - Markus J Riemenschneider
- Department of Neuropathology, Regensburg University Hospital, Regensburg, Germany.,Wilhelm Sander-NeuroOncology Unit, Regensburg University Hospital, Regensburg, Germany
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