Ashton A Connor1, Robert E Denroche2, Gun Ho Jang3, Lee Timms4, Sangeetha N Kalimuthu5, Iris Selander6, Treasa McPherson6, Gavin W Wilson2, Michelle A Chan-Seng-Yue5, Ivan Borozan7, Vincent Ferretti7, Robert C Grant8, Ilinca M Lungu9, Eithne Costello10, William Greenhalf10, Daniel Palmer10, Paula Ghaneh10, John P Neoptolemos10, Markus Buchler11, Gloria Petersen12, Sarah Thayer13, Michael A Hollingsworth14, Alana Sherker15, Daniel Durocher15, Neesha Dhani16, David Hedley16, Stefano Serra17, Aaron Pollett18, Michael H A Roehrl19, Prashant Bavi5, John M S Bartlett9, Sean Cleary20, Julie M Wilson5, Ludmil B Alexandrov21, Malcolm Moore16, Bradly G Wouters22, John D McPherson23, Faiyaz Notta5, Lincoln D Stein24, Steven Gallinger1. 1. PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada2Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada3Hepatobiliary/Pancreatic Surgical Oncology Program, University Health Network, Toronto, Ontario, Canada. 2. PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada4Informatics and Bio-computing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada. 3. PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada4Informatics and Bio-computing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada5Department of Statistical Science, University of Toronto, Toronto, Ontario, Canada. 4. PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada6Genome Technologies Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada. 5. PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada. 6. Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada. 7. Informatics and Bio-computing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada. 8. PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada2Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada. 9. Transformative Pathology, Ontario Institute for Cancer Research, Toronto, Ontario, Canada. 10. University of Liverpool, Liverpool, England. 11. Heidelberg University Hospital, Heidelberg, Germany. 12. Mayo Clinic, Rochester, Minnesota. 13. Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts. 14. University of Nebraska Medical Centre, Omaha, Nebraska. 15. Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada13Molecular Genetics Department, University of Toronto, Toronto, Ontario, Canada. 16. Division of Medical Oncology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada. 17. Hepatobiliary/Pancreatic Surgical Oncology Program, University Health Network, Toronto, Ontario, Canada. 18. Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada15Department of Laboratory Medicine and Pathobiology, University of Toronto, Ontario, Canada. 19. PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada15Department of Laboratory Medicine and Pathobiology, University of Toronto, Ontario, Canada16Department of Pathology, University Health Network, Toronto, Ontario, Canada17Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada18BioSpecimen Sciences Program, University Health Network, Toronto, Ontario, Canada. 20. PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada3Hepatobiliary/Pancreatic Surgical Oncology Program, University Health Network, Toronto, Ontario, Canada. 21. Theoretical Biology and Biophysics (T-6), Los Alamos National Laboratory, Los Alamos, New Mexico20Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico. 22. Department of Pathology, University Health Network, Toronto, Ontario, Canada. 23. Genome Technologies Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada17Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. 24. Informatics and Bio-computing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada13Molecular Genetics Department, University of Toronto, Toronto, Ontario, Canada.
Abstract
IMPORTANCE: Outcomes for patients with pancreatic ductal adenocarcinoma (PDAC) remain poor. Advances in next-generation sequencing provide a route to therapeutic approaches, and integrating DNA and RNA analysis with clinicopathologic data may be a crucial step toward personalized treatment strategies for this disease. OBJECTIVE: To classify PDAC according to distinct mutational processes, and explore their clinical significance. DESIGN, SETTING, AND PARTICIPANTS: We performed a retrospective cohort study of resected PDAC, using cases collected between 2008 and 2015 as part of the International Cancer Genome Consortium. The discovery cohort comprised 160 PDAC cases from 154 patients (148 primary; 12 metastases) that underwent tumor enrichment prior to whole-genome and RNA sequencing. The replication cohort comprised 95 primary PDAC cases that underwent whole-genome sequencing and expression microarray on bulk biospecimens. MAIN OUTCOMES AND MEASURES: Somatic mutations accumulate from sequence-specific processes creating signatures detectable by DNA sequencing. Using nonnegative matrix factorization, we measured the contribution of each signature to carcinogenesis, and used hierarchical clustering to subtype each cohort. We examined expression of antitumor immunity genes across subtypes to uncover biomarkers predictive of response to systemic therapies. RESULTS: The discovery cohort was 53% male (n = 79) and had a median age of 67 (interquartile range, 58-74) years. The replication cohort was 50% male (n = 48) and had a median age of 68 (interquartile range, 60-75) years. Five predominant mutational subtypes were identified that clustered PDAC into 4 major subtypes: age related, double-strand break repair, mismatch repair, and 1 with unknown etiology (signature 8). These were replicated and validated. Signatures were faithfully propagated from primaries to matched metastases, implying their stability during carcinogenesis. Twelve of 27 (45%) double-strand break repair cases lacked germline or somatic events in canonical homologous recombination genes-BRCA1, BRCA2, or PALB2. Double-strand break repair and mismatch repair subtypes were associated with increased expression of antitumor immunity, including activation of CD8-positive T lymphocytes (GZMA and PRF1) and overexpression of regulatory molecules (cytotoxic T-lymphocyte antigen 4, programmed cell death 1, and indolamine 2,3-dioxygenase 1), corresponding to higher frequency of somatic mutations and tumor-specific neoantigens. CONCLUSIONS AND RELEVANCE: Signature-based subtyping may guide personalized therapy of PDAC in the context of biomarker-driven prospective trials.
IMPORTANCE: Outcomes for patients with pancreatic ductal adenocarcinoma (PDAC) remain poor. Advances in next-generation sequencing provide a route to therapeutic approaches, and integrating DNA and RNA analysis with clinicopathologic data may be a crucial step toward personalized treatment strategies for this disease. OBJECTIVE: To classify PDAC according to distinct mutational processes, and explore their clinical significance. DESIGN, SETTING, AND PARTICIPANTS: We performed a retrospective cohort study of resected PDAC, using cases collected between 2008 and 2015 as part of the International Cancer Genome Consortium. The discovery cohort comprised 160 PDAC cases from 154 patients (148 primary; 12 metastases) that underwent tumor enrichment prior to whole-genome and RNA sequencing. The replication cohort comprised 95 primary PDAC cases that underwent whole-genome sequencing and expression microarray on bulk biospecimens. MAIN OUTCOMES AND MEASURES: Somatic mutations accumulate from sequence-specific processes creating signatures detectable by DNA sequencing. Using nonnegative matrix factorization, we measured the contribution of each signature to carcinogenesis, and used hierarchical clustering to subtype each cohort. We examined expression of antitumor immunity genes across subtypes to uncover biomarkers predictive of response to systemic therapies. RESULTS: The discovery cohort was 53% male (n = 79) and had a median age of 67 (interquartile range, 58-74) years. The replication cohort was 50% male (n = 48) and had a median age of 68 (interquartile range, 60-75) years. Five predominant mutational subtypes were identified that clustered PDAC into 4 major subtypes: age related, double-strand break repair, mismatch repair, and 1 with unknown etiology (signature 8). These were replicated and validated. Signatures were faithfully propagated from primaries to matched metastases, implying their stability during carcinogenesis. Twelve of 27 (45%) double-strand break repair cases lacked germline or somatic events in canonical homologous recombination genes-BRCA1, BRCA2, or PALB2. Double-strand break repair and mismatch repair subtypes were associated with increased expression of antitumor immunity, including activation of CD8-positive T lymphocytes (GZMA and PRF1) and overexpression of regulatory molecules (cytotoxic T-lymphocyte antigen 4, programmed cell death 1, and indolamine 2,3-dioxygenase 1), corresponding to higher frequency of somatic mutations and tumor-specific neoantigens. CONCLUSIONS AND RELEVANCE: Signature-based subtyping may guide personalized therapy of PDAC in the context of biomarker-driven prospective trials.
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