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Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine.

ABSTRACT: Clinically relevant subtypes exist for pancreatic ductal adenocarcinoma (PDAC), but molecular characterization is not yet standard in clinical care. We implemented a biopsy protocol to perform time-sensitive whole-exome sequencing and RNA sequencing for patients with advanced PDAC. Therapeutically relevant genomic alterations were identified in 48% (34/71) and pathogenic/likely pathogenic germline alterations in 18% (13/71) of patients. Overall, 30% (21/71) of enrolled patients experienced a change in clinical management as a result of genomic data. Twenty-six patients had germline and/or somatic alterations in DNA-damage repair genes, and 5 additional patients had mutational signatures of homologous recombination deficiency but no identified causal genomic alteration. Two patients had oncogenic in-frame BRAF deletions, and we report the first clinical evidence that this alteration confers sensitivity to MAPK pathway inhibition. Moreover, we identified tumor/stroma gene expression signatures with clinical relevance. Collectively, these data demonstrate the feasibility and value of real-time genomic characterization of advanced PDAC.Significance: Molecular analyses of metastatic PDAC tumors are challenging due to the heterogeneous cellular composition of biopsy specimens and rapid progression of the disease. Using an integrated multidisciplinary biopsy program, we demonstrate that real-time genomic characterization of advanced PDAC can identify clinically relevant alterations that inform management of this difficult disease. Cancer Discov; 8(9); 1096-111. ©2018 AACR.See related commentary by Collisson, p. 1062This article is highlighted in the In This Issue feature, p. 1047.

SUBMITTER: Aguirre AJ

PROVIDER: S-EPMC6192263 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine.

Aguirre Andrew J AJ Nowak Jonathan A JA Camarda Nicholas D ND Moffitt Richard A RA Ghazani Arezou A AA Hazar-Rethinam Mehlika M Raghavan Srivatsan S Kim Jaegil J Brais Lauren K LK Ragon Dorisanne D Welch Marisa W MW Reilly Emma E McCabe Devin D Marini Lori L Anderka Kristin K Helvie Karla K Oliver Nelly N Babic Ana A Da Silva Annacarolina A Nadres Brandon B Van Seventer Emily E EE Shahzade Heather A HA St Pierre Joseph P JP Burke Kelly P KP Clancy Thomas T Cleary James M JM Doyle Leona A LA Jajoo Kunal K McCleary Nadine J NJ Meyerhardt Jeffrey A JA Murphy Janet E JE Ng Kimmie K Patel Anuj K AK Perez Kimberly K Rosenthal Michael H MH Rubinson Douglas A DA Ryou Marvin M Shapiro Geoffrey I GI Sicinska Ewa E Silverman Stuart G SG Nagy Rebecca J RJ Lanman Richard B RB Knoerzer Deborah D Welsch Dean J DJ Yurgelun Matthew B MB Fuchs Charles S CS Garraway Levi A LA Getz Gad G Hornick Jason L JL Johnson Bruce E BE Kulke Matthew H MH Mayer Robert J RJ Miller Jeffrey W JW Shyn Paul B PB Tuveson David A DA Wagle Nikhil N Yeh Jen Jen JJ Hahn William C WC Corcoran Ryan B RB Carter Scott L SL Wolpin Brian M BM

Cancer discovery 20180614 9

Clinically relevant subtypes exist for pancreatic ductal adenocarcinoma (PDAC), but molecular characterization is not yet standard in clinical care. We implemented a biopsy protocol to perform time-sensitive whole-exome sequencing and RNA sequencing for patients with advanced PDAC. Therapeutically relevant genomic alterations were identified in 48% (34/71) and pathogenic/likely pathogenic germline alterations in 18% (13/71) of patients. Overall, 30% (21/71) of enrolled patients experienced a cha ...[more]

PMID: 29903880

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Project description:PurposeData standards and interoperability are critical for improving care for patients with cancer. Recent efforts by ASCO include the Data Standards and Interoperability Summit in 2016, which led to the Omics and Precision Oncology and Advancing Interoperability workshops. To facilitate improved patient care, several recommendations for data sharing and standardization were made to the community.MethodsTo address these recommendations, we developed SMART Cancer Navigator, a Web application that uses application programming interfaces to gather clinical and genomic data from 11 public knowledge bases ranging from basic to clinical content coverage; three (CIViC, ClinVar, and OncoKB) explicitly linked genomic variants to clinical factors such as prognosis and treatment selection. We illustrated the utility of this application by selecting one of the monthly case studies presented by the ASCO University Molecular Oncology Tumor Board: Ovarian Cancer (BRCA Mutation). We also performed analyses on information from the three clinico-genomic knowledge bases to corroborate previous work and illustrate the state of data sharing among publicly available resources.ResultsSMART Cancer Navigator aggregates and contextualizes data from 11 different knowledge bases and stores user queries in a lightweight Web application that can link into Fast Healthcare Interoperability Resources-enabled electronic health records. Potentially relevant clinical trials and/or approved treatments were identified for three mutations found in a hypothetical patient with advanced ovarian cancer. A comparison of the three clinico-genomic knowledge bases indicated substantial differences in coverage at the gene and variant levels.ConclusionSMART Cancer Navigator has immediate relevance to practicing oncologists and others. Additional knowledge bases can be added without undue effort. As a first step toward utility, we generalized and disseminated the resulting implementation (https://smart-cancer-navigator.github.io) and data sets.

Project description:BACKGROUND:Genomic profiling of colorectal cancer aims to identify actionable somatic mutations but can also discover incidental germline findings. OBJECTIVE:The purpose of this study was to report the detection of pathogenic germline variants that confer heritable cancer predisposition. DESIGN:This was a retrospective study. SETTINGS:The study was conducted at a tertiary-referral institution. PATIENTS:Between 2012 and 2015, 1000 patients with advanced cancer underwent targeted exome sequencing of a 202-gene panel. The subgroup of 151 patients with advanced colorectal cancer who underwent matched tumor-normal (blood) sequencing formed our study cohort. INTERVENTIONS:Germline variants in 46 genes associated with hereditary cancer predisposition were classified according to a defined algorithm based on in silico predictions of pathogenicity. Patients with presumed pathogenic variants were examined for type of mutation, as well as clinical, pedigree, and clinical genetic testing data. MAIN OUTCOME MEASURES:We measured detection of pathogenic germline variants. RESULTS:A total of 1910 distinct germline variants were observed in 151 patients. After filtering, 15 pathogenic germline variants (9.9%) were found in 15 patients, arising from 9 genes of varying penetrance for colorectal cancer (APC (n = 2; 13%), ATM (n = 1; 6%), BRCA1 (n = 2; 13%), CDH1 (n = 2; 13%), CHEK2 (n = 4; 27%), MSH2 (n = 1; 7%), MSH6 (n = 1; 7%), NF2 (n = 1; 7%), and TP53 (n = 1; 7%)). Patients with pathogenic variants were diagnosed at a younger age than those without (median, 45 vs 52 y; p = 0.03). Of the 15 patients, 7 patients (46.7%) with variants in low/moderate- penetrant genes for colorectal cancer would likely have not been tested based on clinical and pedigree criteria, where 2 harbored clinically actionable variants (CDH1 and NF2, 28.5% of 7). LIMITATIONS:This study was limited by its small sample size and advanced-stage patients. CONCLUSIONS:Tumor-normal sequencing can incidentally discover clinically unsuspected germline variants that confer cancer predisposition in 9.9% of patients with advanced colorectal cancer. Precision medicine should integrate clinical cancer genetics to inform and interpret the actionability of germline variants and to provide follow-up care to mutation carriers. See Video Abstract at http://links.lww.com/DCR/A906.

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Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine.

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Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine.

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