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Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma.

ABSTRACT: Gastroesophageal adenocarcinoma (GEA) is a lethal disease where targeted therapies, even when guided by genomic biomarkers, have had limited efficacy. A potential reason for the failure of such therapies is that genomic profiling results could commonly differ between the primary and metastatic tumors. To evaluate genomic heterogeneity, we sequenced paired primary GEA and synchronous metastatic lesions across multiple cohorts, finding extensive differences in genomic alterations, including discrepancies in potentially clinically relevant alterations. Multiregion sequencing showed significant discrepancy within the primary tumor (PT) and between the PT and disseminated disease, with oncogene amplification profiles commonly discordant. In addition, a pilot analysis of cell-free DNA (cfDNA) sequencing demonstrated the feasibility of detecting genomic amplifications not detected in PT sampling. Lastly, we profiled paired primary tumors, metastatic tumors, and cfDNA from patients enrolled in the personalized antibodies for GEA (PANGEA) trial of targeted therapies in GEA and found that genomic biomarkers were recurrently discrepant between the PT and untreated metastases. Divergent primary and metastatic tissue profiling led to treatment reassignment in 32% (9/28) of patients. In discordant primary and metastatic lesions, we found 87.5% concordance for targetable alterations in metastatic tissue and cfDNA, suggesting the potential for cfDNA profiling to enhance selection of therapy.Significance: We demonstrate frequent baseline heterogeneity in targetable genomic alterations in GEA, indicating that current tissue sampling practices for biomarker testing do not effectively guide precision medicine in this disease and that routine profiling of metastatic lesions and/or cfDNA should be systematically evaluated. Cancer Discov; 8(1); 37-48. ©2017 AACR.See related commentary by Sundar and Tan, p. 14See related article by Janjigian et al., p. 49This article is highlighted in the In This Issue feature, p. 1.

SUBMITTER: Pectasides E

PROVIDER: S-EPMC5894850 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma.

Pectasides Eirini E Stachler Matthew D MD Derks Sarah S Liu Yang Y Maron Steven S Islam Mirazul M Alpert Lindsay L Kwak Heewon H Kindler Hedy H Polite Blase B Sharma Manish R MR Allen Kenisha K O'Day Emily E Lomnicki Samantha S Maranto Melissa M Kanteti Rajani R Fitzpatrick Carrie C Weber Christopher C Setia Namrata N Xiao Shu-Yuan SY Hart John J Nagy Rebecca J RJ Kim Kyoung-Mee KM Choi Min-Gew MG Min Byung-Hoon BH Nason Katie S KS O'Keefe Lea L Watanabe Masayuki M Baba Hideo H Lanman Rick R Agoston Agoston T AT Oh David J DJ Dunford Andrew A Thorner Aaron R AR Ducar Matthew D MD Wollison Bruce M BM Coleman Haley A HA Ji Yuan Y Posner Mitchell C MC Roggin Kevin K Turaga Kiran K Chang Paul P Hogarth Kyle K Siddiqui Uzma U Gelrud Andres A Ha Gavin G Freeman Samuel S SS Rhoades Justin J Reed Sarah S Gydush Greg G Rotem Denisse D Davison Jon J Imamura Yu Y Adalsteinsson Viktor V Lee Jeeyun J Bass Adam J AJ Catenacci Daniel V DV

Cancer discovery 20171004 1

Gastroesophageal adenocarcinoma (GEA) is a lethal disease where targeted therapies, even when guided by genomic biomarkers, have had limited efficacy. A potential reason for the failure of such therapies is that genomic profiling results could commonly differ between the primary and metastatic tumors. To evaluate genomic heterogeneity, we sequenced paired primary GEA and synchronous metastatic lesions across multiple cohorts, finding extensive differences in genomic alterations, including discre ...[more]

PMID: 28978556

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Project description:BackgroundCancer is a somatic evolutionary disease and adenocarcinomas of the stomach and gastroesophageal junction (GC) may serve as a two-dimensional model of cancer expansion, in which tumor subclones are not evenly mixed during tumor progression but rather spatially separated and diversified. We hypothesize that precision medicine efforts are compromised when clinical decisions are based on a single-sample analysis, which ignores the mechanisms of cancer evolution and resulting intratumoral heterogeneity. Using multiregional whole-exome sequencing, we investigated the effect of somatic evolution on intratumoral heterogeneity aiming to shed light on the evolutionary biology of GC.MethodsThe study comprised a prospective discovery cohort of 9 and a validation cohort of 463 GCs. Multiregional whole-exome sequencing was performed using samples form 45 primary tumors and 3 lymph node metastases (range 3-10 tumor samples/patient) of the discovery cohort.ResultsIn total, the discovery cohort harbored 16,537 non-synonymous mutations. Intratumoral heterogeneity of somatic mutations and copy number variants were present in all tumors of the discovery cohort. Of the non-synonymous mutations, 53-91% were not present in each patient's sample; 399 genes harbored 2-4 different non-synonymous mutations in the same patient; 175 genes showed copy number variations, the majority being heterogeneous, including CD274 (PD-L1). Multi-sample tree-based analyses provided evidence for branched evolution being most complex in a microsatellite instable GC. The analysis of the mode of evolution showed a high degree of heterogeneity in deviation from neutrality within each tumor. We found evidence of parallel evolution and evolutionary trajectories: different mutations of SMAD4 aligned with different subclones and were found only in TP53 mutant GCs.ConclusionsNeutral and non-neutral somatic evolution shape the mutational landscape in GC along its lateral expansions. It leads to complex spatial intratumoral heterogeneity, where lymph node metastases may stem from different areas of the primary tumor, synchronously. Our findings may have profound effects on future patient management. They illustrate the risk of mis-interpreting tumor genetics based on single-sample analysis and open new avenues for an evolutionary classification of GC, i.e., the discovery of distinct evolutionary trajectories which can be utilized for precision medicine.

Dataset Information

Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma.

Publications

Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma.

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