Prevalence of Germline Alterations on Targeted Tumor-Normal Sequencing of Esophagogastric Cancer.

Importance: Among patients with esophagogastric cancers, only individuals who present with known features of heritable cancer syndromes are referred for genetic testing. Broader testing might identify additional patients with germline alterations. Objectives: To examine the prevalence of likely pathogenic or pathogenic (LP/P) germline alterations among patients with esophagogastric cancer and to assess associations between germline variant prevalence and demographic and clinicopathologic features. Design, Setting, and Participants: This cross-sectional study was performed at a tertiary referral cancer center from January 1, 2014, to December 31, 2019, in 515 patients with esophagogastric cancer who consented to tumor and blood sequencing. Main Outcomes and Measures: Presence or absence of LP/P variants in up to 88 genes associated with cancer predisposition syndromes as identified by targeted sequencing (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets). Results: Among 515 patients (median age, 59 years; range, 18-87 years; 368 [71.5%] male; 398 [77.3%] White), 243 (47.2%) had gastric cancer, 111 (21.6%) had gastroesophageal junction (GEJ) cancer, and 161 (31.3%) had esophageal cancer. A total of 48 patients with gastric cancer (19.8%), 16 (14.4%) with GEJ cancer, and 17 (10.6%) with esophageal cancer had LP/P germline variants. The number of LP/P variants in high- and moderate-penetrance genes was significantly higher in patients with gastric cancer (29 [11.9%]; 95% CI, 8.1%-16.7%) vs patients with esophageal cancer (8 [5.0%]; 95% CI, 2.2%-9.6%; P = .03), and the difference was greater for high-penetrance germline alterations in patients with gastric cancer (25 [10.3%]; 95% CI, 6.8%-14.8%) vs in patients with esophageal cancer (3 [1.9%]; 95% CI, 0.38%-5.3%; P = .001). The most frequent high- and moderate-penetrance LP/P alterations were in BRCA1/2 (14 [2.7%]), ATM (11 [2.1%]), CDH1 (6 [1.2%]), and MSH2 (4 [0.8%]). Those with early-onset disease (≤50 years of age at diagnosis) were more likely to harbor an LP/P germline variant (29 [21.0%]; 95% CI, 14.5%-28.8%) vs those with late-onset disease (patients >50 years of age at diagnosis) (52 [13.8%]; 95% CI, 10.5%-17.7%; P = .046). ATM LP/P variants occurred in 6 patients (4.3%; 95% CI, 1.6%-9.1%) with early-onset esophagogastric cancer vs 5 (1.3%; 95% CI, 0.4%-3.1%; P = .08) of those with late-onset esophagogastric cancer. Conclusions and Relevance: These results suggest that pathogenic germline variants are enriched in gastric and early-onset esophagogastric cancer and that germline testing should be considered in these populations. The role of ATM alterations in esophagogastric cancer risk warrants further investigation.

Correction: Toward automation of germline variant curation in clinical cancer genetics.

An update to the original published conflict of interest for author Liying Zhang, PhD. L.Z. received compensation from Future Technology Research LLC (seminar on precision medicine), Roche Diagnostics Asia Pacific, BGI, Illumina (speaking activities at conferences/workshop). L.Z.'s family member has a leadership position and ownership interest of Shanghai Genome Center. This correction has been made.

Toward automation of germline variant curation in clinical cancer genetics.

PURPOSE: Cancer care professionals are confronted with interpreting results from multiplexed gene sequencing of patients at hereditary risk for cancer. Assessments for variant classification now require orthogonal data searches and aggregation of multiple lines of evidence from diverse resources. The clinical genetics community needs a fast algorithm that automates American College of Medical Genetics and Genomics (ACMG) based variant classification and provides uniform results. METHODS: Pathogenicity of Mutation Analyzer (PathoMAN) automates germline genomic variant curation from clinical sequencing based on ACMG guidelines. PathoMAN aggregates multiple tracks of genomic, protein, and disease specific information from public sources. We compared expertly curated variant data from clinical laboratories to assess performance. RESULTS: PathoMAN achieved a high overall concordance of 94.4% for pathogenic and 81.1% for benign variants. We observed negligible discordance (0.3% pathogenic, 0% benign) when contrasted against expert curated variants. Some loss of resolution (5.3% pathogenic, 18.9% benign) and gain of resolution (1.6% pathogenic, 3.8% benign) were also observed. CONCLUSION: Automation of variant curation enables unbiased, fast, efficient delivery of results in both clinical and laboratory research. We highlight the advantages and weaknesses related to the programmable automation of variant classification. PathoMAN will aid in rapid variant classification by generating robust models using a knowledgebase of diverse genetic data ( https://pathoman.mskcc.org).