Abstract

Abstract Gastric cancer is a heterogeneous malignancy and the fifth most common cancer worldwide, with 44% of cases occurring in China. Elucidation of genetic subtypes may improve gastric cancer treatment planning. Matched tumour and peritumoural (non-malignant gastric mucosa) tissue samples were collected from 306 Chinese patients and subjected to whole-exome sequencing (WES). The results were used to produce a Chinese Gastric Cancer Genome Atlas (CGCGA). Patients from nine Chinese ethnic groups (Han, Zhuang, Hui, Uygur, Yi, Tibetan, Mongolian, Bai, and Kazakh), representing 95% of the Chinese population were included. Systematic comparison of CGCGA data with TCGA (The Cancer Genome Atlas) data, in which 437 gastric cancer cases are represented, showed that genomic alteration signatures in the present cohort differed markedly from those reported for Western cohorts. TP53 and FAT1 deletions were more frequent (35% vs. 0%) while ARID1A deletions (13% vs. 25%), MYC oncogene amplifications (53% vs. 70%), and SMAD4 deletions (34% vs. 46%) were less frequent in our CGCGA data than in the TCGA data. TRIM49B mutation was associated with worse survival. Thus, TRIM49B was identified as a novel oncogene. The Zhuang ethnic group had a much higher tumour mutation burden (TMB) than the other ethnic groups. Typically, tumours from Han group had microsatellite stability, whereas those from the other groups had microsatellite instability (MSI). We further propose a molecular classification of four gastric cancer subtypes that are associated with distinct survival outcomes: TP53 mutation positive (TP53+)/TTN_missense+; TP53+/TTN_missense–; TP53–/TTN_missense+, and TP53–/TTN_missense–. Our study established a comprehensive gastric cancer genome atlas in China and underscored the importance of considering population context in genomic mapping and rational treatment options for the disease. Citation Format: Liang Zong. Mutational landscape and genetic feature of gastric adenocarcinoma in multiple Chinese ethnicities [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B036.

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