Clonal Architectures Predict Clinical Outcome in Gastric Adenocarcinoma Based on Genomic Variation, Tumor Evolution, and Heterogeneity

Abstract

Stomach adenocarcinoma (STAD) is a highly heterogeneous disease. Due to the lack of effective molecular markers and personalized treatment, the prognosis of gastric cancer patients is still very poor. The ABSOLUTE algorithm and cancer cell fraction were used to evaluate the clonal and subclonal status of 349 TCGA (The Cancer Genome Cancer Atlas)-STAD patients. Non-negative matrix factorization was used to identify the mutation characteristics of the samples. Univariate Cox regression analysis was used to determine the relationship between clonal/subclonal events and prognosis, and the Spearman correlation was used to evaluate the relationship of clonal/subclonal events to tumor mutation burden (TMB) and neoantigens. The evolution pattern of STAD demonstrated great tumor heterogeneity. TP53, USH2A, and GLI3 appeared earliest in STAD and may drive STAD. CTNNB1, LRP1B, and ERBB4 appeared the latest in STAD, and may be related to STAD’s progress. Univariate Cox regression analysis identified four early genes, eight intermediate genes, and seven late genes significantly associated with overall survival. The number of subclonal events in the T stage was significantly different. The N stage, gender, and histological type were significantly different for clonal events, and there was a significant correlation between clonal/subclonal events and TMB/neoantigens. Our results highlight the importance of systematic evaluation of evolutionary models in the clinical management of STAD and personalized gastric cancer treatment.

An integrated analysis of prognostic mRNA signature in early- and progressive-stage gastric adenocarcinoma

“…However, some limitations of these studies should be noticed: most of them were reports of key biomarkers in overall STAD, while neglecting STAD stages ( Li et al, 2019 ; Fu et al, 2020 ; Qiu et al, 2020 ). Nevertheless, STAD is a cancer characterized with high heterogeneity, and the differences of pathological features in distinct STAD stages were evident ( Ren et al, 2021 ). Therefore, it is inappropriate to use the same mRNAs as biomarkers to classify patients with STAD at all the different stages in the clinical work.…”