Identification of fatty acid anabolism patterns to predict prognosis and immunotherapy response in gastric cancer - Weijie Sun; Yanhong Xia; Feifan Jin; Jinghao Cao; Gaoping Wu; Keyi Li; Yanhua Yu; Yunyi Wu; Gaoqi Ye; Ke Xu; Dengpan Liu; Weidong Jin (Discover Oncology)
Abstract Gastric cancer (GC), one of the most common and heterogeneous malignancies, is the second leading cause of cancer death worldwide and is closely related to dietary habits. Fatty acid is one of the main nutrients of human beings, which is closely related to diabetes, hypertension and other diseases. However, the correlation between fatty acid metabolism and the development and progression of GC remains largely unknown. Here, we profiled the genetic alterations of fatty acid anabolism-related genes (FARGs) in gastric cancer samples from the TCGA cohort and GEO database to evaluate the possible relationships and their internal regulatory mechanism. Through consistent clustering and functional enrichment analysis, three distinct fatty acid anabolism clusters and three gene subtypes were identified to participate in different biological pathways, and correlated with the characteristics of immune cell infiltration and clinical prognosis. Importantly, a distinctive FA-score was constructed through the principal component analysis to quantify the characteristics of fatty acid anabolism in each GC patient. Further analysis showed patients grouped in the high FA-score group were characterized with greater tumor mutational burden (TMB) and higher microsatellite stability (MSI-H), which may be more aeschynomenous to immunotherapy and had a favorable prognosis. Altogether, our bioinformatics analysis based on FARGs uncovered the potential roles of fatty acid metabolism in GC, and may provide newly prognostic information and novel approaches for promoting individualized immunotherapy in patients with GC.