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基于胃癌肿瘤微环境特征的预后基因表达签名鉴定

Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer

Sang Qingqing, Dai Wentao, Yu Junxian, Chen Yunqin, Fan Zhiyuan, Liu Jixiang, Li Fangyuan, Li Jianfang, Wu Xiongyan, Hou Junyi, Yu Beiqin, Feng Haoran, Zhu Zheng-Gang, Su Liping, Li Yuan-Yuan, Liu Bi

Journal:Frontiers in Immunology

IF:8.79

DOI:10.3389/fimmu.2022.983632

PMID:36032070

Published:2022-08-12

research field:肿瘤学细胞生物学表观遗传学

Abstract

Increasing evidence has elucidated that the tumor microenvironment (TME) shows a strong association with tumor progression and therapeutic outcome. We comprehensively estimated the TME infiltration patterns of 111 gastric cancer (GC) and 21 normal stomach mucosa samples based on bulk transcriptomic profiles based on which GC could be clustered as three subtypes, TME-Stromal, TME-Mix, and TME-Immune. The expression data of TME-relevant genes were utilized to build a GC prognostic model—GC_Score. Among the three GC TME subtypes, TME-Stomal displayed the worst prognosis and the highest GC_Score, while TME-Immune had the best prognosis and the lowest GC_Score. Connective tissue growth factor (CTGF), the highest weighted gene in the GC_Score, was found to be overexpressed in GC. In addition, CTGF exhibited a significant correlation with the abundance of fibroblasts. CTGF has the potential to induce transdifferentiation of peritumoral fibroblasts (PTFs) to cancer-associated fibroblasts (CAFs). Beyond characterizing TME subtypes associated with clinical outcomes, we correlated TME infiltration to molecular features and explored their functional relevance, which helps to get a better understanding of carcinogenesis and therapeutic response and provide novel strategies for tumor treatments.

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