ArticleFrontiers in immunology2025
Hypoxia-associated genes as predictors of outcomes in gastric cancer: a genomic approach.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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3 authors.
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Abstract
Objective: To investigate the effects of hypoxia-related genes in stomach adenocarcinoma (STAD) and construct an excellent prognostic model. Methods: RNA expression data and clinical details were retrieved from the TCGA and GEO database dataset. scRNA-seq analysis was conducted on primary gastric cancer samples from GSE183904. Cellular hypoxia status was predicted using the CHPF software. WGCNA and GO-BP/KEGG enrichment of module genes analyses were performed to identify gene modules associated with hypoxia and biological pathway enrichment. A prognostic model was developed employing the LassoCox algorithm. GES-1, AGS, BGC823, and MGC803 cell lines were obtained for qRT-PCR analysis to identify the expression of model genes. Results: Single-cell atlas within STAD delineated that most of neoplastic cells, fibroblasts, endothelial cells, and myeloid cells were hypoxic. Further analysis of neoplastic cell subpopulations identified four hypoxic subpopulations (H1-H4) and four non-hypoxic subpopulations (N1-N4), with H1 subpopulation had the highest degree of hypoxia. The prognostic model constructed by five H1-specific transcription factors EHF, EIF1AD, GLA, KEAPI, and MAGED2, was demonstrated efficacy in predicting overall survival (OS), with significantly worse OS in high-risk patients. qRT-PCR analysis determined the higher expression level of five H1-specific transcription factors in gastric cancer cell lines than that in normal gastric epithelial cell line. Conclusion: Hypoxia exerts a profound influence on STAD due to the overexpression of hypoxic cellular subpopulations-specific transcription factors EHF, EIF1AD, GLA, KEAPI, and MAGED2. The novel prognostic model developed by these hypoxia-associated genes presents a novel approach to risk stratification, exhibiting an excellent prognostic value for STAD patients.
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