Yang Shuo, Jiang Yuhao, Yang Zhonghua
Department of Pediatric Surgery, Shengjing Hospital of China Medical University, Shenyang, China.
NHC Key Laboratory of Congenital Malformation, Shengjing Hospital of China Medical University, Shenyang, China.
Front Immunol. 2025 Mar 10;16:1553477. doi: 10.3389/fimmu.2025.1553477. eCollection 2025.
To investigate the effects of hypoxia-related genes in stomach adenocarcinoma (STAD) and construct an excellent prognostic model.
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.
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.
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.
研究缺氧相关基因在胃腺癌(STAD)中的作用,并构建一个优良的预后模型。
从TCGA和GEO数据库数据集中检索RNA表达数据和临床细节。对来自GSE183904的原发性胃癌样本进行scRNA-seq分析。使用CHPF软件预测细胞缺氧状态。进行WGCNA和模块基因的GO-BP/KEGG富集分析,以确定与缺氧相关的基因模块和生物通路富集。采用LassoCox算法建立预后模型。获取GES-1、AGS、BGC823和MGC803细胞系进行qRT-PCR分析,以鉴定模型基因的表达。
STAD内的单细胞图谱描绘出大多数肿瘤细胞、成纤维细胞、内皮细胞和髓样细胞处于缺氧状态。对肿瘤细胞亚群的进一步分析确定了四个缺氧亚群(H1-H4)和四个非缺氧亚群(N1-N4),其中H1亚群的缺氧程度最高。由五个H1特异性转录因子EHF、EIF1AD、GLA、KEAPI和MAGED2构建的预后模型在预测总生存期(OS)方面显示出有效性,高危患者的OS明显更差。qRT-PCR分析确定五个H1特异性转录因子在胃癌细胞系中的表达水平高于正常胃上皮细胞系。
由于缺氧细胞亚群特异性转录因子EHF、EIF1AD、GLA、KEAPI和MAGED2的过表达,缺氧对STAD产生深远影响。由这些缺氧相关基因开发的新型预后模型为风险分层提供了一种新方法,对STAD患者具有优良的预后价值。