Prognostic significance and immune microenvironment infiltration patterns of hypoxia and endoplasmic reticulum stress-related genes in gastric cancer - Li, Libin; Liang, Yizhi; Xu, Wenji (Frontiers in Oncology, 2025)
BackgroundGastric cancer (GC) is a prevalent malignant neoplasm within the digestive system, accounting for approximately 740,000 deaths globally each year, significantly impacting patients' quality of life and survival rates. The objective of this investigation was to elucidate the expression patterns of Hypoxia and Endoplasmic Reticulum Stress-related Differentially Expressed Genes (HERSRDEGs) in GC and their association with prognostic outcomes of the patients.MethodsUtilizing The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, GC datasets were retrieved, and standard normalization was performed. Differential expression analysis was conducted using DESeq2, while somatic mutations and copy number variations were examined using maftools and GISTIC2.0. Spearman's correlation assessed the interplay between HERSRDEGs across datasets. Functional enrichment analyses were carried out using clusterProfiler for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, alongside Gene Set Enrichment Analysis (GSEA). A prognostic risk model was obtained by utilizing univariate Cox regression analysis with a survival R package. We employed RT-qPCR to validate the mRNA expression levels of five model genes that impact the prognostic risk of gastric cancer in human gastric adenocarcinoma tissues.ResultsThe acquired data revealed 19 HERSRDEGs including ANGPT2, CXCL8, and AURKA exhibiting significant variation in expression between GC and controls. In the Cox regression analysis, a total of five genes—ANGPT2, CD36, EGR1, NOX4, TLR2—emerged as statistically significant, correlating strongly with overall survival. A LASSO regression model featuring ANGPT2, CD36, and NOX4 yielded a risk score formula capable of predicting patient outcomes. Furthermore, multivariate Cox regression analysis highlighted RiskScore, age and stage as significant survival predictors. The analysis of immune infiltration revealed notable differences in the populations of immune cells, such as Natural Killer cells and T-helper cells, when comparing high-risk and low-risk groups.ConclusionIn conclusion, this investigation elucidates the involvement of HERSRDEGs in GC progression and their potential as prognostic biomarkers.