In silico analysis suggests ELL2 as a survival-associated cross-tissue biomarker in gastric cancer

BackgroundThe main aim of this study is to identify prognostic biomarkers through integrating bioinformatics analysis in gastric cancer, which is a significant global health challenge.MethodsGene expression datasets related to blood, tissue, and saliva in gastric cancer were downloaded from the Gene Expression Omnibus (GEO) database and analyzed. The bioinformatics approaches included the identification of differentially expressed genes (DEGs) and enrichment analysis, as well as Kaplan-Meier Plotter survival analysis. The DEGs were also validated through The Cancer Genome Atlas (TCGA) database. Additionally, DEGs-associated lncRNAs and microRNAs were identified. Subsequently, Tumor and Immune System Interaction Database (TISIDB) was utilized to examine the correlation of the genes of interest with immune and molecular subtypes.ResultsTwenty-six common DEGs were identified across blood, tissue, and saliva samples. Among them, 17 genes showed significant expression based on TCGA data. RAB23, LOX, ELL2, ELK3, CENPF, CD44, ANP32E, AKR1C2, and SMAD5 displayed significant association with patient survival. Particularly, ELL2 exhibit decreased expression in all specimens. The results indicated that ELL2 has a significant correlation with the immune system. The ELL2 gene regulates immune cell functions in gastric cancer, potentially influencing cancer immune responses, and tumor progression.ConclusionELL2 downregulated expression and its correlation with survival across blood, tissue, and saliva samples using bioinformatics analysis underscores the necessity of more investigation to fully comprehend its function in cancer immunology.