Identification of key regulatory networks and prognostic biomarkers in Stomach Adenocarcinoma; a comprehensive analysis based on RNAseq data

Introduction Gastric cancer poses a significant clinical challenge, ranking as the ۵th most common cancer and the ۴th leading cause of cancer-related mortality worldwide. In ۲۰۲۰, there were approximately ۱,۰۸۹,۱۰۳ new cases diagnosed, resulting in an estimated ۷۶۸,۷۹۳ fatalities, equating to one in every ۱۳ deaths globally (۱). Survival outcomes for the patients stands poor, with an overall ۵-year survival rate ۲۵% worldwide and ۳۱% in the United States (۲). The combination of surgical intervention and chemotherapy has led to an increase in survival rates for early-stage gastric cancer, reaching up to ۶۰% to ۸۰%. However, most patients are diagnosed at advanced stages, resulting in a significantly lower ۵-year survival rate of only ۱۸% to ۵۰% (۳). These findings indicate a pressing need for more effective treatment strategies based on molecular mechanisms. Identifying hub genes that can function as therapeutic targets and prognostic biomarkers is crucial for advancing gastric cancer therapy. In this research, we investigated a lncRNA–miRNA–mRNA network employing differentially expressed genes in stomach adenocarcinoma, which presents potential targets for its management and follow-up. Materials and Methods The RNA-seq data of ۴۴۸ patients from TCGA-STAD project were downloaded and normalized using the “GDCRNATools” package in R studio software. Under log۲FC > ۰.۵ and p-value < ۰.۰۵ filtration, the volcano plot of DEGs was created via the “TCGAbiolinks” package. Top ۱۰۰ differentially expressed protein coding genes were chosen for Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis via the Database for Annotation, Visualization and Integrated Discovery (DAVID). STRING database was used for protein-protein interaction (PPI) analysis. Additionally, lncRNA-miRNA-mRNA interaction network of cancer related genes was constructed based on RAID version ۲ database data. Finally, the prognostic value of the selected genes was investigated employing Gepia version ۲ database. Results Among ۸۸۰۳ DEGs, ۱۰۰ top coding DEGs were filtered, of which ۵, ۱۸, ۳۵, and ۱۷ genes were respectively enriched in the (pathway) transcriptional misregrulation in cancer, (Biological Function) regulation of transcription by RNA polymerase II, (Cellular Component) extracellular region, and (Molecular Function) DNA-binding transcription factor activity, RNA polymerase II-specific. lncRNA-miRNA-mRNA interaction network was constructed based on HOXA۱۰, HOXA۱۱, MMP۳ (the ۳ up-regulated with log۲FC of ۴.۱۸, ۵.۰۶, ۳.۳۷ and False Discovery Rate (FDR) of ۶.۰۸e-۱۱, ۱.۷۶e-۱۶, ۳.۱e-۵, respectively), HPGD, and ZBTB۱۶ (the ۲ down-regulated with log۲FC of -۳.۲, -۳.۴ and FDR of ۷.۲۱e-۲۰, ۶.۷e-۲۹, respectively) genes which were enriched in transcriptional misregulation in cancer. Also, ZBTB۱۶ expression was identified as a prognostic biomarker for STAD patients (p-value = ۰.۰۰۵۸ and Hazard Ratio (HR) = ۱.۶). Conclusion We introduced a lncRNA-miRNAs-mRNA network, differentially expressed in STAD that might be considered for further experimental research as a potential therapeutic target. In addition, ZBTB۱۶ may serve as a prognostic biomarker for STAD patient management.

کلیدواژه ها:

RNA-seq ، Gene interaction network ، stomach adenocarcinoma ، prognostic biomarker ، protein protein interaction network