Gastric cancer (GC) represents the fifth most common tumor and the fourth leading cause of cancer-related deaths worldwide[۱]. Several genetic and epigenetic factors, including microRNAs(miRNAs) and lncRNAs, affect its initiation and progression. MiRNAs are short chains of nucleic acidsthat can regulate several cellular processes by controlling their gene expression, Long noncodingRNA (LncRNA) is a large class of RNA molecules with size larger than ۲۰۰ nucleotides. They exhibitcellular functions although having no protein-coding capability [۲]. In recent decades, miRNAa andlncRNAs have been st

Numerous studies have demonstrated the influence of polyp pathways on the likelihood ofbenign or malignant occurrences, as well as the clinical manifestations in patients [۱]. In recent years,the consensus molecular subclassification (CMS) has proven effective in predicting the prognosis ofcolorectal cancer and the risk of recurrence in affected individuals [۲]. This study aims to investigatethe gene expression signatures (GSEs) associated with CMS and polyps, particularly high-risk polyps,and to identify shared genes to identify a biomarker that can predict the likelihood of polyps becomingmalignant and provide a more favorable prognosis for patients. Initially, GSEs related to CMS andsessile serrated adenoma polyps (SSA) were selected (GSE۱۰۳۴۷۹, GSE۷۹۴۶۲, GSE۱۹۸۶۹۲, andGSE۴۵۲۷۰), and microarray analysis was conducted to identify genes with differential expressionacross different CMS groups and SSA polyps. Subsequently, the differentially expressed genes (DEGs)were compared to identify commonalities, and a Venn diagram was constructed to visualize the sharedgenes. The expression levels of the identified genes were then validated using the UALCAN database,and the Gepia۲ and EnrichR databases were utilized for gene enrichment analysis. Microarray analysisof these GSEs revealed ۱۶ common genes and enrichment analysis indicated their involvement invarious cancers, including colorectal, prostate, endometrial, and breast cancer. This study demonstratedthe potential use of EGFR as biomarkers for CMS۱, and SLC۷A۴, RARRES۱, ACAP۱, and IFI۳۰ genesas biomarkers for CMS۳. Additionally, PI۱۵, AKT۳, PTEN, KLF۶, TNS۱, and ACE genes wereidentified as potential biomarkers for CMS۴.