METABOLIC PATHWAY AND MOLECULAR SIGNATURE ANALYSIS OF GASTRIC CARCINOMA FROM PERIPHERAL BLOOD MONONUCLEAR CELLS FROM HOSPITALIZED PATIENTS

Abstract

Gastric carcinoma (GC) is one of the most aggressive cancers globally, characterized by high death rates resulting from late-stage diagnosis and poor therapeutic effectiveness. This research examines the metabolic pathways and molecular signature changes in peripheral blood mononuclear cells (PBMCs) from hospitalized gastric cancer patients, with the objective of identifying novel biomarkers for early detection and prognosis. Gene expression data from the Gene Expression Omnibus (GEO) collection (GSE118916 and GSE54129) were examined to find differentially expressed genes (DEGs) between gastric cancer (GC) and normal samples. The research used bioinformatics tools such as GEO2R, STRING, Cytoscape, and DAVID to identify differentially expressed genes (DEGs), create protein-protein interaction (PPI) networks, and conduct gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment studies. A total of 764 differentially expressed genes (DEGs) were discovered in GSE54129 and 356 in GSE118916, with 189 genes exhibiting overlap. Significant upregulation of key hub genes, such as FN1, MMP9, COL1A1, SPP1, CXCL8, COL1A2, THBS2, and THBS1, was observed, indicating their involvement in extracellular matrix remodelling, immunological modulation, and oxidative stress responses. The KEGG pathway study indicated the participation of focal adhesion, ECM-receptor interaction, xenobiotic metabolism, and protein digestion and absorption, underscoring their significance in tumour growth. Survival research indicated that THBS1, FN1, and THBS2 have considerable predictive significance. The results indicate that PBMC profiling provides a less intrusive method for elucidating GC etiology and discovering possible indicators for patient classification and targeted treatments. Future investigations, including multi-omics methodologies, are advised to corroborate these results and examine their therapeutic relevance in personalized treatment for gastric cancer.