Gastric carcinoma (GC) in one of the most common malignant tumors in the worldwide. Despite numerous studies, the molecular mechanism of is still unclear and the prognosis of GC remains poor.
The present study obtained expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The gene risk signature and lncRNA signature were constructed by performing the univariate cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis. The receive operator curve (ROC) analysis was applied to evaluated the specificity and sensitivity of risk signature. The potential pathway was performed by using the Gene Set Enrichment Analysis (GSEA).
In total, 1641 differentially expressed genes (DEGs) and 985 differentially expressed lncRNAs (DElncRNAs) were obtained among GC samples. A 6 prognostic DEGs (DIRC1, IQCM, MATN3, SOX14, C5orf46 and CYP19A1) classifier and 9 prognostic DElncRNAs (AC007126.1, AC011352.1, AL356417.2, AP000695.1, LINC01210, LINC01614, VCAN-AS1, AC005165.1 and AC011586.2) classifier were identified using lasso-penalized multivariate survival modelling with 10 fold cross-validation. According to median risk score, patients were divided into high risk group and low risk group. The overall survival result for patients have a significant divergence between high rosk group and low risk group (p < 0.001). The 6 DEGs signature risk model and 9 DElncRNAs signature risk model was further verified that can served as an independent prognostic biomarkers for GC prediction among the clinical traits (P < 0.001). Moreover, two independent cohort GEO dataset (GSE13911 and GSE70800) was employed to evaluate the specificity and sensitivity of the prognostic gene and prognostic lncRNA. Gene set enrichment analysis (GSEA) result for the risk model revealed that these gene involved in ECM receptor interaction pathway, ERBB signaling pathway, UBIQUITIN mediated proteolysis, cell adhesion molecules CAMS, ECM receptor interaction, focal adhesion, pathways in cancer and TGF beta signaling pathway, meaning that the prognostic gene risk model and lncRNAs risk model play an crucial role and have important prognostic values.
These findings may have important significance in understanding the molecular mechanism of GC and potential therapeutic method for the GC patients.