Genes associated with calcium signaling have promising diagnostic potential for gastric cancer

Gastric cancer (GC) represents a considerable health risk, characterized by a poor 5-year survival rate of approximately 8%. Using data from The Cancer Genome Atlas (TCGA), this study investigated the function of calcium signaling-related genes in the context of GC.

The RNA sequencing data and clinical characteristic data of GC patients were retrieved from TCGA database. A comprehensive analysis was conducted to identify the prognostic genes, and a significant correlation was found between these genes and the calcium signaling pathways related to GC.

The univariate Cox regression analysis identified 829 prognostic genes, primarily related to the calcium signaling pathway, focal adhesion, extracellular matrix (ECM)-receptor interaction, and cancer-associated pathways, all of which may significantly affect GC. Through consensus clustering, two distinct molecular subtypes of GC were identified [Cluster 1 (C1) and Cluster 2 (C2)] based on the genes associated with calcium signaling. Notably, C2 may serve as a prognostic indicator of risk, potentially reflecting the progression of clinical symptoms. The Gene Ontology (GO) analysis of biological processes revealed that these genes were significantly involved in cell-matrix adhesion, calcium ion homeostasis, and cell-substrate adhesion in the high-risk C1 cohort. Similarly, the Kyoto Encyclopedia of Genes and Genomes analysis indicated that the differentially expressed genes were largely associated with the pathways related to ECM-receptor interactions, focal adhesion, vascular smooth muscle contraction, cancer-related proteoglycans, and calcium signaling pathways in the high-risk C1 group. Further, there were significant differences in the immune activity of the two calcium signaling-related GC groups. The least absolute shrinkage and selection operator regression analysis identified 10 genes associated with calcium signaling in GC (i.e., PDE1B, NGF, FGF1, ADRA1B, TACR1, CXCR4, GNAS, EDNRB, EGF, and ERBB4). The accuracy of the prognostic model was assessed by a receiver operating characteristic curve analysis, yielding areas under the curve of 0.639 for 1 year, 0.707 for three years, and 0.674 for 5 years.

We established an innovative signature associated with calcium signaling that serves as a reliable prognostic indicator for GC. Our findings may pave the way for enhanced diagnostic and therapeutic approaches in the context of GC.