Transcription analysis of the THBS2 gene through regulation by potential non-coding diagnostic biomarkers and oncogenes of gastric cancer in the ECM receptor interaction signaling pathway: integrated systems biology and experimental investigation

Abstract

Abstract Background Gastric cancer (GC) is the second most frequent cause of cancer-related death worldwide and the fourth most common malignancy. Despite significant improvements in patient survival over the past few decades, the prognosis for patients with GC remains dismal because of the high recurrence rate. In this comprehensive systems biology and experimental investigation, we aimed to find new novel diagnostic biomarkers of GC through a regulatory RNA interaction network. Methods Gene expression, co-expression, and survival analyses were performed using microarray and RNAseq datasets (analyzed by R Studio, GEPIA2, and ENCORI). RNA interaction analysis was performed using miRWalk and ENCORI online databases. Gene set enrichment analysis (GSEA) was performed to find related signaling pathways of up and down-regulated genes in the microarray dataset. Gene ontology and pathway enrichment analysis were performed by the enrichr database. Protein interaction analysis was performed by STRING online database. Validation of expression and co-expression analyses was performed using a qRT-PCR experiment. Results Based on bioinformatics analyses, THBS2 (FC: 7.14, FDR < 0.0001) has a significantly high expression in GC samples. lncRNAs BAIAP2-AS1, TSIX, and LINC01215 have RNA interaction with THBS2. BAIAP2-AS1 (FC: 1.44, FDR: 0.018), TSIX (FC: 1.34, FDR: 0.038), and LINC01215 (FC: 1.19, FDR: 0.046) have significant up-regulation in GC samples. THBS2 has a significant role in the regulation of the ECM-receptor signaling pathway. miR-4677-5p has a significant RNA interaction with THBS2. The expression level of THBS2, BAIAP2-AS1, TSIX, and LINC01215 has a non-significant negative correlation with the survival rate of GC patients (HR: 0.28, logrank p: 0.28). qRT-PCR experiment validates mentioned bioinformatics expression analyses. BAIAP2-AS1 (AUC: 0.7136, p-value: 0.0096), TSIX (AUC: 0.7456, p-value: 0.0029), and LINC01215 (AUC: 0.7872, p-value: 0.0005) could be acceptable diagnostic biomarkers of GC. Conclusion BAIAP2-AS1, lncRNA LINC01215, lncRNA TSIX and miR-4677-5p might modulate the ECM-receptor signaling pathway via regulation of THBS2 expression level, as the high-expressed non-coding RNAs in GC. Furthermore, mentioned lncRNAs could be considered potential diagnostic biomarkers of GC.