Transcription Analysis of the THBS2 Gene through Regulation by Potential Noncoding Diagnostic Biomarkers and Oncogenes of Gastric Cancer in the ECM-Receptor Interaction Signaling Pathway: Integrated System Biology and Experimental Investigation

Ali Barani; Kamyar Beikverdi; Benyamin Mashhadi; Naeimeh Parsapour; Mohammad Rezaei; Pegah Javid; Mansoureh Azadeh

doi:10.1155/2023/5583231

Transcription Analysis of the THBS2 Gene through Regulation by Potential Noncoding Diagnostic Biomarkers and Oncogenes of Gastric Cancer in the ECM-Receptor Interaction Signaling Pathway: Integrated System Biology and Experimental Investigation

Int J Genomics. 2023 Dec 22:2023:5583231. doi: 10.1155/2023/5583231. eCollection 2023.

Authors

Ali Barani^{1

2}, Kamyar Beikverdi^{1

3}, Benyamin Mashhadi^{1

4}, Naeimeh Parsapour^{1

5}, Mohammad Rezaei^{1

6}, Pegah Javid^{1

7}, Mansoureh Azadeh¹

Affiliations

¹ Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran.
² Department of Biosciences, University of Milan, Milan, Italy.
³ Department of Molecular Medicine, University of Pavia, Pavia, Italy.
⁴ Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
⁵ Department of Immunology, Genetics and Pathology, Faculty of Medicine, Uppsala University, Uppsala, Sweden.
⁶ Department of Biology and Biotechnology, University of Pavia, Pavia, Italy.
⁷ Molecular Genetics Research Lab, Persian Gulf Biotechnology Park, Qeshm Island, Hormozgan, Iran.

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 system biology and experimental investigation, we aimed to find new novel diagnostic biomarkers of GC through a regulatory RNA interaction network.

Methods: Gene expression, coexpression, and survival analyses were performed using microarray and RNAseq datasets (analyzed by RStudio, 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 downregulated 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 coexpression 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 upregulation 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 nonsignificant 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 noncoding RNAs in GC. Furthermore, mentioned lncRNAs could be considered potential diagnostic biomarkers of GC.