Bioinformatics Identification of Therapeutic Gene Targets for Gastric Cancer

• Published in: Advances in therapy 2023-04, Vol.40 (4), p.1456-1473
• Main Authors: Li, Yuanting, Chen, Minghao, Chen, Qing, Yuan, Min, Zeng, Xi, Zeng, Yan, He, Meibo, Wang, Baiqiang, Han, Bin
• Format: Article
• Language: English
• Subjects: Biomarkers, Tumor - genetics; Biomarkers, Tumor - metabolism; Cardiology; Computational Biology; Endocrinology; Gene Expression Profiling; Humans; Internal Medicine; Medicine; Medicine & Public Health; Oncology; Original Research; Pharmacology/Toxicology; Prognosis; Protein Interaction Maps - genetics; Rheumatology; Stomach Neoplasms - drug therapy; Stomach Neoplasms - genetics
• ISSN: 0741-238X; 1865-8652
• DOI: 10.1007/s12325-023-02428-x

Introduction The global prevalence of gastric cancer (GC) is increasing, and novel chemotherapeutic targets are needed. Methods We searched for potential biomarkers for GC in three microarray data sets within the Gene Expression Omnibus (GEO) database. FunRich (v3.1.3) was used to perform Gene Ontology (GO) analyses and STRUN and Cytoscape (v3.6.0) were employed to construct a protein–protein interaction (PPI) network. To explore hub gene expression and survival, we used Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan–Meier (KM) plotter. Drugs that were closely related to key genes were screened by the Gene Set Cancer Analysis (GSCA), and relevant correlations were verified experimentally. We validated that the sensitivity of a GC cell line to these drugs was correlated with fibrillin 1 ( FBN1 ) mRNA expression levels. Results We identified 83 upregulated and 133 downregulated differentially expressed genes (DEGs) and these were enriched with regards to their cellular component (extracellular and exosomes), molecular function (extracellular matrix structural constituent and catalytic activity), and biological process (cell growth and/or maintenance and metabolism). The biological pathways most prominently involved were epithelial-to-mesenchymal transition (EMT) and β3 integrin cell surface interactions. For the PPI network, we selected 10 hub genes, and 70% of these were significantly connected to poor overall survival (OS) in patients with GC. We found a significant link between the expression of FBN1 and two small molecule drugs (PAC-1 and PHA-793887). Conclusions Overall, we suggest that these hub genes can be used as biomarkers and novel targets for GC. FBN1 may be associated with drug resistance in gastric cancer.