Abstract
BACKGROUND: Serpin Peptidase Inhibitor 1 (SERPINE1) promotes cancer progression by making it easier for cancer cells to spread to surrounding normal tissue. We expect to understand the prognostic value and regulatory network of SERPINE1 in colon cancer using bioinformatics methods. METHODS: The expression of target gene SERPINE1 in varying cancers was analyzed by the Tumor Immune Estimation Resource (TIMER) database. SERPINE1 expression in Colon Adenocarcinoma and normal tissue samples was assessed by starBase and UALCAN databases. SERPINE1 expression in clinical tissues was assayed using quantitative reverse transcription Polymerase Chain Reaction (qRT-PCR). SERPINE1 expression was detected in colon cancer patients with various clinical features (age, gender, nodal metastasis status, race, stages, and subtype) using analysis of variance. Survival curve was used to analyze the effect of high and low expression of SERPINE1 on the survival time of patients with different clinical phenotypes. Gene Set Enrichment Analysis (GSEA) was conducted on the results of LinkFinder calculation using LinkInterpreter module, which was combined with Pearson correlation analysis to obtain the kinase targets and miRNA targets, transcription factor targets, and corresponding signaling pathways associated with SERPINE1. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on GSEA result. Finally, Gene Multiple Association Network Integration Algorithm (GeneMANIA) was utilized to establish a network of genes related to the kinases MAPK1, miR-18a, and SRF_Q, and biological functions were analyzed. RESULTS: Based on TIMER, starBase, and UALCAN databases, SERPINE1 was found to be remarkably highly expressed in colon cancer patients, which was further verified by clinical tissue. It was also associated with different clinical features (nodal metastasis status, stages, subtypes). Additionally, survival analysis showed that patients with low expression of SERPINE1 had a longer survival time, suggesting that SERPINE1 was a prognostic risk factor for colon cancer. Pearson correlation analysis revealed that the expression of Integrin Alpha 5 (ITGA5), Matrix Metallopeptidase 19 (MMP19), and ADAM Metallopeptidase with Thrombospondin Type 1 Motif, 4 (ADAMTS4) had the highest correlation with that of SERPINE1. The GSEA results indicated that these genes were mainly enriched in the pathways of RNA expression and kinases. Finally, GeneMANIA analysis was introduced to construct the molecular network of SERPINE1. CONCLUSION: Overall, our bioinformatics analyses comprehensively described the networks involved SERPINE1 in colon cancer and the potentially associated molecular mechanisms.