Network based integration of multi-omic profiles to purpose new biomarker candidates in pancreatic cancer

Abstract

Due to its late diagnosis, poor survival rates, and high incidence of metastasis, pancreatic cancer is one of the most fatal malignancies. Considering the uncertainties in its molecular mechanism, in the present study, we aimed to provide shed more light on the molecular regulatory signatures of circRNAs in PDAC progression and a different perspective to identify potential biomarkers for PDAC by network-based integrative analysis. PDAC expression profiles for the mRNA, miRNA, and circRNA were downloaded nine Gene Expression Omnibus microarray datasets. The statistical analysis of the microarray datasets established the differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs), and circRNAs (DEcircRNAs). Utilizing a combination method of circRNA-miRNA pairs with miRNA-mRNA pairs, the competitive endogenous RNA (ceRNA; DEcircRNA-DEmiRNA-DEmRNA) regulatory network was created. The pathway and functional enrichment analysis were carried out using the Metascape, and hub genes were identified using the MCODE plugin. An overall, 110 DEcircRNAs, 10 DEmiRNAs, and 248 DEmRNAs were detected. The ceRNA network including 46 circRNAs, 10 miRNAs, and 31 mRNAs specific to PDAC was established. In ceRNA network, seven hubgenes were found (SUZ12, IGF2BP2, PPP1CB, FN1, ACTN4, TP53, and PRKAA1) by using the protein-protein interaction network and module analysis. The functional annotation of the DEmRNAs in the ceRNA regulatory network showed that these DEmRNAs were considerably augemented in focal adhesion, regulation of muscle tissue development and assembly of collagen fibrils and other multimeric structures. In conclusion, this research improve present knowledge of the ceRNA regulatory mechanisms in the regulation of PDAC carcinogenesis and provide novel circRNAs as candidate biomarkers.