Bioinformatics Analysis of mRNAs and miRNAs for Identifying Potential Biomarkers in Lung Adenosquamous Carcinoma. (2nd March 2022) - Nie, Jin; Gong, Ling; Li, Zhu; Ou, Dong; Zhang, Ling; Liu, Yi; Zhang, Jianyong; Liu, Daishun
Abstract : Background . Lung adenosquamous carcinoma (LASC) is a special type of lung cancer. LASC is a malignant tumor with strong aggressiveness and a poor prognosis. Previous studies have revealed that microRNAs (miRNAs) are widely involved in the development of tumors by targeting mRNA. This study is aimed at identifying the key mRNAs and miRNAs of LASC and constructing miRNA-mRNA networks for deeply comprehending the latent molecular mechanisms. Methods . mRNA dataset (GSE51852) and miRNA dataset (GSE51853) were extracted and downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were picked out by the GEO2R web tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted in the DAVID database. The protein-protein interaction (PPI) network was performed and analyzed by using the STRING database and Cytoscape software, respectively. TransmiR v2.0 was applied to predict potential transcription factors of miRNAs. The target genes of DEMs were predicted in the miRWalk database. Results . In comparison to normal tissues, a total of 1458 DEGs (511 upregulated and 947 downregulated) and 13 DEMs (5 upregulated and 8 downregulated) were screened out in LASC tissues. The PPI network of the DEGs displayed five key modules and seventeen hub genes. Six target genes of the DEMs were predicted, and five essential miRNA-mRNA regulatory pairs were established. Ensuingly, CENPF, one of the target genes, was also the hub genes of GSE51852, which was obtained from MCODE and cytoHubba and regulated by hsa-miR-205. Conclusions . We constructed the miRNA-mRNA regulatory pairs, which are helpful to study the potential regulatory mechanisms and find out promising diagnosis biomarkers and therapeutic targets for LASC.