Circulating miR-1246 Targeting UBE2C, TNNI3, TRAIP, UCHL1 Genes and Key Pathways as a Potential Biomarker for Lung Adenocarcinoma: Integrated Biological Network Analysis

Abstract

Analysis of circulating miRNAs (cmiRNAs) before surgical operation (BSO) and after the surgical operation (ASO) has been informative for lung adenocarcinoma (LUAD) diagnosis, progression, and outcomes of treatment. Thus, we performed a biological network analysis to identify the potential target genes (PTGs) of the overexpressed cmiRNA signatures from LUAD samples that had undergone surgical therapy. Differential expression (DE) analysis of microarray datasets, including cmiRNAs (GSE137140) and cmRNAs (GSE69732), was conducted using the Limma package. cmiR-1246 was predicted as a significantly upregulated cmiRNA of LUAD samples BSO and ASO. Then, 9802 miR-1246 target genes (TGs) were predicted using 12 TG prediction platforms (MiRWalk, miRDB, and TargetScan). Briefly, 425 highly expressed overlapping miRNA-1246 TGs were observed between the prediction platform and the cmiRNA dataset. ClueGO predicted cell projection morphogenesis, chemosensory behavior, and glycosaminoglycan binding, and the PI3K–Akt signaling pathways were enriched metabolic interactions regulating miRNA-1245 overlapping TGs in LUAD. Using 425 overlapping miR-1246 TGs, a protein–protein interaction network was constructed. Then, 12 PTGs of three different Walktrap modules were identified; among them, ubiquitin-conjugating enzyme E2C (UBE2C), troponin T1(TNNT1), T-cell receptor alpha locus interacting protein (TRAIP), and ubiquitin c-terminal hydrolase L1(UCHL1) were positively correlated with miR-1246, and the high expression of these genes was associated with better overall survival of LUAD. We conclude that PTGs of cmiRNA-1246 and key pathways, namely, ubiquitin-mediated proteolysis, glycosaminoglycan binding, the DNA metabolic process, and the PI3K–Akt–mTOR signaling pathway, the neurotrophin and cardiomyopathy signaling pathway, and the MAPK signaling pathway provide new insights on a noninvasive prognostic biomarker for LUAD.

Identification of Immune-Related Key Genes in Ovarian Cancer Based on WGCNA

“…To evaluate the ability of key genes in the prediction of the prognosis of OV patients, 376 patients were divided into low and high groups according to the median expression level of key genes, Then, a survival curve was drawn based on the OS status and OS.time information of each sample by Kaplan-Meier survival analysis by use of R package “ survival ” ( Huang et al, 2020 ). The log-rank test was carried out to measure the statistical significance ( Huang et al, 2020 ). The log-rank test was carried out to measure the statistical significance.…”

Microarray analysis of genes with differential expression of m6A methylation in lung cancer

“…This observation was similar with our data in this study. Regulation of Akt activation and autophagy induction were found to be significantly related to the treatment and prognosis of lung cancers such as NSCLC, lung squamous cell carcinoma and lung adenocarcinoma [33][34][35] . Apaf1 and autophagy induction could underlie the recovery process of cell [36] .…”

Multiomics Identification of Potential Targets for Alzheimer Disease and Antrocin as a Therapeutic Candidate

“…We explored the NetworkAnalyst server (https://www.networkanalyst.ca/, accessed on 21 September 2021) [32] to conduct a brain-specific gene co-expression analysis. In accordance with the protocol described in previous studies [33,34], the DEGs were uploaded to the GENELIST module of the server and were analyzed for specific selected parameters: organism (Homo sapiens), ID type (gene symbol), tissue-specific co-expression (brain) analysis minimum-order network analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and gene ontology (GO) enrichment analyses of the DEGs were conducted using the Enrich server [35,36].…”