Identification of a Potentially Functional microRNA–mRNA Regulatory Network in Lung Adenocarcinoma Using a Bioinformatics Analysis

Abstract

BackgroundLung adenocarcinoma (LUAD) is a common lung cancer with a high mortality, for which microRNAs (miRNAs) play a vital role in its regulation. Multiple messenger RNAs (mRNAs) may be regulated by miRNAs, involved in LUAD tumorigenesis and progression. However, the miRNA–mRNA regulatory network involved in LUAD has not been fully elucidated.MethodsDifferentially expressed miRNAs and mRNA were derived from the Cancer Genome Atlas (TCGA) dataset in tissue samples and from our microarray data in plasma (GSE151963). Then, common differentially expressed (Co-DE) miRNAs were obtained through intersected analyses between the above two datasets. An overlap was applied to confirm the Co-DEmRNAs identified both in targeted mRNAs and DEmRNAs in TCGA. A miRNA–mRNA regulatory network was constructed using Cytoscape. The top five miRNA were identified as hub miRNA by degrees in the network. The functions and signaling pathways associated with the hub miRNA-targeted genes were revealed through Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The key mRNAs in the protein–protein interaction (PPI) network were identified using the STRING database and CytoHubba. Survival analyses were performed using Gene Expression Profiling Interactive Analysis (GEPIA).ResultsThe miRNA–mRNA regulatory network consists of 19 Co-DEmiRNAs and 760 Co-DEmRNAs. The five miRNAs (miR-539-5p, miR-656-3p, miR-2110, let-7b-5p, and miR-92b-3p) in the network were identified as hub miRNAs by degrees (>100). The 677 Co-DEmRNAs were targeted mRNAs from the five hub miRNAs, showing the roles in the functional analyses of the GO analysis and KEGG pathways (inclusion criteria: 836 and 48, respectively). The PPI network and Cytoscape analyses revealed that the top ten key mRNAs were NOTCH1, MMP2, IGF1, KDR, SPP1, FLT1, HGF, TEK, ANGPT1, and PDGFB. SPP1 and HGF emerged as hub genes through survival analysis. A high SPP1 expression indicated a poor survival, whereas HGF positively associated with survival outcomes in LUAD.ConclusionThis study investigated a miRNA–mRNA regulatory network associated with LUAD, exploring the hub miRNAs and potential functions of mRNA in the network. These findings contribute to identify new prognostic markers and therapeutic targets for LUAD patients in clinical settings.

Identification of Down-Regulated ADH1C is Associated With Poor Prognosis in Colorectal Cancer Using Bioinformatics Analysis

“…The PPI network complex of the common DEGs was then imported into Cytoscape, which is a free software for visualization of PPI networks to detect the hub DEGs (confidence score ≥0.4, maximum number of interactors = 0) ( Shannon et al, 2003 ). The Cytoscape application, cytoHubba, was applied to determine the hub genes of the PPI network and the top 15 hub genes was ranking by the Maximal Clique Centrality (MCC) algorithm ( Wang et al, 2021 ).…”

Macrophage-Related SPP1 as a Potential Biomarker for Early Lymph Node Metastasis in Lung Adenocarcinoma

“…Secreted phosphoprotein 1 (SPP1), a hallmark gene of the EMT process, can participate in extracellular matrix (ECM)-receptor interactions and the focal adhesion response pathway to regulate tumor metastasis and invasion. SPP1 is significantly associated with adverse survival outcomes in various cancers ( Wei et al, 2020 ; He et al, 2021 ; Wang et al, 2021 ). Notably, higher SPP1 expression levels are related to a higher N stage in LUAD patients ( Guo et al, 2020 ), although the underlying mechanism has not yet been studied fully.…”

Plasma tRNA-derived small RNAs signature as a predictive and prognostic biomarker in lung adenocarcinoma

“…Patients who had just undergone surgery, as well as those who were undergoing chemotherapy or radiotherapy, were excluded from the study. For further analysis, 10 plasma samples (6 LUAD and 4 normal, SRP266333) and 96 tissue samples (48 LUAD and 48 normal, SRP133217) were included for further [ 21 , 22 ]. These high-throughput sequencing data was downloaded by SRA Toolkit.…”