Abstract
In our study, we aimed to reveal potential long non-coding RNAs (lncRNA) biomarkers in lung adenocarcinoma (LAD) using lncRNA-mediated competing endogenous RNAs (ceRNAs) network (LMCN). Competing lncRNA-mRNA interactions were identified using the hypergeometric test. Co-expression analysis for the competing lncRNA-mRNA interactions was implemented, and relying on the weight value >0.8, a highly competitive LMCN was further constructed. Degree distribution, betweenness and closeness for LMCN were carried out to analyze the network structure. Functional analyses of mRNAs in LMCN were carried out to further explore the biological functions of lncRNAs. Biclique algorithm was utilized to extract competing modules from the LMCN. Finally, we verified our findings in an independent sample set using qRT-PCR. Based on degrees >60, we identified 4 hubs, including DLEU2, SNHG12, HCP5, and LINC00472. Furthermore, 2 competing modules were identified, and LINC00472 in module 1 functioned as a hub in both LMCN and module. Functional implications of lncRNAs demonstrated that lncRNAs were related to histone modification, negative regulation of cell cycle, neuroactive ligand-receptor interaction, and regulation of actin cytoskeleton. qRT-PCR results demonstrated that lncRNAs LINC00472, and HCP5 were down-regulated in LAD tissues, while the expression level of SNHG12 was up-regulated in LAD tissues. Our study sheds novel light on the roles of lncRNA-related ceRNA network in LAD and facilitates the detection of potential lncRNA biomarkers for LAD diagnosis and treatment. Remarkably, in our study, LINC00472, HCP5, and SNHG12 might be potential biomarkers for LAD management.
Highlights
Lung adenocarcinoma (LAD) is the most common histological type of lung cancer, which is the leading cause of cancer-related deaths [1]
A total of 57 long non-coding RNAs (lncRNA), 10,133 mRNAs, and 48,939 competing endogenous RNAs (ceRNAs) interactions were selected to establish an original network based on false discovery rate (FDR) 0.01, and their relationships were not displayed because the data in this original network could not be clearly visualized due to size
We found that the lncRNAs were in the central area of the network, but the mRNAs were typically in the outside layer
Summary
Lung adenocarcinoma (LAD) is the most common histological type of lung cancer, which is the leading cause of cancer-related deaths [1]. An early and accurate diagnosis may warrant timely treatment to potentially decrease the mortality. A critical problem in the progression of LAD is the limited access to early detection and timely treatment. Understanding the mechanisms underlying LAD progression is urgent for improving the therapy and overall prognosis of this disease. Traditional recognizable pathological symptoms have limited value in detecting early stage of LAD. Molecular biosignatures have been proven to be a promising tool for identifying patients in early-stage disease
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