A new method for excavating feature lncRNA in lung adenocarcinoma based on pathway crosstalk analysis

Abstract

Recent theoretical and experimental studies indicate that long-chain noncoding RNAs (lncRNAs) are essential for the growth and differentiation of cells and the occurrence and development of tumors in epigenetics, but the regulation of lncRNA on gene expression, transcriptional activation, and transcriptional interference in diseases is still unclear. There is an urgent need for effective methods to discover significant lncRNAs with their functions on gene regulatory mechanisms. For this purpose, a new method of extracting significant lncRNA based on pathway crosstalk and dysfunction caused by the differentially expressed genes in lung adenocarcinoma (LUAD) was proposed. The pathway analysis method based on global influence (PAGI) was first applied to find the feature genes that play an important role in the crosstalks of disease-related pathways. Then to explore the hub lncRNAs, the weighted gene coexpression network analysis (WGCNA) was used to construct coexpression models of the feature genes and lncRNAs. The experiment results showed that 64 out of the 322 hub lncRNAs were closely related to the clinical features of patients with LUAD. Among them, nine lncRNAs (UCA1, LINC00857, PVT1, PCAT6, LINC00460, LINC00319, AP000553.1, AP000439.2, and AP005233.2) were identified to be tightly correlated with non-small-cell lung cancer (NSCLC) pathways. In summary, we offer an effective way to extract significant lncRNA by dysfunctional pathway crosstalk in LUAD which allows the selected lncRNAs with more biologically interpreted and reproducible results. This method can be applied to other diseases and provide useful information for understanding the pathogenesis of human cancer. K E Y W O R D S long-chain noncoding RNAs (lncRNAs), lung adenocarcinoma (LUAD), pathway analysis method based on global influence (PAGI), pathway crosstalk, weighted gene coexpression network analysis (WGCNA)

Long Noncoding RNA RAET1K Enhances CCNE1 Expression and Cell Cycle Arrest of Lung Adenocarcinoma Cell by Sponging miRNA-135a-5p

“…Cell cycle dysfunction in LUAD was consistent with our results. A recent study demonstrated that cell cycle-related genes, such as E2F1 (Chen et al, 2019), were enriched during the regulation of the cell cycle progression (Li et al, 2018;Qi et al, 2019). In the present study, we found that lncRNA RAET1K could promote cell cycle dysfunction, providing insight into the crosstalk regulatory mechanism between lncRNAs and coding genes.…”

High throughput circRNA sequencing analysis reveals novel insights into the mechanism of nitidine chloride against hepatocellular carcinoma

“…WGCNA analysis was performed based on the 857 genes to identify gene co-expression networks and their underlying clinical significances. WGCNA is a system-level method for identifying modules of highly correlated genes from microarray or RNA-seq datasets and for relating modules to clinical traits 29 , which has been applied in various biological contexts, including cancer 30,31 . In this study, we identified three modules of the 857 genes by using the WGCNA approach, among which MEturquoise with 423 genes showed close links with the survival time, pathology grade and TNM stage of patients with HCC.…”

PVT1 Promotes Cancer Progression via MicroRNAs

“…There have been several studies exploring lncPVT1's clinical application. The results reveal that lncPVT1 is a potential biomarker for some tumors as its expression is abnormal and the detecting technology has been optimized (62–66). And as a more stable form, circPVT1 may be more valuable in clinic practice.…”