Construction and Analysis of the Tumor-Specific mRNA–miRNA–lncRNA Network in Gastric Cancer

Abstract

Weighted correlation network analysis (WGCNA) is a statistical method that has been widely used in recent years to explore gene co-expression modules. Competing endogenous RNA (ceRNA) is commonly involved in the cancer gene expression regulation mechanism. Some ceRNA networks are recognized in gastric cancer; however, the prognosisassociated ceRNA network has not been fully identified using WGCNA. We performed WGCNA using datasets from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) to identify cancer-associated modules. The criteria of differentially expressed RNAs between normal stomach samples and gastric cancer samples were set at the false discovery rate (FDR) < 0.01 and |fold change (FC)| > 1.3. The ceRNA relationships obtained from the RNAinter database were examined by both the Pearson correlation test and hypergeometric test to confirm the mRNA-lncRNA regulation. Overlapped genes were recognized at the intersections of genes predicted by ceRNA relationships, differentially expressed genes, and genes in cancer-specific modules. These were then used for univariate and multivariate Cox analyses to construct a risk score model. The ceRNA network was constructed based on the genes in this model. WGCNAuncovered genes in the green and turquoise modules are those most associated with gastric cancer. Eighty differentially expressed genes were observed to have potential prognostic value, which led to the identification of 12 prognosis-related mRNAs (KIF15, FEN1, ZFP69B, SP6, SPARC, TTF2, MSI2, KYNU, ACLY, KIF21B, SLC12A7, and ZNF823) to construct a risk score model. The risk genes were validated using the GSE62254 and GSE84433 datasets, with 0.82 as the universal cutoff value. 12 genes, 12 lncRNAs, and 35 miRNAs were used to build a ceRNA network with 86 dysregulated lncRNA-mRNA ceRNA pairs. Finally, we developed a 12-gene signature from both prognosis-related and tumorspecific genes, and then constructed a ceRNA network in gastric cancer. Our findings may provide novel insights into the treatment of gastric cancer.

Identification of a Novel Prognostic Signature for Gastric Cancer Based on Multiple Level Integration and Global Network Optimization

“…In another study, Zhang et al adopted the WGCNA method to identify GC related networks. A ceRNA network that included 86 dysregulated relationships was also constructed for simple display (Zheng et al, 2020). In many other tumor types, a similar integrated analysis was also performed.…”

Construction and analysis of a ceRNA network and patterns of immune infiltration in bladder cancer

“…After diagnosis, the physical, mental, and social health-related quality of life (HRQoL) of patients with BC significantly declines (42). Increasing evidence indicated that ceRNAs and dysregulation of the immune system are involved in the progression of human tumors (43)(44)(45)(46)(47)(48).…”

Close interactions between lncRNAs, lipid metabolism and ferroptosis in cancer

“…WGCNA can identify the genes most related to cancer in the database. Then, a series of methods, including univariate and multivariate Cox regression analyses and Pearson correlation and hypergeometric tests, confirmed that ACLY was correlated with lncRNA PPP1R26-AS1, lncRNA DLEU1 and lncRNA TMPO-AS1 [79]. However, further experiments are needed to verify the relationship between these lncRNAs and ACLY.…”