背景

加权基因共表达网络（WGCNA）是近年来广泛用于探索基因共表达模块的一种统计方法。 竞争性内源RNA（ceRNA）是癌症中最常见的基因表达调控机制之一。 少数ceRNA网络已在胃癌中得到公认，但是，使用WGCNA建立与预后相关的ceRNA网络尚未被充分研究。

方法

我们在癌症基因组图谱（TCGA）和基因型组织表达（GTEx）的数据集中进行了加权相关网络分析（WGCNA）分析，以鉴定与癌症相关的模块。在正常胃样品和胃癌样品之间进行差异分析，标准的错误发现率（FDR）<0.01，|倍数变化（FC）| > 1.3。通过Pearson相关检验和超几何检验检验了从RNAinter数据库获得的ceRNA关系证实了mRNA-lncRNA在胃癌中的调控。在由ceRNA关系预测的基因的交集，差异表达的基因，癌症特定模块中的基因中识别出重叠的基因，然后将其放入单变量和多变量cox分析中，以构建风险评分模型。ceRNA网络是基于风险模型中的基因构建的。

结果

加权基因相关网络分析在绿色和青绿色模块中发现的基因是胃癌中与癌症最相关的基因。发现80个与癌症相关的不同表达基因具有潜在的预后价值，从而进一步鉴定了12种与预后相关的mRNA（KIF15，FEN1，ZFP69B，SP6，SPARC，TTF2，MSI2，KYNU，ACLY，KIF21B，SLC12A7，和ZNF823）来构建风险评分模型。GSE62254和GSE84433的数据集使用0.82作为通用截断值验证了风险基因。最后，12个基因，12个lncRNAs和35个miRNA ，被用来建立一个含有86个失调mRNA-lncRNA-miRNA关系对的竞争性内源性RNA网络。

结论

我们使用加权基因共表达网络发现了由预后相关和肿瘤特异性的12基因构建的ceRNA网络，这可能为胃癌的治疗方法提供新的见解。

Background

WGCNA is a statistical method widely used in recent years to explore gene co-expression modules. The competing endogenous RNA (ceRNA) is one of the most common gene expression regulation mechanisms among cancer. A handful of ceRNA networks has been recognized in gastric cancer, however, the prognosis-associated ceRNA network has not been fully identified using WGCNA.

Methods

We performed the weighted correlation network analysis (WGCNA) analysis in datasets of The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) to identify the cancer-associated modules. Differential analysis was performed between normal stomach samples and gastric cancer samples with the standard of 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 tests and the hypergeometric tests to confirmed the regulation of mRNA-lncRNA in gastric cancer. Overlapped genes were recognized in the intersection of genes predicted by the ceRNA relationships, differentially expressed genes, genes in the cancer-specific modules, which then were put into the univariate and multivariate cox analysis to construct the risk-score model. The ceRNA network was constructed based on genes in the risk-model model.

Results

WGCNA uncovered genes in the green and turquoise module are the most cancer-associated ones in gastric cancer. 80 cancer-associated different expressed genes were found to have potential prognostic value, which further led to the identification of 12 prognosis-related mRNAs (KIF15, FEN1, ZFP69B, SP6, SPARC, TTF2, MSI2, KYNU, ACLY, KIF21B, SLC12A7, and ZNF823) for constructing a risk score model. The risk genes were validated by the datasets of the GSE62254 and GSE84433 using 0.82 as the universal cut-off value. Finally, 12 genes, 12 lncRNAs, and 35 miRNAs were used to build a ceRNA network with 86 dysregulated lncRNA-mRNA ceRNA pairs.

Conclusions

We discovered a ceRNA network constructed by both prognosis-related and cancer-associated co-expression genes using WGCNA, which may deliver novel insight into the treatment method of gastric cancer.