Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis.

Qingjia Chi,Kang Xu,Xinge Geng,Chunli Wang,Han Zhao

doi:10.1042/bsr20200124

Abstract

Hepatocellular carcinoma (HCC) is one of the most common malignant tumor. miR-331-3p has been reported relevant to the progression of HCC, but the molecular mechanism of its regulation is still unclear. In the study, we comprehensively studied the role of miR-331-3p in HCC through weighted gene coexpression network analysis (WGCNA) based on The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Oncomine. WGCNA was applied to build gene co-expression networks to examine the correlation between gene sets and clinical characteristics, and to identify potential biomarkers. Five hundred one target genes of miR-331-3p were obtained by overlapping differentially expressed genes (DEGs) from the TCGA database and target genes predicted by miRWalk. The critical turquoise module and its eight key genes were screened by WGCNA. Enrichment analysis was implemented based on the genes in the turquoise module. Moreover, 48 genes with a high degree of connectivity were obtained by protein–protein interaction (PPI) analysis of the genes in the turquoise module. From overlapping genes analyzed by WGCNA and PPI, two hub genes were obtained, namely coatomer protein complex subunit zeta 1 (COPZ1) and elongation factor Tu GTP binding domain containing 2 (EFTUD2). In addition, the expression of both hub genes was also significantly higher in tumor tissues compared with normal tissues, as confirmed by analysis based on TCGA and Oncomine. Both hub genes were correlated with poor prognosis based on TCGA data. Receiver operating characteristic (ROC) curve validated that both hub genes exhibited excellent diagnostic efficiency for normal and tumor tissues.

Highlights

Liver cancer is the fifth and third malignant tumor with morbidity and mortality [1]
We comprehensively studied the role of miR-331-3p in hepatocellular carcinoma (HCC) through weighted gene coexpression network analysis (WGCNA) based on The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Oncomine
WGCNA were applied to build gene co-expression networks to examine the correlation between gene sets and clinical characteristics, and to identify hub genes and critical pathways. miR-331-3p is upregulated in HCC and demonstrates good prognosis and diagnostic performance for HCC based on the GEO and TCGA data sets

Summary

Introduction

Liver cancer is the fifth and third malignant tumor with morbidity and mortality [1]. Hepatocellular carcinoma (HCC) cannot be diagnosed at an early stage, and is often not detected until the late stage of cancer [2,3]. Some progress has been made in diagnosis and treatment strategies, the high metastasis rate and recurrence rate of HCC make it difficult for patients with advanced HCC to be effectively treated [5,6]. It is meaningful for the treatment to study the underlying molecular and identify novel markers for diagnosis and prognosis. MiRNAs play an important part in a variety of biological processes (BPs) by regulating gene expression post-transcriptionally [9,10]. Let-7, miR-101 and miR-370 are down-regulated in HCC [11,12,13]. While miR-155, miR-21, miR- 221, miR-146a, License 4.0 (CC BY)

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