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BMC Cancer

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01-12-2021 | Hepatocellular Carcinoma | Research

Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

Authors: Ping Yan, Zuotian Huang, Tong Mou, Yunhai Luo, Yanyao Liu, Baoyong Zhou, Zhenrui Cao, Zhongjun Wu

Published in: BMC Cancer | Issue 1/2021

Abstract

Background

Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers.

Methods

We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively.

Results

With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients.

Conclusions

In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

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Title: Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence
Authors: Ping Yan
Zuotian Huang
Tong Mou
Yunhai Luo
Yanyao Liu
Baoyong Zhou
Zhenrui Cao
Zhongjun Wu
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Hepatocellular Carcinoma
Hepatocellular Carcinoma
Biomarkers
Published in: BMC Cancer / Issue 1/2021
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-021-08173-0

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Abstract

Background

Methods

Results

Conclusions

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