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通过加权基因共表达网络分析鉴定与肝细胞癌进展和预后相关的13个关键基因

Identification of 13 Key Genes Correlated With Progression and Prognosis in Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis.

作者信息

Gu Yang, Li Jun, Guo Deliang, Chen Baiyang, Liu Pengpeng, Xiao Yusha, Yang Kang, Liu Zhisu, Liu Quanyan

机构信息

Department of Hepatobiliary and Pancreas Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.

出版信息

Front Genet. 2020 Feb 28;11:153. doi: 10.3389/fgene.2020.00153. eCollection 2020.

DOI:10.3389/fgene.2020.00153
PMID:32180800
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7059753/
Abstract

Hepatocellular carcinoma (HCC) remains hard to diagnose early and cure due to a lack of accurate biomarkers and effective treatments. Hence, it is necessary to explore the tumorigenesis and tumor progression of HCC to discover new biomarkers for clinical treatment. We performed weighted gene co-expression network analysis (WGCNA) to explore hub genes that have high correlation with clinical information. In this study, we found 13 hub genes (, , , , , , , , , , , , and ) that have high correlation with histologic grade in HCC by analyzing TCGA LIHC dataset. All of these 13 hub genes could be used to effectively distinguish high histologic grade from low histologic grade of HCC through analysis of the ROC curve. The overall survival and disease-free survival information showed that high expression of these 13 hub genes led to poor prognosis. Meanwhile, these 13 hub genes had significantly different expression in HCC tumor and non-tumor tissues. We downloaded GSE6764, which contains corresponding clinical information, to validate the expression of these 13 hub genes. At the same time, we performed quantitative real-time PCR to validate the differences in the expression tendencies of these 13 hub genes between HCC tumor tissues and non-tumor tissues and high histologic grade and low histologic grade. We also explored mutation and methylation information of these 13 hub genes for further study. In summary, 13 hub genes correlated with the progression and prognosis of HCC were discovered by WGCNA in our study, and these hub genes may contribute to the tumorigenesis and tumor progression of HCC.

摘要

由于缺乏准确的生物标志物和有效的治疗方法，肝细胞癌（HCC）仍然难以早期诊断和治愈。因此，有必要探索HCC的肿瘤发生和肿瘤进展，以发现用于临床治疗的新生物标志物。我们进行了加权基因共表达网络分析（WGCNA），以探索与临床信息高度相关的枢纽基因。在本研究中，我们通过分析TCGA LIHC数据集，发现了13个与HCC组织学分级高度相关的枢纽基因（、、、、、、、、、、、和）。通过ROC曲线分析，所有这13个枢纽基因均可有效区分HCC的高组织学分级和低组织学分级。总生存和无病生存信息显示，这13个枢纽基因的高表达导致预后不良。同时，这13个枢纽基因在HCC肿瘤组织和非肿瘤组织中的表达存在显著差异。我们下载了包含相应临床信息的GSE6764，以验证这13个枢纽基因的表达。同时，我们进行了定量实时PCR，以验证这13个枢纽基因在HCC肿瘤组织与非肿瘤组织之间以及高组织学分级与低组织学分级之间表达趋势的差异。我们还探索了这13个枢纽基因的突变和甲基化信息以进行进一步研究。总之，我们的研究通过WGCNA发现了13个与HCC进展和预后相关的枢纽基因，这些枢纽基因可能促进了HCC的肿瘤发生和肿瘤进展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/9cbf5f579c2e/fgene-11-00153-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/a531b1f5f55f/fgene-11-00153-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/96a19b2c28a2/fgene-11-00153-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/c9a6aaebfa76/fgene-11-00153-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/7213ac55dafa/fgene-11-00153-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/4b52948650eb/fgene-11-00153-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/17fb40ea1df1/fgene-11-00153-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/f4b3c06f2332/fgene-11-00153-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/15ad7558f99b/fgene-11-00153-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/9cbf5f579c2e/fgene-11-00153-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/a531b1f5f55f/fgene-11-00153-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/96a19b2c28a2/fgene-11-00153-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/c9a6aaebfa76/fgene-11-00153-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/7213ac55dafa/fgene-11-00153-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/4b52948650eb/fgene-11-00153-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/17fb40ea1df1/fgene-11-00153-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/f4b3c06f2332/fgene-11-00153-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/15ad7558f99b/fgene-11-00153-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4862/7059753/9cbf5f579c2e/fgene-11-00153-g009.jpg

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