Gene Network Analysis of Hepatocellular Carcinoma Identifes Modules Associated with Disease Progression, Survival, and Chemo Drug Resistance

Background: Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. HCC transcriptome has been extensively studied; however, the pro-gress in disease mechanisms, prognosis, and treatment is still slow. Methods: A rank-based module-centric workfow was introdu...

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Bibliographic Details
Published inInternational journal of general medicine Vol. 14; p. 9333
Main Authors Ye, Hua, Sun, Mengxia, Huang, Shiliang, Xu, Feng, Wang, Jian, Liu, Huiwei, Zhang, Liangshun, Luo, Wenjing, Guo, Wenying, Wu, Zhe, Zhu, Jie, Li, Hong
Format Journal Article
LanguageEnglish
Published Dove Medical Press Limited 31.12.2021
Subjects
Analysis
Cancer
Chemotherapy
China
Development and progression
Drug resistance
Genes
Genetic aspects
Health aspects
Hepatitis C virus
Hepatoma
Mortality
Prognosis
RNA
RNA sequencing
China
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Summary:Background: Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. HCC transcriptome has been extensively studied; however, the pro-gress in disease mechanisms, prognosis, and treatment is still slow. Methods: A rank-based module-centric workfow was introduced to analyze important modules associated with HCC development, prognosis, and drug resistance. The currently largest HCC cell line RNA-Seq dataset from the LIMORE database was used to construct the reference modules by weighted gene co-expression network analysis. Results: Thirteen reference modules were identified with validated reproducibility. These modules were all associated with specific biological functions. Differentially expressed module analysis revealed the crucial modules during HCC development. Modules and hub genes are indicative of patient survival. Modules can differentiate patients in different HCC stages. Furthermore, drug resistance was revealed by drug-module association analysis. Based on differentially expressed modules and hub genes, six candidate drugs were screened. The hub genes of those modules merit further investigation. Conclusion: We proposed a reference module-based analysis of the HCC transcriptome. The identified modules are associated with HCC development, survival, and drug resistance. M3 and M6 may play important roles during HCV to HCC development. M1, M3, M5, and M7 are associated with HCC survival. High M4, high M9, low M1, and low M3 may be associated with dasatinib, doxorubicin, CD532, and simvastatin resistance. Our analysis provides useful information for HCC diagnosis and treatment. Keywords: HCV, IC50, microarray, module preservation, WGCNA
ISSN:1178-7074
1178-7074
DOI:10.2147/IJGM.S336729