International Journal of General Medicine (Dec 2021)
Gene Network Analysis of Hepatocellular Carcinoma Identifies Modules Associated with Disease Progression, Survival, and Chemo Drug Resistance
Abstract
Hua Ye,1 Mengxia Sun,2 Shiliang Huang,1 Feng Xu,1 Jian Wang,3 Huiwei Liu,1 Liangshun Zhang,1 Wenjing Luo,1 Wenying Guo,1 Zhe Wu,1 Jie Zhu,4 Hong Li4 1Department of Gastroenterology, Ningbo Medical Treatment Center Lihuili Hospital, Medical School of Ningbo University, Ningbo, Zhejiang, 315040, People’s Republic of China; 2Department of Clinical Medicine, Medical School of Ningbo University, Ningbo, Zhejiang, 315211, People’s Republic of China; 3Department of Dermatology, Ningbo Medical Treatment Center Lihuili Hospital, Medical School of Ningbo University, Ningbo, Zhejiang, 315040, People’s Republic of China; 4Department of Hepatobiliary Surgery, Ningbo Medical Treatment Center Lihuili Hospital, Medical School of Ningbo University, Ningbo, Zhejiang, 315040, People’s Republic of ChinaCorrespondence: Hua YeDepartment of Gastroenterology, Ningbo Medical Treatment Center Lihuili Hospital, Medical School of Ningbo University, Ningbo, Zhejiang, 315040, People’s Republic of ChinaTel/Fax +86 57483023687Email [email protected] LiDepartment of Hepatobiliary Surgery, Ningbo Medical Treatment Center Lihuili Hospital, Medical School of Ningbo University, Ningbo, Zhejiang, 315040, People’s Republic of ChinaEmail [email protected]: Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. HCC transcriptome has been extensively studied; however, the progress in disease mechanisms, prognosis, and treatment is still slow.Methods: A rank-based module-centric workflow 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