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Identifying Hepatocellular Carcinoma Driver Genes by Integrative Pathway Crosstalk and Protein Interaction Network.

ABSTRACT: In this study, we mined out hepatocellular carcinoma (HCC) driver genes from MEDLINE literatures by bioinformatics methods of pathway crosstalk and protein interaction network. Furthermore, the relationship between driver genes and their clinicopathological characteristics, as well as classification effectiveness was verified in the public databases. We identified 560 human genes reported to be associated with HCC in 1074 published articles. Functional analysis revealed that biological processes and biochemical pathways relating to tumor pathogenesis, cancer disease, tumor cell molecule, and hepatic disease were enriched in these genes. Pathway crosstalk analysis indicated that significant pathways could be divided into three modules: cancer disease, virus infection, and tumor signaling pathway. The HCC-related protein-protein interaction network comprised 10,212 nodes, and 56,400 edges were mined out to identify 18 modules corresponding to 14 driver genes. We verified that these 14 driver genes have high classification effectiveness to distinguish cancer samples from normal samples and the classification effectiveness was better than that of randomly selected genes. Present study provided pathway crosstalk and protein interaction network for understanding potential tumorigenesis genes underlying HCC. The 14 driver genes identified from this study are of great translational value in HCC diagnosis and treatment, as well as in clinical study on the pathogenesis of HCC.

SUBMITTER: Chen W

PROVIDER: S-EPMC6791483 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Identifying Hepatocellular Carcinoma Driver Genes by Integrative Pathway Crosstalk and Protein Interaction Network.

Chen Wenbiao W Jiang Jingjing J Wang Peizhong Peter PP Gong Lan L Chen Jianing J Du Weibo W Bi Kefan K Diao Hongyan H

DNA and cell biology 20190829 10

In this study, we mined out hepatocellular carcinoma (HCC) driver genes from MEDLINE literatures by bioinformatics methods of pathway crosstalk and protein interaction network. Furthermore, the relationship between driver genes and their clinicopathological characteristics, as well as classification effectiveness was verified in the public databases. We identified 560 human genes reported to be associated with HCC in 1074 published articles. Functional analysis revealed that biological processes ...[more]

PMID: 31464520

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Project description:Background and aimsTumor microenvironment plays an essential role in cancer development and progression. Cancer immunotherapy has become a promising approach for the treatment of hepatocellular carcinoma (HCC). We aimed to analyze the HCC immune microenvironment characteristics to identify immune-related genetic changes.MethodsKey immune-relevant genes (KIRGs) were obtained through integrating the differentially expressed genes of The Cancer Genome Atlas, immune genes from the Immunology Database and Analysis Portal, and immune differentially expressed genes determined by single-sample gene set enrichment analysis scores. Cox regression analysis was performed to mine therapeutic target genes. A regulatory network based on KIRGs, transcription factors, and immune-related long non-coding RNAs (IRLncRNAs) was also generated. The outcomes of risk score model were validated in a testing cohort and in clinical samples using tissue immunohistochemistry staining. Correlation analysis between risk score and immune checkpoint genes and immune cell infiltration were investigated.ResultsIn total, we identified 21 KIRGs, including programmed cell death-1 (PD-1) and cytotoxic T-lymphocyte associated protein 4 (CTLA4), and found IKBKE, IL2RG, EDNRA, and IGHA1 may be equally important to PD-1 or CTLA4. Meanwhile, KIRGs, various transcription factors, and IRLncRNAs were integrated to reveal that the NRF1-AC127024.5-IKBKE axis might be involved in tumor immunity regulation. Furthermore, the immune-related risk score model was established according to KIRGs and key IRLncRNAs, and verified more obvious discriminating power in the testing cohort. Correlation analysis indicated TNFSF4 , LGALS9 , KIAA1429 , IDO2, and CD276 were closely related to the risk score, and CD4 T cells, macrophages, and neutrophils were the primary immune infiltration cell types.ConclusionsOur results highlight the importance of immune genes in the HCC microenvironment and further unravel the underlying molecular mechanisms in the development of HCC.

Dataset Information

Identifying Hepatocellular Carcinoma Driver Genes by Integrative Pathway Crosstalk and Protein Interaction Network.

Publications

Identifying Hepatocellular Carcinoma Driver Genes by Integrative Pathway Crosstalk and Protein Interaction Network.

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