Dataset Information

Comprehensive characterization of cancer genes in hepatocellular carcinoma genomes.

ABSTRACT: The present study was performed to detect moderate or low-frequency mutated cancer driver genes in hepatocellular carcinoma (HCC), using OncodriveFM and Dendrix. Following this, integrated analyses were conducted on these novel cancer driver genes. A total of 112,980 somatic mutations were retrieved from TCGA and classified into 11 categories based on their function. Driver genes and pathways were predicted by OncodriveFM and Dendrix, followed by differential expression, DNA-methylation, copy number variations and survival analyses. Overall, non-synonymous mutations accounted for >60% (72,149/112, 980) of total variants, 108 and 3 driver genes were determined by OncodriveFM and Dendrix, respectively. Tumor protein p53, SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4, smad family member 3, RB transcriptional corepressor 1, catenin ? 1, smad family member 4, mitogen-activated protein kinase 1 and TSC complex subunit 2 are at the core of the driver gene interaction network. Two genes, transportin 1 (TNPO1) and chaperonin containing TCP1 subunit 3 (CCT3), were hypomethylated and overexpressed, and high expression of TNPO1 and CCT3 indicated a poor prognosis in patients with HCC. ?-carotene oxygenase 2 was hypermethylated, under-expressed and associated with favorable prognosis in HCC. The present study has identified a set of novel cancer genes and pathways, offering potential therapeutic targets and prognostic biomarkers for the treatment of HCC.

SUBMITTER: Zhang Z

PROVIDER: S-EPMC5777097 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Comprehensive characterization of cancer genes in hepatocellular carcinoma genomes.

Zhang Zhihao Z Xu Liping L Sun Changyu C

Oncology letters 20171205 2

The present study was performed to detect moderate or low-frequency mutated cancer driver genes in hepatocellular carcinoma (HCC), using OncodriveFM and Dendrix. Following this, integrated analyses were conducted on these novel cancer driver genes. A total of 112,980 somatic mutations were retrieved from TCGA and classified into 11 categories based on their function. Driver genes and pathways were predicted by OncodriveFM and Dendrix, followed by differential expression, DNA-methylation, copy nu ...[more]

PMID: 29434842

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Project description:BackgroundCurrently, the most predominant type of liver cancer is hepatocellular carcinoma (HCC), which is also the fourth leading cause of cancer-related death in the global population. Pyroptosis is an emerging form of cell death that affects the prognosis of cancer patients by modulating tumor cell migration, proliferation and invasion. However, the evaluation of pyroptosis in the prognosis of HCC is still insufficient.MethodsA total of 365 HCC patients from the TCGA-LIHC cohort were classified into two distinct subtypes using consensus clustering of pyroptosis-related genes (PRGs). Following univariate Cox analysis of differentially expressed genes between subtypes, we established a prognostic model (PRGs-score, PRGS) by LASSO Cox analysis. We further tested the predictive power of the prognostic model in the ICGC (LIRI-JP) and GEO (GSE14520) cohorts. The tumor microenvironment (TME) was studied using the CIBERSORT. The enrichment scores for immune cells and immune functions in low- and high-PRGS groups were assessed using ssGSEA. The IMvigor210 cohort was used to investigate the immunotherapy efficacy. Furthermore, we validated the expression of prognostic genes in PRGS by RT-qPCR in vitro.ResultsThe subtyping of HCC based on PRGs exhibited distinct clinical characteristics. We developed a prognostic model PRGS by differentially expressed genes between different subtypes. The results showed that PRGS could well forecast the survival of HCC patients in different cohorts and was associated with the immune microenvironment. Moreover, PRGS was considered to be an independent prognostic risk factor and superior to other pyroptosis-related signatures. Low-PRGS implied greater immune cell infiltration and better overall survival with immunotherapy. The results of RT-qPCR also showed that prognostic genes were significantly dysregulated in HCC.ConclusionsPRGS has promising application in forecasting the prognosis of HCC patients, and its relationship with the immune microenvironment provides a basis for the subsequent treatment and research of HCC.

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

Comprehensive characterization of cancer genes in hepatocellular carcinoma genomes.

Publications

Comprehensive characterization of cancer genes in hepatocellular carcinoma genomes.

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