Dataset Information

Epigenetic basis of hepatocellular carcinoma: A network-based integrative meta-analysis.

ABSTRACT: AIM:To identify the key epigenetically modulated genes and pathways in HCC by performing an integrative meta-analysis of all major, well-annotated and publicly available methylation datasets using tools of network analysis. METHODS:PubMed and Gene Expression Omnibus were searched for genome-wide DNA methylation datasets. Patient clinical and demographic characteristics were obtained. DNA methylation data were integrated using the Ingenuity Pathway Analysis, a software package for visualizing and analyzing biological networks. Pathway enrichment analysis was performed using IPA, which also provides literature-driven and computationally-predicted annotations for significant association of genes to curated molecular pathways. RESULTS:From an initial 928 potential abstracts, we identified and analyzed 11 eligible high-throughput methylation datasets representing 354 patients. A significant proportion of studies did not provide concomitant clinical data. In the promoter region, HIST1H2AJ and SPDYA were the most commonly methylated, whereas HRNBP3 gene was the most commonly hypomethylated. ESR1 and ERK were central genes in the principal networks. The pathways most associated with the frequently methylated genes were G-protein coupled receptor and cAMP-mediated signalling. CONCLUSION:Using an integrative network-based analysis approach of genome-wide DNA methylation data of both the promoter and body of genes, we identified G-protein coupled receptor signalling as the most highly associated with HCC. This encompasses a diverse range of cancer pathways, such as the PI3K/Akt/mTOR and Ras/Raf/MAPK pathways, and is therefore supportive of previous literature on gene expression in HCC. However, there are novel targetable genes such as HIST1H2AJ that are epigenetically modified, suggesting their potential as biomarkers and for therapeutic targeting of the HCC epigenome.

SUBMITTER: Bhat V

PROVIDER: S-EPMC5787679 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Epigenetic basis of hepatocellular carcinoma: A network-based integrative meta-analysis.

Bhat Venkat V Srinathan Sujitha S Pasini Elisa E Angeli Marc M Chen Emily E Baciu Cristina C Bhat Mamatha M

World journal of hepatology 20180101 1

<h4>Aim</h4>To identify the key epigenetically modulated genes and pathways in HCC by performing an integrative meta-analysis of all major, well-annotated and publicly available methylation datasets using tools of network analysis.<h4>Methods</h4>PubMed and Gene Expression Omnibus were searched for genome-wide DNA methylation datasets. Patient clinical and demographic characteristics were obtained. DNA methylation data were integrated using the Ingenuity Pathway Analysis, a software package for ...[more]

PMID: 29399289

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Project description:Background:Elucidation of epigenetic alterations in bladder cancer will lead to further understanding of the biology of the disease and hopefully improved therapies. Our aim was to perform an integrative epigenetic analysis of invasive urothelial carcinoma of the bladder to identify the epigenetic abnormalities involved in the development and progression of this cancer. Methods:Pre-processed methylation data and RNA-seq data were downloaded from The Cancer Genome Atlas (TCGA) and processed using the R package TCGA-Assembler. An R package MethylMix was used to perform an analysis incorporating both methylation and gene expression data on all samples, as well as a subset analysis comparing patients surviving less than 2 years and patients surviving more than 2 years. Genes associated with poor prognosis were individually queried. Pathway analysis was performed on statistically significant genes identified by MethylMix criteria using ConsensusPathDB. Validation was performed using flow cytometry on bladder cancer cell lines. Results:A total of 408 patients met all inclusion criteria. There were a total of 240 genes differentially methylated by MethylMix criteria. Review of individual genes specific to poor-prognosis patients revealed the majority to be candidate tumor suppressors in other cancer types. Pathway analysis showed increase in methylation of genes involved in antioxidant pathways including glutathione and NRF2. Genes involved in estrogen metabolism were also hypermethylated while genes involved in the EGFR pathway were found to be hypomethylated. EGFR expression was confirmed to be elevated in six bladder cancer cell lines. Conclusions:In patients with invasive urothelial carcinoma, we found differential methylation in patients with better and worse prognosis after cystectomy. Differentially methylated genes are involved in many relevant oncologic pathways, including EGFR and antioxidant pathways, that may be a target for therapy or chemoprevention.

Project description:BACKGROUND:Hepatocellular carcinoma (HCC) is the major type of primary liver cancer. Intrahepatic metastasis, such as portal vein tumor thrombosis (PVTT), strongly indicates poor prognosis of HCC. But now, there are limited understandings of the molecular features and mechanisms of those metastatic HCCs. METHODS:To characterize the molecular alterations of the metastatic HCCs, we implemented an integrative analysis of the copy number variations (CNVs), DNA methylations and transcriptomes of matched adjacent normal, primary tumor and PVTT samples from 19 HCC patients. RESULTS:CNV analysis identified a frequently amplified focal region chr11q13.3 and a novel deletion peak chr19q13.41 containing three miRNAs. The integrative analysis with RNA-seq data suggests that CNVs and differential promoter methylations regulate distinct oncogenic processes. Then, we used individualized differential analysis to identify the differentially expressed genes between matched primary tumor and PVTT of each patient. Results show that 5 out of 19 studied patients acquire evidential progressive alterations of gene expressions (more than 1000 differentially expressed genes were identified in each patient). While, another subset of eight patients have nearly identical gene expressions between the corresponding matched primary tumor and PVTT. Twenty genes were found to be recurrently and progressively differentially expressed in multiple patients. These genes are mainly associated with focal adhesion, xenobiotics metabolism by cytochrome P450 and amino acid metabolism. For several differentially expressed genes in metabolic pathways, their expressions are significantly associated with overall survivals and vascular invasions of HCC patients. The following transwell assay experiments validate that they can regulate invasive phenotypes of HCC cells. CONCLUSIONS:The metastatic HCCs with PVTTs have significant molecular alterations comparing with adjacent normal tissues. The recurrent alteration patterns are similar to several previously published general HCC cohorts, but usually with higher severity. By an individualized differential analysis strategy, the progressively differentially expressed genes between the primary tumor and PVTT were identified for each patient. A few patients aquire evidential progressive alterations of gene expressions. And, experiments show that several recurrently differentially expressed genes can strongly regulate HCC cell invasions.

Project description:There is an urgent need to develop more effective therapies for hepatocellular carcinoma (HCC) because of its aggressiveness. Guadecitabine (SGI-110) is a second-generation DNA methyltransferase inhibitor (DNMTi), which is currently in clinical trials for HCC and shows greater stability and performance over first-generation DNMTis. In order to identify potential therapeutic targets of SGI-110 for clinical trials, HCC cell lines (SNU398, HepG2, and SNU475) were used to evaluate the effects of transient SGI-110 treatment by an integrative analysis of DNA methylation, nucleosome accessibility, gene expression profiles, and its clinical relevance by comparison to The Cancer Genome Atlas (TCGA) HCC clinical data. Each HCC cell line represents a different DNA methylation subtype of primary HCC tumors based on TCGA data. After SGI-110 treatment, all cell lines were sensitive to SGI-110 with prolonged antiproliferation effects. Expression of up-regulated genes, including tumor suppressors, was positively correlated with nucleosome accessibility and negatively correlated with gene promoter DNA methylation. Alternatively, expression of down-regulated genes, such as oncogenes, was negatively correlated with nucleosome accessibility and positively correlated with gene body DNA methylation. SGI-110 can also act as a dual inhibitor to down-regulate polycomb repressive complex 2 (PRC2) genes by demethylating their gene bodies, resulting in reactivation of PRC2 repressed genes without involvement of DNA methylation. Furthermore, it can up-regulate endogenous retroviruses to reactivate immune pathways. Finally, about 48% of frequently altered genes in primary HCC tumors can be reversed by SGI-110 treatment. CONCLUSION:Our integrative analysis has successfully linked the antitumor effects of SGI-110 to detailed epigenetic alterations in HCC cells, identified potential therapeutic targets, and provided a rationale for combination treatments of SGI-110 with immune checkpoint therapies.

Project description:Background:Hepatocellular carcinoma (HCC) is an aggressive cancer with a poor prognosis and a high incidence. The molecular changes and novel biomarkers of HCC need to be identified to improve the diagnosis and prognosis of this disease. We investigated the current research concentrations of HCC and identified the transcriptomics-related biomarkers of HCC from The Cancer Genome Atlas (TGCA) database. Methods:We investigated the current research concentrations of HCC using literature metrology analysis for studies conducted from 2008 to 2018. We identified long noncoding RNAs (lncRNAs) that correlated with the clinical features and survival prognoses of HCC from The Cancer Genome Atlas (TGCA) database. Differentially expressed genes (lncRNAs, miRNAs, and mRNAs) were also identified by TCGA datasets in HCC tumor tissues. A lncRNA competitive endogenous RNA (ceRNA) network was constructed from lncRNAs based on intersected lncRNAs. Survival times and the association between the expression levels of the key lncRNAs of the ceRNA network and the clinicopathological characteristics of HCC patients were analyzed using TCGA. Real-time polymerase chain reaction (qRT-PCR) was used to validate the reliability of the results in tissue samples from 20 newly-diagnosed HCC patients. Results:Analysis of the literature pertaining to HCC research revealed that current research is focused on lncRNA functions in tumorigenesis and tumor development. A total of 128 HCC dysregulated lncRNAs were identified; 66 were included in the co-expressed ceRNA network. We analyzed survival times and the associations between the expression of 66 key lncRNAs and the clinicopathological features of the HCC patients identified from TCGA. Twenty-six lncRNAs were associated with clinical features of HCC (P < 0.05) and six key lncRNAs were associated with survival time (log-rank test P < 0.05). Six key lncRNAs were selected for the validation of their expression levels in 20 patients with newly diagnosed HCC using qRT-PCR. Consistent fold changes in the trends of up and down regulation between qRT-PCR validation and TCGA proved the reliability of our bioinformatics analysis. Conclusions:We used integrative bioinformatics analysis of the TCGA datasets to improve our understanding of the regulatory mechanisms involved with the functional features of lncRNAs in HCC. The results revealed that lncRNAs are potential diagnostic and prognostic biomarkers of HCC.

Dataset Information

Epigenetic basis of hepatocellular carcinoma: A network-based integrative meta-analysis.

Publications

Epigenetic basis of hepatocellular carcinoma: A network-based integrative meta-analysis.

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