Project description:Background & aimsLifestyle and environmental-related exposures are important risk factors for hepatocellular carcinoma (HCC), suggesting that epigenetic dysregulation significantly underpins HCC. We profiled 30 surgically resected tumours and the matched adjacent normal tissues to understand the aberrant epigenetic events associated with HCC.MethodsWe identified tumour differential enhancers and the associated genes by analysing H3K27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) and Hi-C/HiChIP data from the resected tumour samples of 30 patients with early-stage HCC. This epigenome dataset was analysed with previously reported genome and transcriptome data of the overlapping group of patients from the same cohort. We performed patient-specific differential expression testing using multiregion sequencing data to identify genes that undergo both enhancer and gene expression changes. Based on the genes selected, we identified two patient groups and performed a recurrence-free survival analysis.ResultsWe observed large-scale changes in the enhancer distribution between HCC tumours and the adjacent normal samples. Many of the gain-in-tumour enhancers showed corresponding upregulation of the associated genes and vice versa, but much of the enhancer and gene expression changes were patient-specific. A subset of the upregulated genes was activated in a subgroup of patients' tumours. Recurrence-free survival analysis revealed that the patients with a more robust upregulation of those genes showed a worse prognosis.ConclusionsWe report the genomic enhancer signature associated with differential prognosis in HCC. Findings that cohere with oncofoetal reprogramming in HCC were underpinned by genome-wide enhancer rewiring. Our results present the epigenetic changes in HCC that offer the rational selection of epigenetic-driven gene targets for therapeutic intervention or disease prognostication in HCC.Impact and implicationsLifestyle and environmental-related exposures are the important risk factors of hepatocellular carcinoma (HCC), suggesting that tumour-associated epigenetic dysregulations may significantly underpin HCC. We profiled tumour tissues and their matched normal from 30 patients with early-stage HCC to study the dysregulated epigenetic changes associated with HCC. By also analysing the patients' RNA-seq and clinical data, we found the signature genes - with epigenetic and transcriptomic dysregulation - associated with worse prognosis. Our findings suggest that systemic approaches are needed to consider the surrounding cellular environmental and epigenetic changes in HCC tumours.

Project description:Background - Hepatocellular carcinomas (HCCs) are heterogeneous tumors with respect to etiology, cell of origin and biology. The course of the disease is unpredictable and is in part dependent on the tumor microenvironment. One of the microenvironmental factors is hypoxia, which is known to promote aggressiveness in other malignant tumors. We hypothesized that certain regions in HCC exist with chronic hypoxia and a characteristic gene expression pattern. Moreover, during the development of HCC there is an important contribution of this chronic hypoxia on prognosis via this gene expression. Until now, most research has been performed in acute hypoxic models (< 24 hours). Methods – Human hepatoblastoma cells HepG2 were cultured in either normoxic (20% O2) or hypoxic (2% O2) conditions for 72 hrs, the time it takes to adapt to chronic hypoxia. After 3 days the cells were harvested and analyzed by microarray technology. The highly significant differentially expressed genes were selected and used to assess the clinical value of our in vitro chronic hypoxia gene signature in four published patient studies. Three of these independent microarray studies on HCC patients were used as training sets to determine a minimal prognostic gene set and one study was used for validation. Gene expression analysis and correlation with clinical outcome was assessed with the bioinfomatic method of Goeman et al (). Results – In the HepG2 cells, 3592 genes were differentially expressed in cells cultured at 2% oxygen for 72 hrs. Out of these, 265 showed a high significant change (2-fold change and p=0.0001). The level of gene expression after 72 hrs was different from the acute hypoxic response (during the first 24 hours) and represented chronicity. Using computational methods we identified 7 out of the 265 highly significant genes that showed correlation with prognosis in all three different training sets and this was independently validated in a 4th dataset. With our approach we could include the largest number of HCC patients in one single study. Conclusion – We identified a 7-gene signature, which is associated with chronic hypoxia and predicts prognosis in patients with HCC. In the future this signature could be used as a diagnostic tool. In addition, chronic hypoxia gene expression information can be used in the search for new therapeutic targets. Two conditions were compared and each sample has a biological replicate. Samples are hybridized in dye-swap, resulting in 4 hybridizations.

Project description:An integrative transcriptomics analysis was performed to evaluate the clinical relevance of genes associated with hepatocyte differentiation in human hepatocellular carcinoma (HCC). The well-established HepaRG cell line model was used to define a gene expression signature reflecting the status of tumor hepatocyte differentiation. This signature was able to stratify HCC patients into clinically relevant molecular subtypes. Then, a minimal subset of 7 differentiation-associated genes was identified to predict a poor prognosis in several cancer datasets. Hepatocellular carcinoma (HCC) is a deadly cancer worldwide as a result of a frequent late diagnosis which limits the therapeutic options. Tumor progression is correlated with a dedifferentiation of hepatocytes, the main parenchymal cells in the liver. Here, we hypothesized that the level of expression of genes reflecting the differentiation status of tumor hepatocytes could be clinically relevant in defining subsets of patients with variable clinical outcomes. To test this hypothesis, an integrative transcriptomic approach was used to stratify a cohort of 139 HCC patients based on a gene expression signature established using a well-controlled in vitro model of tumor hepatocyte differentiation in HepaRG cell line. First, we validated the HepaRG model by identifying a robust gene expression signature associated with hepatocyte differentiation and liver metabolism. This signature was able to distinguish specific developmental stages in mice. More importantly, the signature identified a subset of human HCC associated with a poor prognosis and cancer stem cell features. By using an independent HCC dataset (TCGA), a minimal subset of 7 differentiation-related genes was shown to predict a reduced overall survival, not only in patients with HCC but also in other types of cancers (e.g. kidney, pancreas, skin). In conclusion, the study demonstrates that genes reflecting the differentiation status of tumor hepatocytes are clinically relevant for predicting the prognosis of HCC patients.

Project description:Background - Hepatocellular carcinomas (HCCs) are heterogeneous tumors with respect to etiology, cell of origin and biology. The course of the disease is unpredictable and is in part dependent on the tumor microenvironment. One of the microenvironmental factors is hypoxia, which is known to promote aggressiveness in other malignant tumors. We hypothesized that certain regions in HCC exist with chronic hypoxia and a characteristic gene expression pattern. Moreover, during the development of HCC there is an important contribution of this chronic hypoxia on prognosis via this gene expression. Until now, most research has been performed in acute hypoxic models (< 24 hours). Methods – Human hepatoblastoma cells HepG2 were cultured in either normoxic (20% O2) or hypoxic (2% O2) conditions for 72 hrs, the time it takes to adapt to chronic hypoxia. After 3 days the cells were harvested and analyzed by microarray technology. The highly significant differentially expressed genes were selected and used to assess the clinical value of our in vitro chronic hypoxia gene signature in four published patient studies. Three of these independent microarray studies on HCC patients were used as training sets to determine a minimal prognostic gene set and one study was used for validation. Gene expression analysis and correlation with clinical outcome was assessed with the bioinfomatic method of Goeman et al (). Results – In the HepG2 cells, 3592 genes were differentially expressed in cells cultured at 2% oxygen for 72 hrs. Out of these, 265 showed a high significant change (2-fold change and p=0.0001). The level of gene expression after 72 hrs was different from the acute hypoxic response (during the first 24 hours) and represented chronicity. Using computational methods we identified 7 out of the 265 highly significant genes that showed correlation with prognosis in all three different training sets and this was independently validated in a 4th dataset. With our approach we could include the largest number of HCC patients in one single study. Conclusion – We identified a 7-gene signature, which is associated with chronic hypoxia and predicts prognosis in patients with HCC. In the future this signature could be used as a diagnostic tool. In addition, chronic hypoxia gene expression information can be used in the search for new therapeutic targets.

Project description:During embryogenesis, Hepatocyte Growth Factor (HGF) elicits a distinctive morphogenetic program, the invasive growth, by the activation of MET, whose aberrant activation in cancer drives metastatic progression. Aim of this work is to define and characterize the transcriptional signature of invasive growth, and to verify its activation in human cancers. Global expression profiling was carried out on mouse liver stem/progenitor cells (MLP-29) stimulated for different times, one, six and twenty-four hours, in vitro with HGF to define the invasive growth signature. Meta-analysis of human cancer microarray data was carried out to dissect the transcriptional modules of the invasive growth that are aberrantly activated during carcinogenesis of hepatocellular carcinoma. Differential expression analysis identified 2643 regulated genes by HGF, the invasive growth signature, subdivided in 11 gene expression clusters revealing waves of time coded transcriptional regulation. Those waves have been in-silico associated with the regulative role of the transcriptional unit of Rela/Nfkbia and Fos/Jun and biological features recapitulating the physiological invasive growth phenotype observed in cell line, such as cell motility and scattering, cellular proliferation and protection from apoptosis, cytoskeletal rearangement. Genomic meta-analysis on hepatocellular carcinoma identified of a core genes set (323 gene symbols), consistently regulated between MLP-29 and human tumors and significantly associated with cancer aggressiveness and metastasis p.val < 1*10-6, HR=5.404 CI= 2.570-11.365. The invasive growth signature recapitulates the physiopatological program driven by the stimulation of HGF in normal embryonic liver cells and its activity is observed in HCC as well as in several other tumors. This signature is associated with neoplastic progression and reliably predicts human HCC disease outcome, suggesting the involvement of the invasive growth and cancer in cancer progression. These results prompt the future application of anti-met target therapies in HCC and the application of the signature for both prognostic and predictive purposes.

			Action	DRS
	SRR21354700_1.fastq.gz	Fastqsanger.gz
	SRR21354700_2.fastq.gz	Fastqsanger.gz
	SRR21354701_1.fastq.gz	Fastqsanger.gz
	SRR21354701_2.fastq.gz	Fastqsanger.gz
	SRR21354702_1.fastq.gz	Fastqsanger.gz

Dataset Information

A genomic enhancer signature associates with Hepatocellular Carcinoma prognosis

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets