Transcriptomic changes in human liver cancer cell lines caused by the demethylating drug zebularine.
An integrated genomic and epigenomic approach predicts therapeutic response to zebularine in human liver cancer.
Cell line
View SamplesAlthough epigenetic mechanisms, such as specific histone modifications, control common and cell-specific genetic programs, a role for histone modifying enzymes in liver metabolism and disease has not been investigated. This report demonstrates that the combined loss of the histone methyltransferases EZH1 and EZH2 in mouse hepatocytes led to the disruption of H3K27me3 homeostasis by age three months, simple fatty liver by age six months and fatal fibrosis by age 15 months. Global and gene-specific reduction of H3K27me3 marks paralleled a concomitant increase of H3K4me3 marks at genes associated with chronic liver disease. Advanced disease was accompanied by widespread infiltration of immune cells, an increase of activated hepatic stellate cells and collagen deposition. Expression of genes from the cytochrome P450 family that control drug metabolism was already deregulated by age two months and mice were fatally hypersensitive to carbon tetrachloride (CCl4). These genetic experiments, for the first time, illustrate that the simple loss of EZH1/EZH2, which results in the disruption of epigenetic modifications, is sufficient for the progression of fatal liver disease. Overall design: RNA-seq and ChIP-seq were performed in liver tissues.
The methyltransferases enhancer of zeste homolog (EZH) 1 and EZH2 control hepatocyte homeostasis and regeneration.
No sample metadata fields
View SamplesWe used Affymetrix microarray profiling to analyze gene expression patterns in healthy donor liver as well as tumor and paired non-tumor tissue of HCC patients.
A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients.
Specimen part, Disease, Disease stage, Subject
View SamplesMany cancer cells require more glycolytic adenosine triphosphate production due to a mitochondrial respiratory defect. However, the roles of mitochondrial defects in cancer development and progression remain unclear. To address the role of transcriptomic regulation by mitochondrial defects in liver cancer cells, we performed gene expression profiling for three different cell models of mitochondrial defects: cells with chemical respiratory inhibition (rotenone, thenoyltrifluoroacetone, antimycin A, and oligomycin), cells with mitochondrial DNA depletion (Rho0), and liver cancer cells harboring mitochondrial defects (SNU354 and SNU423). By comparing gene expression in the three models, we identified 10 common mitochondrial defectrelated genes that may be responsible for retrograde signaling from cancer cell mitochondria to the intracellular transcriptome. The concomitant expression of the 10 common mitochondrial defect genes is significantly associated with poor prognostic outcomes in liver cancers, suggesting their functional and clinical relevance. Among the common mitochondrial defect genes, we found that nuclear protein 1 (NUPR1) is one of the key transcription regulators. Knockdown of NUPR1 suppressed liver cancer cell invasion, which was mediated in a Ca2+ signalingdependent manner. In addition, by performing an NUPR1-centric network analysis and promoter binding assay, granulin was identified as a key downstream effector of NUPR1. We also report association of the NUPR1granulin pathway with mitochondrial defectderived glycolytic activation in human liver cancer. Conclusion: Mitochondrial respiratory defects and subsequent retrograde signaling, particularly the NUPR1granulin pathway, play pivotal roles in liver cancer progression.
Identification of a mitochondrial defect gene signature reveals NUPR1 as a key regulator of liver cancer progression.
Specimen part
View SamplesWe performed gene expression profiling of hepatocellular carcinoma (HCC), cholangiocarcinoma (CC), and mixed type of combined HCC and CC (CHC). In comparison of the profiles, a novel class of HCC expressing CC-like traits was identified.
Identification of a cholangiocarcinoma-like gene expression trait in hepatocellular carcinoma.
Specimen part
View SamplesDetermine the effect and specificity of HDAC2 siRNA compared to SAHA inhibition of HDAC2 in hepatocellular carcinoma (HCC)
Antitumor effects in hepatocarcinoma of isoform-selective inhibition of HDAC2.
Cell line, Treatment
View SamplesGene expression data from 100 human hepatocellular carcinomas (HCC) were generated and analyzed as part of effort for validating prognostic gene expression signatures from previous studies. Using four different classification algorithms and leave-one-out cross-validation approaches, four different prognostic signatures were applied to test the robustness and concordance of predicted outcome in individual patients. All four tumor-derived signatures were significantly associated with prognosis and had a high rate of concordance with predicted outcomes for individual patients.
Sixty-five gene-based risk score classifier predicts overall survival in hepatocellular carcinoma.
No sample metadata fields
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Transcriptomic profiling reveals hepatic stem-like gene signatures and interplay of miR-200c and epithelial-mesenchymal transition in intrahepatic cholangiocarcinoma.
Specimen part, Disease, Disease stage
View SamplesWe compared transcriptomic profiles of 23 ICC tumor specimens to hepatocellular carcinoma (HCC) specimens using Affymetrix mRNA array and the miRNA array platforms to search for unique gene signatures linked to patient prognosis.
Transcriptomic profiling reveals hepatic stem-like gene signatures and interplay of miR-200c and epithelial-mesenchymal transition in intrahepatic cholangiocarcinoma.
Specimen part, Disease, Disease stage
View SamplesWhile we and others have uncovered and validated several genomic predictors for metastatic recurrences, a molecular or genomic predictor that can reliably identify high-risk patients for late de novo recurrence has not been firmly established. We analyzed previously reported gene expression data from human livers that underwent partial hepatectomy or transplantation, which were representative physiological conditions that trigger liver regeneration signals. We generated gene expression data from tumor and matched non-tumor surrounding tissues of 72 hepatocellular carcinoma (HCC) patients who underwent surgical resection as the primary treatment. We used these gene expression data to develop a new prognostification model for recurrence of HCC after surgery.
Genomic predictors for recurrence patterns of hepatocellular carcinoma: model derivation and validation.
Sex, Age, Specimen part, Disease, Disease stage
View Samples