Expression data from human hepatocellular carcinoma (HCC), Cirrhosis, and non-tumor liver tissues.
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE45050 | GEO | 2017/08/25
SECONDARY ACCESSION(S): PRJNA192897
REPOSITORIES: GEO
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Project description:Hepatocellular carcinoma (HCC) is the fifth most-common cancer worldwide causing nearly 600,000 deaths esch year. Approximately 80% of HCC develops on the background of cirrhosis.It is necessary to identify novel genes involved in HCC to implement new diagnostic and treatment options. However, the molecular pathogenesis of HCC largely remains unsolved. Only a few genetic alterations, namely those affecting p53, β-catenin and p16INK4a have been implicated at moderate frequencies of these cancers. Early detection of HCC with appropriate treatment can decrease tumor-related deaths We used microarrays to detail the global programme of gene expression profiles of cirrhosis and tumor liver samples. 15 cirrhosis and 15 HCC samples were collected with informed constent of each patient. Surgically resected tissues were snap frozen in liquid nitrogen and stored at -80C, and subjected to RNA extraction. Histology slides were prepared for all samples and scored by an experienced scientist. For the tumor samples, tissues were resected from inside the tumor, while tissues were resected from adjacent tissue sorrounding the tumor for non-tumor samples.
2013-05-23 | E-GEOD-17548 | biostudies-arrayexpress
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Project description:In this study, we utilized microRNA expression profiling to assess risk of HCC recurrence after liver resection. We examined microRNA expression profiling in paired tumor and non-tumor liver tissues of 73 HCC patients with mild cirrhosis (Child-Pugh A/B) who satisfy Milan Criteria. We constructed prediction models of recurrence-free survival using Cox proportional hazard model and principal component analysis.
2011-02-08 | E-GEOD-21362 | biostudies-arrayexpress
Project description:In this study, we used the Affymetrix HG-U133A 2.0 GeneChip for deriving a multigenic classifier capable of predicting HCV+cirrhosis with vs without concomitant HCC. We studied gene expression in cirrhotic tissues with (N=16) and without (N=47) HCC. Keywords: cross-sectional Liver tissue samples were obtained from patients waiting for liver transplantation. For each sample, RNA was extracted and hybridized to an Affymetrix GeneChip. This dataset is part of the TransQST collection.
2009-09-11 | E-GEOD-17967 | biostudies-arrayexpress
Project description:Hepatocellular carcinoma (HCC) is the fifth most-common cancer worldwide causing nearly 600,000 deaths esch year. Approximately 80% of HCC develops on the background of cirrhosis.It is necessary to identify novel genes involved in HCC to implement new diagnostic and treatment options. However, the molecular pathogenesis of HCC largely remains unsolved. Only a few genetic alterations, namely those affecting p53, β-catenin and p16INK4a have been implicated at moderate frequencies of these cancers. Early detection of HCC with appropriate treatment can decrease tumor-related deaths We used microarrays to detail the global programme of gene expression profiles of cirrhosis and tumor liver samples.
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Project description:Characterizing the metabolic changes pertaining to hepatocellular carcinoma (HCC) in patients with liver cirrhosis is believed to contribute towards early detection, treatment, and understanding of the molecular mechanisms of HCC. In this study, we compare metabolite levels in sera of 78 HCC cases with 184 cirrhotic controls by using ultra performance liquid chromatography coupled with a hybrid quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS). Following data preprocessing, the most relevant ions in distinguishing HCC cases from patients with cirrhosis are selected by parametric and non-parametric statistical methods. Putative metabolite identifications for these ions are obtained through mass-based database search. Verification of the identities of selected metabolites is conducted by comparing their MS/MS fragmentation patterns and retention time with those from authentic compounds. Quantitation of these metabolites is performed in a subset of the serum samples (10 HCC and 10 cirrhosis) using isotope dilution by selected reaction monitoring (SRM) on triple quadrupole linear ion trap (QqQLIT) and triple quadrupole (QqQ) mass spectrometers. The results of this analysis confirm that metabolites involved in sphingolipid metabolism and phospholipid catabolism such as sphingosine-1-phosphate (S-1-P) and lysophosphatidylcholine (lysoPC 17:0) are up-regulated in sera of HCC vs. those with liver cirrhosis. Down-regulated metabolites include those involved in bile acid biosynthesis (specifically cholesterol metabolism) such as glycochenodeoxycholic acid 3-sulfate (3-sulfo-GCDCA), glycocholic acid (GCA), glycodeoxycholic acid (GDCA), taurocholic acid (TCA), and taurochenodeoxycholate (TCDCA). These results provide useful insights into HCC biomarker discovery utilizing metabolomics as an efficient and cost-effective platform. Our work shows that metabolomic profiling is a promising tool to identify candidate metabolic biomarkers for early detection of HCC cases in high risk population of cirrhotic patients.
2013-06-30 | MTBLS17 | MetaboLights
Project description:The aim of this study is to compare post-hepatitis C virus (HCV) and post-alcoholism cirrhosis gene expression profiling. By transcriptome analysis with a cDNA array virtually covering every transcript in liver, we compared transcript levels in alcoholic- , HCV-cirrhosis and control liver. A stringent selection identified a list of 70 transcripts which completely separated the 3 groups of patients (7 HCV-cirrhosis, 7 alcoholic cirrhosis and 8 control livers). In contrast, in an hepatocellular carcinoma (HCC) context, comparison of 10 HCV-cirrhosis, 10 alcoholic cirrhosis and the 8 control livers failed to identify such transcripts. We report that dysregulations at the transcriptional level do exist in HCC-free cirrhosis, are transiently observed prior to detectable HCC. Keywords: etiology-dependent and HCC-dependent analysis
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Project description:Gene-expression profiles of hepatitis C-related, early-stage liver cirrhosis Background & Aims: Liver cirrhosis affects 1%M-bM-^HM-^R2% of population and is the major risk factor of hepatocellular carcinoma (HCC). Hepatitis C cirrhosis-related HCC is the most rapidly increasing cause of cancer death in the US. Non-invasive methods have been developed to identify patients with asymptomatic, early-stage cirrhosis, increasing the burden of HCC surveillance, but biomarkers are needed to identify patients with cirrhosis who are most in need of surveillance. We investigated whether a liver-derived 186-gene signature previously associated with outcomes of patients with HCC is prognostic for patients newly diagnosed with cirrhosis but without HCC. Methods: We performed gene expression profile analysis of formalin-fixed needle biopsies from the livers of 216 patients with hepatitis C-related early-stage (Child-Pugh class A) cirrhosis who were prospectively followed for a median of 10 years at an Italian center. We evaluated whether the 186-gene signature was associated with death, progression of cirrhosis, and development of HCC. Results: Fifty-five (25%), 101 (47%), and 60 (28%) patients were classified as having poor-, intermediate-, and good-prognosis signatures, respectively. In multivariable Cox regression modeling, the poor-prognosis signature was significantly associated with death (P=.004), progression to advanced cirrhosis (P<.001), and development of HCC (P=.009). The 10-year rates of survival were 63%, 74%, and 85% and the annual incidences of HCC were 5.8%, 2.2%, and 1.5% for patients with poor-, intermediate-, and good-prognosis signatures, respectively. Conclusions: A 186-gene signature used to predict outcomes of patients with HCC is also associated with outcomes of patients with hepatitis C-related early-stage cirrhosis. This signature might be used to identify patients with cirrhosis in most need of surveillance and strategies to prevent their development of HCC. 216 liver biopsy specimens
2013-01-22 | E-GEOD-15654 | biostudies-arrayexpress