Gene Expression Profiling of Hepatocellular Carcinoma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE5975 | GEO | 2007/10/25
SECONDARY ACCESSION(S): PRJNA97451
REPOSITORIES: GEO
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2009-01-06 | E-GEOD-4108 | biostudies-arrayexpress
Project description:Hepatocellular carcinoma (HCC) remains a major health problem worldwide, and HCC patients have a poor prognostic outcome. In this study, we systematically disclose mechanisms of hepatocarcinogenesis, and also effectively identify and validate novel anticancer targets in HCCs. Keywords: disease state analysis
2009-01-06 | GSE4108 | GEO
Project description:Genomic analysis of human hepatocellular carcinoma (HCC) is potentially confounded by the differentiation state of the hepatic cell-of-origin. Here we integrated genomic analysis of mouse HCC (with defined cell-of-origin) along with normal liver development. We found a major shift in expression of Wnt and RXR-α pathway genes (up and down, respectively) coincident with the transition from hepatoblasts to hepatocytes. A combined Wnt and RXR-α gene signature categorized HCCs into two subtypes (high Wnt, low RXR-α and low Wnt, high RXR-α), which matched cell-of-origin in mouse models and the differentiation state of human HCC. Suppression of RXR-α levels in hepatocytes increased Wnt signaling and enhanced tumorigenicity, whereas ligand activation of RXR-α achieved the opposite. These results corroborate that there are two main HCC subtypes that correspond to the degree of hepatocyte differentation and that RXR-α, in part via Wnt signaling, plays a key functional role in the hepatocyte-like subtype and potentially could serve as a selective therapeutic target.
2015-01-17 | GSE65063 | GEO
Project description:Hepatocellular carcinoma (HCC) is a common malignancy with high mortality due to a lack of effective therapies. HCC represents a collection of highly heterogeneous tumor types but a general molecular classification of HCC is lacking. Here, we define three molecular subtypes of HCC that are observed across various independent patient cohorts and profiling platforms. Analysis of the expression signatures indicates that a limited number of pathways and processes drive the clustering of these subtypes. Notably, TGF-beta signaling is a critical factor that distinguishes two subtypes of high-grade tumors, and is associated with early tumor recurrence. Furthermore, both bioinformatics and functional analyses reveal molecular crosstalk between TGF-beta and WNT signaling pathways. These findings suggest that TGF-beta plays a critical role in a subclass of HCC tumors and may enhance WNT pathway activation in the absence of activating mutations in canonical pathway components. This study is an example of how robust molecular subclassification can be used to interrogate molecular abnormalities in the context of human cancer. Experiment Overall Design: Four hepatocellular carcinoma (HCC) cell line samples treated or untreated by TGF-beta
2009-09-17 | E-GEOD-10393 | biostudies-arrayexpress
Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses. Center and peripheral portions of hepatocellular carcinoma tumors as well as surrounding non-tumor cirrhotic liver tissues were obtained from fresh frozen surgically resected tissues, and isolated total RNA samples were analyzed for genome-wide expression profiles.
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Project description:Epigenetic deregulation is a critical event in human malignancies. A number of DNA methylation markers are currently under evaluation as diagnostic and prognostic biomarkers for many cancers. However, its potential role in hepatocellular carcinoma (HCC) is under-explored. Aims: To develop a DNA methylation-based prognostic signature in surgically resected HCC
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Project description:Expression of miR-4730 in hepatocellular carcinoma suppresses tumor progression, and might be a prognostic marker or a therapeutic target of miRNA-based therapies.
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Project description:Genomic analysis of human hepatocellular carcinoma (HCC) is potentially confounded by the differentiation state of the hepatic cell-of-origin. Here we integrated genomic analysis of mouse HCC (with defined cell-of-origin) along with normal liver development. We found a major shift in expression of Wnt and RXR-α pathway genes (up and down, respectively) coincident with the transition from hepatoblasts to hepatocytes. A combined Wnt and RXR-α gene signature categorized HCCs into two subtypes (high Wnt, low RXR-α and low Wnt, high RXR-α), which matched cell-of-origin in mouse models and the differentiation state of human HCC. Suppression of RXR-α levels in hepatocytes increased Wnt signaling and enhanced tumorigenicity, whereas ligand activation of RXR-α achieved the opposite. These results corroborate that there are two main HCC subtypes that correspond to the degree of hepatocyte differentation and that RXR-α, in part via Wnt signaling, plays a key functional role in the hepatocyte-like subtype and potentially could serve as a selective therapeutic target. Total RNA from whole livers taken at different developmental timepoints (embryonic day 14, embryonic day 18, post-natal day 5 and post-natal day 56) along with hepatoblasts isolated from E14 livers and immature hepatocytes isolated from E18 livers was extracted and purified using the Qiagen RNeasy Mini Kit. RNA purity and integrity were assayed by the Bioanalyser 2100 (Agilent Technologies). For each sample, 2 µg of total RNA was reverse transcribed and amplified by using an RNA amplification kit from Ambion. Fifteen micrograms of amplified RNA were labeled by direct chemical coupling to the Cy5 NHS ester (Amersham Biosciences). Normal adult mouse liver (Agilent) was used as control and Cy3 labeled. Labeled RNAs were purified, fragmented, and used as probes to hybridize microarrays. Gene expression profiling was done with the 4x44k mouse Agilent platform. Expression profiling of the 23 human HCC samples was previously described
2015-01-17 | E-GEOD-65063 | biostudies-arrayexpress