The dataset contained 99 human hepatocellular carcinomas was uploaded in KCGP database. This dataset was incoporated in the database for cross-comparative analysis with Korean liver cancer patients.

Dataset ID: DS_LIVER_004

Title: Human Hepatocellular Carcinoma study


Global gene expression patterns of 91 human hepatocellular carcinomas (HCC) were analyzed to define the molecular characteristics of the tumors and to test the prognostic value of the expression profiles. Total RNAs were isolated from frozen liver tissue using CsCl density gradient centrifugation methods. Total RNA from 18 normal livers were pooled and used as reference in entire microarray experiments. To obtain gene expression profile data from human HCC, 20 ¥ìg of total RNAs from tissues were used to drive fluorescently (Cy-5 or Cy-3) labeled cDNA. At least two hybridizations were carried out for each tissue using dye-swap strategy to eliminate dye labeling bias. Unsupervised classification methods revealed two distinctive subclasses of HCC that are highly associated with survival of the patients. This association was validated by five independent supervised learning methods. Genes most strongly associated with survival were identified by using the Cox proportional hazards survival analysis. This approach identified a limited number of genes that accurately predicted the length of survival and provides new molecular insight into the pathogenesis of HCC. Tumors from the low survival subclass have strong cell proliferation and anti-apoptosis gene expression signatures. In addition, the low survival subclass displayed higher expression of genes involved in ubiquitination and histone modification suggesting an etiological involvement of these processes in accelerating the progression of HCC. The biological differences identified in the HCC subclasses should provide an attractive source for the development of therapeutic targets (e.g. HIF1a) for selective treatment(s) of HCC patients. This dataset was incorporated for cross comparison between Korean (DS_LIVER_001 and DS_LIVER_002) and non-Korean HCC patients (GEO accession number: GSE1898)

Experiements type: expression profiling by array

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