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Functional and Topological Properties in Hepatocellular Carcinoma Transcriptome

Public Library of Science
Publication Date
DOI: 10.1371/journal.pone.0035510
  • Research Article
  • Biology
  • Computational Biology
  • Genomics
  • Genome Analysis Tools
  • Genetic Networks
  • Functional Genomics
  • Genome Expression Analysis
  • Microarrays
  • Systems Biology
  • Medicine
  • Gastroenterology And Hepatology
  • Gastrointestinal Cancers
  • Oncology
  • Basic Cancer Research
  • Metastasis
  • Tumor Physiology
  • Cancer Risk Factors
  • Genetic Causes Of Cancer
  • Cancers And Neoplasms
  • Gastrointestinal Tumors
  • Hepatocellular Carcinoma
  • Biology
  • Mathematics
  • Medicine


Hepatocellular carcinoma (HCC) is a leading cause of global cancer mortality. However, little is known about the precise molecular mechanisms involved in tumor formation and pathogenesis. The primary goal of this study was to elucidate genome-wide molecular networks involved in development of HCC with multiple etiologies by exploring high quality microarray data. We undertook a comparative network analysis across 264 human microarray profiles monitoring transcript changes in healthy liver, liver cirrhosis, and HCC with viral and alcoholic etiologies. Gene co-expression profiling was used to derive a consensus gene relevance network of HCC progression that consisted of 798 genes and 2,012 links. The HCC interactome was further confirmed to be phenotype-specific and non-random. Additionally, we confirmed that co-expressed genes are more likely to share biological function, but not sub-cellular localization. Analysis of individual HCC genes revealed that they are topologically central in a human protein-protein interaction network. We used quantitative RT-PCR in a cohort of normal liver tissue (n = 8), hepatitis C virus (HCV)-induced chronic liver disease (n = 9), and HCC (n = 7) to validate co-expressions of several well-connected genes, namely ASPM, CDKN3, NEK2, RACGAP1, and TOP2A. We show that HCC is a heterogeneous disorder, underpinned by complex cross talk between immune response, cell cycle, and mRNA translation pathways. Our work provides a systems-wide resource for deeper understanding of molecular mechanisms in HCC progression and may be used further to define novel targets for efficient treatment or diagnosis of this disease.

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