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Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma

Ming-Huang Chen1, Wu-Lung R Yang, Kuan-Ting Lin

  • 1Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan.

Plos One
|November 17, 2011
PubMed

Insights

This study identified potential new treatments for hepatocellular carcinoma (HCC) by analyzing gene expression data and drug profiles. Several existing drugs showed promise in lab tests and animal models for treating liver cancer.

Area of Science:

  • Oncology
  • Pharmacology
  • Bioinformatics

Background:

  • Hepatocellular carcinoma (HCC) is a deadly cancer with limited treatment options.
  • There is a critical need for novel therapeutic agents to combat advanced HCC.
  • Existing treatments like sorafenib have shown efficacy, but drug resistance and prognosis remain significant challenges.

Purpose of the Study:

  • To discover and validate potential therapeutic drugs for hepatocellular carcinoma (HCC) using a drug-repurposing strategy.
  • To develop and implement an integrative bioinformatics platform (EHCO2) for analyzing HCC gene expression data.
  • To systematically screen drug-induced gene expression profiles against HCC signatures to identify candidate drugs.

Main Methods:

  • Developed the "Encyclopedia of Hepatocellular Carcinoma genes Online 2" (EHCO2) platform, compiling 4,020 HCC-related genes.
  • Queried the Connectivity Map (CMap) database of 6,100 drug profiles using advanced gene signature analysis methods.
  • Validated prioritized drug candidates through in vitro assays (MTT, clonogenic) in HCC cell lines and in vivo studies using orthotopic mouse models.

Main Results:

  • Identified 28 promising drug candidates from 50 prioritized compounds, including tanespimycin, trichostatin A, thioguanosine, and antipsychotic drugs with anti-tumor properties.
  • Validated the anti-cancer effects of chlorpromazine and trifluoperazine in HCC cell lines and demonstrated their ability to inhibit orthotopic liver tumor growth in mice.
  • Confirmed the efficacy of drug repurposing for HCC treatment through a combination of computational analysis and laboratory verification.

Conclusions:

  • Successfully identified and validated existing drugs as potential treatments for hepatocellular carcinoma (HCC).
  • The developed pipeline integrating EHCO2 and Connectivity Map analysis is effective for accelerating drug discovery and repurposing for HCC.
  • This approach offers a promising strategy to expedite the clinical application of new therapies for liver cancer.

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