Genes regulating the sensitivity of solid tumor cell lines to cytotoxic agents: a literature review

Ikuo Sekine1, John D Minna, Kazuto Nishio

  • 1Division of Internal Medicine and Thoracic Oncology, National Cancer Center Hospital, Tokyo, Japan. isekine@ncc.go.jp

Insights

Researchers identified 80 genes associated with in vitro drug resistance and sensitivity in cancer cell lines. These genes are candidates for developing predictive chemosensitivity tests to guide cancer treatment.

Area of Science:

  • Genomics
  • Cancer Biology
  • Pharmacology

Background:

  • Predictive chemosensitivity testing aims to identify optimal cancer drug treatments.
  • Understanding gene alterations linked to drug response is crucial for personalized medicine.

Purpose of the Study:

  • To identify candidate genes associated with in vitro chemosensitivity for predictive testing.
  • To systematically review literature on gene alterations and cancer cell line drug responses.

Main Methods:

  • Defined 'in vitro chemosensitivity associated genes' based on drug resistance, induced resistance via transfection, or increased sensitivity via down-regulation.
  • Conducted Medline searches using gene names to find studies on gene alterations and cancer cell line chemosensitivity.
  • Categorized identified genes based on encoded protein function.

Main Results:

  • Identified 80 candidate genes associated with in vitro chemosensitivity.
  • Genes were categorized into functional groups including transporters, drug targets, DNA repair, and apoptosis regulators.
  • Strong evidence (≥2 studies) linked major vault protein, thymidylate synthetase, glutathione S-transferase pi, metallothionein, tumor suppressor p53, and bcl-2 to chemosensitivity.

Conclusions:

  • The 80 identified genes represent potential candidates for clinical predictive chemosensitivity testing.
  • Further validation is needed to translate these findings into clinical applications.
  • This review provides a foundation for developing gene-based biomarkers for cancer therapy selection.

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