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Pharmacogenetic biomarkers for the prediction of response to antiangiogenic treatment

Bryan P Schneider1, Fei Shen, Kathy D Miller

  • 1Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA. bpschnei@iupui.edu

The Lancet. Oncology
|October 3, 2012
PubMed

Insights

Personalizing antiangiogenic treatments using germline single-nucleotide polymorphisms (SNPs) may improve patient outcomes. Research explores SNPs as predictive biomarkers to optimize therapy and reduce toxicity in cancer care.

Area of Science:

  • Oncology
  • Pharmacogenomics
  • Cancer Therapeutics

Background:

  • Antiangiogenic treatments are effective against various cancers but have variable therapeutic indices.
  • Personalizing antiangiogenic therapy is limited by the lack of reliable predictive biomarkers.
  • Germline single-nucleotide polymorphisms (SNPs) are being investigated as potential host-related biomarkers.

Purpose of the Study:

  • To review the role of germline SNPs as predictive biomarkers for antiangiogenic treatments.
  • To evaluate the strengths and pitfalls of using SNPs in clinical practice.
  • To highlight ongoing research and future directions in biomarker development.

Main Methods:

  • Review of existing clinical trial data and scientific literature.
  • Analysis of associations between germline SNPs and treatment outcomes/toxicity.
  • Exploration of the biological rationale for host-related genetic variations.

Main Results:

  • Several germline SNPs have shown associations with differential efficacy and toxicity of antiangiogenic drugs.
  • The host's genetic makeup (regulated by SNPs) may significantly influence treatment response.
  • Variability in therapeutic index is substantial across different patient populations.

Conclusions:

  • Germline SNPs hold promise as predictive biomarkers for personalizing antiangiogenic therapy.
  • Further confirmatory studies are needed to validate SNP associations and clinical utility.
  • Optimizing antiangiogenic treatment through pharmacogenomics can potentially improve patient outcomes and reduce adverse events.

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