Pharmacogenomic biomarkers for personalized cancer treatment

C Rodríguez-Antona1,2, M Taron3

  • 1Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.

Insights

Personalized medicine uses patient and tumor molecular data to tailor cancer treatments for better outcomes. Understanding these complex genetic factors drives pharmacogenomic advances for individualized therapies.

Area of Science:

  • Oncology
  • Pharmacogenomics
  • Molecular Biology

Background:

  • Personalized medicine tailors drug selection to patient molecular profiles for optimal safety and efficacy.
  • Tumor cell alterations significantly impact anticancer drug activity, with most response biomarkers originating from these cells.
  • Patient genetic background influences severe toxicity risk, necessitating comprehensive molecular understanding.

Purpose of the Study:

  • To review challenges and opportunities in pharmacogenomic studies for oncology.
  • To highlight clinically established biomarkers and advances in personalized cancer treatment.
  • To discuss future prospects for personalizing cancer medicine.

Main Methods:

  • Review of current literature on pharmacogenomics in oncology.
  • Analysis of established biomarkers and high-throughput data generation.
  • Case studies illustrating personalized treatment in lung and renal cancer.

Main Results:

  • EGFR mutation as a paradigm for targeted lung cancer therapy.
  • Dissection of lung cancer into molecular subsets.
  • Emerging role of single nucleotide polymorphisms in antiangiogenic agent response.

Conclusions:

  • Integrating tumor and patient molecular data is crucial for identifying predictive biomarkers and enabling individualized treatments.
  • High-throughput data facilitates pharmacogenomic progress and novel drug discovery.
  • Continued research into molecular complexities and novel approaches will advance personalized oncology.

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