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Pharmacogenomic biomarkers for personalized cancer treatment
C Rodríguez-Antona1,2, M Taron3
1Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
Abstract:
Personalized medicine involves the selection of the safest and most effective pharmacological treatment based on the molecular characteristics of the patient. In the case of anticancer drugs, tumour cell alterations can have a great impact on drug activity and, in fact, most biomarkers predicting response originate from these cells. On the other hand, the risk of developing severe toxicity may be related to the genetic background of the patient. Thus, understanding the molecular characteristics of both the tumour and the patient, and establishing their relation with drug outcomes will be critical for the identification of predictive biomarkers and to provide the basis for individualized treatments. This is a complex scenario where multiple genes as well as pathophysiological and environmental factors are important; in addition, tumours exhibit large inter- and intraindividual variability in space and time. Against this background, the huge amounts of biological and genetic data generated by the high-throughput technologies will facilitate pharmacogenomic progress, suggest novel druggable molecules and support the design of future strategies aimed at disease control. Here, we will review the current challenges and opportunities for pharmacogenomic studies in oncology, as well as the clinically established biomarkers. Lung and renal cancer, two areas in which huge progress has been made in the last decade, will be used to illustrate advances in personalized cancer treatment; we will review EGFR mutation as the paradigm of targeted therapies in lung cancer, and discuss the dissection of lung cancer into clinically relevant molecular subsets and novel advances that suggest an important role of single nucleotide polymorphisms in the response to antiangiogenic agents, as well as the challenges that remain in these fields. Finally, we will present new approaches and future prospects for personalizing medicine in oncology.
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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