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Prognostic and predictive biomarkers: tools in personalized oncology
Ewelina Nalejska1, Ewa Mączyńska, Marzena Anna Lewandowska
1Department of Thoracic Surgery and Tumors, Ludwik Rydygier Collegium Medicum, Bydgoszcz, Nicolaus Copernicus University, Torun, Poland.
Molecular Diagnosis & Therapy
|January 4, 2014
Summary
Personalized oncology uses pharmacogenomics and biomarkers to tailor cancer treatment. Biomarkers predict patient response to chemotherapy, improving outcomes and guiding therapy decisions for various cancers.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Personalized medicine revolutionizes oncology by enabling individualized patient approaches.
- Pharmacogenomics, analyzing genetic variations (germline and somatic), is key to understanding patient response to chemotherapy.
- Molecular biomarkers are crucial for characterizing cancer, guiding personalized treatment strategies.
Purpose of the Study:
- To explore the role of biomarkers in personalized oncology.
- To differentiate between prognostic and predictive biomarkers.
- To highlight the application of biomarkers in various cancer types and treatment evaluations.
Main Methods:
- Utilizing molecular biology tools for biomarker detection.
- Analyzing germline and somatic mutations.
- Measuring DNA methylation changes and microRNA (miRNA) levels.
- Detecting circulating tumor cells (CTCs).
Main Results:
- Biomarkers are categorized into prognostic (predicting overall outcome) and predictive (forecasting therapy response).
- Prognostic factors include mutations, DNA methylation, miRNA, and CTCs, aiding diagnosis and risk assessment.
- Predictive biomarkers optimize therapy selection and help evaluate potential toxicities.
Conclusions:
- Biomarkers are essential for molecular diagnostics in personalized oncology.
- Applications span chronic myeloid leukemia, colon, breast, lung cancer, and melanoma.
- Biomarkers enhance targeted therapy efficacy and toxicity assessments.
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