Prognostic and predictive biomarkers: tools in personalized oncology.

Abstract

Oncology indispensably leads us to personalized medicine, which allows an individual approach to be taken with each patient. Personalized oncology is based on pharmacogenomics and the effect of genetic differences in individuals (germline and somatic) on the way cancer patients respond to chemotherapeutics. Biomarkers detected using molecular biology tools allow the molecular characterization of cancer signatures and provide information relevant for personalized treatment. Biomarkers can be divided into two main subgroups: prognostic and predictive. The aim of the application of prognostic biomarkers, which provide information on the overall cancer outcome in patients, is to facilitate cancer diagnosis, usually with no need for putting invasive methods into use. Predictive biomarkers help to optimize therapy decisions, as they provide information on the likelihood of response to a given chemotherapeutic. Among the prognostic factors that identify patients with different outcome risks (e.g., recurrence of the disease), the following factors can be distinguished: somatic and germline mutations, changes in DNA methylation that lead to the enhancement or suppression of gene expression, the occurrence of elevated levels of microRNA (miRNA) capable of binding specific messenger RNA (mRNA) molecules, which affects gene expression, as well as the presence of circulating tumor cells (CTCs) in blood, which leads to a poor prognosis for the patient. Biomarkers for personalized oncology are used mainly in molecular diagnostics of chronic myeloid leukemia, colon, breast and lung cancer, and recently in melanoma. They are successfully used in the evaluation of the benefits that can be achieved through targeted therapy or in the evaluation of toxic effects of the chemotherapeutic used in the therapy.