Biomarker panels and contemporary practice in clinical trials of targeted therapy

Abstract

Development of cancer therapy follows three main veins: Mutationdriven drug development, immunomodulatory therapy, and evolution of conventional chemo- and radiotherapy. All of these therapeutic modalities require more precise biomarkers, not only for increasing precision and enhancing efficiency but also to avoid unnecessary toxicity for the patient and costs for the society. In clinical trials, there is an increasing use of biomarker panels for risk stratification and therapy guidance. Single biomarkers, in particular genetic mutations, have been tested to optimize therapy with only limited success. So far, only a small fraction of the patients may benefit from state-of-the-art diagnostics and biomarker determination, although predictive factors have successfully been implemented in treatment of, for instance, breast cancer and colorectal cancer. We will exemplify and illustrate the use of biomarkers in late- and early-phase clinical trials, in which biomarker panels employed on acute leukemia or sarcoma assisted in pivotal decision-making. Clinical trials in acute leukemia and sarcoma often include biomarkers based on combinations of cytogenetics, gene mutations, gene expression, and protein detection. Acute leukemia and sarcoma are suggested to originate from progenitor or stem cells of hematopoietic or mesenchymal origin, respectively. The different biology of these diseases, based on cancer cell context and in relation to healthy tissue and tumor stroma, leads to their clinical manifestations and may provide guidance on the direction of future biomarker-tailored therapy. There is no fast track to establishing biomarker-based targeted therapy. However, combining biomarkers of different nature may provide clinically relevant and robust biomarker panels that can be used in late-phase clinical trials in acute leukemia and soft tissue sarcoma. For future prospects of simplifying biomarker approaches, functional subdivision of particular cancers into defined subsets may be the most promising path to provide molecular personalized therapy that optimally benefits the patient.