Personalized radiotherapy: concepts, biomarkers and trial design

Abstract

In the past decade, and pointing onwards to the immediate future, clinical radiotherapy has undergone considerable developments, essentially including technological advances to sculpt radiation delivery, the demonstration of the benefit of adding concomitant cytotoxic agents to radiotherapy for a range of tumour types and, intriguingly, the increasing integration of targeted therapeutics for biological optimization of radiation effects. Recent molecular and imaging insights into radiobiology will provide a unique opportunity for rational patient treatment, enabling the parallel design of next-generation trials that formally examine the therapeutic outcome of adding targeted drugs to radiation, together with the critically important assessment of radiation volume and dose-limiting treatment toxicities. In considering the use of systemic agents with presumed radiosensitizing activity, this may also include the identification of molecular, metabolic and imaging markers of treatment response and tolerability, and will need particular attention on patient eligibility. In addition to providing an overview of clinical biomarker studies relevant for personalized radiotherapy, this communication will highlight principles in addressing clinical evaluation of combined-modality-targeted therapeutics and radiation. The increasing number of translational studies that bridge large-scale omics sciences with quality-assured phenomics end points-given the imperative development of open-source data repositories to allow investigators the access to the complex data sets-will enable radiation oncology to continue to position itself with the highest level of evidence within existing clinical practice.

Figure 1.

Biological modelling is the backbone of study design in personalized radiotherapy. High-throughput omics and functional imaging technologies are applied to determine tumour and circulating molecular, metabolic and imaging signatures descriptive for the patient's tumour and normal tissue constitution. This information is utilized to individualize the combined-modality radiotherapy protocol to each specific case. Curated phenomic data from clinical end point assessments (treatment toxicity and efficacy) are integrated together with the biological data in open-source repositories to provide investigators the access to the data sets within global networks. As a toolbox for data mining across a range of technology platforms and based on rational study design, the ultimate objective is to develop knowledge-driven decision support systems to guide clinical practice by the learning models that are generated. Images are from our own work or purchased from a commercial stock photo agency.