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Radiotherapy is a highly personalized treatment, where dose distribution is tailored to the patient based on anatomical and clinical information. Advances in particle therapy, image guidance and treatment adaptation will broaden the scope and precision of radiotherapy, while novel prognostic and predictive biomarkers will act as a basis for further individualized treatment. Additionally, a sound understanding of biological radioresistance mechanisms will be essential, for example, to combat relapse after therapy. Future developments in personalized and high precision medicine will depend on comprehensive research networks to collect reliable data from large and homogeneous patient collectives.

The etiological bases of cancer are a large number of ‘bugs’, mutations in the human genome, mostly accumulating in somatic cells during patient’s lifespan. It took more than a century to translate this etiological insight into new ways to smart-bomb the cancer away. As new treatment options emerge, healthcare guidelines seek ways, such companion testing, to identify the patient, the treatment is most likely to benefit. The dynamic nature of the field of medical discoveries poses a challenge to the clinical decision making process, and guidelines have therefore gone through a series of paradigm shifts, all based on risk-benefit assessments. First, in the evidence-based paradigm, optional treatments are ranked according to the fraction of patients the treatment is likely to benefit, starting from the most commonly useful treatment and down the fractional benefit rank. Then, personalized medicine approach utilizes clinical and genomic sequence and molecular analyses, to rearrange the treatments rank, and recommend each patient with their own best treatment. In the most recent paradigm, immune-oncology, we profile the direct adaptive immune reaction, T-cell receptor sequence, to cancer-borne somatic mutations. The unique sequence of the respective T-cell receptors had been demonstrated to genetically code for the recognition and elimination of cells, carrying and presenting the mutant sequence. In other words, the cure to each patient is hidden in their own body, and once discovered, has the potential to harness the progression of cancer, as is being done for patients with high mutation load and immunological checkpoint inhibitors. While this approach is more bioinformatically and experimentally intensive, the results obtained from this approach are far superior, both in the end-stage patients it succeeds to benefit, as well as the duration of remission. Using double-autologous patient-derived xenografts, that model both the cancer tissue, as well as the immune system of each patient, we are harnessing these technologies to improve and accelerate the implementation of those new paradigms in the clinical practice.