Radiogenomics and Its Application in Personalized Medicine

Radiotherapy is known as one of the most effective cancer treatments, but like other cancer treatments, it often causes side effects. Meanwhile, early and late normal tissue side effects after radiotherapy are common and can have a significant negative impact on the quality of life. These effects cannot be shown only through factors such as dosimetric, therapeutic, clinical and demographic factors, and the evidence shows that genetic factors are related to the adverse effects of radiotherapy, that examining these factors can improve the personalization of cancer treatment(۱, ۲). Therefore, aggressive treatments can be used for low-risk patients, and on the contrary, cancers that are sensitive to radiation can be treated through a lower dose of radiotherapy.Studies that supporting the role of genetic factors responsible for variation in radiosensitivity have shown that patients with rare genetic syndromes such as Ataxia Telangiectasia, Bloom's syndrome, Fanconi anemia, and Nijmegen breakage syndrome, which have mutations in the genes involved in the detection of DNA damage and the initiation of its repair, have been predisposing radiation sensitivity and severe side effects can occur in normal tissues(۳).Radiogenomics is the identification of the relationship between imaging phenotypes and the tumour genome, some of which studies investigate the relationship between imaging characteristics of cancer tissue with one or more genomic, molecular or related characteristics.Radiogenomics studies are generally performed with several main goals. (I) Identifying genomic markers predicting side effects of cancer radiotherapy (II) help to develop imaging surrogates instead of genetic tests, which may be often invasive and expensive(III) Developing predictive tools to identify people who are at risk of negative effects of radiotherapy or even (IV) Identification of specific imaging modality for each group of patients (۴, ۵).In this presentation, we will learn about Radiogenomics basics and its applications in cancer treatments.