FRRB Project 2721017 - Discovering the MicroBiota potential for personalised Radiotherapy

Name and Surname of PI

Jacopo Iacovacci

Project Acronym


Project ID


Host Institution

Fondazione IRCCS Istituto Nazionale dei Tumori - Milan

Pathology of Interest

Head-and-neck cancer and prostate cancer

Research Area


Project Start Date

28 October 2021

Project End Date

27 October 2023


€ 171.473,28

Type of Project



Investigation of approaches to avoid, ameliorate or treat the long-term side effects of radiotherapy, that often highly compromise the quality of life of treated patients, is a poorly pursued research area. For head-and-neck cancer and prostate cancer, radiotherapy is effectively used as curative treatment in single-mode or within a multidisciplinary approach including surgery and/or chemotherapy. Prediction and reduction of radio-induced side effects are of particular relevance for prostate cancer, characterised by high survival rate, and for head-and-neck cancer, for which irradiation dose modification strategies could improve survival without increasing toxicity. However, heterogeneity of toxicity levels observed in the patient population after the treatment is hard to model because of many individual-specific factors, such as genetic background, premorbid conditions, and cellular microenvironment, which might affect tissue response to radiation. The microbiome, which is the overall bacterial populations which live in our body and whose composition is specific for each of us, is determinant in driving and controlling inflammation in several diseases, including inflammatory bowel disease and Crohn’s disease, and recent evidence indicates that radiotherapy-induced toxicity in the bowel (enteropathy) and the onset and severity of radioinduced oral mucositis could be related to the unbalance of intestinal and salivary microbiome, respectively. MicBioRadio aims at understanding through ecological network modelling of the intestinal and salivary microbiota how radiation impacts the equilibrium of bacterial communities in those patients who develop gastrointestinal or oral toxicity during radiotherapy, and at defining via state-of-the-art machine learning techniques efficient biomarkers from microbiota profiles of individual atients affected by prostate/head-and-neck cancer for improving pre-radiotherapy toxicity risk assessment and irradiation planning optimisation.