## 3 Factors Regulating Tolerability of RT in Cancer Patients  
The current clinical practice for radioprotection is based on medical experience and population outcomes and does not fully address variations in radiobiological responses in individual patients. On the one hand, the clinical cut-offs are not tailored for patients with radio-resistant tumors since they are based mainly on clinical data and population averages. It is of note that a remarkable percentage of patients exhibit a hypersensitive phenotype by developing severe side effects even when subjected to hypo-fractionated RT [6]. In the real world, different individuals may have individualized responses to a given dose protocol in terms of treatment efficacy and toxicity. The occurrence of distinctive effects related to radiosensitivity among individuals depends on a number of parameters, including both the radiation characteristics (type, dose, and dose rate of radiation) and the features of individual patients and/or their tumors.  
A prominent factor related to the toxicity risk in RT is genetic predisposition (intrinsic radiosensitivity). This appears to contribute the most to the individual variability in radiosensitivity [25]. According to [PERSON] et al., 2012, heritability is responsible for radiosensitivity in 60-80% of oncologic patients [26], while [PERSON] et al., 2014, estimate a contribution of around 80% [27]. Other patient-relative critical factors affecting variations in radiosensitivity are age and sex. For instance, children are considered to be the most sensitive group in terms of radiation-induced cancer, for all the spectrum of dose exposures [28; 29]. Sex is also differently related to radiation responses [30], as mostly shown in studies on the survivors of the Hiroshima and Nagasaki atomic bombs [31]. Lifestyle (such as smoking, alcohol drinking, dietary habits, etc.) is also another factor influencing tissue/organ radiosensitivity [32], as well as the body mass index (BMI) and individual metabolism [33]. The primary cancer type and the use of parallel or preceding treatments (e.g., chemotherapy) also modulate radiosensitivity.  
Other important factors include the tumor doubling time, along with the redox and hypoxic status of tissues, and have an important contribution to the total dose delivered to the oncologic patient and the dose fractionation scheme. Any likely association between these alterations and the average normal tissue response to IR reaching the limit of toxicity would be a key step for treatment optimization and individualization. Moreover, the tumor microenvironment (TME) plays a critical role in the optimization of the efficacy of RT. According to [PERSON] et al., 2021, the effects of RT on the TME scale involve changes in immune cells, vasculature, and stromal components [13]. In this regard, precision medicine approaches that consider the genomic signatures of patients and the TME are crucial to optimize the efficacy of RT and minimize adverse effects.  
The mechanisms underlying radiosensitivity are multifactorial [34]. Mechanism-driven strategies to predict, monitor, and treat RT-induced side effects are currently missing. This is not only due to the poor understanding of the underlying pathways but also because the type of side effects may vary depending on the cancer type, therapeutic regimen, and individual patient. The identification of radiation injury mechanisms and the specification of the in vivo toxicity caused by several agents remain topics of immense research. The need to evaluate radiosensitivity and radiotoxic risk prediction for an oncologic patient undergoing RT is of leading priority in modern radiation oncology. For this reason, new tools to predict tumor radioresistance and healthy tissue radiosensitivity are highly needed for developing personalized RT strategies. Reliable biomarkers would greatly help to establish the dose-effect relationship in RT for evaluating its efficacy for tumor control and its toxicity for normal tissues in a personalized manner.