Previous investigations in gene expression changes in blood after radiation exposure have highlighted its potential to provide biomarkers of exposure. Here, FDXR transcriptional changes in blood were investigated in humans undergoing a range of external radiation exposure procedures covering several orders of magnitude (cardiac fluoroscopy, diagnostic computed tomography (CT)) and treatments (total body and local radiotherapy). Moreover, a method was developed to assess the dose to the blood using physical exposure parameters. FDXR expression was significantly up-regulated 24 hr after radiotherapy in most patients and continuously during the fractionated treatment. Significance was reached even after diagnostic CT 2 hours post-exposure. We further showed that no significant differences in expression were found between ex vivo and in vivo samples from the same patients. Moreover, potential confounding factors such as gender, infection status and anti-oxidants only affect moderately FDXR transcription. Finally, we provided a first in vivo dose-response showing dose-dependency even for very low doses or partial body exposure showing good correlation between physically and biologically assessed doses. In conclusion, we report the remarkable responsiveness of FDXR to ionising radiation at the transcriptional level which, when measured in the right time window, provides accurate in vivo dose estimates.

External beam radiation therapy leads to cellular activation of the DNA damage response (DDR). DNA double-strand breaks (DSBs) activate the ATM/CHEK2/p53 pathway, inducing the transcription of stress genes. The dynamic nature of this transcriptional response has not been directly observed in vivo in humans. In this study we monitored the messenger RNA transcript abundances of nine DNA damage-responsive genes (CDKN1A, GADD45, CCNG1, FDXR, DDB2, MDM2, PHPT1, SESN1, and PUMA), eight of them regulated by p53 in circulating blood leukocytes at different time points (2, 6–8, 16–18, and 24 h) in cancer patients (lung, neck, brain, and pelvis) undergoing radiotherapy. We discovered that, although the calculated mean physical dose to the blood was very low (0.038–0.169 Gy), an upregulation of Ferredoxin reductase (FDXR) gene transcription was detectable 2 h after exposure and was dose dependent from the lowest irradiated percentage of the body (3.5% whole brain) to the highest, (up to 19.4%, pelvic zone) reaching a peak at 6–8 h. The radiation response of the other genes was not strong enough after such low doses to provide meaningful information. Following multiple fractions, the expression level increased further and was still significantly up-regulated by the end of the treatment. Moreover, we compared FDXR transcriptional responses to ionizing radiation (IR) in vivo with healthy donors’ blood cells exposed ex vivo and found a good correlation in the kinetics of expression from the 8-hours time-point onward, suggesting that a molecular transcriptional regulation mechanism yet to be identified is involved. To conclude, we provided the first in vivo human report of IR-induced gene transcription temporal response of a panel of p53-dependant genes. FDXR was demonstrated to be the most responsive gene, able to reliably inform on the low doses following partial body irradiation of the patients, and providing an expression pattern corresponding to the % of body exposed. An extended study would provide individual biological dosimetry information and may reveal inter-individual variability to predict radiotherapy-associated adverse health outcomes.

Context. In modern medical practice the automation and information technologies are increasingly being implemented for diagnosing diseases, monitoring the condition of patients, determining the treatment program, etc. Therefore, the development of new and improvement of existing methods of the patient stratification in the medical monitoring systems is timely and necessary. Objective. The goal of intelligent diagnostics of patient’s state in the medical monitoring systems – reducing the likelihood of adverse states based on the choice of an individual treatment program: − reducing the probability of incorrectly determining the state of the patients when monitoring patients; − obtaining stable effective estimates of unknown values of treatment actions for patients (corresponding to the found state); − the choice of a rational individual treatment program for the patients, identified on the basis of the forecasted state. Method. Proposed methodology, which includes the following computational intelligence methods to patient’s stratification in the medical monitoring systems: 1) method of cluster analysis based on the agent-based approach – the determination of the possible number of patient’s states using controlled variables of state; 2) method of robust metamodels development by means artificial neuron networks under a priori data uncertainty (only accuracy of measurements is known) in the monitoring data: a) a multidimensional logistic regression model in the form of analytical dependences of the posterior probabilities of different states of the patients on the control and controlled variables of state; b) a multidimensional diagnostic model in the form of analytical dependences of the objective functions (quality criteria of the patient’s state) on the control and controlled variables of state; 3) method of estimating informativeness controlled variables of state at a priori data uncertainty; 4) method of robust multidimensional models development for the patient’s state control under a priori data uncertainty in the monitoring data in the form of analytical dependencies predicted from the measured values of the control and controlled variables of state in the monitoring process; 5) method of reducing the controlled state variables space dimension based on the analysis of the variables informativeness of the robust multidimensional models for the patient’s state control; 6) method of patient’s states determination based on the classification problem solution with the values of the control and forecasted controlled variables of state with using the probabilistic neural networks; 7) method of synthesis the rational individual patient’s treatment program in the medical monitoring system, for the state identified on the basis of the forecast. Proposed the structure of the model for choosing the rational individual patient’s treatment program based on IT Data Stream Mining, which implements the «Big Data for Better Outcomes» concept. Results. The developed advanced computational intelligence methods for forecast states were used in choosing the tactics of treating patients, to forecast treatment complications and assess the patient’s curability before and during special treatment. Conclusions. Experience in the implementation of “Big Data for Better Outcomes” concept for the solution of the problem of computational models for new patient stratification strategies is presented. Advanced methodology, computational methods for a patient stratification in the medical monitoring systems and applied information technology realizing them have been developed. The developed methods for forecast states can be used in choosing the tactics of treating patients, to forecast treatment complications and assess the patient’s curability before and during special treatment.

Background. In the modern world, the incidence of cancer diseases is rapidly increasing and is the second most common cause of death. This is preconditioned by the quantitative growth of the senior and elderly population, as well as the growth of the main risk factors for cancer, which is related to the socio-economic development of society. About half of cancer cases require radiation therapy (RT) as a component of multimodal treatment, therefore its improvement, namely the introduction of hypofractionated radiation regimens, is considered today as one of the most effective ways to increase availability of oncological care and optimize the use of health care system resources. Purpose. To find out clinical and medico-social advantages of the hypofractionated approach in radiation oncology in order to optimize the functioning of the health care system by increasing availability of treatment for cancer patients. To highlight the importance of hypofractionated RT in terms of evidence-based medicine for the most common oncological pathology and in neuro-oncology. To demonstrate the influence of the COVID-19 pandemic on the implementation of hypofractionated RT. To present our own experience of using hypofractionated radiation regimens in patients with glioblastoma (GB). Materials and methods. MEDLINE (Pubmed), EMBASE (Ovid), Web of Science (Web of Knowledge) databases were used to search for literature. The search was performed in the English-language sources with the following keywords: «Radiation», «Hypofractionation radiotherapy», «Hypofractionated radiotherapy», «Hypofractionated irradiation»; «Breast cancer»; «Prostate cancer»; «Lung cancer»; «Glioblastoma», COVID-19. Systematic reviews, meta-analyses, randomized controlled trials and retrospective clinical trials were reviewed in full. The primary sources were backreferenced to identify additional relevant studies related to hypofractionated radiation treatment regimens. The last date of the search is 05.25.2023. The authors’ own experience of the hypofractionated approach in the adjuvant radiation treatment of patients with GB is presented briefly, as a reflection of the relevance of the authors’ practical experience to the provisions of the narrative review, based on the results of a retrospective single-center non-randomized study conducted at the State Institution «Romodanov Neurosurgery Institute National Academy of Medical Sciences of Ukraine» in 2014–2020. The oncological results of 110 (69.2%) patients of the hypofractionated RT group (15 fractions, single fraction dose (SFD) 3.5 Gy, total fraction dose (TFD) 52.5 Gy) and 49 (30.8%) patients of the standard RT group (30 fractions, RVD 2.0 Gy, SVD 60.0 Gy) were compared. RT was performed with Trilogy linear accelerator (USA) (6 MeV) using the intensity-modulated radiotherapy method (IMRT). Overall survival (OS) and recurrence-free survival (RFS) in the groups were analyzed. Results and discussion. Hypofractionated approaches, which allow to significantly decrease the duration of radiation treatment, have clinical, medical and social advantages, including: increased comfort for a patient; reduction of the workload on staff and technological equipment of medical facilities; reduction of the cost of treatment. The introduction of hypofractionated RT allows to increase access to cancer care at the global level, reducing disparity in the results of treatment of cancer patients between low- and middle-income countries and the countries with high income level. Hypofractionated radiation regimens are included in the clinical guidelines of professional associations, as for the most common forms of cancer and for malignant brain tumors, and represent the standard of treatment for particular clinical cases. Our experience of using the hypofractionated radiation regimen is based on the adjuvant radiation treatment of 110 patients with GB and in terms of clinical results is a relevant concept presented in a narrative review. The analysis showed no statistical difference between the groups of standard fractionation and hypofractionated RT in OS (Logrank test p = 0.06757) and RFS (Logrank test p = 0.43374). In the hypofractionation group, with an observation time median of 22.3 months, the OS median was 16.5 (95% CI 14.1–18.8) months; median RFS was 9.0 (95% CI 8.0–10.0) months. In the standard radiation regimen group, with a median of observation time of 24.4 months, the median OS was 15.0 (95% CI 14.1–17.1) months; median RFS is 9.0 (95% CI 9.0–10.0) months. Conclusion. Development and implementation of the measures designed to optimize the use of resources of medical facilities of Ukraine is a necessary condition for maintaining high-quality care for cancer patients in the conditions of full-scale military aggression, which has been ongoing since February 24, 2022. Increased application of hypofractionated approaches in radiation oncology can be considered as a potential tool for optimization of the use of resources of the healthcare system of Ukraine and enhancing public health.

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