Small Molecule Responses to Sequential Irradiation with Neutrons and Photons for Biodosimetry Applications: An Initial Assessment

Sex differences in radiation research

PURPOSE

The Sex Differences in Radiation Research workshop addressed the role of sex as a confounder in radiation research and its implication in real-world radiological and nuclear applications.

METHODS

In April 2022, HHS-wide partners from the Radiation and Nuclear Countermeasures Program, the Office of Research on Women's Health National Institutes of Health Office of Women's Health, U.S. Food and Drug Administration, and the Radiological and Nuclear Countermeasures Branch at the Biomedical Advanced Research and Development Authority conducted a workshop to address the scientific implication and knowledge gaps in understanding sex in basic and translational research. The goals of this workshop were to examine sex differences in 1. Radiation animal models and understand how these may affect radiation medical countermeasure development; 2. Biodosimetry and/or biomarkers used to assess acute radiation syndrome, delayed effects of acute radiation exposure, and/or predict major organ morbidities; 3. medical research that lacks representation from both sexes. In addition, regulatory policies that influence inclusion of women in research, and the gaps that exist in drug development and device clearance were discussed. Finally, real-world sex differences in human health scenarios were also considered.

RESULTS

This report provides an overview of the two-day workshop, and open discussion among academic investigators, industry researchers, and U.S. government representatives.

CONCLUSIONS

This meeting highlighted that current study designs lack the power to determine statistical significance based on sex, and much is unknown about the underlying factors that contribute to these differences. Investigators should accommodate both sexes in all stages of research to ensure that the outcome is robust, reproducible, and accurate, and will benefit public health.

The NIAID/RNCP Biodosimetry Program: An Overview

Established in 2004, the Radiation and Nuclear Countermeasures Program (RNCP), within the National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health has the central mission to advance medical countermeasure mitigators/therapeutics, and biomarkers and technologies to assess, triage, and inform medical management of patients experiencing acute radiation syndrome and/or the delayed effects of acute radiation exposure. The RNCP biodosimetry mission space encompasses: (1) basic research to elucidate novel approaches for rapid and accurate assessment of radiation exposure, (2) studies to support advanced development for US Food and Drug Administration (FDA) clearance of promising triage or treatment devices/approaches, (3) characterization of biomarkers and/or assays to determine degree of tissue or organ dose that can predict outcome of radiation injuries (i.e., organ failure, morbidity, and/or mortality), and (4) outreach efforts to facilitate interactions with researchers developing cutting edge biodosimetry approaches. Thus far, no biodosimetry device has been FDA cleared for use during a radiological/nuclear incident. At NIAID, advancement of radiation biomarkers and biodosimetry approaches is facilitated by a variety of funding mechanisms (grants, contracts, cooperative and interagency agreements, and Small Business Innovation Research awards), with the objective of advancing devices and assays toward clearance, as outlined in the FDA's Radiation Biodosimetry Medical Countermeasure Devices Guidance. The ultimate goal of the RNCP biodosimetry program is to develop and establish accurate and reliable biodosimetry tools that will improve radiation preparedness and ultimately save lives during a radiological or nuclear incident.

Biomarker integration for improved biodosimetry of mixed neutron + photon exposures

There is a persistent risk of a large-scale malicious or accidental exposure to ionizing radiation that may affect a large number of people. Exposure will consist of both a photon and neutron component, which will vary in magnitude between individuals and is likely to have profound impacts on radiation-induced diseases. To mitigate these potential disasters, there exists a need for novel biodosimetry approaches that can estimate the radiation dose absorbed by each person based on biofluid samples, and predict delayed effects. Integration of several radiation-responsive biomarker types (transcripts, metabolites, blood cell counts) by machine learning (ML) can improve biodosimetry. Here we integrated data from mice exposed to various neutron + photon mixtures, total 3 Gy dose, using multiple ML algorithms to select the strongest biomarker combinations and reconstruct radiation exposure magnitude and composition. We obtained promising results, such as receiver operating characteristic curve area of 0.904 (95% CI: 0.821, 0.969) for classifying samples exposed to ≥ 10% neutrons vs. < 10% neutrons, and R2 of 0.964 for reconstructing photon-equivalent dose (weighted by neutron relative biological effectiveness) for neutron + photon mixtures. These findings demonstrate the potential of combining various -omic biomarkers for novel biodosimetry.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Biomarkers to Predict Lethal Radiation Injury to the Rat Lung

Currently, there are no biomarkers to predict lethal lung injury by radiation. Since it is not ethical to irradiate humans, animal models must be used to identify biomarkers. Injury to the female WAG/RijCmcr rat has been well-characterized after exposure to eight doses of whole thorax irradiation: 0-, 5-, 10-, 11-, 12-, 13-, 14- and 15-Gy. End points such as SPECT imaging of the lung using molecular probes, measurement of circulating blood cells and specific miRNA have been shown to change after radiation. Our goal was to use these changes to predict lethal lung injury in the rat model, 2 weeks post-irradiation, before any symptoms manifest and after which a countermeasure can be given to enhance survival. SPECT imaging with 99mTc-MAA identified a decrease in perfusion in the lung after irradiation. A decrease in circulating white blood cells and an increase in five specific miRNAs in whole blood were also tested. Univariate analyses were then conducted on the combined dataset. The results indicated that a combination of percent change in lymphocytes and monocytes, as well as pulmonary perfusion volume could predict survival from radiation to the lungs with 88.5% accuracy (95% confidence intervals of 77.8, 95.3) with a p-value of < 0.0001 versus no information rate. This study is one of the first to report a set of minimally invasive endpoints to predict lethal radiation injury in female rats. Lung-specific injury can be visualized by 99mTc-MAA as early as 2 weeks after radiation.

Metabolic response to radiation therapy in cancer

Tumor metabolism has emerged as a hallmark of cancer and is involved in carcinogenesis and tumor growth. Reprogramming of tumor metabolism is necessary for cancer cells to sustain high proliferation rates and enhanced demands for nutrients. Recent studies suggest that metabolic plasticity in cancer cells can decrease the efficacy of anticancer therapies by enhancing antioxidant defenses and DNA repair mechanisms. Studying radiation-induced metabolic changes will lead to a better understanding of radiation response mechanisms as well as the identification of new therapeutic targets, but there are few robust studies characterizing the metabolic changes induced by radiation therapy in cancer. In this review, we will highlight studies that provide information on the metabolic changes induced by radiation and oxidative stress in cancer cells and the associated underlying mechanisms.