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bioRxiv · 10.1101/2025.02.17.638732

Machine learning ensemble identifies distinct age-related response to spaceflight in mammary tissue

Casaletto, J. A.·Zhao, T.·Yeung, J.·Ansari, A.·Raj, A.·Mishra, A.·Fry, A.·Sun, K.·Lee, A.·Sanders, L. M.·Costes, S. V.
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Abstract

BackgroundSpaceflight presents unique environmental stressors, such as microgravity and radiation, that significantly affect biological systems at the molecular, cellular, and organismal levels. Astronauts face an increased risk of developing cancer due to exposure to ionizing radiation and other spaceflight-related factors. Age plays a crucial role in the bodys response to the cellular stresses that lead to cancer, with younger organisms generally exhibiting more efficient response mechanisms than older ones. The vast majority of research investigating breast cancer risk from spaceflight is done in vitro, using cell lines exposed to simulated radiation and microgravity. ObjectivesThe primary objective of this observational study is to characterize the response to spaceflight of in vivo murine mammary tissue and identify the molecular biomarkers enriched in this response using mice flown on the International Space Station. The secondary objective is to determine if age plays a role in this response. MethodsThe NASA Open Science Data Repository (OSDR) has curated transcriptomic data obtained from murine mammary tissue in a controlled experiment (OSD-511) which includes 43 young and old female mice. In this study, we utilized an ensemble of four machine learning binary classifiers (logistic regression, support vector machine, random forest, and single-layer perceptron) to analyze gene expression profiles to predict age (old vs young) and condition (spaceflight vs ground control). Using the genes our ensemble identified as most predictive, we performed pathway enrichment analysis to investigate the molecular pathways involved in spaceflight-related health risks, particularly in the context of breast cancer. ResultsAll space-flown mice responded to spaceflight with evidence of systemic metabolic reprogramming and mitochondrial adaptation to microgravity and radiation as compared to their 33 ground control counterparts. For the 10 mice flown in space, older mice exhibited chronic, significantly enriched pathways related to cell adhesion and extracellular matrix (ECM) structure, while younger mice showed acute activation of pathways involved in cortisol synthesis and adrenergic stress response (with false discovery rate adjusted q-values < .001). These results provide putative biomarkers for monitoring and treating breast cancer. ConclusionsThese findings highlight the critical role of age in modulating the response to spaceflight-induced stress and suggest that these molecular pathways may contribute to differential outcomes in tissue homeostasis, metabolic disorders, and breast cancer tumorigenesis. Moreover, our computational methodology may be applied to several unexplored datasets in OSDR and beyond.

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Casaletto, J. A., Zhao, T., Yeung, J., Ansari, A., Raj, A., Mishra, A., Fry, A., Sun, K., Lee, A., Sanders, L. M., Costes, S. V.. 2025-02-23. Machine learning ensemble identifies distinct age-related response to spaceflight in mammary tissue. https://doi.org/10.1101/2025.02.17.638732

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