Mikhail Potievskiy*, Ilya Klabukov, Aleksei Traspov, Peter Shatalov, Peter Shegai and Andrei Kaprin
National Medical Research Center of Radiology, Ministry of Health (Russia)
potievskiymikhail [at] gmail.com
Abstract
Evolutionary medicine studies the disease pathogenesis in result of natural selection. Evolutionary oncology studies tumor under natural selection pressure and through the process of clonal evolution. Tumor microevolution refers to the dynamic genetic, epigenetic, and phenotypic changes that occur within a tumor over time, driven by selective pressures from the microenvironment, immune system, and therapy. Environment and physiology change may cause cancer risk increase or decrease. Our study is aimed to evaluate the strength and the direction of the selection, acting on oncosuppressor genes in association with phenotypic changes.
We calculated gene-specific rates of evolution on branches of phylogenetic trees, using linear regression. We examined how alterations in the evolutionary dynamics of tumor-suppressor genes—primarily those involved in DNA repair and cell-cycle regulation—correlate with key lineage-specific traits. Evolutionary rate variation was assessed both at the level of individual genes and across functional pathways. The analysis focused on major vertebrate traits (homeothermy, powered flight, presence of the amnion) and mammalian traits (increased body mass and lifespan, subterranean lifestyle, and hibernation). Our dataset comprised 19,445 genes across 100 vertebrate and 46 mammalian species. We evaluated evolutionary rate changes on specific ancestral branches as well as across entire clades exhibiting a given trait.
Individual oncosupressor genes were accelerated in association with the ability to fly (positive/relaxed negative selection) and decelerated in homeothermic species (stabilizing selection). DNA repair genes were accelerated in ancestral branches and all the clades of amniotic and homothermic animals, and high body mass mammals. Cell cycle control genes were under stabilizing selection in homothermic animals, high body mass, long-lived, and underground mammals. The data on the oncosupressors evolution are crucial for understanding cancer origin and will be important for future studies of tumor pathogenesis, pathomorphosis, and microevolution.
Artificial intelligence (AI) allows to integrate various data, including genomic, histopathological, and clinical data, helping to map these evolutionary processes. Combining insights from tumor microevolution with AI-driven analytics offers a pathway toward more adaptive and effective cancer care.
Keywords: oncosupressors, mammalian adaptations, evolutionary oncology