Cancer is a disease acquired through mutations which leads to uncontrolled cell division and destruction of normal tissue within the body. Recent increases in available cross-species data of cancer in mammals, reptiles, birds, and other vertebrates has revealed that the prevalence of cancers varies widely across species. Life-history theory suggests that there could be traits that potentially explain some of that variation. We are particularly interested in species that get very little cancer. How are they preventing cancer and can we learn from them how to prevent cancer in humans? Comparative oncology focuses on the analysis of cancer prevalence and traits in different non-human species and allows researchers to apply their findings to humans with the goal of improving and advancing cancer treatment. We incorporate the predictions that animals with larger bodies have evolved better cancer suppression mechanisms than animals with small bodies. Ruminants in the past were larger in size than modern day ruminants and they may have retained cancer defenses from their large ancestors. The strong cancer defenses and small body size combined may explain the low prevalence of cancer in Ruminants. This paper aims to evaluate the presence of benign and malignant neoplasia prevalence across multiple ruminant species following a time of dramatic decrease in body size across the clade. Our aim is to illuminate the potential impact that these shifts in body size had on their cancer prevalence as well as test the statistical power of other key life history variables to predict cancer prevalence.

Cancer rates vary between people, between cultures, and between tissue types, driven by clinically relevant distinctions in the risk factors that lead to different cancer types. Despite the importance of cancer location in human health, little is known about tissue-specific cancers in non-human animals. We can gain significant insight into how evolutionary history has shaped mechanisms of cancer suppression by examining how life history traits impact cancer susceptibility across species. Here, we perform multi-level analysis to test how species-level life history strategies are associated with differences in neoplasia prevalence, and apply this to mammary neoplasia within mammals. We propose that the same patterns of cancer prevalence that have been reported across species will be maintained at the tissue-specific level. We used a combination of factor analysis and phylogenetic regression on 13 life history traits across 90 mammalian species to determine the correlation between a life history trait and how it relates to mammary neoplasia prevalence. The factor analysis presented ways to calculate quantifiable underlying factors that contribute to covariance of entangled life history variables. A greater risk of mammary neoplasia was found to be correlated most significantly with shorter gestation length. With this analysis, a framework is provided for how different life history modalities can influence cancer vulnerability. Additionally, statistical methods developed for this project present a framework for future comparative oncology studies and have the potential for many diverse applications.

The risk of developing cancer should theoretically increase with both the number of cells and the lifespan of an organism. However, gigantic animals do not get more cancer than humans, suggesting that super-human cancer suppression has evolved numerous times across the tree of life. This is the essence and promise of Peto’s Paradox. We discuss what is known about Peto’s Paradox and provide hints of what is yet to be discovered.

Risk factors for breast cancer are often confusing and contradictory. Discrepancies are likely due to different subtypes having divergent risk factors. An important distinction between breast cancer subtypes is hormone-receptor status. Compared to women diagnosed with estrogen receptor positive (ER+) breast cancer, those with estrogen receptor negative (ER−) tumors are usually diagnosed at a younger age and have a higher mortality [1]. Few studies have attempted to explain ‘why’ breast cancer subtypes have different risk factors.