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 purpose of this project is to analyze the current state of cancer nanomedicine and its challenges. Cancer is the second most deadly illness in the United States after heart disease. Nanomedicine, the use of materials between 1 and 100 nm to for the purpose of addressing healthcare-related problems, is particularly suited for treating it since nanoparticles have properties such as high surface area-to-volume ratios and favorable drug release profiles that make them more suitable for tasks such as consistent drug delivery to tumor tissue. The questions posed are: What are the current nanomedical treatments for cancer? What are the technical, social, and legal challenges related to nanomedical treatments and how can they be overcome? To answer the questions mentioned above, information from several scientific papers on nanomedical treatments for cancer as well as from social science journals was synthesized. Based on the findings, nanomedicine has a wide range of applications for cancer drug delivery, detection, and immunotherapy. The main technical challenge related to nanomedical treatments is navigating through biological barriers such as the mononuclear phagocyte system, the kidney, the blood-brain barrier, and the tumor microenvironment. Current approaches to meeting this challenge include altering the size, shape, and charge of nanoparticles for easier passage. The main social and legal challenge related to nanomedical treatments is the difficulty of regulating them due to factors such as the near impossibility of detecting nanowaste. Current approaches to meeting this challenge include the use of techniques such as scanning tunneling microscopy and atomic force microscopy to help distinguish nanowaste from the surroundings. More research will have to be done in these and other areas to enhance a major cancer-fighting tool.

Age is the most significant risk factor for cancer development in humans. The somatic mutation theory postulates that the accumulation of genomic mutations over time results in cellular function degradation which plays an important role in understanding aging and cancer development. Specifically, degradation of the mechanisms that underlie somatic maintenance can occur due to decreased immune cell function and genomic responses to DNA damage. Research has shown that this degradation can lead to the accumulation of mutations that can cause cancer in humans. Despite recent advances in our understanding of cancer in non-human species, how this risk factor translates across species is poorly characterized. Here, we analyze a veterinarian cancer dataset of 4,178 animals to investigate if age related cancer prevalence is similar in non-human animals. We intend for this work to be used as a primary step towards understanding the potential overlap and/or uniqueness between human and non-human cancer risk factors. This study can be used to better understand cancer development and how evolutionary processes have shaped somatic maintenance across species.

Cancers of the reproductive tissues make up a significant portion of the cancer burden and mortality experienced by humans. Humans experience several proximal causative carcinogens that explain a portion of cancer risk, but an evolutionary viewpoint can provide a unique lens into the ultimate causes of reproductive cancer vulnerabilities. A life history framework allows us to make predictions on cancer prevalence based on a species’ tempo of reproduction. Moreover, certain variations in the susceptibility and prevalence of cancer may emerge due to evolutionary trade-offs between reproduction and somatic maintenance. For example, such trade-offs could involve the demand for rapid proliferation of cells in reproductive tissues that arises with reproductive events. In this study, I compiled reproductive cancer prevalence for 158 mammalian species and modeled the predictive power of 13 life history traits on the patterns of cancer prevalence we observed, such as Peto’s Paradox or slow-fast life history strategies. We predicted that fast-life history strategists will exhibit higher neoplasia prevalence risk due to reproductive trade-offs. Furthering this analytical framework can aid in predicting cancer rates and stratifying cancer risk across the tree of life.