Adaptive therapy is a novel up-and-coming cancer treatment strategy to minimize chemoresistance in cells to improve patient prognosis. The standard of care cancer treatment has a fixed linear approach known as Maximum Tolerated Dose (MTD) which promotes an exponential growth of resistant cancer cell populations in the tumor. Through this treatment procedure, a population of chemoresistant cells resurges, decreasing the survival in patients, and narrowing potential treatment options (Gatenby). An assortment of chemotherapeutic drugs and dosing schedules were tested on ER+ endocrine-resistant MCF7 breast cancer cells in an immunodeficient mouse model. After the cessation of treatment, some mouse models’ tumors remained stable or began to shrink. Several immunodeficient mouse models have indicated unexpectedly high levels of neutrophils stemming from an unknown origin. We aim to understand if neutrophils' innate immunity may affect tumor size post-chemotherapy treatment and if it has therapeutic implications along with adaptive therapy. MCF7 breast cancer tumors were extracted from the mice, embedded in wax, and sliced, and immunofluorescence was performed to detect neutrophils and nuclear components. Currently, the protocol is in its third round of optimization.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic, declared in March 2020 resulted in an unprecedented scientific effort that led to the deployment in less than a year of several vaccines to prevent severe disease, hospitalizations, and death from coronavirus disease 2019 (COVID-19). Most vaccine models focus on the production of neutralizing antibodies against the spike (S) to prevent infection. As the virus evolves, new variants emerge that evade neutralizing antibodies produced by natural infection and vaccination, while memory T cell responses are long-lasting and resilient to most of the changes found in variants of concern (VOC). Several lines of evidence support the study of T cell-mediated immunity in SARS-CoV-2 infections. First, T cell reactivity against SARS-CoV-2 is found in both (cluster of differentiation) CD4+ and CD8+ T cell compartments in asymptomatic, mild, and severe recovered COVID-19 patients. Second, an early and stronger CD8+ T cell response correlates with less severe COVID-19 disease [1-4]. Third, both CD4+ and CD8+ T cells that are reactive to SARS-CoV-2 viral antigens are found in healthy unexposed individuals suggesting that cross-reactive and conserved epitopes may be protective against infection. The current study is focused on the T cell-mediated response, with special attention to conserved, non-spike-cross-reactive epitopes that may be protective against SARS-CoV-2. The first chapter reviews the importance of epitope prediction in understanding the T cell-mediated responses to a pathogen. The second chapter centers on the validation of SARS-CoV-2 CD8+ T cell predicted peptides to find conserved, immunodominant, and immunoprevalent epitopes that can be incorporated into the next generation of vaccines against severe COVID-19 disease. The third chapter explores pre-existing immunity to SARS-CoV-2 in a pre-pandemic cohort and finds two highly immunogenic epitopes that are conserved among human common cold coronaviruses (HCoVs). To end, the fourth chapter explores the concept of T cell receptor (TCR) cross-reactivity by isolating SARS-CoV-2-reactive TCRs to elucidate the mechanisms of cross-reactivity to SARS-CoV-2 and other human coronaviruses (HCoVs).

Can Body Height and BMI predict cancer trends in humans? Using a dataset of 220,181 individuals, with 31,822 individuals having malignancy records, we found that body height (p < 2e-16) and Body Mass Index (BMI) (p < 5.6e-05) are significant predictors of developing cancer. After stratifying by sex, we determined that men and women face an elevated risk of developing cancer with increases in body height, but a very slight increase in cancer risk with increases in BMI.

Life history theory offers a powerful framework to understand evolutionary selection pressures and explain how adaptive strategies use the life history trade-off and differences in cancer defenses across the tree of life. There is often some cost to the phenotype of therapeutic resistance and so sensitive cells can usually outcompete resistant cells in the absence of therapy. Adaptive therapy, as an evolutionary and ecologically inspired paradigm in cancer treatment, uses the competitive interactions between drug-sensitive, and drug-resistant subclones to help suppress the drug-resistant subclones. However, there remain several open challenges in designing adaptive therapies, particularly in extending this approach to multiple drugs. Furthermore, the immune system also plays a role in preventing and controlling cancers. Life history theory may help to explain the variation in immune cell levels across the tree of life that likely contributes to variance in cancer prevalence across vertebrates. However, this has not been previously explored. This work 1) describes resistance management for cancer, lessons cancer researchers learned from farmers since adaptive evolutionary strategies were inspired by the management of resistance in agricultural pests, 2) demonstrates how adaptive therapy protocols work with gemcitabine and capecitabine in a hormone-refractory breast cancer mouse model, 3) tests for a relationship between life history strategy and the immune system, and tests for an effect of immune cells levels on cancer prevalence across vertebrates, and 4) provides a novel approach to improve the teaching of life history theory. This work applies lessons that cancer researchers learned from pest managers, who face similar issues of pesticide resistance, to control cancers. It represents the first time that multiple drugs have been used in adaptive therapy for cancer, and the first time that adaptive therapy has been used on hormone-refractory breast cancer. I found that this evolutionary approach to cancer treatment prolongs survival in mice and also selects for the slow life history strategy. I also discovered that species with slower life histories have higher concentrations of white blood cells and a higher percentage of heterophils, monocytes and segmented neutrophils. Moreover, larger platelet size is associated with higher cancer prevalence in mammals.

Adaptive therapy utilizes competitive interactions between resistant and sensitive cells by keeping some sensitive cells to control tumor burden with the aim of increasing overall survival and time to progression. The use of adaptive therapy to treat breast cancer, ovarian cancer, and pancreatic cancer in preclinical models has shown significant results in controlling tumor growth. The adaptive therapy model comes from the integrated pest management agricultural strategy, predator prey model, and the unique intra- and inter-tumor heterogeneity of tumors. The purpose of this thesis is to analyze and compare gemcitabine dose response on hormone refractory breast cancer cells retrieved from mice using an adaptive therapy strategy with standard therapy treatment. In this study, we compared intermittent (drug holiday) adaptive therapy with maximum tolerated dose therapy. The MCF7 resistant cell lines to both fulvestrant and palbociclib were injected into the mammary fat pads of 8 weeks old NOD/SCID gamma (NSG) mice which were then treated with gemcitabine. Tumor burden graphs were made to track tumor growth/decline during different treatments while Drug Dose Response (DDR) curves were made to test the sensitivity of the cell lines to the drug gemcitabine. The tumor burden graphs showed success in controlling the tumor burden with intermittent treatment. The DDR curves showed a positive result in using the adaptive therapy treatment method to treat mice with gemcitabine. Due to some fluctuating DDR results, the sensitivity of the cell lines to gemcitabine needs to be further studied by repeating the DDR experiment on the other mice cell lines for stronger results.

A big part of understanding cancer is understanding the cellular environment itthrives in by analyzing it from a microecological perspective. Humans and other species are affected by different cancer types, and this highlights the notion that there may be a correlation between specific tissues and neoplasia prevalence. Research shows that humans are the most susceptible to adenocarcinomas and carcinomas which include the following tissues: lungs, breast, prostate, and pancreas. Furthermore, research shows that adenocarcinoma accounts for 38.5% of all lung cancer cases, 20% of small cell carcinomas, and 2.9% of large cell carcinoma. The incidence of the most common cancer types in humans is consistently increasing annually. This study analyzes trends of tissue-specific cancers across species to examine possible contributors to vulnerability to cancer. I predicted that adenocarcinomas would be the most prevalent cancer type across the tree of life. To test this hypothesis, I reviewed over 130 species that reported equal to or greater than 50 individual necropsy pathology records across 4 classes (Mammalia, amphibia, Reptilia, Aves) and ranked them by neoplasia prevalence. This information was then organized in tables in descending order. The study’s resulting tables and data concluded that the hypothesis was correct. I found that across all species adenocarcinomas were the most common cancer type and account for 30.4% of malignancies reported among species. Future research should investigate how organ size contributes to neoplasia prevalence.

The Patient Guidance Project was created by a team of research assistants in the Arizona Cancer Evolution Center as a source of supplemental education and support for recently diagnosed cancer patients. Extensive background research in the form of literature reviews highlighted disparities between the information patients want and are receiving, as well as between average literacy levels of patients and the literacy levels at which cancer information is commonly provided. The Patient Guidance Project has published comprehensive guides for specific types of cancer, which so far include metastatic melanoma, glioblastoma, prostate cancer, oral cancer, kidney cancer, breast cancer, and colorectal cancer. The content of the guides is intended to bridge the gaps in information for patients with an emphasis on treatment options, treatment side effects, and psychological support resources, which surveys have identified as the topics patients want information on most. Written at a sixth-grade literacy level, which over half of adults in the U.S. read at, the guides are meant to be of benefit to as many people as possible. In the future, the team hopes to expand the Patient Guidance Project to include more cancer types, guides in different languages, and multimodal features to increase their effectiveness.

Cancer is a problem of multicellularity, making it a problem across all species. This pervasiveness has led to much research into the defense and the pathology of the disease. Previously, studies have been limited in sample size, taxonomic breadth, and comparative methods to explain and understand the data available. Here, we have access to life history and cancer risk data of 17,563 individuals for 327 species, spanning across three monophyletic clades: Amphibians, Sauropsids, and Mammals. Comparative biology’s approach to cross-species cancer prevalence is crucial to the identification of species that are uniquely resistant to cancer as well as stratifying risk across a phylogeny based on the life history framework. Using the life history framework, alongside a multitude of life history data, was able to find that neoplasia prevalence increases with adult weight and longevity, but decreases with gestation time. It was also discovered that malignancy prevalence decreases with gestation time. Gestation and adult weight are also both significant predictors of neoplasia and malignancy prevalence when controlling for the other. On an evolutionary scale, cancer risk appears to be best described by sudden shifts in cancer prevalence followed by stabilizing selection of that trait. The understanding of increases and decreases of cancer risk across species could create better insight on human’s own cancer risk, as well as disease prevention in humans.