As cancer progresses, its impact should manifest in the foraging behavior of its host much like the effects of endo-parasites that hinder foraging aptitudes and risk management abilities. Furthermore, the lifestyle of the host can impact tumor growth and quality of life. To approach these questions, we conducted novel experiments by letting C57BL/6 laboratory mice, with or without oral squamous cell carcinoma, free range in a large outdoor vivarium. Our goals were to: (1) determine whether one could conduct experiments with a mouse model under free range conditions, (2) measure effects of cancer burden on foraging metrics, (3) compare tumor growth rates with laboratory housed mice, and (4) begin to sort out confounding factors such as diet. With or without cancer, the C57BL/6 laboratory mice dealt with natural climatic conditions and illumination, found shelter or dug burrows, sought out food from experimental food patches, and responded to risk factors associated with microhabitat by foraging more thoroughly in food patches under bush (safe) than in the open (risky). We quantified foraging using giving-up densities of food left behind in the food patches. The mice’s patch use changed over time, and was affected by disease status, sex, and microhabitat. Males, which were larger, consumed more food and had lower giving-up densities than females. Relative to cancer-free mice, mice with growing tumors lost weight, harvested more food, and increasingly relied on patches in the bush microhabitat. The tumors of free-ranging mice in the vivarium grew slower than those of their cohort that were housed in mouse cages in animal facilities. Numerous interesting factors could explain the difference in tumor growth rates: activity levels, stress, weather, food intake, diet, and more. To tease apart one of these intertwined factors, we found that tumors grew faster when mice in the laboratory were fed on millet rather than laboratory mouse chow. While just a start, these novel experiments and framework show how free-ranging mice provide a model that can test a broader range of hypotheses and use a broader range of metrics regarding cancer progression and its consequences for the host.
Tumor Growth Rates Derived from Data for Patients in a Clinical Trial Correlate Strongly with Patient Survival: A Novel Strategy for Evaluation of Clinical Trial Data