Current preclinical testing for cancer therapeutics generally consists of small animal (typically murine) studies followed by studies in primates to quickly assess gross toxicities prior to moving into phase I trials. To further complicate things, preclinical studies are often performed on young, lean, inbred, specific pathogen free (SPF) organisms which do not accurately reflect the demographic of the typical cancer patient. To address these discrepancies, our site is specifically proposing to utilize the unique environment at UC Davis which will combine basic research using murine models and large animal models, namely canines, from the UC Davis School of Veterinary Medicine. In addition to the multi-species comparisons, we are uniquely suited to address age and BMI related responses, which have not been extensively determined in any one model, yet alone confirmed across multiple species. We will extensively characterize and integrate responses based on a variety of assays and look for commonalities as predictable markers of outcomes focusing on differences with age and BMI to demonstrate that preclinical models need to be reflective of the cancer patient phenotype. Finally, we will be validating our findings using samples from both murine and canine tumor models, again another unique attribute specific to UC Davis which has access to canine cancer patients through the Veterinary Medical Teaching Hospital. Overall, our grant proposal ties into our collaborative proposal, which aims to link three specialized laboratories in a multi-disciplinary collaborative study to improve the utility of mouse cancer and tumor models for translational research. Each linked proposal will integrate imaging sciences, immunology, and pathobiology to advance current standard practices of using lean, young, SPF models and cell-culture-derived tumors into demographically appropriate mouse models with a shared focus on utilization of the mammary intraepithelial neoplasia outgrowth (MINO) model of human pre-cancer (provided by Dr. Cardiff's laboratory). The findings from our studies will together address the current incongruence between preclinical and clinical outcomes, and also demonstrate means to overcome these limitations through defining more appropriate models that will increase translatability into the clinic.
Current means of preclinical testing have come under scrutiny for their inaccuracies in predicting toxicities in response to cancer therapies in human clinical trials. Cancer is a disease of the aged, and with the rising pandemic of obesity, the 'typical' cancer patient phenotype is not accurately reflected in the usage of young lean animal models. Therefore, we are proposing to improve preclinical testing by more accurately reflecting patient characteristics, including age and body fat content into preclinical models. We are proposing that the inflammatory profiles present in aged and obese models are directly correlative to the potential for adverse reactions in individuals undergoing cancer therapy, a tenet central to deciding appropriate animal model use preclinically.
