Friday, July 26, 2024
7/26/2024
PROJECT SUMMARY/ABSTRACT Osteosarcoma, the most common primary tumor of bone, primarily affects children, adolescents, and young adults. A diagnosis of osteosarcoma is devastating, as approximately half of pediatric osteosarcoma patients experience metastasis and ultimately succumb to the disease within 10 years of their diagnosis. Currently there is no diagnostic test to predict prognosis, so all patients are treated with aggressive surgery and intense chemotherapy with high rates of toxicity. However, a subset of patients may not require as aggressive therapy to achieve remission. Additionally, those that survive have a high incidence of lifelong morbidities, including treatment-related secondary malignancies. Accurate prognostic indicators could be integrated into the standard of care for osteosarcoma to guide therapy. Children with more favorable prognoses could be treated more conservatively, reducing the need for aggressive surgery, and decreasing the intensity of systemic therapy. This would decrease the likelihood and severity of long-term morbidities, and reduce the probability of secondary, treatment-related malignancies without negatively affecting prognosis. Conversely, patients with a worse prognosis could receive more aggressive treatments or be guided to experimental clinical trials to improve their long-term survival. In this project, we will develop a serum exosomal gene signature associated with prognosis in pediatric osteosarcoma. Exosomes are membrane-bound microvesicles containing cargo associated with tumor biology and disease state. We will first identify biomarkers by sequencing serum exosomes from a large cohort of pediatric osteosarcoma patients with known clinical outcomes. We will then identify genes associated with metastatic propensity using xenograft mouse models established from pediatric osteosarcomas with distinct biologic behavior. We will analyze co-regulated gene clusters and apply machine learning, improving sensitivity and specificity, and ultimately resulting in a more robust gene signature. The osteosarcoma gene signature developed in this project can be utilized in the clinical setting to predict prognosis, stratifying patients into more appropriate treatment categories, and having the potential to improve management of this devastating disease. Additionally, these biomarkers will contribute to our understanding of the biological behavior and progression of osteosarcoma, allowing us to infer mechanisms of host response, metastasis, and response to therapy. Importantly, this K01 is critical to advancing my career as a translational scientist by providing the necessary protected time and dedicated resources to perform high-quality, clinically relevant research, under the guidance of an exceptional multidisciplinary mentor team. This award will facilitate my transition to independence, as the data procured in this project will allow me to be competitive for future independent funding applications. Additionally, as I complete these aims, I will develop the necessary knowledge and leadership skills of a successful independent research scientist specializing in exosome biology and translational models of pediatric osteosarcoma and ultimately expanding to other cancers.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
