Abstract 2191 Unveiling the Target: Investigating the Protective Potential of EnsembleMHC-Predicted T-Cell Epitopes against Metastatic Osteosarcoma

Childhood cancer ranks as the third leading cause of death in children and adolescents in the U.S. Osteosarcoma, a malignant bone cancer, primarily affects those aged 10 to 20. Originating in the long bone it will typically metastisize to the lungs. Metastatic osteosarcoma is an aggressive disease and has a five-year survival rate of less than 30%. Significant progress has been made in primary osteosarcoma treatment, but metastatic osteosarcoma remains a challenge because it can evade and shut down the immune system. The current treatment options are chemotherapy and surgical resection, but cancer immunotherapy shows promise and is currently being tested as a treatment option. Cancer immunotherapy harnesses the power of the immune system to target and eliminate abnormal cells. Cancer cells can express inhibitory ligands, such as PD-L1 and CTLA4, that will halt a T-cell response. A T-cell response is vital in eliminating cancer cells. Research focusing on immune checkpoint inhibitors to reinvigorate T-cells to kill metastatic osteosarcoma within a mouse model has been conducted. Blocking PD-1/PD-L1 and CTLA4 interactions with antibodies and blocking inhibitory ligands prevents T-cell inhibition, allowing sustained cancer elimination. To further understand the immune response against metastatic osteosarcoma when treated with immune checkpoint inhibitors, we must define the epitopes the T-cells target. Epitopes are specific regions of molecules, including proteins and macromolecules, that are recognized by the immune system. T-cells require epitopes to be presented on Major Histocompatibility Complexes (MHC) to activate and kill infected and cancer cells. Neoepitopes are mutated self-proteins unique to cancer cells, allowing T-cells to target and kill the cancer while minimizing harm to healthy tissue. Defining the epitopes T-cells target can further our knowledge of the immune response against metastatic osteosarcoma and improve cancer immunotherapies. RNAseq and Epitope Prediction Modeling (EPM) software are great tools that will help identify critical epitopes. EPM software called EnsembleMHC has been created and has been deemed the most accurate of its kind. It determined the most common epitopes of SARS-CoV-2 the T-cells were targeting and whether a patient would have a poor outcome based on if they could effectively present them to their T-cells. Computational tools like this have advanced research without relying on living organisms. EnsembleMHC's prediction accuracy will be tested with metastatic osteosarcoma and further validated in a living mouse model. Using a metastatic osteosarcoma mouse model, confounding variables not accounted for within EnsembleMHC will be evaluated. This proposal's primary goal is to determine what neoepitopes are being targeted by the immune system to combat metastatic osteosarcoma. We will accomplish this by comparing two cell lines: K7M2 mouse metastatic osteosarcoma cell line and the precursor cell (osteoblasts). We will perform RNAseq on the above cell lines, compare their differences, and process the sequences through EnsembleMHC. Once we have computed the epitopes for metastatic osteosarcoma, we will test their protective nature within our mouse model. We will vaccinate the mice by injecting them with the predicted neoepitope proteins and the mice will then be challenged with K7M2 metastatic osteosarcoma cells. If the predicted neoepitopes are protective, the vaccinated group of mice will mount an immune response and eliminate the cancer.