Project Summary Despite advances in treatment, sarcomas like rhabdoid tumors and desmoplastic small round cell tumors (DSRCT) remain challenging, with frequent therapy resistance and fatal outcomes. The rarity of these cancers (<1 case per 1,000,000 people per year for each type) and the limitations of current genomics and proteomics methods underscore a critical need for innovative approaches to discover improved targets for therapy. Our project aims to propel the study of ultra-rare cancers by integrating cutting-edge genomic and proteomic technologies to uncover tumor-specific biological mechanisms and therapeutic targets, as envisioned by the FDA Oncology Center of Excellence. Our overarching goal is to elucidate the fundamental biological processes and molecular mechanisms driving cancer pathogenesis, specifically for rare cancers such as rhabdoid and DSRCT tumors. By defining their tumor-specific proteomes, we seek to enable the discovery of specific therapeutic targets to improve the survival rates of children and adults facing these refractory cancers. Leveraging a unique MSK cohort of over 80,000 diverse patients with active disease, including those with rhabdoid and DSRCT tumors, we propose a synthetic integration of long-read sequencing of bulk DNA, bulk RNA and single cell RNA, and high-resolution multidimensional mass spectrometry proteomics. This approach will enable us to construct comprehensive maps of tumor-specific cell surface proteomes, revealing neomorphic gene products and non-canonical protein isoforms. In Aim 1, we will delineate tumor-specific neomorphic and non-canonical cell-surface gene transcripts through the combined use of integrative long-read and single-cell sequencing. Aim 2 will define the expression of neomorphic cell surface proteins directly using integrative mass spectrometry proteogenomic approaches, focusing on non-canonical proteoforms and their tumor-specific post-translational modifications. This approach includes rigorous technical validation measures and aims to contribute to the NIH Cancer Data Science Initiative’s vision for an open data cancer ecosystem. By addressing the critical gap in current cancer research methodologies and focusing on rare rhabdoid and DSRCT tumors, this project stands to make a significant impact on the understanding and treatment of ultra-rare cancers, paving the way for the development of targeted therapies and improving patient outcomes.