Abstract 4515: PIONEER: harnessing multi-omics data to enhance immunotherapeutic target discovery and development

Abstract

Abstract Introduction: Immunotherapeutic strategies have produced remarkable results in some malignancies. However, optimal cell surface targets in many childhood cancers remain elusive and tools for novel target discovery are limited. We developed a proteogenomic approach to identify high confidence cell surface proteins for immunotherapy development and applied it to neuroblastoma, an often fatal childhood cancer. Through the Pediatric Immunotherapy Discovery and Development Network (PI-DDN), we have extended this approach to 14 high-risk childhood cancers. This effort includes MS-based surfaceome data generation for 175 patient-derived xenograft (PDX) models, 30 primary patient tumors, and 10 human derived cell line models. Methods/Results: To optimize the utility of our approach and data, we are developing a web-based application called PIONEER (Pediatric Integrative Omics Network Enhancing Early Research). The goal of PIONEER is to disseminate data to the broader scientific community and to provide the necessary analysis, query and visualization tools to make these data accessible to everyone, regardless of computational expertise. A pilot version of PIONEER was developed using R Shiny Dashboard and is derived from our neuroblastoma efforts. The application is comprised of two main categories: (1) target discovery data and prioritization (2) target validation and preclinical development. Modules include proteomics, transcriptomics, epigenomics, multi-omics, validation and pre-clinical drug development. Cancer ‘omics data currently housed in PIONEER include tumor and cancer cell line mass-spectrometry based proteomics, RNA-sequencing, and chromatin immunoprecipitation (ChIP) sequencing. Extensive normal tissue expression data from GTEx and mass spectrometry will be integrated. Surface proteins are prioritized through an integrative multi-omic analysis of tumor and normal tissue data. Users can perform queries and cancer subtype and cross-histotype studies, apply custom cutoffs, and generate plots for visualization. We are currently adding functionality to support automatic data analysis and integration for surface proteins (SPACE: Surface Protein Analysis for Collaborative Efforts). Through the target validation and preclinical development modules, users can view an antibody repository, immunofluorescence, immunohistochemistry, drugs in development for each protein, and efficacy in patient derived xenograft models. PIONEER will be deployed using R Connect; data for additional histotypes will be incorporated as available. Conclusion: PIONEER will provide a comprehensive characterization of the surfaceome of high-risk pediatric cancers and a web-based application for data integration, visualization and sharing. This interface facilitates the discovery of optimal immunotherapeutic drug targets in high-risk childhood cancers. Citation Format: Amber K. Weiner, Hemma Murali, Rawan Shraim, Karina L. Conkrite, Alexander B. Radaoui, Daniel Martinez, Brian Mooney, Sandra E. Spencer Miko, Gian Negri, Alberto Delaidelli, Caitlyn de Jong, Yuankun Zhu, Allison P. Heath, Jennifer Pogoriler, Yael P. Mosse, Deanne M. Taylor, Poul H. Sorensen, Gregg B. Morin, Benjamin A. Garcia, John M. Maris, Sharon J. Diskin. PIONEER: harnessing multi-omics data to enhance immunotherapeutic target discovery and development. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4515.