Abramson Cancer Center Support Grant

University Of Pennsylvania, Philadelphia PA

Investigators

Linked publications & trials

Abstract

PROJECT SUMMARY This project seeks to develop, apply, and disseminate informatics tools for building a Childhood Cancer Isoform Atlas, enabling multiomics-augmented and big data-informed studies of alternative isoform variation and resulting immunotherapy targets using Childhood Cancer Data Initiative (CCDI) data. Alternative splicing (AS) is a prevalent mechanism for generating transcriptomic and proteomic diversity. AS is frequently dysregulated in cancer cells and contributes to the various “hallmarks of cancer”. Compelling evidence suggests that protein isoforms resulting from dysregulated AS represent a vast yet understudied repertoire of tumor antigens and potential targets for cancer immunotherapy. Thus, a systematic exploration of alternative isoform variation in CCDI and other pediatric cancer data repositories will enhance our understanding of cancer pathophysiology and accelerate clinical translation through the discovery of novel biomarkers and therapeutic targets. The accumulation of large-scale RNA-seq, proteomic, and clinical data in pediatric cancer data repositories, including data held in the CCDI Data Ecosystem, provides unprecedented opportunities to uncover the biological significance and therapeutic potential of alternative isoform variation in pediatric cancer. Advances in long-read RNA-seq strategies for transcriptome analysis and proteotranscriptomic data integration enable the comprehensive determination of full-length transcript and protein isoforms as well as the resulting antigen repertoire of pediatric cancer. However, to make full use of these cutting-edge technologies and rapidly growing data resources, robust, scalable, and user-friendly informatics tools are needed. Our multidisciplinary team has deep expertise in computational biology, transcriptomics, and multiomics data integration (Xing), as well as clinical pediatric oncology, pediatric hematological malignancies, and cancer epidemiology (Aplenc). We have developed and disseminated innovative algorithms and widely used software for characterizing AS and isoform variation using short-read and long-read RNA-seq data (rMATS, ESPRESSO), and for discovering AS-derived cancer immunotherapy targets (IRIS, IRIS-long). Building on our expertise, we will apply and enhance our informatics tools to: 1) define the landscape of alternative isoform variation, 2) discover immunotherapy targets, and 3) integrate and visualize data on alternative isoforms and immunotherapy targets in pediatric cancer. The proposed research is directly responsive to the objectives of the RFA seeking studies that involve the 1) aggregation, integration, analysis, and visualization of CCDI datasets, and 2) development and deposition of new tools into the CCDI data ecosystem to enhance data re-use. All software developed in this project will be made open source, readily usable on NCI-supported cloud computing systems, and freely available to the research community. Overall, this project will generate broadly applicable tools and novel resources to enhance the utility of CCDI data for elucidating alternative isoform variation and discovering novel immunotherapy targets for hard-to-treat pediatric cancers.