Abstract 4396: A bioinformatics approach for cancer immunotherapeutic target identification by evaluating surfaceome gene and protein expression (CITIESGAPE) in tumor and pan-normal tissues

Abstract

Abstract Targeted therapeutic strategies and some immunotherapies for cancer including but not limited to therapeutic antibodies, antibody-drug conjugates (ADCs) and CAR-T cells therapy demand precisely targeting cell-surface proteins that are distinctively expressed by cancer cells. We developed a robust analytical tool for cancer immunotherapeutic target identification by evaluating surfaceome gene and protein expression (CITIESGAPE) that are uniquely overrepresented by the tumor in contrast to pan-normal tissues. The first step was to run differential expression testing on RNA-seq transcriptome of cancer (for example, data from TARGET and TCGA) against each normal tissue (31 tissues from GTEx_v8), from which candidate genes were defined as those are higher expressed in tumor than all normal tissues (minimum LogFC > 1 and maximum q < 0.05). We then validated the protein expression level of candidate genes through the Human Protein Atlas (HPA) and ProteomicsDB (The latter includes mass spectrometry-based label-free proteomic data of some tumor cells and 39 normal tissues). The final and crucial step was to run surfaceome protein predicting using the COMPARTMENTS database, the HPA database and the Membranome database (v2.0), depending on an optimized confidence score. We have applied this analytical pipeline to search surfaceome proteins that are unique to Osteosarcoma, a common primary malignant bone tumor in children and young adults, and obtained 57 candidates that are potential immunotherapeutic targets. To date, eight of the top confident candidates have been further validated in clinical samples, patient-derived cell lines and xenograft models. We believe this robust analytical tool could be adaptable to other types/subtypes of cancer in searching of candidate surfaceome proteins for targeted therapy and immunotherapy, as well as precision medicine and personalized therapy. Citation Format: Xiangjun Tian, Jing Wang, Yifei Wang, Zhongting Zhang, Michael Roth, Jonathan B. Gill, Richard Gorlick. A bioinformatics approach for cancer immunotherapeutic target identification by evaluating surfaceome gene and protein expression (CITIESGAPE) in tumor and pan-normal tissues [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4396.