Abstract LB107: Identification of a promising renal cell carcinoma target using a unique in silico approach
Authors: Musch Alexandra , Peille Anne-Lise , Hasani Hoor Al , Fiebig Heinz-Herbert , Vuaroqueaux Vincent 
Published: July 2021

Abstract
In 2020, kidney cancers accounted for more than 4.1% of new cancer cases worldwide. Among these, more than 90% were renal cell carcinoma (RCC), a very heterogenous disease consisting of 3 major subtypes: chromophobe , papillary and clear cell. These subtypes differ in histology, genetic alterations, clinical outcome and therapeutic response. Over the last decades, great advances in the treatment of RCC have been made with additional targeting agents inhibiting RTKs, VEGFR and mTORC1. However, for local RCC surgery remains the main treatment modality whereas metastatic RCC is still difficult to treat due to chemoresistance. Antibody drug conjugates (ADC) or small molecule drug conjugates (SMDC) are emerging approaches for the treatment of cancer patients. By coupling highly potent chemotherapeutic agents to a specific antibody/small molecule, tumor cells can be selectively targeted allowing treatment with higher drug doses leading to an enhanced efficacy, while maintaining low toxicity in healthy tissues. 4HF Biotec has developed a proprietary database containing, among others, curated molecular data from tumor patient samples, preclinical models (cell lines, cell line-derived xenografts, and patient-derived xenografts) and normal tissues. Using this platform, we established a unique methodology to identify and prioritize genes that could be targeted by ADCs/SMDCs. By performing bioinformatics analyses of this molecular data, we identified genes that are differentially expressed across cancer (sub)types. We further selected those that are overexpressed in the tumor entity compared to matching normal tissue and in the tumor entity compared to all normal tissues. The overlapping genes were assessed in preclinical models to confirm their tumor-specificity. For the final selection, we investigated target druggability by curating data regarding protein function, targetability and localization. With this approach, we identified a total of 374 potential drug targets across 15 cancer (sub)types for the development of ADCs or SMDCs. Analyses of kidney cancer identified Semaphorin 5B (SEMA5B) among the top candidates. SEMA5B was significantly upregulated in patient samples of the kidney compared to other tumor entities. Comparison with normal kidney samples revealed a significant higher expression in tumor samples. In addition to the expression profiles, association between SEMA5B expression and clinical and molecular features will be presented. Furthermore, we will present curated information about protein function and structure that will facilitate antibody generation. Our findings indicate that targeting SEMA5B on tumor cells could represent a new therapeutic option in the treatment of renal cancer.
Citation Format: Alexandra Musch, Anne-Lise Peille, Hoor Al Hasani, Heinz-Herbert Fiebig, Vincent Vuaroqueaux. Identification of a promising renal cell carcinoma target using a unique in silico approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB107.