Abstract 4689: 4HF CancerDataMiner platform accelerates target discovery and evaluation

Abstract For the management of metastasized cancer, tumor-targeted chemotherapies with improved therapeutic index are urgently needed. Over the last 25 years, antibody drug conjugates (ADCs) targeting cancer-associated proteins have emerged as a promising new treatment modality. While the first ADCs were registered for the treatment of acute leukemias and lymphomas, more recently at least six ADCs were approved by the FDA for solid tumors. Despite these successes, clinical development of ADCs remains a risky exercise as evident from the failure of more than 20 pivotal clinical phase III trials. A narrow therapeutic index due to excessive toxicity of potent payloads, little therapeutic activity, and difficulties in chemistry, manufacturing, and controls were among the limiting factors. Meanwhile, ADC technology and production have advanced substantially. More than 100 ADCs are currently in clinical development in approximately 600 clinical trials, with some of the investigated ADCs being close to approval. While issues related to ADC linkers and payloads have been extensively investigated and many problems have been solved, the choice of molecular targets for ADCs remains challenging. This is, in part, due to a lack of information about candidate targets: while knowledge about generally accepted cancer targets such as ERBB2 is abundant, data about many novel targets is still scarce. In particular, reliable information about expression in normal tissues, subcellular localization and protein function is often missing. 4HF Biotec has established the CancerDataMiner, an in-silico platform dedicated to cancer data mining by integrating large OMICS datasets that are connected and aligned. It allows molecular analyses of all human genes in 12, 000 tumor samples and 14, 000 normal tissues, using proprietary tools and widgets for visualization and statistics. Target evaluations are performed at the DNA, RNA and protein levels and employ complementary tools such as pathway analysis and literature search to obtain a comprehensive picture of candidate targets. Using this approach, we recently reviewed the molecular targets of all ADCs that either have already received approval or are in clinical development. As proof-of-concept for the CancerDataMiner, here we analyze targets of ADCs and compare our findings with the clinical data obtained for those ADCs. The profiles of selected ADC targets will be discussed, among them CD79B and CD33 for hematologic malignancies and FOLR1 and Claudin 18. 2 for solid cancers. We will demonstrate that proteins with very diverse profiles can make good ADC targets. In conclusion, the 4HF CancerDataMiner is a platform which has proven its value for the identification and characterization of cancer-associated targets for ADC development for all tumor types. Citation Format: Heinz-Herbert Fiebig, Anne-Lise Peille, Mirko Schmitz, Vincent Vuaroqueaux, Thomas Metz. 4HF CancerDataMiner platform accelerates target discovery and evaluation abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 4689.