Abstract 7414: Claire: a search engine leveraging deep databases for reliable detection of peptides, with a special focus on proteogenomic applications

Abstract

Abstract As the field of cancer diagnostics and treatment evolves, the significance of peptides characterized by post-translational modifications and amino acid substitutions is becoming increasingly prominent. These molecular alterations frequently offer critical insights into tumor biology, aiding the development of targeted therapies and methods for personalized medicine. However, despite ongoing advances in shotgun proteomics, the field still faces multiple challenges for the reliable detection of rare peptide forms, for instance, amino acid substitutions when the corresponding DNA or RNA sequencing is unavailable. As a response to these challenges, our group has developed Claire—a probabilistic search engine employing large peptide databases for detection. These databases, often on the terabyte scale, further incorporate the estimates of peptides' prior probabilities to improve detection accuracy and utilize several optimizations to allow fast interpretation of tandem mass spectra. Claire outperformed state-of-the-art software, such as MSFragger and TagGraph when evaluated on the protein-level detection of single nucleotide variants in the public NCI60 proteome dataset. Further, Claire's analysis of a range of NCI60 datasets revealed high protein-level mutational burdens in genomically unstable cancer cell lines and detected mislabeling and contamination across several omics datasets. In a clinical domain, Claire discerned the hypermutation status of colorectal cancer patients' tumors, identifying candidates suitable for immunotherapy. Protein-level variation in peripheral blood mononuclear cells also recognized individuals, monozygotic twins aside, revealing the pseudonymous nature of germline proteome datasets, and raising the need for their protection. From a computational perspective, Claire can be run as a standalone software in the Linux operating system, or its capabilities accessed remotely using an interface on our cloud computing infrastructure. Claire has thus shown remarkable potential in enhancing peptide detection, offers substantial advancements for both clinical and research applications, and allows direct incorporation of its capabilities into various computational workflows. Citation Format: Miroslav Hruska, Petr Dzubak, Marian Hajduch. Claire: a search engine leveraging deep databases for reliable detection of peptides, with a special focus on proteogenomic applications [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(6_Suppl):Abstract nr 7414.