title: Pharmacological modification of RNA surveillance in microsatellite-unstable colorectal cancer
creator: Becker, Jonas Philipp
subject: ddc-570
subject: 570 Life sciences
description: Microsatellite-unstable colorectal cancers are characterized by the accumulation of somatic insertion/deletion mutations in repetitive DNA stretches termed microsatellites. Two-thirds of these mutations cause a shift of the reading frame thus encoding for tumor-specific protein sequences. HLA class I-presented peptides derived from such frameshifted protein sequences, termed InDel neoepitopes, allow patrolling CD8+ T cells to identify and target the presenting tumor cell. The expression of frameshifted protein sequences, and therefore the HLA class I-mediated presentation of InDel neoepitopes, is, however, limited by nonsense-mediated RNA decay (NMD), a translation-dependent quality control pathway that recognizes and degrades mRNAs with premature termination codons introduced by nonsense or frameshift mutations. In the context of microsatellite-unstable cancers, pharmacological NMD inhibition is therefore hypothesized to provide clinical benefit by increasing the abundance of HLA class I-presented InDel neoepitopes on cancer cells and thus their immune recognition. In this thesis, a mass spectrometry-based approach was established to identify neoepitopes and investigate the effect of pharmacological NMD inhibition on HLA class I-presented peptides and neoepitopes.  For the identification of HLA class I-presented peptides, a previously published high-throughput protocol was extended and tailored for the identification of frameshift-derived InDel neoepitopes. To this end, standard mass spectrometry fragmentation and precursor selection methods were combined with advanced methodologies providing deep coverage of the immunopeptidome and additional sequence information on the identified peptides. Together with cell line-specific protein databases based, e.g., on publicly available sequencing data, this enabled the unbiased, mass spectrometry-based identification of InDel neoepitopes.  Using a label-free quantification approach integrating untargeted and targeted MS2 data, it was shown that pharmacological NMD inhibition by the approved drug 5-azacytidine augments the HLA class I-mediated presentation of peptides, including InDel neoepitopes, derived from NMD-targeted transcripts. Moreover, the mutation underlying one of the previously unknown InDel neoepitopes exhibits a high frequency in microsatellite-unstable cancer cell lines and colorectal cancer patients, and in vivo immunization with the InDel neoepitope induces strong CD8+ T cell responses in an HLA-humanized mouse model.  Taken together, the presented work provides an extendable immunopeptidomics platform for neoepitope discovery utilizing sequencing data and advanced mass spectrometry. The use of this platform allowed for the first time the unbiased, mass spectrometry-based identification of previously unknown, immunogenic InDel neoepitopes. Moreover, it was shown that NMD inhibition by 5-azacytidine augments HLA class I-mediated InDel neoepitope presentation suggesting that future immunotherapeutic strategies for microsatellite-unstable cancers may benefit from a combination with NMD inhibition, thereby turning cancer cells into easily identifiable targets for tumor-specific T cells.
date: 2021
type: Dissertation
type: info:eu-repo/semantics/doctoralThesis
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/30306/1/Becker_2021_dissertation_final.pdf
identifier: DOI:10.11588/heidok.00030306
identifier: urn:nbn:de:bsz:16-heidok-303067
identifier:   Becker, Jonas Philipp  (2021) Pharmacological modification of RNA surveillance in microsatellite-unstable colorectal cancer.  [Dissertation]     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/30306/
rights: info:eu-repo/semantics/openAccess
rights: Please see front page of the work (Sorry, Dublin Core plugin does not recognise license id)
language: eng