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- Herbst, SA, et al.
(författare)
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Proteogenomics refines the molecular classification of chronic lymphocytic leukemia
- 2022
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1, s. 6226-
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Tidskriftsartikel (refereegranskat)abstract
- Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.
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- Kurzawa, N, et al.
(författare)
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Deep thermal profiling for detection of functional proteoform groups
- 2023
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Ingår i: Nature chemical biology. - : Springer Science and Business Media LLC. - 1552-4469 .- 1552-4450. ; 19:8, s. 962-
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Tidskriftsartikel (refereegranskat)abstract
- The complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematically. Here we applied thermal proteome profiling with deep peptide coverage to detect functional proteoform groups in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detected 15,846 proteoforms, capturing differently spliced, cleaved and post-translationally modified proteins expressed from 9,290 genes. We identified differential co-aggregation of proteoform pairs and established links to disease biology. Moreover, we systematically made use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach, thus, provides a powerful and unique tool for systematic detection and functional annotation of proteoform groups.
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- Peltonen, K, et al.
(författare)
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Therapeutic Cancer Vaccination with Immunopeptidomics-Discovered Antigens Confers Protective Antitumor Efficacy
- 2021
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 13:14
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Tidskriftsartikel (refereegranskat)abstract
- Knowledge of clinically targetable tumor antigens is becoming vital for broader design and utility of therapeutic cancer vaccines. This information is obtained reliably by directly interrogating the MHC-I presented peptide ligands, the immunopeptidome, with state-of-the-art mass spectrometry. Our manuscript describes direct identification of novel tumor antigens for an aggressive triple-negative breast cancer model. Immunopeptidome profiling revealed 2481 unique antigens, among them a novel ERV antigen originating from an endogenous retrovirus element. The clinical benefit and tumor control potential of the identified tumor antigens and ERV antigen were studied in a preclinical model using two vaccine platforms and therapeutic settings. Prominent control of established tumors was achieved using an oncolytic adenovirus platform designed for flexible and specific tumor targeting, namely PeptiCRAd. Our study presents a pipeline integrating immunopeptidome analysis-driven antigen discovery with a therapeutic cancer vaccine platform for improved personalized oncolytic immunotherapy.
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