Analysis of Wilms' tumor protein 1 specific TCR repertoire in AML patients uncovers higher diversity in patients in remission than in relapsed.

Autor: Gielis S; Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium.; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium.; Biomedical Informatics Research Network Antwerp (Biomina), University of Antwerp, Antwerp, Belgium., Flumens D; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Edegem, Belgium., van der Heijden S; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Edegem, Belgium.; Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium., Versteven M; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Edegem, Belgium., De Reu H; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Edegem, Belgium., Bartholomeus E; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium.; Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.; Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium., Schippers J; Genetics, Pharmacology and Physiopathology of Heart, Blood Vessels and Skeleton (GENCOR) department, University of Antwerp, Edegem, Belgium., Campillo-Davo D; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Edegem, Belgium., Berneman ZN; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Edegem, Belgium.; Center for Cell Therapy & Regenerative Medicine (CCRG), Antwerp University Hospital, Edegem, Belgium., Anguille S; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Edegem, Belgium.; Center for Cell Therapy & Regenerative Medicine (CCRG), Antwerp University Hospital, Edegem, Belgium.; Division of Hematology, Antwerp University Hospital, Edegem, Belgium., Smits E; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium.; Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium.; Center for Cell Therapy & Regenerative Medicine (CCRG), Antwerp University Hospital, Edegem, Belgium., Ogunjimi B; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium.; Department of Paediatrics, Antwerp University Hospital, Edegem, Belgium.; Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.; Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium., Lion E; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium.; Laboratory of Experimental Hematology (LEH), Vaccine & Infectious Disease Institute (VAXINFECTIO), Faculty of Medicine and Health Sciences, University of Antwerp, Edegem, Belgium.; Center for Cell Therapy & Regenerative Medicine (CCRG), Antwerp University Hospital, Edegem, Belgium., Laukens K; Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium.; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium.; Biomedical Informatics Research Network Antwerp (Biomina), University of Antwerp, Antwerp, Belgium., Meysman P; Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium. pieter.meysman@uantwerpen.be.; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium. pieter.meysman@uantwerpen.be.; Biomedical Informatics Research Network Antwerp (Biomina), University of Antwerp, Antwerp, Belgium. pieter.meysman@uantwerpen.be.
Jazyk: angličtina
Zdroj: Annals of hematology [Ann Hematol] 2024 Sep 11. Date of Electronic Publication: 2024 Sep 11.
DOI: 10.1007/s00277-024-05919-1
Abstrakt: The Wilms' tumor protein 1 (WT1) is a well-known and prioritized tumor-associated antigen expressed in numerous solid and blood tumors. Its abundance and immunogenicity have led to the development of different WT1-specific immune therapies. The driving player in these therapies, the WT1-specific T-cell receptor (TCR) repertoire, has received much less attention. Importantly, T cells with high affinity against the WT1 self-antigen are normally eliminated after negative selection in the thymus and are thus rare in peripheral blood. Here, we developed computational models for the robust and fast identification of WT1-specific TCRs from TCR repertoire data. To this end, WT1 37-45 (WT1-37) and WT1 126-134 (WT1-126)-specific T cells were isolated from WT1 peptide-stimulated blood of healthy individuals. The TCR repertoire from these WT1-specific T cells was sequenced and used to train a pattern recognition model for the identification of WT1-specific TCR patterns for the WT1-37 or WT1-126 epitopes. The resulting computational models were applied on an independent published dataset from acute myeloid leukemia (AML) patients, treated with hematopoietic stem cell transplantation, to track WT1-specific TCRs in silico. Several WT1-specific TCRs were found in AML patients. Subsequent clustering analysis of all repertoires indicated the presence of more diverse TCR patterns within the WT1-specific TCR repertoires of AML patients in complete remission in contrast to relapsing patients. We demonstrate the possibility of tracking WT1-37 and WT1-126-specific TCRs directly from TCR repertoire data using computational methods, eliminating the need for additional blood samples and experiments for the two studied WT1 epitopes.
(© 2024. The Author(s).)
Databáze: MEDLINE
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