Brittany L. Ford, Emmi Jokinen, Jani Huuhtanen, Sofia Forstén, Jay Klievink, Gabriella Antignani, Oscar Brück, Vincenzo Cerullo, Karita Peltonen, Satu Mustjoki
{"title":"预测血液癌中针对Wilms肿瘤1抗原特异性t细胞免疫","authors":"Brittany L. Ford, Emmi Jokinen, Jani Huuhtanen, Sofia Forstén, Jay Klievink, Gabriella Antignani, Oscar Brück, Vincenzo Cerullo, Karita Peltonen, Satu Mustjoki","doi":"10.1038/s41375-025-02727-y","DOIUrl":null,"url":null,"abstract":"<p>Wilms tumor 1 (WT1) is a tumor-associated antigen expressed in solid tumors and hematological malignancies. T-cell immunotherapies targeting WT1 are currently under development. To analyze endogenous T-cell responses against WT1, we trained computational models capable of detecting WT1-specific T-cell responses from T-cell receptor (TCR) sequencing data. We peptide-pulsed healthy donor and acute myeloid leukemia (AML) patient samples with VLDFAPPGA (VLD, WT1<sub>37-45</sub>) and RMFPNAPYL (RMF, WT1<sub>126-134</sub>) peptides, then sequenced the WT1 dextramer-positive CD8 + T-cells with single-cell RNA + TCRαβ sequencing. The TCRGP machine-learning TCR-classification method was trained with epitope-specific and control TCR repertoires, and we obtained AUROC values of 0.74 (VLD) and 0.75 (RMF), allowing reliable identification of WT1-specific T-cells. In bulk TCRβ sequenced patient samples (AML n = 21, chronic myeloid leukemia (CML) n = 26, and myelodysplastic syndrome n = 25), the median WT1-specific T-cell abundance was similar to healthy controls, but their VLD and RMF-specific TCR repertoires exhibited higher clonality with two patients presenting up to 13% of WT1-specific T-cells. ScRNA+TCRαβ sequencing of AML bone marrow T-cells revealed that WT1-specific T-cells predominantly exhibit an effector or terminal effector memory phenotype. In conclusion, our novel computational models enable large-scale WT1-specific T-cell identification from TCR sequencing datasets and leukemia-antigen-specific immune response monitoring.</p>","PeriodicalId":18109,"journal":{"name":"Leukemia","volume":"22 1","pages":""},"PeriodicalIF":13.4000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting antigen-specific T-cell immunity against Wilms tumor 1 in hematologic cancer\",\"authors\":\"Brittany L. Ford, Emmi Jokinen, Jani Huuhtanen, Sofia Forstén, Jay Klievink, Gabriella Antignani, Oscar Brück, Vincenzo Cerullo, Karita Peltonen, Satu Mustjoki\",\"doi\":\"10.1038/s41375-025-02727-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Wilms tumor 1 (WT1) is a tumor-associated antigen expressed in solid tumors and hematological malignancies. T-cell immunotherapies targeting WT1 are currently under development. To analyze endogenous T-cell responses against WT1, we trained computational models capable of detecting WT1-specific T-cell responses from T-cell receptor (TCR) sequencing data. We peptide-pulsed healthy donor and acute myeloid leukemia (AML) patient samples with VLDFAPPGA (VLD, WT1<sub>37-45</sub>) and RMFPNAPYL (RMF, WT1<sub>126-134</sub>) peptides, then sequenced the WT1 dextramer-positive CD8 + T-cells with single-cell RNA + TCRαβ sequencing. The TCRGP machine-learning TCR-classification method was trained with epitope-specific and control TCR repertoires, and we obtained AUROC values of 0.74 (VLD) and 0.75 (RMF), allowing reliable identification of WT1-specific T-cells. In bulk TCRβ sequenced patient samples (AML n = 21, chronic myeloid leukemia (CML) n = 26, and myelodysplastic syndrome n = 25), the median WT1-specific T-cell abundance was similar to healthy controls, but their VLD and RMF-specific TCR repertoires exhibited higher clonality with two patients presenting up to 13% of WT1-specific T-cells. ScRNA+TCRαβ sequencing of AML bone marrow T-cells revealed that WT1-specific T-cells predominantly exhibit an effector or terminal effector memory phenotype. 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Predicting antigen-specific T-cell immunity against Wilms tumor 1 in hematologic cancer
Wilms tumor 1 (WT1) is a tumor-associated antigen expressed in solid tumors and hematological malignancies. T-cell immunotherapies targeting WT1 are currently under development. To analyze endogenous T-cell responses against WT1, we trained computational models capable of detecting WT1-specific T-cell responses from T-cell receptor (TCR) sequencing data. We peptide-pulsed healthy donor and acute myeloid leukemia (AML) patient samples with VLDFAPPGA (VLD, WT137-45) and RMFPNAPYL (RMF, WT1126-134) peptides, then sequenced the WT1 dextramer-positive CD8 + T-cells with single-cell RNA + TCRαβ sequencing. The TCRGP machine-learning TCR-classification method was trained with epitope-specific and control TCR repertoires, and we obtained AUROC values of 0.74 (VLD) and 0.75 (RMF), allowing reliable identification of WT1-specific T-cells. In bulk TCRβ sequenced patient samples (AML n = 21, chronic myeloid leukemia (CML) n = 26, and myelodysplastic syndrome n = 25), the median WT1-specific T-cell abundance was similar to healthy controls, but their VLD and RMF-specific TCR repertoires exhibited higher clonality with two patients presenting up to 13% of WT1-specific T-cells. ScRNA+TCRαβ sequencing of AML bone marrow T-cells revealed that WT1-specific T-cells predominantly exhibit an effector or terminal effector memory phenotype. In conclusion, our novel computational models enable large-scale WT1-specific T-cell identification from TCR sequencing datasets and leukemia-antigen-specific immune response monitoring.
期刊介绍:
Title: Leukemia
Journal Overview:
Publishes high-quality, peer-reviewed research
Covers all aspects of research and treatment of leukemia and allied diseases
Includes studies of normal hemopoiesis due to comparative relevance
Topics of Interest:
Oncogenes
Growth factors
Stem cells
Leukemia genomics
Cell cycle
Signal transduction
Molecular targets for therapy
And more
Content Types:
Original research articles
Reviews
Letters
Correspondence
Comments elaborating on significant advances and covering topical issues