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  • 1
    In: Clinical Lymphoma Myeloma and Leukemia, Elsevier BV, Vol. 23 ( 2023-09), p. S135-S136
    Type of Medium: Online Resource
    ISSN: 2152-2650
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
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    detail.hit.zdb_id: 2193618-3
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  • 2
    In: Cell Reports, Elsevier BV, Vol. 31, No. 7 ( 2020-05), p. 107628-
    Type of Medium: Online Resource
    ISSN: 2211-1247
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
    detail.hit.zdb_id: 2649101-1
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  • 3
    In: Blood, American Society of Hematology, Vol. 136, No. Supplement 1 ( 2020-11-5), p. 4-5
    Abstract: Only half of chronic myeloid leukemia (CML) patients in deep molecular remission are able to maintain treatment free remission (TFR) after tyrosine kinase inhibitor (TKI) discontinuation. Identifying predictive markers for TFR remains a key issue. The immunological control or eradication of TKI insensitive leukemic stem cells may contribute to successful cessation, as recent work has demonstrated that differences in immune cell compositions can be associated with better probability of TFR. In order to understand the precise immunological changes in CML, we profiled over 170,000 cells from 25 CML samples from different clinical phases (untreated, during TKI therapy and after TKI cessation) using single-cell RNA and T cell receptor (TCR) αβ sequencing (scRNA+TCRab-seq). We profiled both CD45+ sorted peripheral blood samples (n=20) and CD34+ sorted bone marrow samples (n=5). To understand antigen-specific responses, we profiled TCRs specific to tumor-antigen PR1 (n=12) and compared these to unsorted TCRβ-sequenced samples from CML (n=137) and healthy donors (n=786). To understand the distinctive immunological features in CML, we compared the immune system in CML (n=20) to those in other hematological and solid malignancies profiled with scRNA+TCRab-seq (n=9). We discovered NK cells to be the most unique feature in CML, as NK CD56dim cells were more abundant in CML patients (Padj & lt;0.001) and the NK cell repertoire was more transcriptionally heterogenous and included otherwise rarely seen exhausted NK population with upregulated HAVCR2 and TIGIT expression (Padj & lt;0.0001). Further, the NK cell maturation changed during TKI-treatment from an effector CD56dim state towards an adaptive NK-cell state. We sought to understand whether the immunological activity differs before and after TKI discontinuation in different clinical outcomes following discontinuation. Therefore, we reclustered the discontinuation samples from three different outcomes: TFR, early relapse ( & lt;6 months after cessation) or late relapse ( & gt;6 months). In all clinical outcomes, TKI cessation invigorated NK cell exhaustion and the most upregulated pathways included IFNg and TNFa via NFkB pathways. Patients with successful TFR had less differences in their immune system after cessation in comparison to relapsing patients, which could hint that their immune subsets were better prepared for the cessation. Unlike the early relapse patients' quiescent immune cells, the late relapse patients' immune subsets were active, but under pronounced inhibitory Treg signals, providing a clinically interesting approach to alter the outcome of these patients. Next, to understand how malignant CML cells evade or interact with the immune system, we analyzed CD34+ cells and calculated a BCR-ABL1 activity score. The most primitive CD34+ cells had lower BCR-ABL1 score and not as many immunological ligand-receptor pairs as their less primitive, highly BCR-ABL1 pathway expressing, counterparts (P & lt;0.0001). LGALS9, that is expressed on both BCR-ABL1 high and low CD34+ cells, arose as one of the most interesting ligands mediating tumor-immune cell interactions and it has many potential receptors expressed by NK cells, including HAVCR2. Finally, we found that tumor-antigen PR1 is preferentially expressed on CD34+ cells with high BCR-ABL1 score. Most TCRs recognizing PR1 are restricted to individuals, but they share short amino-acid motifs that are shared across patients. Thus, we were able to generate an in silico tool to recognize PR1-specific TCRs from unsorted TCR-seq samples with high accuracy (AUC 0.91 from 10-fold cross validation). With our tool, we were able to show that anti-PR1 responses were more frequent in CML than in healthy donors (P & lt;0.0001), are more expanded in bone-marrow than in blood (P & lt;0.0001) and diversified during TKI treatment (P & lt;0.0001). In the scRNA+TCRab-seq data, the anti-PR1 response differed between TFR and early relapse patient significantly at phenotype level, where the TFR patient had cytotoxic anti-leukemic response before TKI cessation, in comparison to the early relapse patient's exhausted and less cytotoxic PR1-specific cells. In conclusion, our results provide high-resolution insights into anti-leukemic immune responses in CML and how we could harness and monitor them to enable successful TKI cessations. Figure Disclosures Olsson-Strömberg: Pfizer: Research Funding. Hjorth-Hansen:Pfizer: Honoraria, Research Funding; Austrian Orphan Pharma: Honoraria, Research Funding; Bristol-Myers Squibb: Research Funding. Mustjoki:Pfizer: Research Funding; Novartis: Research Funding; BMS: Honoraria, Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2020
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    detail.hit.zdb_id: 80069-7
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  • 4
    In: Blood, American Society of Hematology, Vol. 134, No. Supplement_1 ( 2019-11-13), p. 108-108
    Abstract: Immune aplastic anemia (AA) is a life-threatening bone marrow failure syndrome in which the hematopoietic stem cells are destroyed, leading to pancytopenia. Although the exact biological process leading to AA remains largely unknown, bone marrow destruction is thought to be mediated by an autologous T cell response. We hypothesized that the autoimmune process in AA would create a T cell fingerprint unique to aplastic anemia. To decipher this signature, we collected an international, multi-centre cohort of 245 AA-samples from bone marrow and peripheral blood profiled with T-cell receptor beta (TCRβ) -sequencing. CD8+ T cell- and MNC-sorted samples from 153 clinically annotated AA patients were obtained from diagnosis, during remission and at relapse. To compare AA to similar diseases, we gathered 116 samples from other bone marrow failure syndromes, including MDS, PNH and hypoplastic LGL, and 45 samples from other autoimmune disorders. As healthy controls, we profiled 60 CD4+ and CD8+ T cells and utilized 786 MNC samples from public data repositories. To gain insight into T cell phenotypes, we also profiled 6 longitudinal samples with scRNA+TCRαβ-sequencing. As there are 1x1012-16 different TCRs and most of them are exclusive to individuals (private), we reasoned that by studying the most biologically interesting clonotypes from each individual, we could explain differences in disease severities, variation in treatment responses and pathogenesis. From all subjects, we selected private response clonotypes: highly expanded clonotypes (at least 1% of the total repertoire), convergent clonotypes (in which multiple nucleotide sequences converge to encode the same amino acid sequence) and from patients with AA, treatment-responding clonotypes (clonotypes that were suppressed/expanded after immune therapy). To analyse epitope-specificities of these clonotypes we leveraged TCRGP, our recently described Gaussian process method that can predict if TCRs recognize previously known epitopes. Clonotypes recognising viral epitopes (CMV, EBV and Influenza A) were enriched among private response clonotypes in comparison to the total repertoire (Fisher's exact test, p=2e-16), indicating that our filtering strategy indeed enriched for epitope-specific clonotypes. Of interest, the healthy donors' private response clonotypes showed more anti-viral clonotypes than did AA-patients (p=0.003), suggesting that in AA the epitope-specifities of private response clonotypes are not driven by common viral antigens. To identify specifities against unknown epitopes of the private response AA clones, we used an unsupervised learning strategy, GLIPH,that groups TCRs recognising the same epitope based on amino acid level similarities. Clonotypes in AA showed high convergence in their epitope-targets, as 1709 of 5744 (29.75%) clonotypes formed a single, potentially epitope-specific cluster that was not viral-specific. Similar analysis of control samples resulted in fewer clones clustering to the most prominent cluster (23.20%, p=1.63e-10), suggesting for a more homogenous target population within AA patients' clones. After showing sequence-level similarity of the private response clonotypes in AA, we aimed to link these pathological clonotypes to transcriptomes at the single-cell level using scRNA+TCRαβ-sequenced samples. The cells of the private response clonotypes showed multiple T cell phenotypes, but most cells (47.13%) in the bone marrow environment were recently activated CD8+ effector phenotype, marked by expression of GZMH, GNLY and PRF1. In comparison, the anti-viral clonotypes were mostly (37.3%) central memory phenotype (CCR7, TCF7). In serially sampled patients, anti-thymocyte globulin treatment suppressed private response clonotypes in a responding patient (55.03% of T cells to 12.79%), while the amount of these clonotypes increased in a non-responding patient (18.65% to 37.86%), where treatment mostly affected the viral-specific clonotypes. In summary, our data suggest that the private response clonotypes in immune AA patients may recognise a common antigen, which was not predicted to be viral. Further, at the single-cell level AA signature clonotypes are of effector phenotype and fluctuate following immunosuppressive treatment. Monitoring of these clonotypes throughout treatment may provide insight into disease biology and variation in treatment responses. Figure Disclosures Blombery: Janssen: Honoraria; Novartis: Consultancy; Invivoscribe: Honoraria. Maciejewski:Novartis: Consultancy; Alexion: Consultancy. Mustjoki:BMS: Honoraria, Research Funding; Novartis: Research Funding; Pfizer: Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2019
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  • 5
    Online Resource
    Online Resource
    Public Library of Science (PLoS) ; 2021
    In:  PLOS Computational Biology Vol. 17, No. 3 ( 2021-3-25), p. e1008814-
    In: PLOS Computational Biology, Public Library of Science (PLoS), Vol. 17, No. 3 ( 2021-3-25), p. e1008814-
    Abstract: Adaptive immune system uses T cell receptors (TCRs) to recognize pathogens and to consequently initiate immune responses. TCRs can be sequenced from individuals and methods analyzing the specificity of the TCRs can help us better understand individuals’ immune status in different disorders. For this task, we have developed TCRGP, a novel Gaussian process method that predicts if TCRs recognize specified epitopes. TCRGP can utilize the amino acid sequences of the complementarity determining regions (CDRs) from TCR α and TCR β chains and learn which CDRs are important in recognizing different epitopes. Our comprehensive evaluation with epitope-specific TCR sequencing data shows that TCRGP achieves on average higher prediction accuracy in terms of AUROC score than existing state-of-the-art methods in epitope-specificity predictions. We also propose a novel analysis approach for combined single-cell RNA and TCR αβ (scRNA+TCR αβ ) sequencing data by quantifying epitope-specific TCRs with TCRGP and identify HBV-epitope specific T cells and their transcriptomic states in hepatocellular carcinoma patients.
    Type of Medium: Online Resource
    ISSN: 1553-7358
    Language: English
    Publisher: Public Library of Science (PLoS)
    Publication Date: 2021
    detail.hit.zdb_id: 2193340-6
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  • 6
    In: Cancer Research Communications, American Association for Cancer Research (AACR), Vol. 3, No. 7 ( 2023-07-18), p. 1260-1276
    Abstract: The successful use of expanded tumor-infiltrating lymphocytes (TIL) in adoptive TIL therapies has been reported, but the effects of the TIL expansion, immunophenotype, function, and T cell receptor (TCR) repertoire of the infused products relative to the tumor microenvironment (TME) are not well understood. In this study, we analyzed the tumor samples (n = 58) from treatment-naïve patients with renal cell carcinoma (RCC), “pre-rapidly expanded” TILs (pre-REP TIL, n = 15) and “rapidly expanded” TILs (REP TIL, n = 25) according to a clinical-grade TIL production protocol, with single-cell RNA (scRNA)+TCRαβ-seq (TCRαβ sequencing), TCRβ-sequencing (TCRβ-seq), and flow cytometry. REP TILs encompassed a greater abundance of CD4+ than CD8+ T cells, with increased LAG-3 and low PD-1 expressions in both CD4+ and CD8+ T cell compartments compared with the pre-REP TIL and tumor T cells. The REP protocol preferentially expanded small clones of the CD4+ phenotype (CD4, IL7R, KLRB1) in the TME, indicating that the largest exhausted T cell clones in the tumor do not expand during the expansion protocol. In addition, by generating a catalog of RCC-associated TCR motifs from & gt;1,000 scRNA+TCRαβ-seq and TCRβ-seq RCC, healthy and other cancer sample cohorts, we quantified the RCC-associated TCRs from the expansion protocol. Unlike the low-remaining amount of anti-viral TCRs throughout the expansion, the quantity of the RCC-associated TCRs was high in the tumors and pre-REP TILs but decreased in the REP TILs. Our results provide an in-depth understanding of the origin, phenotype, and TCR specificity of RCC TIL products, paving the way for a more rationalized production of TILs. Significance: TILs are a heterogenous group of immune cells that recognize and attack the tumor, thus are utilized in various clinical trials. In our study, we explored the TILs in patients with kidney cancer by expanding the TILs using a clinical-grade protocol, as well as observed their characteristics and ability to recognize the tumor using in-depth experimental and computational tools.
    Type of Medium: Online Resource
    ISSN: 2767-9764
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
    detail.hit.zdb_id: 3098144-X
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  • 7
    In: Bioinformatics, Oxford University Press (OUP), Vol. 39, No. 1 ( 2023-01-01)
    Abstract: T cells use T cell receptors (TCRs) to recognize small parts of antigens, called epitopes, presented by major histocompatibility complexes. Once an epitope is recognized, an immune response is initiated and T cell activation and proliferation by clonal expansion begin. Clonal populations of T cells with identical TCRs can remain in the body for years, thus forming immunological memory and potentially mappable immunological signatures, which could have implications in clinical applications including infectious diseases, autoimmunity and tumor immunology. Results We introduce TCRconv, a deep learning model for predicting recognition between TCRs and epitopes. TCRconv uses a deep protein language model and convolutions to extract contextualized motifs and provides state-of-the-art TCR-epitope prediction accuracy. Using TCR repertoires from COVID-19 patients, we demonstrate that TCRconv can provide insight into T cell dynamics and phenotypes during the disease. Availability and implementation TCRconv is available at https://github.com/emmijokinen/tcrconv. Supplementary information Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4811
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 1468345-3
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  • 8
    In: Haematologica, Ferrata Storti Foundation (Haematologica), Vol. 105, No. 12 ( 2019-12-19), p. 2757-2768
    Abstract: Common variable immunodeficiency and other late-onset immunodeficiencies often co-manifest with autoimmunity and lymphoproliferation. The pathogenesis of most cases is elusive, as only a minor subset harbors known monogenic germline causes. The involvement of both B and T cells is however implicated. To study whether somatic mutations in CD4+ and CD8+ T cells associate with immunodeficiency, we recruited 17 patients and 21 healthy controls. Eight patients had late-onset common variable immunodeficiency and nine patients other immunodeficiency and/or severe autoimmunity. In total, autoimmunity occurred in 94% and lymphoproliferation in 65%. We performed deep sequencing of 2533 immune-associated genes from CD4+ and CD8+ cells. Deep T-cell receptor beta sequencing was used to characterize CD4+ and CD8+ T-cell receptor repertoires. The prevalence of somatic mutations was 65% in all immunodeficiency patients, 75% in common variable immunodeficiency and 48% in controls. Clonal hematopoiesis-associated variants in both CD4+ and CD8+ cells occurred in 24% of immunodeficiency patients. Results demonstrated mutations in known tumor suppressors, oncogenes, and genes that are critical for immune- and proliferative functions, such as STAT5B (two patients), C5AR1 (two patients), KRAS (one patient), and NOD2 (one patient). Additionally, as a marker of T-cell receptor repertoire perturbation, common variable immunodeficiency patients harbored increased frequencies of clones with identical complementarity determining region 3 sequences despite unique nucleotide sequences when compared to controls. In conclusion, somatic mutations in genes implicated for autoimmunity and lymphoproliferation are common in CD4+ and CD8+ cells of patients with immunodeficiency. They may contribute to immune dysregulation in a subset of immunodeficiency patients.
    Type of Medium: Online Resource
    ISSN: 1592-8721 , 0390-6078
    Language: Unknown
    Publisher: Ferrata Storti Foundation (Haematologica)
    Publication Date: 2019
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    detail.hit.zdb_id: 2030158-3
    detail.hit.zdb_id: 2805244-4
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  • 9
    In: Blood, American Society of Hematology, Vol. 138, No. Supplement 1 ( 2021-11-05), p. 801-801
    Abstract: Background The success of allogeneic stem cell transplantation supports the notion that immunotherapy can have curative potential in AML, but immune checkpoint therapies (e.g., anti-PD1) have shown only modest clinical efficacy. TIM3 is an immune-checkpoint molecule expressed both on immune and leukemic cells but not on healthy hematopoietic stem cells (HSCs), making it a particularly interesting target in AML. In myeloid malignancies, the combination of anti-TIM3 therapy with hypomethylating agents (HMA), which may prime the tumor microenvironment for immune therapies, has shown promising initial response rates up to 50%-60% of patients, but their mechanism of action is not fully understood. Methods We analyzed the effects of anti-TIM3 (sabatolimab, MBG453) in combination with decitabine in 11 refractory/relapsed AML patients and 1 MDS patient recruited in a phase Ib trial (NCT03066648), with 5/12 responders (3 CR, 2 CRi). We studied paired bone-marrow (BM) and peripheral blood samples with scRNA+TCRαβ-seq enriched for CD45+ immune cells (90% of input) and blast cells (10%) and flow cytometry. Additionally, to explore the expression of TIM3 and other immune checkpoints in different cell populations, we combined scRNAseq data from 160 BM aspirate samples across 10 different hematological malignancies and healthy controls. Results Our pan-heme scRNA-seq data analysis of over 500'000 cells revealed that unlike PD1 and CTLA4, HAVCR2 (TIM3) was primarily expressed in NK and myeloid cells (including dendritic cells [DCs], macrophages, and monocytes). In healthy controls, the expression of HAVCR2 was low in T-cells, but in patients with heme-malignancies, expression was seen on activated T-cells. In HSC populations, AML patients had generally upregulated HAVCR2 expression compared with healthy subjects. ScRNAseq data of 20 samples (n=7 patients) treated with anti-TIM3+HMA revealed that at baseline, DCs were more highly represented in samples from the responding (n=4) than from the non-responding patients (n=3). Following anti-TIM3+HMA treatment, DCs expanded significantly, and upregulated pathways related to interleukin production (IL-1b, IL-18) in responders, suggestive of an activated inflammasome response. At baseline, the most expanded NK-phenotype expressed the highest amounts of HAVCR2, which varied between patients from CD56 bright to adaptive NK cells. Anti-TIM3+HMA therapy modulated NK cells especially in responders, in which NK cells downregulated HAVCR2 and upregulated the NF-κB pathway. Importantly, the NF-κB pathway was upregulated in other cell types in responding patients, but not in non-responding patients. In contrast, the IFN-γ response was downregulated in both responding and non-responding patients in multiple different cell types. The highest expression of HAVCR2 in T cells was seen in cells co-expressing NK-receptors and with the highest cytotoxicity. Analysis of the scTCRαβ-seq revealed that the combination treatment did not have a marked effect on T-cell clonality, but one patient with CR had a significantly expanded large granular lymphocyte (LGL) clone covering 4%-25% of the repertoire. In responding patients, HAVCR2+ regulatory T-cells were more numerous at baseline, contracted following therapy, and lost response to IFN-γ, a pattern not seen in non-responding patients. The analysis of predicted cell-cell interactions between leukemic and immune cells did not show significant interactions between inhibitory PD1 or CTLA4, and their ligands, but ubiquitous LGALS9 - HAVCR2 interactions were predicted in leukemic bone marrows. Responding patients had more these interactions, which decreased following therapy. Non-responding patients had multiple interactions between T/NK cells and blasts via PVR and its ligands which were not seen in responding patients, which represent a putative resistance mechanism for anti-TIM3+HMA therapy. Conclusions Unlike PD1 and CTLA4, TIM3 is expressed on leukemic, DC, myeloid, and NK cells, and consistent with this finding, the effects of TIM3 blockade in vivo were mainly observed in these cell types. In responding patients, NFκB pathway was activated in T/NK cells following anti-TIM3 and HMA treatment concomitant with a decrease in inhibitory interactions. Our results pinpoint the differential effects of TIM3-blockade on immune cells and may aid in developing predictive biomarkers for treatment outcome. Figure 1 Figure 1. Disclosures Kreutzman: Novartis: Current Employment. Kontro: Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding. Orlando: Novartis: Current Employment. Cremasco: Novartis: Current Employment. Wagner: Novartis: Current Employment, Current holder of individual stocks in a privately-held company. Pelletier: Novartis: Current Employment. Sabatos-Peyton: Novartis: Current Employment. Rinne: Novartis: Current Employment; Qiagen: Consultancy. Mustjoki: Janpix: Research Funding; Novartis: Research Funding; Pfizer: Research Funding; BMS: Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2021
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 10
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2022-10-11)
    Abstract: Analyzing antigen-specific T cell responses at scale has been challenging. Here, we analyze three types of T cell receptor (TCR) repertoire data (antigen-specific TCRs, TCR-repertoire, and single-cell RNA + TCRαβ-sequencing data) from 515 patients with primary or metastatic melanoma and compare it to 783 healthy controls. Although melanoma-associated antigen (MAA) -specific TCRs are restricted to individuals, they share sequence similarities that allow us to build classifiers for predicting anti-MAA T cells. The frequency of anti-MAA T cells distinguishes melanoma patients from healthy and predicts metastatic recurrence from primary melanoma. Anti-MAA T cells have stem-like properties and frequent interactions with regulatory T cells and tumor cells via Galectin9-TIM3 and PVR - TIGIT -axes, respectively. In the responding patients, the number of expanded anti-MAA clones are higher after the anti-PD1(+anti-CTLA4) therapy and the exhaustion phenotype is rescued. Our systems immunology approach paves the way for understanding antigen-specific responses in human disorders.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2553671-0
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