16 research outputs found

    Supplemental Figures and Reagent Table from Adaptive NK Cells with Low TIGIT Expression Are Inherently Resistant to Myeloid-Derived Suppressor Cells

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    Supplemental figure. 1: Gating strategy of conventional and adaptive NK cells in healthy donors and MDS patients. Supplemental figure. 2: Gating strategy for MDSC and monocytes, CD16 expression on conventional and adaptive NK cells, expression of different NK cell receptors following co-culture with monocytes or MDSC, and differential production of IFNg on TIGIT high/low NK cells. Supplemental figure. 3: Evaluation of TIGIT blocking antibodies. IFNg production following DNAM-1 and TIGIT co-blocking. NK cell TNFa production in conventional and adaptive NK cells cultured with monocytes or MDSC. Supplemental Table. 1: All antibodies used throughout the study including clone, manufactory, fluorochrome, and marker.</p

    DataSheet_1_Decoupling blood telomere length from age in recipients of allogeneic hematopoietic cell transplant in the BMT-CTN 1202.docx

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    The age of allogeneic hematopoietic cell transplant (HCT) donors and their hematopoietic cell telomere length (TL) might affect recipients’ outcomes. Our goals were to examine the possible effect of these donors’ factors on the recipients’ hematopoietic cell TL and quantify hematopoietic cell TL shortening in the critical first three-month post-HCT. We measured hematopoietic cell TL parameters in 75 recipient-donor pairs, from the Blood and Marrow Transplant Clinical Trials Network (protocol#1202), by Southern blotting (SB), the Telomeres Shortest Length Assay (TeSLA), and quantitative PCR (qPCR). Recipients’ hematopoietic cell TL parameters post-HCT correlated with donors’ age (p0.0001 for all). SB and TeSLA detected hematopoietic cell TL shortening in all recipients post-HCT (mean=0.52kb and 0.47kb, respectively; >15-fold the annual TL shortening in adults; p<0.00001 for both), but qPCR detected shortening only in 57.5% of recipients. TeSLA detected a buildup of post-HCT of telomeres <3 kb in 96% of recipients (p<0.0001). In conclusion, HCT decouples hematopoietic cell TL in the recipients from their own age to reflect the donors’ age. The potential donors’ age effect on outcomes of HCT might be partially mediated by short hematopoietic cell TL in older donors. qPCR-based TL measurement is suboptimal for detecting telomere shortening post-HCT.</p

    DataSheet_1_A Model of Minor Histocompatibility Antigens in Allogeneic Hematopoietic Cell Transplantation.xlsx

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    Minor histocompatibility antigens (mHAg) composed of peptides presented by HLA molecules can cause immune responses involved in graft-versus-host disease (GVHD) and graft-versus-leukemia effects after allogeneic hematopoietic cell transplantation (HCT). The current study was designed to identify individual graft-versus-host genomic mismatches associated with altered risks of acute or chronic GVHD or relapse after HCT between HLA-genotypically identical siblings. Our results demonstrate that in allogeneic HCT between a pair of HLA-identical siblings, a mHAg manifests as a set of peptides originating from annotated proteins and non-annotated open reading frames, which i) are encoded by a group of highly associated recipient genomic mismatches, ii) bind to HLA allotypes in the recipient, and iii) evoke a donor immune response. Attribution of the immune response and consequent clinical outcomes to individual peptide components within this set will likely differ from patient to patient according to their HLA types.</p

    DataSheet1_Donor whole blood DNA methylation is not a strong predictor of acute graft versus host disease in unrelated donor allogeneic haematopoietic cell transplantation.DOCX

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    Allogeneic hematopoietic cell transplantation (HCT) is used to treat many blood-based disorders and malignancies, however it can also result in serious adverse events, such as the development of acute graft-versus-host disease (aGVHD). This study aimed to develop a donor-specific epigenetic classifier to reduce incidence of aGVHD by improving donor selection. Genome-wide DNA methylation was assessed in a discovery cohort of 288 HCT donors selected based on recipient aGVHD outcome; this cohort consisted of 144 cases with aGVHD grades III-IV and 144 controls with no aGVHD. We applied a machine learning algorithm to identify CpG sites predictive of aGVHD. Receiver operating characteristic (ROC) curve analysis of these sites resulted in a classifier with an encouraging area under the ROC curve (AUC) of 0.91. To test this classifier, we used an independent validation cohort (n = 288) selected using the same criteria as the discovery cohort. Attempts to validate the classifier failed with the AUC falling to 0.51. These results indicate that donor DNA methylation may not be a suitable predictor of aGVHD in an HCT setting involving unrelated donors, despite the initial promising results in the discovery cohort. Our work highlights the importance of independent validation of machine learning classifiers, particularly when developing classifiers intended for clinical use.</p

    Table1_Donor whole blood DNA methylation is not a strong predictor of acute graft versus host disease in unrelated donor allogeneic haematopoietic cell transplantation.DOCX

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    Allogeneic hematopoietic cell transplantation (HCT) is used to treat many blood-based disorders and malignancies, however it can also result in serious adverse events, such as the development of acute graft-versus-host disease (aGVHD). This study aimed to develop a donor-specific epigenetic classifier to reduce incidence of aGVHD by improving donor selection. Genome-wide DNA methylation was assessed in a discovery cohort of 288 HCT donors selected based on recipient aGVHD outcome; this cohort consisted of 144 cases with aGVHD grades III-IV and 144 controls with no aGVHD. We applied a machine learning algorithm to identify CpG sites predictive of aGVHD. Receiver operating characteristic (ROC) curve analysis of these sites resulted in a classifier with an encouraging area under the ROC curve (AUC) of 0.91. To test this classifier, we used an independent validation cohort (n = 288) selected using the same criteria as the discovery cohort. Attempts to validate the classifier failed with the AUC falling to 0.51. These results indicate that donor DNA methylation may not be a suitable predictor of aGVHD in an HCT setting involving unrelated donors, despite the initial promising results in the discovery cohort. Our work highlights the importance of independent validation of machine learning classifiers, particularly when developing classifiers intended for clinical use.</p

    Table_2_Determining the Quantitative Principles of T Cell Response to Antigenic Disparity in Stem Cell Transplantation.DOCX

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    Alloreactivity compromising clinical outcomes in stem cell transplantation is observed despite HLA matching of donors and recipients. This has its origin in the variation between the exomes of the two, which provides the basis for minor histocompatibility antigens (mHA). The mHA presented on the HLA class I and II molecules and the ensuing T cell response to these antigens results in graft vs. host disease. In this paper, results of a whole exome sequencing study are presented, with resulting alloreactive polymorphic peptides and their HLA class I and HLA class II (DRB1) binding affinity quantified. Large libraries of potentially alloreactive recipient peptides binding both sets of molecules were identified, with HLA-DRB1 generally presenting a greater number of peptides. These results are used to develop a quantitative framework to understand the immunobiology of transplantation. A tensor-based approach is used to derive the equations needed to determine the alloreactive donor T cell response from the mHA-HLA binding affinity and protein expression data. This approach may be used in future studies to simulate the magnitude of expected donor T cell response and determine the risk for alloreactive complications in HLA matched or mismatched hematopoietic cell and solid organ transplantation.</p

    Image_1_Determining the Quantitative Principles of T Cell Response to Antigenic Disparity in Stem Cell Transplantation.tif

    No full text
    Alloreactivity compromising clinical outcomes in stem cell transplantation is observed despite HLA matching of donors and recipients. This has its origin in the variation between the exomes of the two, which provides the basis for minor histocompatibility antigens (mHA). The mHA presented on the HLA class I and II molecules and the ensuing T cell response to these antigens results in graft vs. host disease. In this paper, results of a whole exome sequencing study are presented, with resulting alloreactive polymorphic peptides and their HLA class I and HLA class II (DRB1) binding affinity quantified. Large libraries of potentially alloreactive recipient peptides binding both sets of molecules were identified, with HLA-DRB1 generally presenting a greater number of peptides. These results are used to develop a quantitative framework to understand the immunobiology of transplantation. A tensor-based approach is used to derive the equations needed to determine the alloreactive donor T cell response from the mHA-HLA binding affinity and protein expression data. This approach may be used in future studies to simulate the magnitude of expected donor T cell response and determine the risk for alloreactive complications in HLA matched or mismatched hematopoietic cell and solid organ transplantation.</p

    Table_3_Determining the Quantitative Principles of T Cell Response to Antigenic Disparity in Stem Cell Transplantation.DOCX

    No full text
    Alloreactivity compromising clinical outcomes in stem cell transplantation is observed despite HLA matching of donors and recipients. This has its origin in the variation between the exomes of the two, which provides the basis for minor histocompatibility antigens (mHA). The mHA presented on the HLA class I and II molecules and the ensuing T cell response to these antigens results in graft vs. host disease. In this paper, results of a whole exome sequencing study are presented, with resulting alloreactive polymorphic peptides and their HLA class I and HLA class II (DRB1) binding affinity quantified. Large libraries of potentially alloreactive recipient peptides binding both sets of molecules were identified, with HLA-DRB1 generally presenting a greater number of peptides. These results are used to develop a quantitative framework to understand the immunobiology of transplantation. A tensor-based approach is used to derive the equations needed to determine the alloreactive donor T cell response from the mHA-HLA binding affinity and protein expression data. This approach may be used in future studies to simulate the magnitude of expected donor T cell response and determine the risk for alloreactive complications in HLA matched or mismatched hematopoietic cell and solid organ transplantation.</p

    Image_3_Determining the Quantitative Principles of T Cell Response to Antigenic Disparity in Stem Cell Transplantation.tif

    No full text
    Alloreactivity compromising clinical outcomes in stem cell transplantation is observed despite HLA matching of donors and recipients. This has its origin in the variation between the exomes of the two, which provides the basis for minor histocompatibility antigens (mHA). The mHA presented on the HLA class I and II molecules and the ensuing T cell response to these antigens results in graft vs. host disease. In this paper, results of a whole exome sequencing study are presented, with resulting alloreactive polymorphic peptides and their HLA class I and HLA class II (DRB1) binding affinity quantified. Large libraries of potentially alloreactive recipient peptides binding both sets of molecules were identified, with HLA-DRB1 generally presenting a greater number of peptides. These results are used to develop a quantitative framework to understand the immunobiology of transplantation. A tensor-based approach is used to derive the equations needed to determine the alloreactive donor T cell response from the mHA-HLA binding affinity and protein expression data. This approach may be used in future studies to simulate the magnitude of expected donor T cell response and determine the risk for alloreactive complications in HLA matched or mismatched hematopoietic cell and solid organ transplantation.</p
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