Dynamical System Modeling of Immune Reconstitution after Allogeneic Stem Cell Transplantation Identifies Patients at Risk for Adverse Outcomes

Toor, Amir A.; Sabo, Roy; Roberts, Catherine; Moore, Bonny L.; Salman, Salman R.; Scalora, Allison F.; Aziz, May; Ali, Ali S. Shubar; Hall, Charles A.; Meier, Jeremy A.; Thorn, Radhika M.; Wang, Elaine; Song, Shiyu; Miller, Kristin; Rizzo, Kathryn; Clark, William; McCarty, John M.; Chung, Harold M.; Manjili, Masoud H.; Neale, Michael C.

doi:10.1016/j.bbmt.2015.03.011

Cited by 29 publications

(51 citation statements)

References 37 publications

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“…Specifically, assuming T cell clonal growth in proportion to the target antigen-HLA binding affinity, both individual T cell clones and the entire T cell repertoire follow a sigmoid, logistic dynamic over time as the system iterates. This is similar to immune reconstitution kinetics in a cohort of allograft recipients reported recently [4]. While this behavior is inherent due to the use of a logistic equation to model the growth of each clone, the generalization to the entire repertoire results from using the rule that the steady state T cell population of specific clones will be proportional to the binding affinity of the variant peptides to HLA.…”

Section: Discussionsupporting

confidence: 74%

“…Using this model, the sum of all the T cell clones in an individual over time (i.e. after several iterations) follows a sigmoid curve, analogous to the sigmoid growth behavior in post allograft setting when lymphocyte populations have been examined (Supplementary Figure 4A) [4]. This behavior was observed in all 34 patients modeled.…”

Section: Resultsmentioning

confidence: 71%

“…Immune reconstitution following allografting is critical for relapse prevention and survival, but may be associated with a higher risk of GVHD in some individuals [4, 5]. Because of the complexity of the variables involved, clinical outcomes following SCT have been studied as a probability function of various clinical features of the transplant.…”

Section: Introductionmentioning

confidence: 99%

“…This makes it very unlikely that GVHD incidence is a probability function of a small number of critical variables, rather it is more likely that GVHD is the result of an integrated sum of all the variant immunogenic peptides presented by the HLA in a unique DRP, modulated by the immunosuppressive influence of pharmacotherapy during immune reconstitution. This is a logical assumption since donor T cell reconstitution corresponds with the likelihood of alloreactivity developing [4, 13, 14]. In order to develop a model to estimate the likelihood of alloreactivity developing in unique SCT-DRP, immune response to the peptide-HLA complex library will need to be modeled in each individual.…”

Section: Introductionmentioning

confidence: 99%

“…Lymphocyte reconstitution following SCT has been modeled as a logistic dynamical system , with a familiar sigmoid growth pattern over time (Supplementary Figure 1) [4, 23]. Logically then, various T cell subsets, including T cell clones should demonstrate the same growth dynamic.…”

Section: Introductionmentioning

confidence: 99%

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Dynamical System Modeling to Simulate Donor T Cell Response to Whole Exome Sequencing-Derived Recipient Peptides Demonstrates Different Alloreactivity Potential in HLA-Matched and -Mismatched Donor–Recipient Pairs

Razzaq

Scalora

Kopardé

et al. 2016

Biology of Blood and Marrow Transplantation

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Immune reconstitution kinetics and subsequent clinical outcomes in HLA-matched recipients of allogeneic stem cell transplantation (SCT) are variable and difficult to predict. Considering SCT as a dynamical system, may allow sequence differences across the exomes of the transplant donors and recipients to be used to simulate an alloreactive T cell response, which may allow better clinical outcome prediction. To accomplish this, whole exome sequencing was performed on 34 HLA matched SCT donor-recipient pairs (DRP), and the nucleotide sequence differences translated to peptides. The binding affinity of the peptides to the relevant HLA in each DRP was determined. The resulting array of peptide-HLA binding affinity values in each patient was considered as an operator modifying a hypothetical T cell repertoire vector, in which each T cell clone proliferates in accordance to the logistic equation of growth. Using an iterating system of matrices, each simulated T cell clone's growth was calculated with the steady state population being proportional to the magnitude of the binding affinity of the driving HLA-peptide complex. Incorporating competition between T cell clones responding to different HLA-peptide complexes reproduces a number of features of clinically observed T cell clonal repertoire in the simulated repertoire. These include, sigmoidal growth kinetics of individual T cell clones and overall repertoire, Power Law clonal frequency distribution, increase in repertoire complexity over time with increasing clonal diversity and finally, alteration of clonal dominance when a different antigen array is encountered, such as in stem cell transplantation. The simulated, alloreactive T cell repertoire was markedly different in HLA matched DRP. The patterns were differentiated by rate of growth, and steady state magnitude of the simulated T cell repertoire and demonstrate a possible correlation with survival. In conclusion, exome wide sequence differences in DRP may allow simulation of donor alloreactive T cell response to recipient antigens and may provide a quantitative basis for refining donor selection and titration of immunosuppression following SCT.

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Section: Discussionsupporting

confidence: 74%

Section: Resultsmentioning

confidence: 71%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Dynamical System Modeling to Simulate Donor T Cell Response to Whole Exome Sequencing-Derived Recipient Peptides Demonstrates Different Alloreactivity Potential in HLA-Matched and -Mismatched Donor–Recipient Pairs

Razzaq

Scalora

Kopardé

et al. 2016

Biology of Blood and Marrow Transplantation

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View full text Add to dashboard Cite

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The Composite Immune Risk Score predicts overall survival after allogeneic hematopoietic stem cell transplantation: A retrospective analysis of 1838 cases

et al. 2023

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There has been little consensus on how to quantitatively assess immune reconstitution after hematopoietic stem cell transplantation (HSCT) as part of the standard of care. We retrospectively analyzed 11 150 post‐transplant immune profiles of 1945 patients who underwent HSCT between 2012 and 2020. 1838 (94.5%) of the cases were allogeneic HSCT. Using the training set of patients (n = 729), we identified a composite immune signature (integrating neutrophil, total lymphocyte, natural killer, total T, CD4+ T, and B cell counts in the peripheral blood) during days 91–180 after allogeneic HSCT that was predictive of early mortality and moreover simplified it into a formula for a Composite Immune Risk Score. When we verified the Composite Immune Risk Score in the validation (n = 284) and test (n = 391) sets of patients, a high score value was found to be associated with hazard ratios (HR) of 3.64 (95% C.I. 1.55–8.51; p = .0014) and 2.44 (95% C.I., 1.22–4.87; p = .0087), respectively, for early mortality. In multivariate analysis, a high Composite Immune Risk Score during days 91–180 remained an independent risk factor for early mortality after allogeneic HSCT (HR, 1.80; 95% C.I., 1.28–2.55; p = .00085). In conclusion, the Composite Immune Risk Score is easy to compute and could identify the high‐risk patients of allogeneic HSCT who require targeted effort for prevention and control of infection.

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Allogeneic haematopoietic cell transplants as dynamical systems: influence of early‐term immune milieu on long‐term T‐cell recovery

et al. 2023

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Objectives Immune recovery following haematopoietic cell transplantation (HCT) functions as a dynamical system. Reducing the duration of intense immune suppression and augmenting antigen presentation has the potential to optimise T‐cell reconstitution, potentially influencing long‐term outcomes. Methods Based on donor‐derived T‐cell recovery, 26 patients were adaptively randomised between mycophenolate mofetil (MMF) administered for 30‐day post‐transplant with filgrastim for cytokine support (MMF30 arm, N = 11), or MMF given for 15 days with sargramostim (MMF15 arm, N = 15). All patients underwent in vivo T‐cell depletion with 5.1 mg kg−1 antithymocyte globulin (administered over 3 days, Day −9 through to Day −7) and received reduced intensity 450 cGy total body irradiation (3 fractions on Day −1 and Day 0). Patients underwent HLA‐matched related and unrelated donor haematopoietic cell transplantation (HCT). Results Clinical outcomes were equivalent between the two groups. The MMF15 arm demonstrated superior T‐cell, as well as T‐cell subset recovery and a trend towards superior T‐cell receptor (TCR) diversity in the first month with this difference persisting through the first year. T‐cell repertoire recovery was more rapid and sustained, as well as more diverse in the MMF15 arm. Conclusion The long‐term superior immune recovery in the MMF15 arm, administered GMCSF, is consistent with a disproportionate impact of early interventions in HCT. Modifying the ‘immune‐milieu’ following allogeneic HCT is feasible and may influence long‐term T‐cell recovery.

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Dynamical System Modeling of Immune Reconstitution after Allogeneic Stem Cell Transplantation Identifies Patients at Risk for Adverse Outcomes

Cited by 29 publications

References 37 publications

Dynamical System Modeling to Simulate Donor T Cell Response to Whole Exome Sequencing-Derived Recipient Peptides Demonstrates Different Alloreactivity Potential in HLA-Matched and -Mismatched Donor–Recipient Pairs

Dynamical System Modeling to Simulate Donor T Cell Response to Whole Exome Sequencing-Derived Recipient Peptides Demonstrates Different Alloreactivity Potential in HLA-Matched and -Mismatched Donor–Recipient Pairs

The Composite Immune Risk Score predicts overall survival after allogeneic hematopoietic stem cell transplantation: A retrospective analysis of 1838 cases

Allogeneic haematopoietic cell transplants as dynamical systems: influence of early‐term immune milieu on long‐term T‐cell recovery

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