Transplant Rejection and Tolerance: Advancing the Field through Integration of Computational and Experimental Investigations

Organ transplantation is a life-saving surgical procedure through which the functionality of a failing organ system can be restored. However, without the life-long administration of immunosuppressive drugs, the recipient’s immune system will launch a massive immune attack that will ultimately destro...

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Prif Awduron: Alan S. Perelson, Kathryn J. Wood, Giorgio Raimondi, Julia C. Arciero
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Cyhoeddwyd: Frontiers Media SA 2021
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author Alan S. Perelson
Kathryn J. Wood
Giorgio Raimondi
Julia C. Arciero
author_browse Alan S. Perelson
Giorgio Raimondi
Julia C. Arciero
Kathryn J. Wood
author_facet Alan S. Perelson
Kathryn J. Wood
Giorgio Raimondi
Julia C. Arciero
author_sort Alan S. Perelson
collection Directory of Open Access Books
description Organ transplantation is a life-saving surgical procedure through which the functionality of a failing organ system can be restored. However, without the life-long administration of immunosuppressive drugs, the recipient’s immune system will launch a massive immune attack that will ultimately destroy the graft. Although successful at protecting the graft from an immune attack, long-term use of immunosuppressive drugs leads to serious complications (e.g., increased risk of infection, diabetes, hypertension, cardiovascular disease, and cancer). Moreover, recipients suffer from limited long-term graft survival rates due to the inability of current treatments to establish tolerance to the transplanted tissues. Thus, there is a great medical need to understand the complex network of immune system interactions that lead to transplant rejection so that new strategies of intervention can be determined that will redirect the system toward transplant acceptance while preserving immune competence against offending agents. In the past 20 years, the discovery and growing understanding of the positive and negative regulators of the activation of the immune system have fostered new interventional procedures targeting one or the other. While pre-clinical results proved the validity of these strategies, their clinical implementation has been troublesome. These results underscore the need for additional methods to determine the most effective interventions to prevent long-term transplant rejection. New tools of genomics, proteomics and metabolomics are being implemented in powerful analyses that promise the development of better, safer personalized treatments. In parallel, theoretical modeling has emerged as a tool that transcends investigations of individual mechanistic processes and instead unravels the relevant mechanisms of complex systems such as the immune response triggered by a transplant. In this way, theoretical models can be used to identify important behavior that arises from complex systems and thereby delineate emergent properties of biological systems that could not be identified studying single components. Employing this approach, interdisciplinary collaborations among immunologists, mathematicians, and system biologists will yield novel perspectives in the development of more effective strategies of intervention. The aim of this Research Topic is to demonstrate how new insight and methods from theoretical and experimental studies of the immune response can aid in identifying new research directions in transplant immunology. First, techniques from various theoretical and experimental studies with applications to the immune response will be reviewed to determine how they can be adapted to explore the complexity of transplant rejection. Second, recent advances in the acquisition and mining of large data sets related to transplant genomics, proteomics, and metabolomics will be discussed in the context of their predictive power and potential for optimizing and personalizing patient treatment. Last, new perspectives will be offered on the integration of computational immune modeling with transplant and omics data to establish more effective strategies of intervention that promote transplant tolerance.
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spelling doab-20.500.12854ir-612472024-03-30T23:22:01Z Transplant Rejection and Tolerance: Advancing the Field through Integration of Computational and Experimental Investigations Alan S. Perelson Kathryn J. Wood Giorgio Raimondi Julia C. Arciero R5-920 RC581-607 systems biology theoretical modeling transplant immunology biomarkers big data and bioinformatics transplant rejection transplant tolerance mechanistic models thema EDItEUR::M Medicine and Nursing Organ transplantation is a life-saving surgical procedure through which the functionality of a failing organ system can be restored. However, without the life-long administration of immunosuppressive drugs, the recipient’s immune system will launch a massive immune attack that will ultimately destroy the graft. Although successful at protecting the graft from an immune attack, long-term use of immunosuppressive drugs leads to serious complications (e.g., increased risk of infection, diabetes, hypertension, cardiovascular disease, and cancer). Moreover, recipients suffer from limited long-term graft survival rates due to the inability of current treatments to establish tolerance to the transplanted tissues. Thus, there is a great medical need to understand the complex network of immune system interactions that lead to transplant rejection so that new strategies of intervention can be determined that will redirect the system toward transplant acceptance while preserving immune competence against offending agents. In the past 20 years, the discovery and growing understanding of the positive and negative regulators of the activation of the immune system have fostered new interventional procedures targeting one or the other. While pre-clinical results proved the validity of these strategies, their clinical implementation has been troublesome. These results underscore the need for additional methods to determine the most effective interventions to prevent long-term transplant rejection. New tools of genomics, proteomics and metabolomics are being implemented in powerful analyses that promise the development of better, safer personalized treatments. In parallel, theoretical modeling has emerged as a tool that transcends investigations of individual mechanistic processes and instead unravels the relevant mechanisms of complex systems such as the immune response triggered by a transplant. In this way, theoretical models can be used to identify important behavior that arises from complex systems and thereby delineate emergent properties of biological systems that could not be identified studying single components. Employing this approach, interdisciplinary collaborations among immunologists, mathematicians, and system biologists will yield novel perspectives in the development of more effective strategies of intervention. The aim of this Research Topic is to demonstrate how new insight and methods from theoretical and experimental studies of the immune response can aid in identifying new research directions in transplant immunology. First, techniques from various theoretical and experimental studies with applications to the immune response will be reviewed to determine how they can be adapted to explore the complexity of transplant rejection. Second, recent advances in the acquisition and mining of large data sets related to transplant genomics, proteomics, and metabolomics will be discussed in the context of their predictive power and potential for optimizing and personalizing patient treatment. Last, new perspectives will be offered on the integration of computational immune modeling with transplant and omics data to establish more effective strategies of intervention that promote transplant tolerance. 2021-02-12T06:27:44Z 2021-02-12T06:27:44Z 2018-02-27 16:16:44 2017 book 25601 16648714 9782889452927 https://directory.doabooks.org/handle/20.500.12854/61247 eng Frontiers Research Topics image/jpeg Attribution 4.0 International https://www.frontiersin.org/books/Transplant_Rejection_and_Tolerance_Advancing_the_Field_through_Integration_of_Computational_and_Exp/1414 https://www.frontiersin.org/research-topics/3281/transplant-rejection-and-tolerance-advancing-the-field-through-integration-of-computational-and-expe Frontiers Media SA 10.3389/978-2-88945-292-7 10.3389/978-2-88945-292-7 bf5ce210-e72e-4860-ba9b-c305640ff3ae 9782889452927 130 open access
spellingShingle R5-920
RC581-607
systems biology
theoretical modeling
transplant immunology
biomarkers
big data and bioinformatics
transplant rejection
transplant tolerance
mechanistic models
thema EDItEUR::M Medicine and Nursing
Alan S. Perelson
Kathryn J. Wood
Giorgio Raimondi
Julia C. Arciero
Transplant Rejection and Tolerance: Advancing the Field through Integration of Computational and Experimental Investigations
title Transplant Rejection and Tolerance: Advancing the Field through Integration of Computational and Experimental Investigations
title_full Transplant Rejection and Tolerance: Advancing the Field through Integration of Computational and Experimental Investigations
title_fullStr Transplant Rejection and Tolerance: Advancing the Field through Integration of Computational and Experimental Investigations
title_full_unstemmed Transplant Rejection and Tolerance: Advancing the Field through Integration of Computational and Experimental Investigations
title_short Transplant Rejection and Tolerance: Advancing the Field through Integration of Computational and Experimental Investigations
title_sort transplant rejection and tolerance advancing the field through integration of computational and experimental investigations
topic R5-920
RC581-607
systems biology
theoretical modeling
transplant immunology
biomarkers
big data and bioinformatics
transplant rejection
transplant tolerance
mechanistic models
thema EDItEUR::M Medicine and Nursing
topic_facet R5-920
RC581-607
systems biology
theoretical modeling
transplant immunology
biomarkers
big data and bioinformatics
transplant rejection
transplant tolerance
mechanistic models
thema EDItEUR::M Medicine and Nursing
url 25601
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AT juliacarciero transplantrejectionandtoleranceadvancingthefieldthroughintegrationofcomputationalandexperimentalinvestigations