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Record W2794671395 · doi:10.1111/ajt.14747

Engineering therapeutic T cells to suppress alloimmune responses using TCRs, CARs, or BARs

2018· review· en· W2794671395 on OpenAlexafffund
A Sicard, Megan K. Levings, David W. Scott

Bibliographic record

VenueAmerican Journal of Transplantation · 2018
Typereview
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersNational Heart, Lung, and Blood InstituteHorizon 2020 Framework ProgrammeNational Institutes of HealthCanadian Institutes of Health ResearchEuropean CommissionBC Children's Hospital
KeywordsAllorecognitionChimeric antigen receptorImmunologyCytotoxic T cellT cellEffectorAntigenImmune systemTransplantationCell therapyReceptorBiologyMedicineCell biologyStem cellGenetics

Abstract

fetched live from OpenAlex

Adoptive cell therapy with therapeutic T cells has become one of the most promising strategies to stimulate or suppress immune responses. Using virus-mediated genetic manipulation, the antigen specificity of T cells can now be precisely redirected. Tailored specificity has not only overcome technical limitations and safety concerns but also considerably broadened the spectrum of therapeutic applications. Different T cell–engineering strategies have now become available to suppress alloimmune responses. We first provide an overview of the allorecognition pathways and effector mechanisms that are responsible for alloimmune injuries in the setting of vascularized organ transplantation. We then discuss the potential to use different T cell–engineering approaches to suppress alloimmune responses. Specifically, expression of allospecific T cell receptors, single-chain chimeric antigen receptors, or antigen domains recognized by B cell receptors (B cell antibody receptors) in regulatory or cytotoxic T cells are considered. The ability of these strategies to control the direct or indirect pathways of allorecognition and the cellular or humoral alloimmune responses is discussed. An intimate understanding of the complex interplay that occurs between the engineered T cells and the alloimmune players is a necessary prerequisite for the design of safe and successful strategies for precise immunomodulation in transplantation. Adoptive cell therapy with therapeutic T cells has become one of the most promising strategies to stimulate or suppress immune responses. Using virus-mediated genetic manipulation, the antigen specificity of T cells can now be precisely redirected. Tailored specificity has not only overcome technical limitations and safety concerns but also considerably broadened the spectrum of therapeutic applications. Different T cell–engineering strategies have now become available to suppress alloimmune responses. We first provide an overview of the allorecognition pathways and effector mechanisms that are responsible for alloimmune injuries in the setting of vascularized organ transplantation. We then discuss the potential to use different T cell–engineering approaches to suppress alloimmune responses. Specifically, expression of allospecific T cell receptors, single-chain chimeric antigen receptors, or antigen domains recognized by B cell receptors (B cell antibody receptors) in regulatory or cytotoxic T cells are considered. The ability of these strategies to control the direct or indirect pathways of allorecognition and the cellular or humoral alloimmune responses is discussed. An intimate understanding of the complex interplay that occurs between the engineered T cells and the alloimmune players is a necessary prerequisite for the design of safe and successful strategies for precise immunomodulation in transplantation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.077
GPT teacher head0.396
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2018
Admission routes2
Has abstractyes

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