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Record W3003231717 · doi:10.1016/j.omtm.2020.01.012

A High-Throughput Method for Characterizing Novel Chimeric Antigen Receptors in Jurkat Cells

2020· article· en· W3003231717 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecular Therapy — Methods & Clinical Development · 2020
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversity of OttawaMcGill UniversityNational Research Council Canada
FundersNational Research Council Canada
KeywordsJurkat cellsChimeric antigen receptorAntigenMonoclonal antibodyBiologyCell biologyElectroporationComputational biologyT cellMolecular biologyChemistryAntibodyImmunologyImmune systemGeneticsGene

Abstract

fetched live from OpenAlex

Chimeric antigen receptor (CAR) development involves extensive empirical characterization of antigen-binding domain (ABD)/CAR constructs for clinical suitability. Here, we present a cost-efficient and rapid method for evaluating CARs in human Jurkat T cells. Using a modular CAR plasmid, a highly efficient ABD cloning strategy, plasmid electroporation, short-term co-culture, and flow-cytometric detection of CD69, this assay (referred to as CAR-J) evaluates sensitivity and specificity for ABDs. Assessing 16 novel anti-CD22 single-chain variable fragments derived from mouse monoclonal antibodies, CAR-J stratified constructs by response magnitude to CD22-expressing target cells. We also characterized 5 novel anti-EGFRvIII CARs for preclinical development, identifying candidates with varying tonic and target-specific activation characteristics. When evaluated in primary human T cells, tonic/auto-activating (without target cells) EGFRvIII-CARs induced target-independent proliferation, differentiation toward an effector phenotype, elevated activity against EGFRvIII-negative cells, and progressive loss of target-specific response upon in vitro re-challenge. These EGFRvIII CAR-T cells also showed anti-tumor activity in xenografted mice. In summary, CAR-J represents a straightforward method for high-throughput assessment of CAR constructs as genuine cell-associated antigen receptors that is particularly useful for generating large specificity datasets as well as potential downstream CAR optimization. Chimeric antigen receptor (CAR) development involves extensive empirical characterization of antigen-binding domain (ABD)/CAR constructs for clinical suitability. Here, we present a cost-efficient and rapid method for evaluating CARs in human Jurkat T cells. Using a modular CAR plasmid, a highly efficient ABD cloning strategy, plasmid electroporation, short-term co-culture, and flow-cytometric detection of CD69, this assay (referred to as CAR-J) evaluates sensitivity and specificity for ABDs. Assessing 16 novel anti-CD22 single-chain variable fragments derived from mouse monoclonal antibodies, CAR-J stratified constructs by response magnitude to CD22-expressing target cells. We also characterized 5 novel anti-EGFRvIII CARs for preclinical development, identifying candidates with varying tonic and target-specific activation characteristics. When evaluated in primary human T cells, tonic/auto-activating (without target cells) EGFRvIII-CARs induced target-independent proliferation, differentiation toward an effector phenotype, elevated activity against EGFRvIII-negative cells, and progressive loss of target-specific response upon in vitro re-challenge. These EGFRvIII CAR-T cells also showed anti-tumor activity in xenografted mice. In summary, CAR-J represents a straightforward method for high-throughput assessment of CAR constructs as genuine cell-associated antigen receptors that is particularly useful for generating large specificity datasets as well as potential downstream CAR optimization.

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.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.165
GPT teacher head0.485
Teacher spread0.320 · 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