Evidence map›Paper›PMID 36970230›Full record

ArticleEngineering biology2020

Mechanistic modelling of tyrosine recombination reveals key parameters determining the performance of a CAR T cell switching circuit.

Jack E Bowyer, Deboki Chakravarti, Wilson W Wong, Declan G Bates

Open access · goldAbstract read
In one paragraph

Article in Engineering biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 50% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Jack E BowyerSchool of Engineering University of Warwick Coventry CV4 7AL UK.
Deboki ChakravartiDepartment of Biomedical Engineering Boston University Boston MA 02215 USA.
Wilson W WongDepartment of Biomedical Engineering Boston University Boston MA 02215 USA.
Declan G BatesSchool of Engineering University of Warwick Coventry CV4 7AL UK.
Boston University · USUniversity of Warwick · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inducible genetic switches based on tyrosine recombinase-based DNA excision are a promising platform for the regulation and control of chimeric antigen receptor (CAR) T cell activity in cancer immunotherapy. These switches exploit the increased stability of DNA excision in tyrosine recombinases through an inversion-excision circuit design. Here, the authors develop the first mechanistic mathematical model of switching dynamics in tyrosine recombinases and validate it against experimental data through both global optimisation and statistical approximation approaches. Analysis of this model provides guidelines regarding which system parameters are best suited to experimental tuning in order to establish optimal switch performance in vivo. In particular, they find that the switching response can be made significantly faster by increasing the concentration of the inducer drug 4-OHT and/or by using promoters generating higher expression levels of the FlpO recombinase.

Indexed as

biochemistrybiomedical materialscancercancer immunotherapyCAR T cellcellular biophysicschimeric antigen receptor T cell activityDNAdrugsenzymesFlpO recombinasegene therapygenetic engineeringincreased stabilityinducer drug 4‐OHTinducible genetic switchesinversion–excision circuit designmechanistic mathematical modelmechanistic modellingmolecular biophysicsoptimal switch performancestatistical approximation approachesswitching responsesystem parameterstumourstyrosine recombinase‐based DNA excisiontyrosine recombinasestyrosine recombination

Identifiers

PMID36970230
PMCPMC9996713
OpenAlexW3007859873

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.