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makeTCR: A Modular Platform for Rapid, Flexible, Scalable, Single-Step T Cell Receptor Synthesis

Hamberger, M.; Neuhoff, M.-T.; Pietrantonio, S. V.; Boschert, T.; Torres, C. M.; Errerd, A.; Tan, C. L.; Lindner, J. M.; Platten, M.; Green, E. W.

2025-07-23 immunology
10.1101/2025.04.27.647198 bioRxiv
Show abstract

Personalised cell therapies utilising T cell receptors (TCRs) show tremendous clinical promise, though TCR synthesis and validation techniques lag behind our ability to sequence TCR repertoires. To address this gap, we developed makeTCR: a flexible modular, scalable TCR cloning system that enables single-step, 100% fidelity assembly of {beta} and {gamma}{delta} TCRs into commonly used expression vectors. By implementing cell-free manufacturing, makeTCR enables patient-derived TCRs to be functionally validated within 48 hours. We provide an open-source, easily extensible, web-based graphical platform that integrates existing tools to simplify and standardise the manufacture of TCRs across all scales of synthesis.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
Nature Communications
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Top 14%
12.8%
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2
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3
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5
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6
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Top 4%
4.8%
7
Cell Reports Medicine
○ 153 papers in training set
Top 0.8%
3.4%
8
Cell
○ 431 papers in training set
Top 3%
3.2%
9
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 22%
2.4%
50% of probability mass above
10
eLife
● 5828 papers in training set
Top 43%
2.4%
11
ACS Synthetic Biology
● 287 papers in training set
Top 1%
2.1%
12
npj Vaccines
○ 67 papers in training set
Top 0.4%
2.1%
13
iScience
○ 1154 papers in training set
Top 15%
1.9%
14
Nature Immunology
○ 79 papers in training set
Top 1%
1.9%
15
Molecular Therapy - Methods & Clinical Development
○ 38 papers in training set
Top 0.4%
1.7%
16
mAbs
○ 32 papers in training set
Top 0.2%
1.7%
17
Cell Reports
○ 1498 papers in training set
Top 19%
1.7%
18
Science Advances
● 1243 papers in training set
Top 21%
1.7%
19
Communications Biology
○ 993 papers in training set
Top 17%
1.5%
20
Frontiers in Immunology
○ 638 papers in training set
Top 6%
1.4%
21
Scientific Reports
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Top 60%
1.3%
22
Immunity
○ 67 papers in training set
Top 1%
1.1%
23
Nature Biomedical Engineering
○ 47 papers in training set
Top 1%
1.1%
24
Cell Systems
○ 201 papers in training set
Top 4%
1.0%
25
Cell Genomics
○ 172 papers in training set
Top 4%
1.0%
26
Science
● 477 papers in training set
Top 8%
1.0%
27
Med
○ 39 papers in training set
Top 0.6%
0.9%
28
Molecular Therapy Oncology
○ 10 papers in training set
Top 0.2%
0.8%
29
Journal for ImmunoTherapy of Cancer
● 75 papers in training set
Top 2%
0.8%
30
Journal of Experimental Medicine
● 119 papers in training set
Top 3%
0.8%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.