Specific Roles of Each TCR Hemichain in Generating Functional Chain-Centric TCR
Bibliographic record
Abstract
TCRα- and β-chains cooperatively recognize peptide-MHC complexes. It has been shown that a "chain-centric" TCR hemichain can, by itself, dictate MHC-restricted Ag specificity without requiring major contributions from the paired TCR counterchain. Little is known, however, regarding the relative contributions and roles of chain-centric and its counter, non-chain-centric, hemichains in determining T cell avidity. We comprehensively analyzed a thymically unselected T cell repertoire generated by transducing the α-chain-centric HLA-A*02:01(A2)/MART127-35 TCRα, clone SIG35α, into A2-matched and unmatched postthymic T cells. Regardless of their HLA-A2 positivity, a substantial subset of peripheral T cells transduced with SIG35α gained reactivity for A2/MART127-35. Although the generated A2/MART127-35-specific T cells used various TRBV genes, TRBV27 predominated with >10(2) highly diverse and unique clonotypic CDR3β sequences. T cells individually reconstituted with various A2/MART127-35 TRBV27 TCRβ genes along with SIG35α possessed a wide range (>2 log orders) of avidity. Approximately half possessed avidity higher than T cells expressing clone DMF5, a naturally occurring A2/MART127-35 TCR with one of the highest affinities. Importantly, similar findings were recapitulated with other self-Ags. Our results indicate that, although a chain-centric TCR hemichain determines Ag specificity, the paired counterchain can regulate avidity over a broad range (>2 log orders) without compromising Ag specificity. TCR chain centricity can be exploited to generate a thymically unselected Ag-specific T cell repertoire, which can be used to isolate high-avidity antitumor T cells and their uniquely encoded TCRs rarely found in the periphery because of tolerance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".