Generation and molecular recognition of melanoma-associated antigen-specific human γδ T cells
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.
Bibliographic record
Abstract
Antigen recognition by T cells bearing αβ T cell receptors (TCRs) is restricted by major histocompatibility complex (MHC). However, how antigens are recognized by T cells bearing γδ TCRs remains unclear. Although γδ T cells can recognize nonclassical MHC, it is generally thought that recognition of antigens is not MHC restricted. Here, we took advantage of an in vitro system to generate antigen-specific human T cells and show that melanoma-associated antigens, MART-1 and gp100, can be recognized by γδ T cells in an MHC-restricted fashion. Cloning and transferring of MART-1-specific γδ TCRs restored the specific recognition of the initial antigen MHC/peptide reactivity and conferred antigen-specific functional responses. A crystal structure of a MART-1-specific γδ TCR, together with MHC/peptide, revealed distinctive but similar docking properties to those previously reported for αβ TCRs, recognizing MART-1 on HLA-A*0201. Our work shows that antigen-specific and MHC-restricted γδ T cells can be generated in vitro and that MART-1-specific γδ T cells can also be found and cloned from the naïve repertoire. These findings reveal that classical MHC-restricted human γδ TCRs exist in the periphery and have the potential to be used in developing of new TCR-based immunotherapeutic approaches.
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 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 | 0.000 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it