Phased differentiation of γδ T and T CD8 tumor-infiltrating lymphocytes revealed by single-cell transcriptomics of human cancers
Bibliographic record
Abstract
γδ T lymphocytes diverge from conventional T CD8 lymphocytes for ontogeny, homing, and antigen specificity, but whether their differentiation in tumors also deviates was unknown. Using innovative analyses of our original and ~150 published single-cell RNA sequencing datasets validated by phenotyping of human tumors and murine models, here we present the first high-resolution view of human γδ T cell differentiation in cancer. While γδ T lymphocytes prominently encompass TCRVγ9 cells more differentiated than T CD8 in healthy donor's blood, a different scenario is unveiled in tumors. Solid tumors and lymphomas are infiltrated by a majority of TCRVγnon9 γδ T cells which are quantitatively correlated and remarkably aligned with T CD8 for differentiation, exhaustion, gene expression profile, and response to immune checkpoint therapy. This cancer-wide association is critical for developing cancer immunotherapies.
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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 | 0.000 | 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 | 0.000 |
| 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 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".