IL6 Induces an IL22+ CD8+ T-cell Subset with Potent Antitumor Function
Bibliographic record
Abstract
Abstract CD8+ T cells can be polarized into several different subsets as defined by the cytokines they produce and the transcription factors that govern their differentiation. Here, we identified the polarizing conditions to induce an IL22-producing CD8+ Tc22 subset, which is dependent on IL6 and the aryl hydrocarbon receptor transcription factor. Further characterization showed that this subset was highly cytolytic and expressed a distinct cytokine profile and transcriptome relative to other subsets. In addition, polarized Tc22 were able to control tumor growth as well as, if not better than, the traditional IFNγ-producing Tc1 subset. Tc22s were also found to infiltrate the tumors of human patients with ovarian cancer, comprising up to approximately 30% of expanded CD8+ tumor-infiltrating lymphocytes (TIL). Importantly, IL22 production in these CD8+ TILs correlated with improved recurrence-free survival. Given the antitumor properties of Tc22 cells, it may be prudent to polarize T cells to the Tc22 lineage when using chimeric antigen receptor (CAR)-T or T-cell receptor (TCR) transduction–based immunotherapies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".