Follicular helper-T cells restore CD8<sup>+</sup>-dependent antitumor immunity and anti-PD-L1/PD-1 efficacy
Bibliographic record
Abstract
Background T follicular helper cells (Tfh) are essential to shape B cell response during germinal center formation. Tfh accumulation has been reported in various human cancers, with positive or negative prognostic roles. However, the mechanisms explaining the accumulation of Tfh and their role in cancer remain obscure. Methods In vitro differentiated and mouse cell sorted Tfh phenotype was evaluated by flow cytometry and quantitative PCR (qPCR). Antitumor effect of Tfh was evaluated by adoptive transfer in different tumor-bearing mice models. The involvement of immune cells, cytokines and chemokines was evaluated, using depleting antibodies. Chemokines and cytokines expression and production were evaluated by qPCR and ELISA. In human, the impact of immune cells and chemokines on survival was evaluated by analyzing transcriptomic data from public databases and from our own patient cohorts. Results In this study, we show that Tfh exert an antitumor immune effect in a CD8+-dependent manner. Tfh produce interleukin-21, which sustains proliferation, viability, cytokine production and cytotoxic functions of exhausted T cells. The presence of Tfh is required for efficacy of antiprogrammed cell death ligand-1 therapy. Tfh accumulate in the tumor bed and draining lymph nodes in different mouse cancer models. This recruitment is due to the capacity of transforming growth factor β to drive Chemokine (C-X-C motif) Ligand 13 expression, a chemoattractant of Tfh, by intratumor CD8+ T cells. Accumulation of Tfh and exhausted CD8+ T cells predicts cancer outcome in various cancer types. In patients treated with anti-programmed cell death-1 mAb, accumulation of Tfh and CD8+ at the tumor site is associated with outcome. Conclusion This study provides evidence that CD8+/Tfh crosstalk is important in shaping antitumor immune response generated by immunotherapy.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".