Overproduction of IFNγ by Cbl-b–Deficient CD8+ T Cells Provides Resistance against Regulatory T Cells and Induces Potent Antitumor Immunity
Bibliographic record
Abstract
Regulatory T cells (Treg) are an integral component of the adaptive immune system that negatively affect antitumor immunity. Here, we investigated the role of the E3 ubiquitin ligase casitas B-lineage lymphoma-b (Cbl-b) in establishing CD8+ T-cell resistance to Treg-mediated suppression to enhance antitumor immunity. Transcriptomic analyses suggested that Cbl-b regulates pathways associated with cytokine signaling and cellular proliferation. We showed that the hypersecretion of IFNγ by Cbl-b-deficient CD8+ T cells selectively attenuated CD8+ T-cell suppression by Tregs. Although IFNγ production by Cbl-b-deficient T cells contributed to phenotypic alterations in Tregs, the cytokine did not attenuate the suppressive function of Tregs. Instead, IFNγ had a profound effect on CD8+ T cells by directly upregulating interferon-stimulated genes and modulating T-cell activation. In murine models of adoptive T-cell therapy, Cbl-b-deficient T cells elicited superior antitumor immune response. Furthermore, Cbl-b-deficient CD8+ T cells were less susceptible to suppression by Tregs in the tumor through the effects of IFNγ. Collectively, this study demonstrates that the hypersecretion of IFNγ serves as a key mechanism by which Cbl-b-deficient CD8+ T cells are rendered resistant to Tregs. See related Spotlight by Wolf and Baier, p. 370.
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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) | 0.001 | 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".