HDACi promotes inflammatory remodeling of the tumor microenvironment to enhance epitope spreading and antitumor immunity
Bibliographic record
Abstract
Adoptive cell therapy (ACT) with tumor-specific memory T cells has shown increasing efficacy in regressing solid tumors. However, tumor antigen heterogeneity represents a longitudinal challenge for durable clinical responses due to the therapeutic selective pressure for immune escape variants. Here, we demonstrated that delivery of the class I histone deacetylase inhibitor MS-275 promoted sustained tumor regression by synergizing with ACT in a coordinated manner to enhance cellular apoptosis. We found that MS-275 altered the tumor inflammatory landscape to support antitumor immunoactivation through the recruitment and maturation of cross-presenting CD103+ and CD8+ DCs and depletion of Tregs. Activated endogenous CD8+ T cell responses against nontarget tumor antigens were critically required for the prevention of tumor recurrence. Importantly, MS-275 altered the immunodominance hierarchy by directing epitope spreading toward the endogenous retroviral tumor-associated antigen p15E. Our data suggest that MS-275 in combination with ACT multimechanistically enhanced epitope spreading and promoted long-term clearance of solid tumors.
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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 | 0.000 |
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 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".