HDACi Delivery Reprograms Tumor-Infiltrating Myeloid Cells to Eliminate Antigen-Loss Variants
Bibliographic record
Abstract
Immune recognition of tumor-expressed antigens by cytotoxic CD8 + T cells is the foundation of adoptive T cell therapy (ACT) and has been shown to elicit significant tumor regression. However, therapy-induced selective pressure can sculpt the antigenicity of tumors, resulting in outgrowth of variants that lose the target antigen. We demonstrate that tumor relapse from ACT and subsequent oncolytic viral vaccination can be prevented using class I HDACi, MS-275. Drug delivery subverted the phenotype of tumor-infiltrating CD11b + Ly6C hi Ly6G – myeloid cells, favoring NOS2/ROS secretion and pro-inflammatory genes characteristic of M1 polarization. Simultaneously, MS-275 abrogated the immunosuppressive function of tumor-infiltrating myeloid cells and reprogrammed them to eliminate antigen-negative tumor cells in a caspase-dependent manner. Elevated IFN-γ within the tumor microenvironment suggests that MS-275 modulates the local cytokine landscape to favor antitumor myeloid polarization through the IFN-γR/STAT1 signaling axis. Exploiting tumor-infiltrating myeloid cell plasticity thus complements T cell therapy in targeting tumor heterogeneity and immune escape.
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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) | 0.002 | 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".