EZH2 inhibition mitigates HIV immune evasion, reduces reservoir formation, and promotes skewing of CD8+ T cells toward less-exhausted phenotypes
Bibliographic record
Abstract
Persistent HIV reservoirs in CD4 + T cells pose a barrier to curing HIV infection. We identify overexpression of enhancer of zeste homolog 2 (EZH2) in HIV-infected CD4 + T cells that survive cytotoxic T lymphocyte (CTL) exposure, suggesting a mechanism of CTL resistance. Inhibition of EZH2 with the US Food and Drug Administration-approved drug tazemetostat increases surface expression of major histocompatibility complex (MHC) class I on CD4 + T cells, counterbalancing HIV Nef-mediated MHC class I downregulation. This improves CTL-mediated elimination of HIV-infected cells and suppresses viral replication in vitro . In a participant-derived xenograft mouse model, tazemetostat elevates MHC class I and the pro-apoptotic protein BIM in CD4 + T cells, facilitating CD8 + T cell-mediated reductions of HIV reservoir seeding. Additionally, tazemetostat promotes sustained skewing of CD8 + T cells toward less-differentiated and exhausted phenotypes. Our findings reveal EZH2 overexpression as a mechanism of CTL resistance and support the clinical evaluation of tazemetostat as a method of enhancing clearance of HIV reservoirs and improving CD8 + T cell function.
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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 | 0.000 |
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".