EZH2 Inhibition: A Promising Strategy to Prevent Cancer Immune Editing
Bibliographic record
Abstract
Immunotherapies are revolutionizing the clinical management of a wide range of cancers. However, intrinsic or acquired unresponsiveness to immunotherapies does occur due to the dynamic cancer immunoediting which ultimately leads to immune escape. The evolutionarily conserved histone modifier enhancer of zeste 2 (EZH2) is aberrantly overexpressed in a number of human cancers. Accumulating studies indicate that EZH2 is a main driver of cancer cells' immunoediting and mediate immune escape through downregulating immune recognition and activation, upregulating immune checkpoints and creating an immunosuppressive tumor microenvironment. In this review, we overviewed the roles of EZH2 in cancer immunoediting, the preclinical and clinical studies of current pharmacologic EZH2 inhibitors and the prospects for EZH2 inhibitor and immunotherapy combination for cancer treatment.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".