Reduction of Global H3K27me3 Enhances HER2/ErbB2 Targeted Therapy
Bibliographic record
Abstract
Monoclonal antibodies (mAbs) targeting the oncogenic receptor tyrosine kinase ERBB2/HER2, such as Trastuzumab, are the standard of care therapy for breast cancers driven by ERBB2 overexpression and activation. However, a substantial proportion of patients exhibit de novo resistance. Here, by comparing matched Trastuzumab-naive and post-treatment patient samples from a neoadjuvant trial, we link resistance with elevation of H3K27me 3 , a repressive histone modification catalyzed by polycomb repressor complex 2 (PRC2). In ErbB2+ breast cancer models, PRC2 silences endogenous retroviruses (ERVs) to suppress anti-tumor type-I interferon (IFN) responses. In patients, elevated H3K27me 3 in tumor cells following Trastuzumab treatment correlates with suppression of interferon-driven viral defense gene expression signatures and poor response. Using an immunocompetent model, we provide evidence that EZH2 inhibitors promote interferon-driven immune responses that enhance the efficacy of anti-ErbB2 mAbs, suggesting the potential clinical benefit of epigenomic reprogramming by H3K27me 3 depletion in Trastuzumab-resistant disease.
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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) | 0.003 | 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".