Efficacy of EZH2 inhibitory drugs in human papillomavirus-positive and human papillomavirus-negative oropharyngeal squamous cell carcinomas
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent cancer worldwide with rates of HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) dramatically increasing. The overexpression of enhancer of zeste homolog 2 (EZH2), a histone methyltransferase responsible for the trimethylation at lysine 27 of histone 3 (H3K27me3), is associated with a poor clinical prognosis and aggressive HPV-positive phenotypes. METHODS: We utilized three EZH2 pathway inhibitors, GSK-343, DZNeP, and EPZ-5687, and tested their efficacy in two HPV-positive and two HPV-negative OPSCC cell lines. RESULTS: Treatment with GSK-343 decreased H3K27me3 in all cell lines and treatment with DZNeP decreased H3K27me3 in only HPV-negative cell lines as determined by Western blot. Cells treated with EPZ-5687 displayed no appreciable change in H3K27me3. Epigenetic effect on gene expression was measured via ddPCR utilizing 11 target probes. Cells treated with DZNeP showed the most dramatic expressional changes, with decreased EGFR in HPV-positive cell lines and an overall increase in proliferation markers in HPV-negative cell lines. GSK-343-treated cells displayed moderate expressional changes, with CCND1 increased in HPV-positive cell lines and decreased TP53 in HPV-negative SCC-1. EPZ-5687-treated cell lines displayed few expressional changes overall. Only DZNeP-treated cells displayed anti-proliferative characteristics shown in wound-healing assays. CONCLUSIONS: Our findings suggest that EZH2 inhibitors are a viable therapeutic option for the role of epigenetic effect, potentially sensitizing tumors to current chemotherapies or limiting cell differentiation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it