BET and BRAF inhibitors act synergistically against <i>BRAF‐</i>mutant melanoma
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
Despite major advances in the treatment of metastatic melanoma, treatment failure is still inevitable in most cases. Manipulation of key epigenetic regulators, including inhibition of Bromodomain and extra-terminal domain (BET) family members impairs cell proliferation in vitro and tumor growth in vivo in different cancers, including melanoma. Here, we investigated the effect of combining the BET inhibitor JQ1 with the BRAF inhibitor Vemurafenib in in vitro and in vivo models of BRAF-mutant melanoma. We performed cytotoxicity and apoptosis assays, and a xenograft mouse model to determine the in vitro and in vivo efficacy of JQ1 in combination with Vemurafenib against BRAF-mutant melanoma cell lines. Further, to investigate the molecular mechanisms underlying the effects of combined treatment, we conducted antibody arrays of in vitro drug-treated cell lines and RNA sequencing of drug-treated xenograft tumors. The combination of JQ1 and Vemurafenib acted synergistically in BRAF-mutant cell lines, resulting in marked apoptosis in vitro, with upregulation of proapoptotic proteins. In vivo, combination treatment suppressed tumor growth and significantly improved survival compared to either drug alone. RNA sequencing of tumor tissues revealed almost four thousand genes that were uniquely modulated by the combination, with several anti-apoptotic genes significantly down-regulated. Collectively, our data provide a rationale for combined BET and BRAF inhibition as a novel strategy for the treatment of melanoma.
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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 | 0.000 | 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) | 0.000 | 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