Pan-Cancer Efficacy of Vemurafenib in <i>BRAF</i> V600-Mutant Non-Melanoma Cancers
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
Abstract BRAF V600 mutations occur in a wide range of tumor types, and RAF inhibition has become standard in several of these cancers. Despite this progress, BRAFV600 mutations have historically been considered a clear demonstration of tumor lineage context–dependent oncogene addiction, based predominantly on the insensitivity to RAF inhibition in colorectal cancer. However, the true broader activity of RAF inhibition pan-cancer remains incompletely understood. To address this, we conducted a multicohort “basket” study of the BRAF inhibitor vemurafenib in non-melanoma BRAFV600 mutation–positive solid tumors. In total, 172 patients with 26 unique cancer types were treated, achieving an overall response rate of 33% and median duration of response of 13 months. Responses were observed in 13 unique cancer types, including historically treatment-refractory tumor types such as cholangiocarcinoma, sarcoma, glioma, neuroendocrine carcinoma, and salivary gland carcinomas. Collectively, these data demonstrate that single-agent BRAF inhibition has broader clinical activity than previously recognized. Significance: These data suggest that BRAFV600 mutations lead to oncogene addiction and are clinically actionable in a broad range of non-melanoma cancers, including tumor types in which RAF inhibition is not currently considered standard of care. See related commentary by Ribas and Lo, p. 640. This article is highlighted in the In This Issue feature, p. 627
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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