Abstract A229: BRAF inhibitors upregulate EGFR ligands: A molecular link to RAF inhibitor-induced cutaneous squamous cell carcinomas.
Bibliographic record
Abstract
Abstract Selective inhibitors of BRAF such as vemurafenib (PLX4032) and GSK2118436 show remarkable efficacy in melanoma patients with tumors harboring BRAF V600 mutations. However these compounds paradoxically activate the MAPK pathway in RAS-mutant cells and are associated clinically with appearance of skin tumors such as cutaneous squamous cell carcinomas (cuSCC), particularly of the keratoacanthoma subtype. Here we further investigated the molecular links between BRAF inhibitor treatment and skin neoplasm. In soft agar, BRAF inhibitors induced growth of HRAS-mutant cuSCC B9 cells via upregulation of several EGFR ligands. The EGFR inhibitor Tarceva antagonized this transforming effect. The “Paradox Breakers,” a class of BRAF inhibitors recently discovered at Plexxikon, did not activate the MAPK pathway in cells with RAS mutation or EGFR family kinase activation and failed to upregulate EGFR ligands or induce soft agar growth of B9 cells. Also when tested in vivo, subcutaneous B9-tumor growth was accelerated by a structural analog (PLX4720) of vemurafenib but not by an equally effective BRAF inhibitor of the Paradox Breaker class. Taken together, a novel mechanism responsible for BRAF inhibitor-induced cuSCC was uncovered. Our data suggest that combination treatment of EGFR inhibitors with BRAF inhibitors might prevent skin tumor growth and that Paradox Breakers represent a new generation of BRAF inhibitors that have fewer unwanted side effects and the potential for greater clinical efficacy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr A229.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".