The evolving treatment landscape for BRAF-mutated non-small cell lung cancer
Bibliographic record
Abstract
Oncogene-driven non-small cell lung cancer (NSCLC) represents a subgroup of lung cancers that harbors specific molecular activations, and is responsive to targeted therapies.Indeed, EGFR and ALK-inhibitors are approved in the first-line setting for NSCLC with EGFR and ALK driver alterations (1).In these subtypes of NSCLC, targeted therapies yield significant improvement in objective response rate (ORR) and progression-free survival (PFS) compared to chemotherapy (1).For other oncogenic drivers in NSCLC, such as BRAF, HER2, MET, RET, ROS1, KRAS and NTRK, targeted therapies are also approved on the basis of single-arm studies (1).Herein we will discuss the implications of the recently published phase 2 PHAROS clinical trial, that evaluated the efficacy of encorafenib and binimetinib for the treatment of BRAF mutant NSCLC (2).BRAF is a kinase that signals in the mitogen activated protein kinase (MAPK) pathway (3).BRAF mutations confer constitutive activation of the MAPK pathway resulting in cell proliferation and tumorigenesis.BRAF mutations are found in 3-5% of NSCLC (4), and can be grouped into three classes based upon molecular characteristics.Class 1 BRAF mutations occur at the V600 residue and signal as constitutively active monomers in a RAS-independent manner (3).BRAF non-V600 mutations can be further classified as RAS-independent active dimers with intermediate to high kinase activity (Class 2), and RAS-dependent kinase-impaired dimers (Class 3) (3).Class 1 BRAF mutations make up the majority of oncogenic BRAF mutations in most cancer types.However, Class 1 mutations only comprise 33-50% of all oncogenic BRAF mutations in NSCLC (5).To date, there are only approved targeted therapies for Class 1 BRAF mutant cancers (6).In NSCLC, all classes of BRAF mutations have been reported as a negative prognostic factor compared to BRAF wildtype (WT) NSCLC (7-9).BRAF inhibitors were first studied for Class 1 BRAF mutant melanoma, demonstrating impressive response rates but were associated with rapid resistance largely due to MAPK pathway reactivation.Indeed, single-agent BRAF inhibitors (vemurafenib or dabrafenib) have elicited ORR of 48-53% and PFS of 5.1-6.8months in melanoma (10-12).Due to MAPK pathway reactivation and the development of rapid resistance with BRAF inhibitor monotherapy,
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.015 | 0.028 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".