A Rare p.T599dup BRAF Mutant NSCLC in a Non-Smoker
Bibliographic record
Abstract
V-RAF murine sarcoma viral oncogene homolog B1 (BRAF) mutated non-small-cell lung cancer (NSCLC) is an exceptionally rare form of lung cancer, found only in one to two percent of patients with an NSCLC diagnosis. BRAF NSCLC traditionally affects former or active smokers. BRAF mutations have always been of special interest to the oncological community, as they offer potential for targeted therapies. BRAF mutation spectrum includes mutations that are of both V600 and non-V600 types. BRAF V600 is an activating mutation, which results in high kinase activity and overproduction of active oncoproteins such as rapidly accelerated fibrosarcoma (RAF). This makes them susceptible to targeted therapies with RAF inhibitors. There has been little evidence, however, regarding efficacy of RAF inhibitors towards non-activating mutations that have intermediate to low kinase activity, such as non-V600 BRAF mutations. While several approaches have been investigated to overcome the limitations of RAF inhibitors, such as use of mitogen-activated protein kinase kinase (MEK) and extracellular signal-regulated kinase (ERK) inhibitors or combination of MEK and RAF inhibitors, none of them have been proven to have a superior efficacy for low kinase activity non-V600 BRAF tumors. We present a case of an extremely rare variant of NSCLC BRAF p.T599dup mutation in a non-smoker that responded to a targeted combination therapy with RAF and MEK inhibitors. The patient responded well to therapy that usually targets high kinase activity V600 mutations. Our hope is to bring more attention to non-V600 mutations and document their responses to existing and new therapies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".