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Record W4223492952 · doi:10.1016/j.celrep.2022.110634

Melanomas with concurrent BRAF non-p.V600 and NF1 loss-of-function mutations are targetable by BRAF/MEK inhibitor combination therapy

2022· article· en· W4223492952 on OpenAlexafffund
Shivshankari Rajkumar, Diana Berry, Kayla A. Heney, Colton Strong, LeeAnn Ramsay, Mathieu Lajoie, Rached Alkallas, Tan-Trieu Nguyen, Cameron Thomson, Mozhdeh Ahanfeshar-Adams, Matthew Dankner, Teresa M. Petrella, April A. N. Rose, Peter M. Siegel, Ian R. Watson

Bibliographic record

VenueCell Reports · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsJewish General HospitalMcGill University Health CentreSunnybrook Health Science CentreHealth Sciences CentreUniversity of British ColumbiaMcGill University
FundersCanadian Institutes of Health Research
KeywordsNeuroblastoma RAS viral oncogene homologMelanomaMutantCancer researchMEK inhibitorMutationCombination therapyTrametinibContext (archaeology)In vivoTargeted therapyMedicineMAPK/ERK pathwayBiologyKinaseCancerKRASPharmacologyGeneticsInternal medicineGene

Abstract

fetched live from OpenAlex

Although combination BRAF/MEK inhibition has produced significant survival benefits for BRAF p.V600 mutant melanomas, targeted therapies approved for BRAF non-p.V600 mutant melanomas remain limited. Through the analysis of 772 cutaneous melanoma exomes, we reveal that BRAF non-p.V600 mutations co-occurs more frequently with NF1 loss, but not with oncogenic NRAS mutations, than expected by chance. We present cell signaling data, which demonstrate that BRAF non-p.V600 mutants can signal as monomers and dimers within an NF1 loss context. Concordantly, BRAF inhibitors that inhibit both monomeric and dimeric BRAF synergize with MEK inhibition to significantly reduce cell viability in vitro and tumor growth in vivo in BRAF non-p.V600 mutant melanomas with co-occurring NF1 loss-of-function mutations. Our data suggest that patients harboring BRAF non-p.V600 mutant melanomas may benefit from current FDA-approved BRAF/MEK inhibitor combination therapy currently reserved for BRAF p.V600 mutant patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.200
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2022
Admission routes2
Has abstractyes

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