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Record W4393155298 · doi:10.1101/2024.03.23.24304779

Clinical activity of Mitogen-Activated Protein Kinase (MAPK) inhibitors in patients with MAP2K1 (MEK1)-mutated metastatic cancers

2024· preprint· en· W4393155298 on OpenAlexafffund
Matthew Dankner, Emmanuelle Rousselle, Sarah Petrecca, François Fabi, Alexander Nowakowski, Anna-Maria Lazaratos, Charles Vincent Rajadurai, Andrew J. B. Stein, David Bian, Peter Tai, Alicia Belaiche, Meredith Li, Andrea Quaiattini, Nicola Normanno, Maria E. Arcila, Arielle Elkrief, Douglas B. Johnson, Marc Ladanyi, April A. N. Rose

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanJewish General HospitalInstitute for Research in Immunology and CancerMcGill UniversityMcGill University Health Centre
FundersFonds de Recherche du Québec - Santé
KeywordsMAPK/ERK pathwayProtein kinase AMitogen-activated protein kinaseCancer researchMitogen-activated protein kinase kinaseKinaseMedicineInternal medicineBiologyCell biology

Abstract

fetched live from OpenAlex

Abstract PURPOSE MAP2K1/MEK1 mutations are potentially actionable drivers in cancer. MAP2K1 mutations have been functionally classified into three groups according to their dependency on upstream RAS/RAF signaling. However, the clinical efficacy of MAPK pathway inhibitors (MAPKi) for MAP2K1 mutant tumors is not well defined. We sought to characterize the genomic and clinical landscape of MAP2K1 mutant tumors to evaluate the relationship between MAP2K1 mutation Class and clinical activity of MAPKi. METHODS We interrogated AACR GENIE (v13) to analyze solid tumors with MAP2K1 mutations. We performed a systematic review and meta-analysis of published reports of patients with MAP2K1 mutant cancers treated with MAPKi according to PRISMA guidelines. The primary endpoint was progression-free survival (PFS), and secondary endpoints were overall response rate (ORR), duration of response (DOR), and overall survival (OS). RESULTS In the AACR GENIE dataset, Class 2 MAP2K1 mutations (63%) were more prevalent than Class 1 (24%) and Class 3 (13%) mutations (P<0.0001). Co-occurring MAPK pathway activating mutations were more likely to occur in Class 1 versus Class 2 or 3 MAP2K1 mutant tumors (P<0.0001). Our systematic meta-analysis of the literature identified 46 patients with MAP2K1 mutant tumors who received MAPKi. In these patients, ORR was 28% and median PFS was 3.9 months. ORR did not differ according to MAP2K1 mutation class or cancer type. However, patients with Class 2 mutations experienced longer PFS (5.0 months) and DOR (23.8 months) compared to patients with Class 1, 3 or unclassified MAP2K1 mutations (PFS 3.5 months, P=0.04; DOR 4.2 months, P=0.02). CONCLUSION Patients with Class 2 MAP2K1 mutations represent a novel subgroup that may derive benefit from MAPKi. Prospective clinical studies with novel MAPKi regimens are warranted in these patients. Highlights - A meta-analysis describing clinical outcomes with MAPK targeted therapy in MAP2K1 mutant tumors. - Clinical validation of MAP2K1 mutation Class as a predictive biomarker. - Class 2 MAP2K1 mutations are sensitive to MEK-inhibitor containing regimens. Graphical Abstract

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.011
Bibliometrics0.0030.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.278
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2024
Admission routes2
Has abstractyes

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