Clinical Activity of Mitogen-Activated Protein Kinase Inhibitors in Patients With MAP2K1 (MEK1)-Mutated Metastatic Cancers
Bibliographic record
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 mitogen-activated protein kinase (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 American Association for Cancer Research (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 Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The primary end point was progression-free survival (PFS), and secondary end points were overall treatment response rate (ORR), duration of response (DOR), and overall survival. RESULTS In the AACR GENIE data set, class 2 MAP2K1 mutations (63%) were more prevalent than class 1 (24%) and class 3 (13%) mutations ( P < .0001). Co-occurring MAPK pathway-activating mutations were more likely to occur in class 1 versus class 2 or 3 MAP2K1-mutant tumors ( P < .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 with patients with class 1, 3, or unclassified MAP2K1 mutations (PFS 3.5 months, P = .04; DOR 4.2 months, P = .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.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".