A phase 1b study of the ERK inhibitor MK-8353 plus pembrolizumab in patients with advanced solid tumors
Bibliographic record
Abstract
Combining a checkpoint inhibitor with an inhibitor of extracellular signal-regulated kinase (ERK) may result in synergistic antitumor activity. We evaluated MK-8353, an ERK1 and ERK2 inhibitor, plus pembrolizumab in a phase 1b study in patients with advanced solid tumors. This open-label, nonrandomized, dose-escalation study (NCT02972034) enrolled adults with advanced solid tumors previously treated with 1‒5 prior lines of therapy. MK-8353 was administered orally in combination with pembrolizumab 200 mg every 3 weeks as follows: twice daily (arm A; MK-8353 50‒350 mg), once daily (arm B; MK-8353 50‒600 mg), or once daily every other week (arm C; MK-8353 50‒300 mg). The primary objective was evaluation of safety via occurrence of dose-limiting toxicities (DLTs). A secondary objective was objective response by RECIST v1.1 per investigator assessment. Among 110 evaluable patients (arm A, n = 22; arm B, n = 50; arm C, n = 38), median age was 58.0 (range, 35‒79) years and 50% had received 1 or 2 prior lines of therapy. DLTs occurred in 19 patients (n = 6 [27%], n = 8 [16%], and n = 5 [13%], respectively); the most frequent was grade 3 maculopapular rash (n = 15). Grade 3/4 treatment-related AEs occurred in 35% of patients; the most common were maculopapular rash (13%) and increased lipase (5%); none were grade 5. Eight patients (7%) attained an objective response (arm B, n = 7 [complete response, n = 1; partial response, n = 6]; arm C, n = 1 [complete response]). In conclusion, MK-8353 once daily plus pembrolizumab could be administered with a manageable toxicity profile but had modest antitumor activity in patients with advanced solid tumors.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".