A parallel-arm phase I trial of the humanised anti-IGF-1R antibody dalotuzumab in combination with the AKT inhibitor MK-2206, the mTOR inhibitor ridaforolimus, or the NOTCH inhibitor MK-0752, in patients with advanced solid tumours
Bibliographic record
Abstract
BACKGROUND: Two strategies to interrogate the insulin growth factor 1 receptor (IGF-1R) pathway were investigated: vertical inhibition with dalotuzumab and MK-2206 or ridaforolimus to potentiate PI3K pathway targeting and horizontal cross-talk inhibition with dalotuzumab and MK-0752 to exert effects against cellular proliferation, angiogenesis, and stem cell propagation. METHODS: A phase I, multi-cohort dose escalation study was conducted in patients with advanced solid tumours. Patients received dalotuzumab (10 mg kg(-1)) and escalating doses of MK-2206 (90-200 mg) or escalating doses of dalotuzumab (7.5-10 mg kg(-1)) and MK-0752 (1800 mg) weekly. Upon maximum tolerated dose determination, patients with low-RAS signature, high-IGF1 expression ovarian cancer were randomised to dalotuzumab/MK-2206 versus dalotuzumab/ridaforolimus, whereas patients with high IGF1/low IGF2 expression colorectal cancer received dalotuzumab/MK-0752. RESULTS: A total of 47 patients were enrolled: 29 in part A (18 in the dalotuzumab/MK-2206 arm and 11 in the dalotuzumab/MK-0752 arm) and 18 in part B (6 in each arm). Dose-limiting toxicities (DLTs) for dalotuzumab/MK-2206 included grade 4 neutropenia and grade 3 serum sickness-like reaction, maculopapular rash, and gastrointestinal inflammation. For dalotuzumab/MK-0752, DLTs included grade 3 dehydration, rash, and diarrhoea. Seven patients remained on study for >4 cycles. CONCLUSIONS: Dalotuzumab/MK-2206 and dalotuzumab/MK-0752 combinations were tolerable. Further developments of prospectively validated predictive biomarkers to aid in patient selection for anti-IGF-1R therapies are needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".