A phase I trial of ANG1/2-Tie2 inhibitor trebaninib (AMG386) and temsirolimus in advanced solid tumors (PJC008/NCI♯9041)
Bibliographic record
Abstract
BACKGROUND: There is crosstalk between the ANG-Tie2 and the PI3K/Akt/mTOR pathways. Combined ANG1/2 and mTOR blockade may have additive anti-cancer activity. The combination of trebananib, an inhibitor of ANG1/2-Tie2 interaction, with temsirolimus was evaluated in patients with advanced solid tumors to determine tolerability, maximum tolerated dose (MTD), and preliminary antitumor activity. METHODS: Patients were enrolled using 3 + 3 design, and were given intravenous trebananib and temsirolimus on Day 1, 8, 15 and 22 of a 28-day cycle. Dose limiting toxicities (DLTs) were evaluated during cycle 1. Peripheral blood was collected for evaluation of Tie2-expressing monocytes (TEMs) and thymidine phosphorylase (TP). Sparse pharmacokinetic (PK) sampling for trebananib drug levels was performed on Day 1 and 8 of cycle 2. RESULTS: Twenty-one patients were enrolled, 6 at dose level (DL) 1, 7 at DL -1, and 8 at DL -2. No effect of temsirolimus on trebananib PK was observed. The most common treatment-related adverse events (AEs) were: fatigue (81 %), edema (62 %), anorexia (57 %), nausea (52 %), rash (43 %) and mucositis (43 %). The most common grade ≥ 3 AEs included lymphopenia (28 %) and fatigue (28 %). The MTD was exceeded at DL-2. Of 18 response evaluable patients, 1 partial response was observed (ER+/HER2-/PIK3CA mutant breast cancer) and 4 patients had prolonged SD ≥ 24 weeks. No correlation with clinical benefit was observed with change in number TEMs or TP expression in TEMs with treatment. CONCLUSIONS: The MTD was exceeded at trebananib 10 mg/kg weekly and temsirolimus 20 mg weekly, with frequent overlapping toxicities including fatigue, edema, and anorexia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".