cMet: Results in papillary renal cell carcinoma of a phase I study of AZD6094/volitinib leading to a phase 2 clinical trial with AZD6094/volitinib in patients with advanced papillary renal cell cancer (PRCC).
Bibliographic record
Abstract
487 Background: Met is a receptor tyrosine kinase that is deregulated across multiple cancer types, leading to uncontrolled tumor cell growth, invasion and survival. MET is frequently dysregulated in PRCC. Activating Met mutations are present in hereditary and a subset of sporadic PRCC cases (up to 21% of type I PRCC, Albiges et al, 2014). Trisomy of chromosome 7 (containing both MET and HGF genes) has been reported in 45-75% of sporadic PRCC cases; 81% of type I and 46% of type II PRCC have copy number alterations of MET (Albiges et al, 2014). Methods: AZD6094 (HMPL-504/volitinib) is a potent, selective Met inhibitor. Preclinically, AZD6094 inhibits in vitro growth of MET-amplified gastric and lung cell lines. In vivo AZD6094 induces regressions in PRCC explant models. Results: In phase I, AZD6094 was well tolerated, with good exposure and low accumulation (Gan et al, 2014). Two PRCC pts in the 600 mg QD cohort (one with ongoing treatment at 19 months) and 1 PRCC in the 1,000 mg QD cohort (ongoing treatment at 13 months) achieved PR. A fourth patient, on 300 mg BD, showed a best tumor response of 25% decrease from baseline. Analysis of tumor samples showed that all the responders had MET copy number increase. Conclusions: These encouraging findings have triggered a phase II trial. This is an open label non-randomised multi-centre study to assess the efficacy of AZD6094 monotherapy in treatment naive and previously treated PRCC patients. Eligibility includes PRCC histopathology, ECOG status 0 or 1, ability to comply with the collection of tumor samples, adequate haematological, liver, and kidney function, and measurable disease (RECIST 1.1). The study is ongoing in collaboration with Sarah Cannon Research Institute in the United States, Canadian, EU centres. This study is sponsored by AstraZeneca, clinical trial information: NCT02127710. Clinical trial information: NCT01773018.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Non-randomized trial | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".