A Clinical and Molecular Phase II Trial of Oral ENMD-2076 in Ovarian Clear Cell Carcinoma (OCCC): A Study of the Princess Margaret Phase II Consortium
Bibliographic record
Abstract
Abstract Purpose: Patients with recurrent ovarian clear cell carcinoma (OCCC) have limited effective options due to chemoresistance. A phase II study was designed to assess the activity of ENMD-2076, an oral multitarget kinase selective against Aurora A and VEGFR. Patients and Methods: This multicenter phase II study included patients with recurrent OCCC who received prior platinum-based chemotherapy. Primary endpoints were objective response and 6-month progression-free survival (PFS) rates. Correlative analyses include ARID1A and PTEN expression by IHC and gene sequencing with a targeted custom capture next-generation sequencing panel. Results: Forty patients were enrolled with a median age of 54, of which 38 patients were evaluable. ENMD-2076 was well tolerated with main related grade 3 toxicities being hypertension (28%), proteinuria (10%), and diarrhea (10%). Best response was partial response for 3 patients (1 unconfirmed) and stable disease for 26 patients. The overall 6-month PFS rate was 22% and differed according to ARID1A expression (ARIDIA− vs. ARID1A+; 33% vs. 12%, P = 0.023). PTEN-positive expression was observed in 20 of 36 patients, and there was no correlation with outcome. Median PFS in patients with PI3KCA wild-type versus PI3KCA-mutated group was 5 versus 3.7 months (P = 0.049). Molecular profiling showed variants in PI3KCA (27%), ARID1A (26%), and TP53 (7%). The patient with the longest treatment duration (22 months) was PTEN wild-type, diploid PTEN with putative biallelic inactivation of ARID1A. Conclusions: Single-agent ENMD-2076 did not meet the preset bar for efficacy. Loss of ARID1A correlated with better PFS on ENMD-2076 and warrants further investigation as a potential predictive biomarker.
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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) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".