Phase 1b Clinical Trial with Alpelisib plus Olaparib for Patients with Advanced Triple-Negative Breast Cancer
Bibliographic record
Abstract
PURPOSE: We had previously reported on the safety and the recommended phase 2 dose (RP2D) of olaparib in combination with the PI3Kα-specific inhibitor alpelisib in patients with high-grade serous ovarian cancer as studied in a phase 1b trial (NCT01623349). Here, we report on the breast cancer cohort from that study. PATIENTS AND METHODS: Eligible patients had recurrent triple-negative breast cancer (TNBC) or recurrent breast cancer of any subtype with a germline BRCA mutation and were enrolled to a dose-escalation or -expansion cohort. After definition of the RP2D, secondary end points included safety and objective response rate (ORR). Exploratory analyses were performed using circulating-free DNA (cfDNA). RESULTS: Seventeen patients with TNBC were enrolled with a median of three prior lines of chemotherapy. The most common treatment-related grade 3-4 adverse events were hyperglycemia (18%) and rash (12%). The ORR was 18% (23% for patients treated at the RP2D) and 59% had disease control. The median duration of response was 7.4 months. Analysis of cfDNA tumor fractions (TFx) revealed that patients with TFx < 15% after completion of the first cycle had a longer progression-free survival compared with those with TFx ≥ 15% (6.0 vs. 0.9 months; P = 0.0001). CONCLUSIONS: Alpelisib in combination with olaparib is tolerable in patients with pre-treated TNBC, with evidence of activity in non-BRCA carriers. cfDNA provided important prognostic information. Results highlight potential synergistic use of a PI3K inhibitor to sensitize HR-proficient (BRCA wild-type) TNBC to PARP inhibition and suggest the potential to expand the use of PARP inhibition beyond BRCA-mutant 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".