Selective AKT kinase inhibitor capivasertib in combination with fulvestrant in PTEN-mutant ER-positive metastatic breast cancer
Bibliographic record
Abstract
Five to ten percent of ER+ metastatic breast cancer (MBC) tumors harbor somatic PTEN mutations. Loss of function of this tumor-suppressor gene defines a highly aggressive, treatment-refractory disease for which new therapies are urgently needed. This Phase I multipart expansion study assessed oral capivasertib with fulvestrant in patients with PTEN-mutant ER+ MBC. Safety and tolerability were assessed by standard methods. Plasma and tumor were collected for NGS and immunohistochemistry analyses of PTEN protein expression. In 31 eligible patients (12 fulvestrant naive; 19 fulvestrant pretreated), the 24-week clinical benefit rate was 17% in fulvestrant-naive and 42% in fulvestrant-pretreated patients, with objective response rate of 8% and 21%, respectively. Non-functional PTEN was centrally confirmed in all cases by NGS or immunohistochemistry. Co-mutations occurred in PIK3CA (32%), with less ESR1 (10% vs 72%) and more TP53 (40% vs 28%) alterations in fulvestrant-naive versus fulvestrant-pretreated patients, respectively. PTEN was clonally dominant in most patients. Treatment-related grade ≥3 adverse events occurred in 32% of patients, most frequently diarrhea and maculopapular rash (both n = 2). In this clinical study, which selectively targeted the aggressive PTEN-mutant ER+ MBC, capivasertib plus fulvestrant was tolerable and clinically active. Phenotypic and genomic differences were apparent between fulvestrant-naive and -pretreated patients.Trial registration number for the study is NCT01226316.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".