Ipatasertib in patients with <i>AKT1/2/3</i> mutation-positive (<i>AKT</i>mut) tumors: TAPISTRY study.
Bibliographic record
Abstract
3092 Background: AKT1/2/3 point mutations are found in ~1% of all solid tumors, with varying prevalence across different tumor types. Ipatasertib is an inhibitor of the AKT kinase, but its antitumor activity as monotherapy in patients with AKTmut tumors is unknown. We present efficacy and safety data of ipatasertib in patients with advanced/metastatic AKTmut solid tumors from Cohort E of the TAPISTRY trial (NCT04589845). Methods: TAPISTRY is a phase II, global, open-label, multi-cohort trial evaluating the efficacy and safety of different therapies in patients with advanced/metastatic solid tumors. Patients in Cohort E were aged ≥12 years and had solid tumors harboring an AKT1/2/3mutation identified by next-generation sequencing and measurable disease by RECIST v1.1. Oral ipatasertib 400 mg was administered once daily. Tumor assessments were performed at screening, every eight weeks from Day 1/Cycle 1 for one year, and every 12 weeks after that. The primary endpoint was objective response rate (ORR) by independent review committee (IRC). Key secondary endpoints included ORR by investigator, duration of response, progression-free survival, overall survival and safety. Results: At data cut-off (16 Jul 2023), 50 patients were safety evaluable and 48 were efficacy evaluable. In the safety-evaluable population, median age was 59 years (range, 30–79); 98% of patients (n/N = 49/50) had an AKT1 mutation ( AKT1 E17K, n=47) and 2% (n/N = 1/50) had an AKT2 E17K mutation; 41/50 patients (82%) had received ≥2 prior lines of treatment. Efficacy-evaluable patients had 10 different tumor types, the most common being breast cancer (n/N = 21/48; 44%). Key outcomes are summarized in the Table. After a median follow-up of 11.3 months, ORR by IRC in efficacy-evaluable patients was 31.3% (n/N = 15/48; 95% CI 18.7–46.3), driven by responses in three tumor types: breast (n/N = 7/21; 33%), endometrial (n/N = 7/7; 100%), and head and neck (n/N = 1/2; 50%). The most frequent adverse event was diarrhea (n/N = 39/50; 78%). Safety was consistent with the known profile of ipatasertib; no new safety signals were identified. Conclusions: Treatment with ipatasertib led to a marked and durable antitumor activity in some tumor types such as endometrial cancer, but not in the overall tumor-agnostic cohort. Further studies are needed to understand the relevance of AKT inhibition in these tumor types. Clinical trial information: NCT04589845 . [Table: see text]
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".