PI3K/AKT pathway biomarkers analysis from the phase III IPATential150 trial of ipatasertib plus abiraterone in metastatic castration-resistant prostate cancer.
Bibliographic record
Abstract
13 Background: In IPATential150 (NCT03072238), ipatasertib (ipat) + abiraterone (abi) as first-line treatment for metastatic castration-resistant prostate cancer (mCRPC) significantly reduced the risk for disease worsening or death vs placebo (pbo) + abi in patients (pts) with tumors with PTEN loss by immunohistochemistry (IHC; HR, 0.77 [95% CI: 0.61, 0.98]; P = 0.0335) but not in the intention-to-treat population (de Bono, ESMO 2020). In patients with PTEN loss tumors by IHC, median radiographic progression-free survival (rPFS) was 16.5 mo (95% CI: 13.9, 17.0) with pbo + abi and 18.5 mo (95% CI: 16.3, 22.1) with ipat + abi. Here, we present exploratory analyses evaluating putative biomarker associations with rPFS. Methods: Before randomization, tumor samples ( > 90% archival) were tested for PTEN loss by VENTANA PTEN (SP218) IHC assay (N = 1101). PTEN loss was pre-defined as ≥ 50% of tumor cells with no specific cytoplasmic IHC staining. Exploratory analysis evaluated different IHC staining cutoffs. Tumor genomic alterations were profiled with next-generation sequencing (NGS) using the Foundation Medicine FoundationOne CDx NGS assay (Shi, ASGO-GU 2020; n = 743 evaluable by NGS, of which n = 518 were PTEN evaluable). rPFS was determined by the investigator. Results: Consistent benefit with the combination arm vs pbo + abi was observed when PTEN loss by IHC was defined more stringently (rPFS at ≥ 60% tumor cells with PTEN loss: HR, 0.72 [95% CI, 0.56, 0.92]; ≥ 70%: HR, 0.72 [95% CI, 0.56, 0.93]; ≥ 80%: HR, 0.71 [95% CI, 0.54, 0.92]; ≥ 90%: HR, 0.72 [95% CI, 0.53, 0.97]; 100%: HR, 0.65 [95% CI, 0.39, 1.08]). In contrast, ipat + abi was not associated with improved rPFS in pts with PTEN intact by IHC tumors ( < 50% no staining; stratified HR, 0.91 [95% CI: 0.72, 1.16]); the median rPFS was 19.1 mo (95% CI: 16.4, 21.9) with pbo + abi and 19.7 mo (95% CI: 16.4, 26.3) with ipat + abi. By NGS assessment, pts with tumors with PTEN loss and with genomic alterations in PIK3CA/AKT1/PTEN had a larger magnitude of rPFS benefit with ipat + abi than pts with no detectable alterations (Table). Conclusions: Analyses of more-stringent biomarkers associated with activation of the PI3K/AKT pathway further support ipat + abi as a treatment option for first-line mCRPC with PI3K/AKT pathway alterations, a mCRPC subtype with a worse prognosis. Clinical trial information: NCT03072238. [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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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, 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".