Abstract PD3-12: <i>PIK3CA</i> alterations and benefit with neratinib after trastuzumab-based adjuvant therapy in early-stage HER2+ breast cancer: Correlative analyses of the phase III ExteNET trial
Bibliographic record
Abstract
Abstract Background: Neratinib is a pan-HER tyrosine kinase inhibitor that blocks the PI3K/Akt and MAPK signaling pathways downstream from HER2. The international, randomized, placebo-controlled phase III ExteNET trial showed that a 1-year course of neratinib after trastuzumab-based adjuvant therapy significantly improved 2-year invasive disease-free survival (iDFS) in early-stage HER2+ breast cancer (HR 0.67; 95% CI 0.50–0.91; p=0.0091) [Chan et al. Lancet Oncol 2016]. Furthermore, the effects of neratinib on iDFS were shown to be durable at 5 years' follow-up (HR 0.73; 95% CI 0.57–0.92; p=0.008) [Martin et al. ESMO 2017]. PIK3CA alterations are common in HER2+ breast cancers, and in general are associated with a worse prognosis. We sought to assess the prognostic and predictive significance of PIK3CA alterations in an exploratory substudy of the ExteNET trial. Methods: ExteNET is an international, multi-center, randomized, double-blind, placebo-controlled phase III trial (Clinicaltrials.gov: NCT00878709). Patients received oral neratinib 240 mg/day or placebo for 1 year. Of the intent-to-treat (ITT) population (n=2840), primary formalin-fixed paraffin-embedded (FFPE) tumor specimens were available from 991 patients for PIK3CA mutation testing by RT-PCR for two hot-spot mutations in exon 9 (E542K, E545K/D) and one hot-spot mutation in exon 20 (H1047R). 702 FFPE tumor slides underwent FISH analysis for PIK3CA amplification with a ratio of ≥2.2 considered as amplified. Primary endpoint: iDFS. iDFS events were tested by 2-sided log-rank tests, and HR (95% CI) were estimated using Cox proportional-hazards models. Data cut-off: March 2017. Results: Baseline demographics and disease characteristics between treatment arms of the correlative cohort (n=1201) were balanced. Overall, 21.2% (n=210) of primary tumors harbored one of the specified PIK3CA mutations, and 8.7% (n=61) were PIK3CA FISH-amplified. Patients with PIK3CA-altered tumors (i.e. PIK3CA mutations or FISH-amplified) had fewer iDFS events with neratinib compared with placebo (HR 0.41; 95% CI 0.17-0.90, p=0.028). The interaction test was not significant (p=0.1842). Results of the various correlative analyses within treatment arms are shown in the table. NeratinibPlacebo iDFS iDFS 2-sidedPopulationnevents, nnevents, nHR (95% CI)P valueaITT142011614201630.73 (0.57–0.92)b0.008bCorrelative cohort59345608700.67 (0.45–0.96)0.0317PIK3CA-mutation positive1047106170.43 (0.17–1.01)0.056PIK3CA-mutation negative38527396420.66 (0.40-1.06)0.089PIK3CA-amplified3312840.20 (0.01-1.33)0.106PIK3CA-non-amplified31629325360.85 (0.52-1.39)0.521PIK3CA-altered1308132200.41 (0.17-0.90)0.028a. Log-rank test; b. Stratified analysis Conclusions: One year of neratinib treatment after trastuzumab-based adjuvant therapy significantly improves iDFS after 5 years in patients with early-stage HER2+ breast cancer. From this modest-sized exploratory cohort, it appears that PIK3CA may be a biomarker for differential sensitivity to neratinib after 1 year of trastuzumab in the adjuvant setting.These exploratory results should be validated in a larger subset. Citation Format: Chia SKL, Martin M, Holmes FA, Ejlertsen B, Delaloge S, Moy B, Iwata H, von Minckwitz G, Mansi J, Barrios CH, Gnant M, Tomašević Z, Denduluri N, Šeparović R, Kim S-B, Hugger Jakobsen E, Harvey V, Robert N, Smith II J, Harker G, Lalani AS, Zhang B, Eli LD, Buyse M, Chan A. PIK3CA alterations and benefit with neratinib after trastuzumab-based adjuvant therapy in early-stage HER2+ breast cancer: Correlative analyses of the phase III ExteNET trial [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD3-12.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".