Abstract P2-10-01: Validation that a histone gene signature predicts anthracycline response in early breast cancer
Bibliographic record
Abstract
Abstract Background: The use of anthracycline-based chemotherapies has improved overall and disease free survival in breast cancer. However, anthracyclines can have significant toxicities including cardiotoxicity and leukemia. It is, therefore, imperative to identify those patients who will benefit from adjuvant anthracycline treatment and patients who could be spared unnecessary toxicities and be considered for alternative adjuvant therapy. Previous work performed by our laboratory identified a histone gene expression signature as a predictive marker of anthracycline benefit in the BR9601 clinical trial. In this study we validate the 18 histone gene signature in the MA.5 clinical trial and examine the role of the signature in individual intrinsic subtypes of breast cancer. Methods We analysed the CCTG MA.5 clinical trial in a prospectively planned retrospective biomarker approach to validate this signature and tested the role of intrinsic subtyping as predictive markers of anthracycline benefit. RNA was extracted from patients in the MA.5 adjuvant trial evaluating the addition of epirubicin (E) to CMF and analysed using NanoString technology. Log-rank analyses validated the predictive values of the signature on distant relapse-free survival (DRFS). Cox-regression models tested independent predictive value on DRFS in the presence of treatment, age, tumour size, nodal status, HER2, ER status and grade, and treatment by marker interactions. Results Analysis of the MA.5 clinical cohort revealed that patients whose tumour had low histone gene signature expression experienced increased DRFS (HR: 0.54, 95% CI 0.38-0.76, p=0.001) when treated with CEF compared with patients treated with CMF alone. Conversely, there was no apparent benefit of CEF vs CMF in patients with high histone gene expression signature (HR: 1.01, 95%CI 0.66-1.55, p=0.963). After multivariate analysis and adjustment for HER2, nodal status, age, grade and ER, the treatment by marker interaction for the gene signature was 0.54 (95%CI 0.31-0.94, p=0.030) for DRFS. The predictive impact of the histone signature was independent of intrinsic subtype. Conclusion The histone gene expression signature is an independent predictor of anthracycline benefit and could be a potential candidate diagnostic assay for patients with early breast cancer. Citation Format: Spears M, Kornaga E, Lyttle N, Liao L, Bayani J, Quintayo M-A, Yao CQ, D'Costa A, Boutros PC, Twelves CJ, Pritchard KI, Levine MN, Nielsen TO, Shepherd L, Bartlett JMS. Validation that a histone gene signature predicts anthracycline response in early breast cancer [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 P2-10-01.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".