A four gene signature predicts benefit from anthracyclines: evidence from the BR9601 and MA.5 clinical trials
Bibliographic record
Abstract
// Melanie Spears 1 , Fouad Yousif 2 , Nicola Lyttle 1 , Paul C. Boutros 2,3,4 , Alison F. Munro 5 , Chris Twelves 6 , Kathleen I. Pritchard 7,8 , Mark N. Levine 9 , Lois Shepherd 10 and John MS. Bartlett 1,5 1 Transformative Pathology, Ontario Institute for Cancer Research, MaRS Centre, Toronto, ON, Canada 2 Informatics and Bio-computing, Ontario Institute for Cancer Research, MaRS Centre, Toronto, ON, Canada 3 Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada 4 Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada 5 Edinburgh Cancer Research UK Centre, MRC IGMM, University of Edinburgh, Crewe Road South, Edinburgh, UK 6 Leeds Institute of Cancer and Pathology and Cancer Research UK Centre, St James’ University Hospital, Leeds, UK 7 Sunnybrook Odette Cancer Centre, Toronto, ON, Canada 8 University of Toronto, Toronto, ON, Canada 9 McMaster University and Hamilton Health Sciences, Hamilton, ON, Canada 10 NCIC Clinical Trials Group (NCIC CTG] and Queen’s University, Kingston, ON, Canada Correspondence to: Melanie Spears, email: // Keywords : breast cancer, anthracycline, chromosome instability, predictive biomarker Received : July 20, 2015 Accepted : August 10, 2015 Published : September 10, 2015 Abstract Chromosome instability (CIN) in solid tumours results in multiple numerical and structural chromosomal aberrations and is associated with poor prognosis in multiple tumour types. Recent evidence demonstrated CEP17 duplication, a CIN marker, is a predictive marker of anthracycline benefit. An analysis of the BR9601 and MA.5 clinical trials was performed to test the role of existing CIN gene expression signatures as predictive markers of anthracycline sensitivity in breast cancer. Univariate analysis demonstrated, high CIN25 expression score was associated with improved distant relapse free survival (DRFS) (HR: 0.74, 95% CI 0.54-0.99, p = 0.046). High tumour CIN70 and CIN25 scores were associated with aggressive clinicopathological phenotype and increased sensitivity to anthracycline therapy compared to low CIN scores. However, in a prospectively planned multivariate analysis only pathological grade, nodal status and tumour size were significant predictors of outcome for CIN25/CIN70. A limited gene signature was generated, patients with low tumour CIN4 scores benefited from anthracycline treatment significantly more than those with high CIN4 scores (HR 0.37, 95% CI 0.20-0.56, p = 0.001). In multivariate analyses the treatment by marker interaction for CIN4/anthracyclines demonstrated hazard ratio of 0.35 (95% CI 0.15-0.80, p = 0.012) for DRFS. This data shows CIN4 is independent predictor of anthracycline benefit for DRFS in breast cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| 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) | 0.000 | 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 teacher head, 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".