Duplication of Chromosome 17 CEP Predicts for Anthracycline Benefit: A Meta-Analysis of 4 Trials.
Bibliographic record
Abstract
Abstract ABSTRACT WITHDRAWN: This abstract was withdrawn by the authors prior to the start of the Symposium. Background: Current evidence for HER2/TOP2A as predictive biomarkers of anthracycline response is conflicting. An interim meta-analysis (Di Leo et al Cancer Res;69:99S SABCS2009) suggested a weak, statistically significant, association between TOP2A and anthracycline benefit. We previously showed duplication of chromosome 17 alpha satellite (CEP17) predicted sensitivity to anthracyclines independently in three trials (BR9601, NEAT and MA.5, Bartlett et al Cancer Res 69:74S/364S). We performed a retrospective meta-analysis, incorporating data from 4 trials (including the Belgium study), to test the hypothesis that CEP17 is a predictive biomarker for anthracycline benefit in order to provide a unifying hypothesis in trials for which previous biomarker data is conflicting.Methods: FISH was performed in 2 labs (Bartlett lab for BR9601/NEAT & Belgian studies & O'Malley lab for MA5). ER/PgR (IHC) etc were collected from trial Case Report Forms. BR9601/NEAT and Belgian study tumors were scored counting all cells with a minimum of one CEP17 signal/cell: in MA.5 a minimum of 2 CEP17 signals were required for cells to be scored. These methodological differences did not affect HER2/CEP17 ratios but necessitated different definitions for CEP17 duplication defined as >1.86 observed copies/cell for BR9601, NEAT and JB (Watters BCRT 2003 77:109-14) and >2.25 for MA.5 (Goetz 2004).Results: FISH was successful in 85% (2531/2975) of cases. CEP17 duplication was detected in 27.5% of tumors (BR9601=37.6%, NEAT=20.0%, MA5=40.2% & JB=28.5%) and was associated with poorer RFS & OS (HR 0.80 95%CI 0.7-0.92 p=0.011 & HR 0.79, 95%CI 0.68-9.92, p=0.018, respectively).A significant treatment*marker interaction was observed in a meta-analysis of all data (2531 cases) as univariate(p<0.005) & multivariate adjusted for treatment, grade, size, ER, nodes CEP17, CEP17*treatment & HER2 and for recurrence free (HR 1.67 95%CI 1.25-2.22, p=0.0006) & overall (1.63 95%CI 1.18-2.25, p=0.003) survival. In the two largest studies, NEAT (n=1462) and MA5 (n=622), this treatment*marker interaction (CEP17) was significant for RFS (p<0.05) in all other analyses non-significant trends for RFS & OS were seen. (Trial specific HRs with 95%CIs RFS: 1.37 (0.56-3.15), 1.77 (1.07-2.90), 1.62 (1.02-2.58) & 1.69 (0.43-6.68), OS: 1.35 (0.54-3.38), 1.64 (0.96-2.80), 1.67 (0.99-2.84) & 2.05 (0.43-9.69); BR9601, NEAT, MA5 & Belgian respectively) analyses.Conclusions: Combined meta-analysis of 4 adjuvant trials demonstrated a highly significant treatment by marker effect for CEP17 duplication as a predictor of benefit from anthracyclines for both RFS in both univariate and multivariate regression analyses. HER2 (all 4 trials) and TOP2A (NEAT/BR9601) did not show any significant interactions. CEP17 duplication may reflect either chromosomal instability or polyploidy and further analysis is warranted to explore the underlying mechanisms for this effect. CEP17 is readily assessed in ISH analysis of HER2 status and may represent a clinically useful biomarker for selection of patients likely to benefit from anthracycline containing chemotherapies.
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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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.033 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".