A four gene signature predicts benefit from anthracyclines: Evidence from the BR9601 and MA.5 clinical trials

Melanie Spears*, Fouad Yousif, Nicola Lyttle, Paul C. Boutros, Alison F. Munro, Chris Twelves, Kathleen I. Pritchard, Mark N. Levine, Lois Shepherd, John M S Bartlett

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)31693-31701
Number of pages9
JournalOncotarget
Volume6
Issue number31
DOIs
Publication statusPublished - 10 Sep 2015

Keywords

  • Anthracycline
  • Breast cancer
  • Chromosome instability
  • Predictive biomarker

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