A relative ordering-based predictor for tamoxifen-treated estrogen receptor-positive breast cancer patients: Multi-laboratory cohort validation

Xianxiao Zhou, Bailiang Li, Yuannv Zhang, Yunyan Gu, Beibei Chen, Tongwei Shi, Lu Ao, Pengfei Li, Shan Li, Chunyang Liu, Zheng Guo

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

Current predictors for estrogen receptor-positive (ER-positive) breast cancer patients receiving tamoxifen are often invalid in inter-laboratory validation. We aim to develop a robust predictor based on the relative ordering of expression measurement (ROE) in gene pairs. Using a large integrated dataset of 420 normal controls and 1,129 ER-positive breast tumor samples, we identified the gene pairs with stable ROEs in normal control and significantly reversed ROEs in ER-positive tumor. Using these gene pairs, we characterized each sample of a cohort of 292 ER-positive patients who received tamoxifen monotherapy for 5 years and then identified relapse risk-associated gene pairs. We extracted a gene pair subset that resulted in the largest positive and negative predictive values for predicting 10-year relapse-free survival (RFS) using a genetic algorithm. A predictor was developed based on the gene pair subset and was validated in 2 large multi-laboratory cohorts (N = 250 and 248, respectively) of ER-positive patients who received 5-year tamoxifen alone. In the first validation cohort, the patients predicted to be tamoxifen sensitive had a 10-year RFS of 91 % (95 % confidence interval [CI] 85-97 %) with an absolute risk reduction of 34 % (95 % CI 17-51 %). The patients predicted to be tamoxifen insensitive had a significantly higher relapse risk than the patients predicted to be tamoxifen sensitive (hazard ratio = 4.99, 95 % CI 2.45-10.17, P = 9.13 × 10-7). Similar performance was achieved for the second validation cohort. The predictor performed well in both node-negative and node-positive subsets and added significant predictive power to the clinical parameters. In contrast, 2 previously proposed predictors did not achieve significantly better performances than the baselines of the validation cohorts. In summary, the proposed predictor can accurately and robustly predict tamoxifen sensitivity of ER-positive breast cancer patients and identified patients with a high probability of 10-year RFS following tamoxifen monotherapy.

Original languageEnglish (US)
Pages (from-to)505-514
Number of pages10
JournalBreast Cancer Research and Treatment
Volume142
Issue number3
DOIs
StatePublished - Dec 1 2013
Externally publishedYes

Keywords

  • Breast cancer
  • Estrogen receptor-positive
  • Gene expression
  • Predictor
  • Relative ordering
  • Tamoxifen

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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