Research article

Risk estimation of distant metastasis in node-negative, estrogen receptor-positive breast cancer patients using an RT-PCR based prognostic expression signature

Andrew Tutt^1,2 , Alice Wang³ , Charles Rowland³ , Cheryl Gillett⁴ , Kit Lau³ , Karen Chew⁵ , Hongyue Dai⁶ , Shirley Kwok³ , Kenneth Ryder² , Henry Shu³ , Robert Springall⁴ , Paul Cane⁷ , Blair McCallie³ , Lauren Kam-Morgan⁸ , Steve Anderson⁸ , Horst Buerger⁹ , Joe Gray¹⁰ , James Bennington¹¹ , Laura Esserman¹² , Trevor Hastie¹³ , Samuel Broder³ , John Sninsky³ , Burkhard Brandt⁹ and Fred Waldman^5,11

¹Breakthrough Breast Cancer Research Unit, King's College, London, UK

²Guy's Hospital, London, UK

³Celera, LLC, Alameda, CA, USA

⁴Guy's and St Thomas' Hospital Breast Research Tissue & Data Bank, London, UK

⁵Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA

⁶Rosetta Inpharmatics, A wholly owned subsidiary of Merck & Co. Inc., Seattle, WA, USA

⁷Cellular Pathology Department, St Thomas' Hospital, London, UK

⁸Laboratory Corporation of America, Triangle Park, NC, USA

⁹Institute of Tumor Biology, University Medical Center, University of Hamburg, Hamburg, Germany

¹⁰Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

¹¹Department of Pathology, California Pacific Medical Center, San Francisco, CA, USA

¹²Carol Franc Buck Breast Cancer Center, University of California San Francisco, San Francisco, CA, USA

¹³Departments of Statistics, and Health Research & Policy, Stanford University, Stanford, CA, USA

author email corresponding author email

BMC Cancer 2008, 8:339doi:10.1186/1471-2407-8-339

Published:	21 November 2008

Abstract

Background

Given the large number of genes purported to be prognostic for breast cancer, it would be optimal if the genes identified are not confounded by the continuously changing systemic therapies. The aim of this study was to discover and validate a breast cancer prognostic expression signature for distant metastasis in untreated, early stage, lymph node-negative (N-) estrogen receptor-positive (ER+) patients with extensive follow-up times.

Methods

197 genes previously associated with metastasis and ER status were profiled from 142 untreated breast cancer subjects. A "metastasis score" (MS) representing fourteen differentially expressed genes was developed and evaluated for its association with distant-metastasis-free survival (DMFS). Categorical risk classification was established from the continuous MS and further evaluated on an independent set of 279 untreated subjects. A third set of 45 subjects was tested to determine the prognostic performance of the MS in tamoxifen-treated women.

Results

A 14-gene signature was found to be significantly associated (p < 0.05) with distant metastasis in a training set and subsequently in an independent validation set. In the validation set, the hazard ratios (HR) of the high risk compared to low risk groups were 4.02 (95% CI 1.91–8.44) for the endpoint of DMFS and 1.97 (95% CI 1.28 to 3.04) for overall survival after adjustment for age, tumor size and grade. The low and high MS risk groups had 10-year estimates (95% CI) of 96% (90–99%) and 72% (64–78%) respectively, for DMFS and 91% (84–95%) and 68% (61–75%), respectively for overall survival. Performance characteristics of the signature in the two sets were similar. Ki-67 labeling index (LI) was predictive for recurrent disease in the training set, but lost significance after adjustment for the expression signature. In a study of tamoxifen-treated patients, the HR for DMFS in high compared to low risk groups was 3.61 (95% CI 0.86–15.14).

Conclusion

The 14-gene signature is significantly associated with risk of distant metastasis. The signature has a predominance of proliferation genes which have prognostic significance above that of Ki-67 LI and may aid in prioritizing future mechanistic studies and therapeutic interventions.