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01.10.2010 | Research article | Ausgabe 5/2010 Open Access

Breast Cancer Research 5/2010

A multigene predictor of metastatic outcome in early stage hormone receptor-negative and triple-negative breast cancer

Breast Cancer Research > Ausgabe 5/2010
Christina Yau, Laura Esserman, Dan H Moore, Fred Waldman, John Sninsky, Christopher C Benz
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​bcr2753) contains supplementary material, which is available to authorized users.

Competing interests

CY, LE, FW, and CCB are named as inventors of the above-mentioned HRneg/Tneg prognostic gene signature in a joint institutional patent application filed by the University of California, San Francisco and the Buck Institute for Age Research. No financial or other support of any kind has resulted from this patent application. The other authors declare that they have no competing interests.

Authors' contributions

CY identified all of the public datasets, carried out all of the biostatistical and informatic analyses, and helped draft the manuscript. LE co-initiated the project, helped guide the study design, and participated in formulating the study conclusions. DHM supervised and participated in the biostatistical analyses. FW and JS participated in the study design, guided the informatic analyses, and helped formulate the study conclusions. CCB conceived and coordinated the project, supervised all data curation and analysis, formulated the study conclusions, and drafted the final manuscript. All authors read and approved the final manuscript.



Various multigene predictors of breast cancer clinical outcome have been commercialized, but proved to be prognostic only for hormone receptor (HR) subsets overexpressing estrogen or progesterone receptors. Hormone receptor negative (HRneg) breast cancers, particularly those lacking HER2/ErbB2 overexpression and known as triple-negative (Tneg) cases, are heterogeneous and generally aggressive breast cancer subsets in need of prognostic subclassification, since most early stage HRneg and Tneg breast cancer patients are cured with conservative treatment yet invariably receive aggressive adjuvant chemotherapy.


An unbiased search for genes predictive of distant metastatic relapse was undertaken using a training cohort of 199 node-negative, adjuvant treatment naïve HRneg (including 154 Tneg) breast cancer cases curated from three public microarray datasets. Prognostic gene candidates were subsequently validated using a different cohort of 75 node-negative, adjuvant naïve HRneg cases curated from three additional datasets. The HRneg/Tneg gene signature was prognostically compared with eight other previously reported gene signatures, and evaluated for cancer network associations by two commercial pathway analysis programs.


A novel set of 14 prognostic gene candidates was identified as outcome predictors: CXCL13, CLIC5, RGS4, RPS28, RFX7, EXOC7, HAPLN1, ZNF3, SSX3, HRBL, PRRG3, ABO, PRTN3, MATN1. A composite HRneg/Tneg gene signature index proved more accurate than any individual candidate gene or other reported multigene predictors in identifying cases likely to remain free of metastatic relapse. Significant positive correlations between the HRneg/Tneg index and three independent immune-related signatures (STAT1, IFN, and IR) were observed, as were consistent negative associations between the three immune-related signatures and five other proliferation module-containing signatures (MS-14, ONCO-RS, GGI, CSR/wound and NKI-70). Network analysis identified 8 genes within the HRneg/Tneg signature as being functionally linked to immune/inflammatory chemokine regulation.


A multigene HRneg/Tneg signature linked to immune/inflammatory cytokine regulation was identified from pooled expression microarray data and shown to be superior to other reported gene signatures in predicting the metastatic outcome of early stage and conservatively managed HRneg and Tneg breast cancer. Further validation of this prognostic signature may lead to new therapeutic insights and spare many newly diagnosed breast cancer patients the need for aggressive adjuvant chemotherapy.
Additional file 1: Supplemental table S1. Summary of patient characteristics (grade, tumor size and number of samples scored for lymphocytic infiltration) by data source. "na" denotes where this annotation is not available to the public; and "nd" represents cohorts where Tneg status by ERBB2 transcript levels were not determined. (XLS 24 KB)
Additional file 2: Supplemental table S2. Established multigene signatures assessed in comparison to HRneg/Tneg signatures. Signatures annotated for Affymetrix probe set information (STAT1 and GGI) are mapped to training data using the Affymetrix probe set ID; otherwise, signatures are mapped using gene symbols. Only signature components that can be mapped (as denoted by a "Y" in the "Mapped to Training Set" or "Mapped to Validation Set" columns) are included in the computation of signature indices in accordance to their reported correlation with prognosis (as denoted in the "Contribution to Index" column). (XLS 148 KB)
Additional file 3: Supplemental figure S1. Prognostic performance of individual HRneg genes in training cohort. Kaplan-Meier plots of distant metastatic events dichotomized at the median by high (red) or low (green) expression of individual HRneg genes in training cohort of 199 HRneg cases. Significant differences in survival between groups were determined by log rank analysis. (PDF 836 KB)
Additional file 4: Supplemental figure S2. Prognostic performance of individual Tneg genes in training cohort. Kaplan-Meier plots of distant metastatic events dichotomized at the median by high (red) or low (green) expression of individual Tneg genes in training cohort subset of 154 Tneg cases. Significant differences in survival between groups were determined by log rank analysis. (PDF 772 KB)
Additional file 5: Supplemental figure S3. Prognostic performance of the 11-gene HRneg and 7-gene Tneg indices considered independently. Kaplan-Meier plots of distant-metastatic events dichotomized at the upper 3rd quartile by high (red) or low (green) expression indices of (A) the 11 prognostic gene candidates identified from the 199 HRneg training cases; and (B) the 7 prognostic gene candidates identified from the subset of 154 Tneg training cases. (PDF 330 KB)
Authors’ original file for figure 1
Authors’ original file for figure 2
Authors’ original file for figure 3
Authors’ original file for figure 4
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