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Breast Cancer Research

Open Access

Reproducibility of molecular portraits in early stage breast cancer

  • DSA Nuyten1, 2,
  • HY Chang3,
  • PO Brown4 and
  • MJ Van de Vijver1
Breast Cancer Research20057(Suppl 2):P4.26

https://doi.org/10.1186/bcr1156

Published: 17 June 2005

Keywords

LuminalBreast CarcinomaEarly Stage Breast CancerCorrelation ThresholdBasal Subgroup

Background

Gene expression profiling has been used to identify specific subgroups of breast carcinomas. Perou and Sørlie [13] described five subtypes (basal, luminal A and luminal B, ErbB2 and normal-breast like). Here we have categorized the 295 tumors that were previously assessed with the 70-gene prognosis profile according to these five subtypes.

Methods

In 295 stage I and stage II breast carcinomas treated at the Netherlands Cancer Institute, we have obtained gene expression data of 25,000 genes using micro-array analysis. We have used the previously described Intrinsic Gene Set [3] to define basal type, luminal A and luminal B, ErbB2 and normal epithelium-like type tumors (431 of 487 unique genes matched). We have used two different methods to classify the tumors: two-dimensional hierarchical cluster analysis and nearest centroid classification. We have compared the reproducibility by both methods and we have analyzed clinical outcome (distant metastasis-free probability and overall survival) of these 295 patients based for the different classes. The median follow-up is 6.7 years for all patients and 7.8 years for patients alive.

Results

Based on hierarchical clustering, the basal subgroup can be easily recognized; the ErbB2 group is reasonably well defined and the luminal A and luminal B groups form a large cluster, with subclusters that have more luminal A or luminal B patients. For the nearest centroid classification we used a correlation threshold of 0.1 to classify patients. One hundred and nine (37%) patients did not have a correlation of more than 0.1 to one of the five centroids ('unclassifiable'). Forty-five (15.25%) patients were assigned to the basal group, 39 (13.2%) ErbB2, 47 (16%) luminal A, 45 (15.25%) luminal B and 10 (3.3%) normal-breast like. The relatively large group of patients that could not be assigned to one of the classes was further analyzed. These tumors appear to represent a relatively homogeneous group that differs from those that can be classified. The ER receptor is positive in 106/109 (120/188 classifiable patients: two-sided Fisher's exact P < 1 × 10-9) and 80% of the tumors are histological grade I or grade II (47% for classifiable patients; P < 1 × 10-6). Not surprisingly, the 10-year overall survival is higher in these patients as well (80% vs 64%; log-rank: 0.0005). Using predicting analysis of micro-arrays [4], the unclassifiable 'class' could be predicted using 200 genes with an accuracy of 90% (cross-validation results).

The 10-year metastasis-free probability and overall survival for the subgroups are: basal, 54% and 46%; erbB2, 55% and 56%; luminal A, 70% and 83%; luminal B, 56% and 63%; and normal-breast like, 67% and 90% (overall P value: metastasis-free probability, 0.15 and overall survival, 0.001).

Conclusion

In this series of consecutively treated breast cancer patients, the molecular portraits identify patients that differ with respect to prognosis. The relatively high proportion of unclassifiable patients can possibly be explained by both the cross-platform matching, the difference in clinical stage (locally advanced in the original series versus early stage in our patients), and the fact that the original classification was derived from a relatively small series of tumors. The subgroup that could not be classified using the intrinsic genes contains mainly ER-positive and grade I or grade II tumors.

Authors’ Affiliations

(1)
Department of Diagnostic Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
(2)
Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
(3)
Program in Epithelial Biology, Stanford University, Stanford, USA
(4)
Department of Biochemistry and Howard Hughes Medical Institute, Stanford University, Stanford, USA

References

  1. Perou CM, Sørlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, et al: Molecular portraits of human breast tumours. Nature. 2000, 406: 747-752. 10.1038/35021093.View ArticlePubMedGoogle Scholar
  2. Sørlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, et al: Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA. 2001, 98: 10869-10874. 10.1073/pnas.191367098.View ArticlePubMedPubMed CentralGoogle Scholar
  3. Sørlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A, Deng S, Johnsen H, Pesich R, Geisler S, et al: Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA. 2003, 100: 8418-8423. 10.1073/pnas.0932692100.View ArticlePubMedPubMed CentralGoogle Scholar
  4. Tibshirani R, Hastie T, Narasimhan B, Chu G: Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc Natl Acad Sci USA. 2002, 99: 6567-6572. 10.1073/pnas.082099299.View ArticlePubMedPubMed CentralGoogle Scholar

Copyright

© BioMed Central 2005

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