Repeated observation of breast tumor subtypes in independent gene expression data sets

2003 Proceedings of the National Academy of Sciences 5,372 citations

Abstract

Characteristic patterns of gene expression measured by DNA microarrays have been used to classify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors were analyzed by hierarchical clustering based on patterns of expression of 534 “intrinsic” genes and shown to subdivide into one basal-like, one ERBB2 -overexpressing, two luminal-like, and one normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. Similar cluster analyses of two published, independent data sets representing different patient cohorts from different laboratories, uncovered some of the same breast cancer subtypes. In the one data set that included information on time to development of distant metastasis, subtypes were associated with significant differences in this clinical feature. By including a group of tumors from BRCA1 carriers in the analysis, we found that this genotype predisposes to the basal tumor subtype. Our results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities.

Keywords

Breast cancerDNA microarrayGene expressionGeneGene expression profilingBiologyGenotypeBasal (medicine)Breast tumorMetastasisCancerPathologyOncologyMedicineInternal medicineGenetics

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Publication Info

Year
2003
Type
article
Volume
100
Issue
14
Pages
8418-8423
Citations
5372
Access
Closed

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Thérese Sørlie, Robert Tibshirani, Joel S. Parker et al. (2003). Repeated observation of breast tumor subtypes in independent gene expression data sets. Proceedings of the National Academy of Sciences , 100 (14) , 8418-8423. https://doi.org/10.1073/pnas.0932692100

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DOI
10.1073/pnas.0932692100