Discovery and validation of breast cancer subtypes
Autor: | Stefanie S. Jeffrey, Dong Young Noh, Robert Tibshirani, Ida R. K. Bukholm, Anita Langerød, Amy V. Kapp, Anne Lise Børresen-Dale, Patrick O. Brown, Wonshik Han, Monica Nicolau |
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Jazyk: | angličtina |
Rok vydání: | 2006 |
Předmět: |
Microarray
lcsh:QH426-470 lcsh:Biotechnology UniGene Breast Neoplasms Genomics Computational biology Biology Bioinformatics Proteomics Basal (phylogenetics) 03 medical and health sciences 0302 clinical medicine Breast cancer Risk Factors lcsh:TP248.13-248.65 Genetics medicine Humans skin and connective tissue diseases Survival analysis Oligonucleotide Array Sequence Analysis Proportional Hazards Models 030304 developmental biology 0303 health sciences Gene Expression Profiling Correction medicine.disease Survival Analysis 3. Good health body regions Gene expression profiling lcsh:Genetics 030220 oncology & carcinogenesis Multivariate Analysis Genome Biology Table (database) Female DNA microarray Algorithms Research Article Biotechnology |
Zdroj: | BMC Genomics, Vol 7, Iss 1, p 231 (2006) BMC Genomics |
ISSN: | 1471-2164 |
Popis: | Background Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+. Results Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. Conclusion As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples. |
Databáze: | OpenAIRE |
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