A three-gene model to robustly identify breast cancer molecular subtypes.

Abstract

Our results suggest that adequate classification of the major and clinically relevant molecular subtypes of breast cancer can be robustly achieved with quantitative measurements of three key genes.

Full Text

• DOI - Journal of the National Cancer Institute (DOI)
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Subjects

• Breast Neoplasms
• Cluster Analysis
• Confounding Factors (Epidemiology)
• Databases, Genetic
• Female
• Gene Expression Profiling
• Gene Expression Regulation, Neoplastic
• Humans
• Kaplan-Meier Estimate
• Microarray Analysis
• Polymorphism, Single-Stranded Conformational
• Predictive Value of Tests
• Prognosis
• Protein-Serine-Threonine Kinases
• Receptor, erbB-2
• Receptors, Estrogen
• Research Design
• Retrospective Studies

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Authors

• Benjamin Haibe-Kains
• Christine Desmedt
• Sherene Loi
• Aedin C Culhane
• Gianluca Bontempi
• John Quackenbush
• Christos Sotiriou

Publication date

2012-02-22

Journal

Journal topics

• Neoplasms

Language

Eng.

Copyright

Journal of the National Cancer Institute

Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA. bhaibeka [at] jimmy.harvard.edu

Release reference

J Natl Cancer Inst. 2012 Feb;104(4):311-25

Related books

• Books of Breast Neoplasms
• Books of Cluster Analysis
• Books of Confounding Factors (Epidemiology)
• Books of Databases, Genetic
• Books of Gene Expression Profiling
• Books of Gene Expression Regulation, Neoplastic
• Books of Kaplan-Meier Estimate
• Books of Microarray Analysis
• Books of Neoplasms
• Books of Polymorphism, Single-Stranded Conformational
• Books of Predictive Value of Tests
• Books of Prognosis
• Books of Protein-Serine-Threonine Kinases
• Books of Receptor, erbB-2
• Books of Receptors, Estrogen
• Books of Research Design
• Books of Retrospective Studies