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Gene expression meta-analysis supports existence of molecular apocrine breast cancer with a role for androgen receptor and implies interactions with ErbB family by Sandeep Sanga; Bradley M Broom; Vittorio Cristini; Mary E Edgerton is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Abstract ## Background Pathway discovery from gene expression data can provide important insight into the relationship between signaling networks and cancer biology. Oncogenic signaling pathways are commonly inferred by comparison with signatures derived from cell lines. We use the Molecular Apocrine subtype of breast cancer to demonstrate our ability to infer pathways directly from patients' gene expression data with pattern analysis algorithms. ## Methods We combine data from two studies that propose the existence of the Molecular Apocrine phenotype. We use quantile normalization and XPN to minimize institutional bias in the data. We use hierarchical clustering, principal components analysis, and comparison of gene signatures derived from Significance Analysis of Microarrays to establish the existence of the Molecular Apocrine subtype and the equivalence of its molecular phenotype across both institutions. Statistical significance was computed using the Fasano & Franceschini test for separation of principal components and the hypergeometric probability formula for significance of overlap in gene signatures. We perform pathway analysis using LeFEminer and Backward Chaining Rule

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Author

Sandeep Sanga; Bradley M Broom; Vittorio Cristini; Mary E Edgerton

Publisher

BioMed Central; Springer (Biomed Central Ltd.); London: BioMed Central, [2008]-; Springer Science and Business Media LLC (ISSN 1755-8794)

Published

2009

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)