An Unsupervised Approach to Identify Molecular Phenotypic Components Influencing Breast Cancer Features

Florin M. Selaru; Jing Yin; Andreea Olaru; Yuriko Mori; Yan Xu; Steven H. Epstein; Fumiaki Sato; Elena Deacu; Suna Wang; Anca Sterian; Amy Fulton; John M. Abraham; David Shibata; Claudia Baquet; Sanford A. Stass; Stephen J. Meltzer

doi:10.1158/0008-5472.CAN-03-3208

An Unsupervised Approach to Identify Molecular Phenotypic Components Influencing Breast Cancer Features

Florin M. Selaru, Jing Yin, Andreea Olaru, Yuriko Mori, Yan Xu, Steven H. Epstein, Fumiaki Sato, Elena Deacu, Suna Wang, Anca Sterian, Amy Fulton, John M. Abraham, David Shibata, Claudia Baquet, Sanford A. Stass, Stephen J. Meltzer

Research output: Contribution to journal › Article › peer-review

18 Scopus citations

Abstract

To discover a biological basis for clinical subgroupings within breast cancers, we applied principal components (PCs) analysis to cDNA microarray data from 36 breast cancers. We correlated the resulting PCs with clinical features. The 35 PCs discovered were ranked in order of their impact on gene expression patterns. Interestingly, PC 7 identified a unique subgroup consisting of estrogen receptor (ER); (+) African-American patients. This group exhibited global molecular phenotypes significantly different from both ER (-) African-American women and ER (+) or ER (-) Caucasian women (P < 0.001). Additional significant PCs included PC 4, correlating with lymph node metastasis (P = 0.04), and PC 10, with tumor stage (stage 2 versus stage 3; P = 0.007). These results provide a molecular phenotypic basis for the existence of a biologically unique subgroup comprising ER (+) breast cancers from African-American patients. Moreover, these findings illustrate the potential of PCs analysis to detect molecular phenotypic bases for relevant clinical or biological features of human tumors in general.

Original language	English (US)
Pages (from-to)	1584-1588
Number of pages	5
Journal	Cancer Research
Volume	64
Issue number	5
DOIs	https://doi.org/10.1158/0008-5472.CAN-03-3208
State	Published - Mar 1 2004
Externally published	Yes

ASJC Scopus subject areas

Oncology
Cancer Research

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Selaru, F. M., Yin, J., Olaru, A., Mori, Y., Xu, Y., Epstein, S. H., Sato, F., Deacu, E., Wang, S., Sterian, A., Fulton, A., Abraham, J. M., Shibata, D., Baquet, C., Stass, S. A., & Meltzer, S. J. (2004). An Unsupervised Approach to Identify Molecular Phenotypic Components Influencing Breast Cancer Features. Cancer Research, 64(5), 1584-1588. https://doi.org/10.1158/0008-5472.CAN-03-3208

Selaru, FM, Yin, J, Olaru, A, Mori, Y, Xu, Y, Epstein, SH, Sato, F, Deacu, E, Wang, S, Sterian, A, Fulton, A, Abraham, JM, Shibata, D, Baquet, C, Stass, SA & Meltzer, SJ 2004, 'An Unsupervised Approach to Identify Molecular Phenotypic Components Influencing Breast Cancer Features', Cancer Research, vol. 64, no. 5, pp. 1584-1588. https://doi.org/10.1158/0008-5472.CAN-03-3208

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AU - Abraham, John M.

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An Unsupervised Approach to Identify Molecular Phenotypic Components Influencing Breast Cancer Features

Abstract

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