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 journalArticle


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 languageEnglish (US)
Pages (from-to)1584-1588
Number of pages5
JournalCancer Research
Issue number5
StatePublished - Mar 1 2004


ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

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.