Gene expression profiling: changing face of breast cancer classification and management

Abstract

Epithelial breast malignancies are a group of several disease entities that vary in their biology and response to specific therapies. Historically, classification of different molecular types of breast cancer was done through the use of conventional methods such as tumor morphology, grade, and immunophenotyping for estrogen, progesterone, and HER-2/neu receptor expression. Such techniques, although helpful, are not sufficient to accurately predict biologic behavior of breast cancers. Over the last several years, much progress has been made in more precise identification of molecular breast cancer subtypes. Such advances hold a great promise in improving estimation of prognosis and assigning most appropriate therapies. Thanks to use of cDNA microarrays expression technology and quantitative reverse transcriptase polymerase chain reaction (RT-PCR), tumors with specific gene expression patterns can now be identified. This process is presently reshaping perceptions of how breast cancer should be classified and treated. Categorization of breast cancers by gene expression is only beginning to make its way into the daily clinical practice and likely will complement, but not replace, the conventional methods of classification.

Figure 1

Schematic representation of classification of breast cancer. (A) Conventional classification. (B) Classification based on gene expression profiles.