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Current Pharmaceutical Biotechnology


ISSN (Print): 1389-2010
ISSN (Online): 1873-4316

Imaging Cellular Receptors in Breast Cancers: An Overview

Author(s): Thillai V. Sekar, Aradhana Dhanabalan and Ramasamy Paulmurugan

Volume 12, Issue 4, 2011

Page: [508 - 527] Pages: 20

DOI: 10.2174/138920111795164039

Price: $65


Breast cancer, a leading cause of cancer death in women, is strongly correlated with the up- and downregulation of hormone and growth factor receptors. Therefore, improving our understanding of such receptor status in different stages of breast cancer will help in the development of novel diagnostic and therapeutic solutions. In particular, molecular imaging technology in association with advanced molecular and cell biology techniques could reveal in detail dynamic molecular events in cells, allowing the study of crucial molecular pathological changes occurring in cancer and other diseases. Molecular imaging techniques such as PET, SPECT, MRI, and the combinatorial techniques have made tremendous strides in elucidating the role of cellular receptors, helping to monitor the course of breast cancer development and the therapeutic efficacy of novel drugs. Optical imaging of cellular receptors is emerging as a powerful tool given the advancement of fluorescent and bioluminescent proteins. Estrogen receptor, progesterone receptor, and HER2/neu have been adopted clinically to detect different types of breast cancer and to test novel treatment strategies; however, other cellular receptors may also be involved in breast cancer subtyping and could emerge as treatment prospects. This review will focus on the recent developments of imaging various cellular receptors pertaining to the growth and development of breast cancer.

Keywords: Breast cancer, estrogen receptor, molecular imaging, PET, reporter gene, optical imaging, up- and downregulation of hormone, growth factor receptors, molecular imaging technology, cell biology techniques, cancer, cellular receptors, therapeutic efficacy, gene expression analysis, DNA microarray based subtyping

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