Identification of therapeutic targets to revert tamoxifen resistance by quantitative proteomic analysis of signaling networks

Tamoxifen resistance is the biggest problem in endocrine treatment against hormone receptor positive breast cancer patients. HER2 is a membrane receptor tyrosine kinase that is known to correlate with poor disease outcome and unresponsiveness to endocrine treatment. Although much work has been done over the past decades to elucidate pathways involved in HER2 receptor signaling, the map of network-wide signaling events that contributes to the resistance to Tamoxifen treatment has not been characterized, making it difficult to pin-point the downstream drug target to revert the Tamoxifen resistance. To gain a molecular understanding of the mechanisms by which cells gain drug resistance, we have employed a proteomic analysis by mass spectrometry to quantitatively analyze cellular tyrosine phosphorylation signaling events in breast cancer model systems and human tumor samples. As a result of research, we have identified the major differences in downstream signaling pathways between Tamoxifen sensitive and Tamoxifen resistant breast cancer cell line models. These findings were further analyzed in Tamoxifen sensitive, and Tamoxifen treated/recurred patient samples to study clinical relevance. Specifically, we determined that P13K/Akt, MEK/ERK, and Src/FAK/Abl pathways are major components of the Tamoxifen resistance. We further showed that they signaling components are possible drug targets to revert Tamoxifen resistance. This study revealed cell-context specific network-wide changes in signaling events in response to use of therapeutic drugs. This is, to our first knowledge, the first phosphoproteomic analysis of the signaling network in breast cancer to address Tamoxifen resistance. We believe that same approach is applicable to other drug resistance problems in various disease settings.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Biological Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2009

Author dc:creator

• Saito-Benz, Hideshiro

Advisor dc:contributor.advisor

• Forest M. White.

• Biological Engineering.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/61231

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/61231