A study suggests that the hormone estrogen works in partnership with other proteins to activate or suppress gene activity in breast cancer cells.
Surprisingly, one of the partner proteins is known as c-MYC, a gene activator that has long been associated with cancer development but was not known to interact with estrogen during tumor progression.

The study, by researchers at The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute, answers the puzzling question of how estrogen can turn on some genes and turn off others during cancer progression.

" Our results indicate that the interaction of estrogen with one of seven different partner proteins determines whether the gene is activated or suppressed," says coauthor Ramana V. Davuluri.

The findings could also reveal potential new drug targets and lead to a test to identify breast-cancer patients with tumors that are likely to become resistant to hormonal therapies such as Tamoxifen and aromatase inhibitors.

The research is published in the journal Molecular Cell.

The study is unusual because it used microarray technology and mathematical modeling to predict which cell proteins work with estrogen to contribute to breast cancer development, and then used more traditional experimental biology to verify one of the predictions.

" We conducted this study with almost equal contributions from computational scientists and experimental scientists," says principal investigator Tim Hui-Ming Huang.

" This strategy, in which computational predictions are verified by the bench scientist, will be a trend for future cancer research," Huang says.

Scientists have known for decades that estrogen plays a key role in the development of cancers of the breast, uterus and ovaries. Upon entering cells in these tissues, the molecules of the hormone first link with a molecule known as the estrogen receptor ( ER ), activating the ER.

The activated ER then links with, or binds to, genes and turns some on and some off.

For this study, Huang, Davuluri and their colleagues first needed to identify the genes that ERs will bind with. They did this using microarray, or gene-chip, technology. Gene chips allow scientists to compare thousands of genes at one time to learn which ones are turned on or turned off in cells under particular conditions, such as exposure to estrogen.

Specifically, the researchers used a form of this technology known as the Chromatin Immunoprecipitation chip, or the ChIP-chip. From this, they learned that ER would bind with 92 genes out of some 10,000 genes tested.

Of these 92, about 40 were strongly activated by the hormone and about 30 were strongly suppressed. The researchers focused on these two groups.

Proteins that bind to DNA do so by linking to specific DNA sequences in a particular region of a gene. The researchers then identified these sequences for each gene in the two groups using a pubic DNA database.

Next, they used that sequence information to write a computer program that scanned a different database, one containing information for the 5,000 or so proteins that are known to bind with DNA.

Of these, the program identified five partner proteins that should bind to one of the genes activated by ER, and two partner proteins that would bind to genes suppressed by ER.

In this way, they investigators computationally identified seven partner proteins that help ER activate or suppress gene activity in breast-cancer cells. And one of the activating partner proteins was c-MYC.

But were the computational predictions right or wrong ? The researchers answered that question for the most important prediction, that c-MYC is an ER partner protein.

This work, by Huang and a group of colleagues, used laboratory-grown breast-cancer cells. They learned, for example, that if either the ER binding site or the c-MYC binding site of a particular gene is lost, estrogen will no longer activate the gene.

Next, the researchers will study how the interaction between ER and its partner proteins is changed in cells from Tamoxifen-resistant tumors.

Source: Ohio State University, 2006


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