Abstract
Antiestrogens, such as tamoxifen, are widely used for endocrine treatment of estrogen receptor-positive breast cancer. However, as breast cancer progresses, development of tamoxifen resistance is inevitable. The mechanisms underlying this resistance are not well understood. To identify genes involved in tamoxifen resistance, we have developed a rapid screening method. To alter the tamoxifen-sensitive phenotype of human ZR-75-1 breast cancer cells into a tamoxifen-resistant phenotype, the cells were infected with retroviral cDNA libraries derived from human placenta, human brain, and mouse embryo. Subsequently, the cells were selected for proliferation in the presence of 4-hydroxy-tamoxifen (OH-TAM) and integrated cDNAs were identified by sequence similarity searches. From 155 OH-TAM-resistant cell colonies, a total of 25 candidate genes were isolated. Seven of these genes were identified in multiple cell colonies and thus cause antiestrogen resistance. The epidermal growth factor receptor, platelet-derived growth factor receptor-alpha, platelet-derived growth factor receptor-beta, colony-stimulating factor 1 receptor, neuregulin1, and fibroblast growth factor 17 that we have identified have been described as key regulators in the mitogen-activated protein kinase pathway. Therefore, this pathway could be a valuable target in the treatment of patients with breast cancer resistant to endocrine treatment. In addition, the putative gene LOC400500, predicted by in silico analysis, was identified. We showed that ectopic expression of this gene, designated as breast cancer antiestrogen resistance 4 (BCAR4), caused OH-TAM resistance and anchorage-independent cell growth in ZR-75-1 cells and that the intact open reading frame was required for its function. We conclude that retroviral transfer of cDNA libraries into human breast cancer cells is an efficient method for identifying genes involved in tamoxifen resistance
| Original language | English |
|---|---|
| Pages (from-to) | 379-386 |
| Journal | Molecular cancer research |
| Volume | 4 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2006 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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