New cell culture model for aromatase inhibitor-resistant breast cancer shows sensitivity to fulvestrant treatment and cross-resistance between letrozole and exemestane

摘要

Aromatase inhibitor (AI) treatment is first-line systemic treatment for the majority of postmenopausal breast cancer patients with estrogen receptor (ER)-positive primary tumor. Although many patients benefit from treatment, some will develop resistance, and models mimicking acquired resistance will be valuable tools to unravel the resistance mechanisms and to find new treatments and biomarkers. Cell culture models for acquired resistance to the three clinically relevant AIs letrozole, anastrozole and exemestane were developed by selection and expansion of colonies of MCF-7 breast cancer cells surviving long-term AI treatment under conditions where endogenous aromatase-mediated conversion of androgen to estrogen was required for growth. Four cell lines resistant to each of the AIs were established and characterized. Maintenance of ER expression and function was a general finding, but ER loss was seen in one of twelve cell lines. HER receptor expression was increased, in particular EGFR expression in letrozole-resistant cell lines. The AI-resistant cell lines had acquired ability to grow without aromatase-mediated conversion of testosterone to estradiol, but upon withdrawal of AI treatment, testosterone induced minor growth stimulation. Letrozole, exemestane and tamoxifen were able to abrogate the testosterone stimulation but could not reduce growth to below the level in standard growth medium with AI, demonstrating cross-resistance between letrozole, exemestane and tamoxifen. In contrast, fulvestrant totally blocked growth of the AI resistant cell lines both after withdrawal of AI and with AI treatment. These data show that ER is the main driver of growth of the AI-resistant cell lines and indicate ligand-independent activation of ER. Fulvestrant is an efficient treatment option for these AI-resistant breast cancer cells, and the cell lines will be useful tools to disclose the underlying molecular mechanism for resistance to the different AIs.