Pluto Bioinformatics

GSE116744: RNA-Seq analysis of long-term estrogen-deprived (LTED) MDA-MB-134VI (MM134) and SUM44PE (SUM44) ILC cell lines

Bulk RNA sequencing

Background: Invasive lobular breast carcinoma (ILC) is a histological subtype of breast cancer that is characterized by loss of E-cadherin, and high expression of estrogen receptor alpha (ER). Many patients with ILC are effectively treated with adjuvant aromatase inhibitors (AIs), however, acquired AI resistance remains a significant problem.; Methods: To identify underlying mechanisms of acquired antiestrogen resistance in ILC, we developed a total of 6 long-term estrogen-deprived (LTED) variant cell lines of the human ILC cell lines SUM44PE (SUM44; 2 lines) and MDA-MB-134VI (MM134; 4 lines). To better understand mechanisms of AI resistance in these models, we performed transcriptional profiling analysis by RNA-sequencing.; Results: MM134 LTED cells expressed ER at decreased level and lost growth response to estradiol, while SUM44 LTED cells retained partial ER activity. Our transcriptional profiling analysis identified shared activation of lipid metabolism across all 6 independent models. However, the underlying basis of this signature was distinct between models. Oxysterols were able to promote the proliferation of SUM44 LTED cells, but not MM134 LTED. In contrast, MM134 LTED cells displayed high expression of the Sterol regulatory element-binding protein 1 (SREBP1), a regulator of fatty acid and cholesterol synthesis, and were hypersensitive to genetic or pharmacological inhibition of SREBPs. Several SREBP1 downstream targets involved in fatty acid synthesis, including FASN, were induced, and MM134 LTED cells were more sensitive to etomoxir, an inhibitor of the rate-limiting enzyme in -oxidation, than their respective parental control cells.; Conclusions: Our characterization of a unique series of AI-resistant ILC models identifies a lipogenic phenotype, including overexpression of SREBP1. This novel metabolic target deserves further studyfor the prevention and treatment of AI-resistance for patients with ILC. SOURCE: Kevin Levine ( - University of Pittsburgh

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