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Updated: Dec 11, 2025

Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells
Published on: February 21, 2014
Ether lipid and sphingolipid expression patterns are estrogen receptor-dependently altered in breast cancer cells
Lisa Hahnefeld1, Lisa Gruber1, Nina Schömel1
1Pharmazentrum frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany.
Abstract:
Identifying co-expression of lipid species is challenging, but indispensable to identify novel therapeutic targets for breast cancer treatment. Lipid metabolism is often dysregulated in cancer cells, and changes in lipid metabolism affect cellular processes such as proliferation, autophagy, and tumor development. In addition to mRNA analysis of sphingolipid metabolizing enzymes, we performed liquid chromatography time-of-flight mass spectrometry analysis in three breast cancer cell lines. These breast cancer cell lines differ in estrogen receptor and G-protein coupled estrogen receptor 1 status. Our data show that sphingolipids and non-sphingolipids are strongly increased in SKBr3 cells. SKBr3 cells are estrogen receptor negative and G-protein coupled estrogen receptor 1 positive. Treatment with G15, a G-protein coupled estrogen receptor 1 antagonist, abolishes the effect of increased sphingolipid and non-sphingolipid levels in SKBr3 cells. In particular, ether lipids are expressed at much higher levels in cancer compared to normal cells and are strongly increased in SKBr3 cells. Our analysis reveals that this is accompanied by increased sphingolipid levels such as ceramide, sphingadiene-ceramide and sphingomyelin. This shows the importance of focusing on more than one lipid class when investigating molecular mechanisms in breast cancer cells. Our analysis allows unbiased screening for different lipid classes leading to identification of co-expression patterns of lipids in the context of breast cancer. Co-expression of different lipid classes could influence tumorigenic potential of breast cancer cells. Identification of co-regulated lipid species is important to achieve improved breast cancer treatment outcome.
Insights
Identifying co-expressed lipids is key for new breast cancer therapies. This study found increased sphingolipids and ether lipids in specific breast cancer cells, linked to estrogen receptor status, offering new therapeutic targets.
Area of Science:
- Oncology
- Lipidomics
- Biochemistry
Background:
- Lipid metabolism is frequently altered in cancer, impacting cell proliferation, autophagy, and tumor growth.
- Identifying co-expressed lipid species is crucial for discovering novel therapeutic targets in breast cancer.
- Dysregulated lipid metabolism plays a significant role in breast cancer development and progression.
Purpose of the Study:
- To investigate co-expression patterns of different lipid classes in breast cancer cell lines.
- To identify novel lipid targets for breast cancer treatment by analyzing lipid metabolism.
- To explore the relationship between estrogen receptor status and lipid profiles in breast cancer.
Main Methods:
- Analysis of sphingolipid metabolizing enzymes via mRNA.
- Liquid chromatography time-of-flight mass spectrometry (LC-TOF-MS) for lipid profiling.
- Comparison of lipid profiles across three breast cancer cell lines with varying estrogen receptor and G-protein coupled estrogen receptor 1 (GPER1) status.
Main Results:
- Elevated levels of sphingolipids and non-sphingolipids were observed in SKBr3 cells (ER-negative, GPER1-positive).
- Treatment with G15 (a GPER1 antagonist) reversed the increased lipid levels in SKBr3 cells.
- Ether lipids, ceramides, sphingadienes, and sphingomyelins were significantly increased in cancer cells, particularly SKBr3.
Conclusions:
- Co-expression of multiple lipid classes is essential for understanding breast cancer's molecular mechanisms.
- Unbiased lipid screening reveals co-expression patterns relevant to breast cancer.
- Targeting co-regulated lipid species holds promise for improving breast cancer treatment outcomes.
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