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Lipid Droplets Define a Sub-Population of Breast Cancer Stem Cells.

ABSTRACT: Tumor recurrence is now the leading cause of breast cancer-related death. These recurrences are believed to arise from residual cancer stem cells that survive initial therapeutic intervention. Therefore, a comprehensive understanding of cancer stem cell biology is needed to generate more effective therapies. Here we investigate the association between dysregulation of lipid metabolism and breast cancer stem cells. Focusing specifically on lipid droplets, we found that the lipid droplet number correlates with stemness in a panel of breast cell lines. Using a flow cytometry-based method developed for this study, we establish a means to isolate cells with augmented lipid droplet loads from total populations and show that they are enriched in cancer stem cells. Furthermore, pharmacological targeting of fatty acid metabolism reveals a metabolic addiction in a subset of cell lines. Our results highlight a key role for the lipid metabolism in the maintenance of the breast cancer stem cell pool, and as such, suggest it as a potential therapeutic target.

SUBMITTER: Hershey BJ

PROVIDER: S-EPMC7019257 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Lipid Droplets Define a Sub-Population of Breast Cancer Stem Cells.

Hershey Benjamin J BJ Vazzana Roberta R Joppi Débora L DL Havas Kristina M KM

Journal of clinical medicine 20191229 1

Tumor recurrence is now the leading cause of breast cancer-related death. These recurrences are believed to arise from residual cancer stem cells that survive initial therapeutic intervention. Therefore, a comprehensive understanding of cancer stem cell biology is needed to generate more effective therapies. Here we investigate the association between dysregulation of lipid metabolism and breast cancer stem cells. Focusing specifically on lipid droplets, we found that the lipid droplet number co ...[more]

PMID: 31905780

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Project description:ObjectivesPolyunsaturated fatty acids (PUFAs) are structural components of membrane phospholipids and precursors of oxygenated lipid mediators with diverse functions, including the control of cell growth, inflammation and tumourigenesis. However, the molecular pathways that control the availability of PUFAs for lipid mediator production are not well understood. Here, we investigated the crosstalk of three pathways in the provision of PUFAs for lipid mediator production: (i) secreted group X phospholipase A2 (GX sPLA2) and (ii) cytosolic group IVA PLA2 (cPLA2α), both mobilizing PUFAs from membrane phospholipids, and (iii) adipose triglyceride lipase (ATGL), which mediates the degradation of triacylglycerols (TAGs) stored in cytosolic lipid droplets (LDs).MethodsWe combined lipidomic and functional analyses in cancer cell line models to dissect the trafficking of PUFAs between membrane phospholipids and LDs and determine the role of these pathways in lipid mediator production, cancer cell proliferation and tumour growth in vivo.ResultsWe demonstrate that lipid mediator production strongly depends on TAG turnover. GX sPLA2 directs ω-3 and ω-6 PUFAs from membrane phospholipids into TAG stores, whereas ATGL is required for their entry into lipid mediator biosynthetic pathways. ATGL controls the release of PUFAs from LD stores and their conversion into cyclooxygenase- and lipoxygenase-derived lipid mediators under conditions of nutrient sufficiency and during serum starvation. In starving cells, ATGL also promotes the incorporation of LD-derived PUFAs into phospholipids, representing substrates for cPLA2α. Furthermore, we demonstrate that the built-up of TAG stores by acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1) is required for the production of mitogenic lipid signals that promote cancer cell proliferation and tumour growth.ConclusionThis study shifts the paradigm of PLA2-driven lipid mediator signalling and identifies LDs as central lipid mediator production hubs. Targeting DGAT1-mediated LD biogenesis is a promising strategy to restrict lipid mediator production and tumour growth.

Project description:BackgroundLocal or distant relapse is the key event for the overall survival of early-stage breast cancer after initial surgery. A small subset of breast cancer cells, which share similar properties with normal stem cells, has been proven to resist to clinical therapy contributing to recurrence.MethodsIn this study, we aimed to develop a prognostic model to predict recurrence based on the prevalence of breast cancer stem cells (BCSCs) in breast cancer. Immunohistochemistry and dual-immunohistochemistry were performed to quantify the stem cells of the breast cancer patients. The performance of Cox proportional hazard regression model was assessed using the holdout methods, where the dataset was randomly split into two exclusive sets (70% training and 30% testing sets). Additionally, we performed bootstrapping to overcome a possible biased error estimate and obtain confidence intervals (CI).ResultsFour groups of BCSCs (ALDH1A3, CD44+/CD24-, integrin alpha 6 (ITGA6), and protein C receptor (PROCR)) were identified as associated with relapse-free survival (RFS). The correlated biomarkers were integrated as a prognostic panel to calculate a relapse risk score (RRS) and to classify the patients into different risk groups (high-risk or low-risk). According to RRS, 67.81 and 32.19% of patients were categorized into low-risk and high-risk groups respectively. The relapse rate at 5 years in the low-risk group (2.67, 95% CI: 0.72-4.63%) by Kaplan-Meier method was significantly lower than that of the high-risk group (19.30, 95% CI: 12.34-26.27%) (p < 0.001). In the multiple Cox model, the RRS was proven to be a powerful classifier independent of age at diagnosis or tumour size (p < 0.001). In addition, we found that high RRS score ER-positive patients do not benefit from hormonal therapy treatment (RFS, p = 0.860).ConclusionThe RRS model can be applied to predict the relapse risk in early stage breast cancer. As such, high RRS score ER-positive patients do not benefit from hormonal therapy treatment.

Dataset Information

Lipid Droplets Define a Sub-Population of Breast Cancer Stem Cells.

Publications

Lipid Droplets Define a Sub-Population of Breast Cancer Stem Cells.

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