Dataset Information

Kinetic Analysis of Lipid Metabolism in Breast Cancer Cells via Nonlinear Optical Microscopy.

ABSTRACT: Investigating the behavior of breast cancer cells via reaction kinetics may help unravel the mechanisms that underlie metabolic changes in tumors. However, obtaining human in vivo kinetic data is challenging because of difficulties associated with measuring these parameters. Nondestructive methods of measuring lipid content in live cells provide a novel approach to quantitatively model lipid synthesis and consumption. In this study, coherent Raman scattering microscopy was used to probe de novo intracellular lipid content. Combining nonlinear optical microscopy and Michaelis-Menten kinetics-based simulations, we isolated fatty acid synthesis/consumption rates and elucidated effects of altered lipid metabolism in T47D breast cancer cells. When treated with 17β-estradiol, the lipid utilization in cancer cells jumped by twofold. Meanwhile, the rate of de novo lipid synthesis in cancer cells treated with 17β-estradiol was increased by 42%. To test the model in extreme metabolic conditions, we treated T47D cells with etomoxir. Our kinetic analysis demonstrated that the rate of key enzymatic reactions dropped by 75%. These results underline the capability to probe lipid alterations in live cells with minimum interruption and to characterize lipid metabolism in breast cancer cells via quantitative kinetic models and parameters.

SUBMITTER: Hou J

PROVIDER: S-EPMC7376090 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundAltered lipid metabolism is an emerging hallmark of aggressive breast cancers. The N-myc downstream regulated gene (NDRG1) gene plays a critical role in peripheral nervous system myelination, as inactivating mutations cause severe demyelinating neuropathy. In breast cancer, elevated NDRG1 expression has been linked to clinical outcomes, but its functional role in breast cancer physiology has remained unclear.MethodsA meta-analysis of NDRG1 expression in multiple large publicly available genomic databases was conducted. Genome-wide expression correlation and Cox proportional hazards and Kaplan-Meier modeling of clinical outcomes associated with elevated expression were assessed. To study NDRG1 function, gene silencing and overexpression phenotypic studies were carried out in a panel of cell lines representing all major breast cancer molecular subtypes. Changes in cell proliferation, morphology, and neutral lipid accumulation due to altered NDRG1 expression were assessed by high throughput, quantitative microscopy. Comprehensive lipidomics mass spectrometry was applied to characterize global changes in lipid species due to NDRG1 silencing. Labeled fatty acids were used to monitor cellular fatty acid uptake and subcellular distribution under nutrient replete and starvation culture conditions.ResultsNDRG1 overexpression correlated with glycolytic and hypoxia-associated gene expression, and was associated with elevated rates of metastasis and patient mortality. Silencing NDRG1 reduced cell proliferation rates, causing lipid metabolism dysfunction including increased fatty acid incorporation into neutral lipids and lipid droplets. Conversely, NDRG1 expression minimized lipid droplet formation under nutrient replete and starvation conditions.ConclusionsHere we report that NDRG1 contributes to breast cancer aggressiveness by regulating the fate of lipids in cells that exhibit an altered lipid metabolic phenotype. In line with its role in promoting myelination and its association with altered metabolism in cancer, our findings show that NDRG1 is a critical regulator of lipid fate in breast cancer cells. The association between NDRG1 and poor prognosis in breast cancer suggests it should play a more prominent role in patient risk assessment. The function of NDRG1 in breast cancer lipid metabolism may represent a promising therapeutic approach in the future.

Dataset Information

Kinetic Analysis of Lipid Metabolism in Breast Cancer Cells via Nonlinear Optical Microscopy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets