Dataset Information

Mapping and Profiling Lipid Distribution in a 3D Model of Breast Cancer Progression.

ABSTRACT: Aberrant lipid accumulation and marked changes in cellular lipid profiles are related to breast cancer metabolism and disease progression. In vitro, these phenomena are primarily studied using cells cultured in monolayers (2D). Here, we employ multicellular spheroids, generated using the MCF10A cell line series of increasing malignancy potential, to better recapitulate the 3D microenvironmental conditions that cells experience in vivo. Breast cancer cell lipid compositions were assessed in 2D and 3D culture models as a function of malignancy using liquid chromatography coupled with mass spectrometry. Further, the spatial distribution of lipids was examined using Raman chemical imaging and lipid staining. We show that with changes in the cellular microenvironment when moving from 2D to 3D cell cultures, total lipid amounts decrease significantly, while the ratio of acylglycerols to membrane lipids increases. This ratio increase could be associated with the formation of large lipid droplets (>10 ?m) that are spatially evident throughout the spheroids but absent in 2D cultures. Additionally, we found a significant difference in lipid profiles between the more and less malignant spheroids, including changes that support de novo sphingolipid production and a reduction in ether-linked lipid fractions in the invasive spheroids. These differences in lipid profiles as a function of cell malignancy and microenvironment highlight the importance of coupled spatial and lipidomic studies to better understand the connections between lipid metabolism and cancer.

SUBMITTER: Vidavsky N

PROVIDER: S-EPMC6535773 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mapping and Profiling Lipid Distribution in a 3D Model of Breast Cancer Progression.

Vidavsky Netta N Kunitake Jennie A M R JAMR Diaz-Rubio Maria Elena ME Chiou Aaron E AE Loh Hyun-Chae HC Zhang Sheng S Masic Admir A Fischbach Claudia C Estroff Lara A LA

ACS central science 20190419 5

Aberrant lipid accumulation and marked changes in cellular lipid profiles are related to breast cancer metabolism and disease progression. <i>In vitro</i>, these phenomena are primarily studied using cells cultured in monolayers (2D). Here, we employ multicellular spheroids, generated using the MCF10A cell line series of increasing malignancy potential, to better recapitulate the 3D microenvironmental conditions that cells experience <i>in vivo</i>. Breast cancer cell lipid compositions were ass ...[more]

PMID: 31139713

Similar Datasets

Project description:MicroRNAs (miRNAs) are known to be deregulated in human breast cancer (BC). The purpose of the current study was to investigate the expression of miRNAs in different stages of BC to assess their biological value in BC progression. MiRNA expression was assessed in a series of BC patients (n=7) with distinct stages of tumour progression (Normal, in-situ (DCIS), primary invasive BC and nodal metastases) to evaluate miRNA differential expression. We used an Agilent miRNA microarray based platform which uses miRBase 16 to screen for 1205 Homo sapiens (hsa) and 144 human viral miRNA candidates. To validate the microarray data, the expression of two deregulated miRNAs was measured by TaqMan quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). This study was conducted Formalin Fixed and Paraffin Embedded (FFPE) specimens from 7 female patients. Twenty μm thick FFPE sections were cut and mounted on PALM Membrane Slides. Under direct microscopic visualization, tissues of interest were micro-dissected using PALM non-contact Laser catapulsion instrument (P.A.L.M. Microlaser Technologies, Carl Zeiss Ltd). Total RNA, including miRNAs, was extracted with the TRIzol reagent (Invitrogen, supplied by Fisher Scientific UK Ltd) according to the manufacturer’s instructions. Total RNA was quantified with Quant-iT RiboGreen RNA Quantitation Kit (Fisher Scientific UK Ltd), which is an accurate method of measuring total RNA with a detection limit of 0.001-1ng/µl. RNA purity and RNA integrity number (RIN) were determined on an Agilent 2100 Bioanalyzer and RNA 6000 NanoLabChip Kits (both Agilent Technologies, Santa Clara, USA), and the RIN of all the samples was >2 but <3. This is expected for FFPE breast samples and is acceptable by Agilent Technologies, Santa Clara, USA, for FFPE samples to undergo miRNA microarray analysis. MiRNAs extracted from laser microdissected tissue components were profiled using Agilent microRNA microarray profiling system (Agilent Technologies, Santa Clara, USA). Total RNA samples were spiked using the MicroRNA Spike-In Kit (Agilent Technologies, Santa Clara, USA) to evaluate efficiencies of labelling and hybridisation. Total RNA was treated with Calf Intestinal Alkaline Phosphatase (CIP), and then 100 ng of total RNA was used per sample to initiate a labelling reaction. Ligation master mix for T4 RNA ligase, which includes Cyanine 3-Cytidine biphosphate (Cyanine 3-pCp) (Complete miRNA Labelling and Hyb Kit, Agilent Technologies, Santa Clara, USA) was used to label the dephosphorylated RNA. Cyanine-3-labelled miRNA samples were hybridised to human miRNA microarrays (Release 16.0, 8x60K) (Agilent Technologies, Santa Clara, USA) at 55°C for 20 hrs. Microarray slides were washed with increasing stringency (Gene Expression Wash Buffers, Agilent Technologies, Santa Clara), and subsequently dried with acetonitrile (Sigma-Aldrich, St. Louis, USA). Fluorescent signal intensities were detected on an Agilent Microarray Scanner (Agilent Technologies, Santa Clara, USA) using the Scan Control A.8.4.1 Software (Agilent Technologies, Santa Clara, USA) and extracted from the images with the Feature Extraction 10.7.3.1 Software (Agilent Technologies, Santa Clara, USA).

Dataset Information

Mapping and Profiling Lipid Distribution in a 3D Model of Breast Cancer Progression.

Publications

Mapping and Profiling Lipid Distribution in a 3D Model of Breast Cancer Progression.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets