ArticleOncotarget2018
Lipid profiles of prostate cancer cells.
Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- "Resolving the SCD1-oleic acid paradox: majority of oleic acid is converted to free cholesterol in colorectal cancer cells".Cancer cell international · 2026Article
- The innate immune mediator group IIA secreted phospholipase AFrontiers in cell and developmental biology · 2026Article
- Cancer Cell Line Classification Using Raman Spectroscopy of Cancer-Derived Exosomes and Machine Learning.Analytical chemistry · 2025Article
- Unsupervised self-organising map classification of Raman spectra from prostate cell lines uncovers substratified prostate cancer disease states.Scientific reports · 2025Article
- Raman spectroscopy reveals oxidative stress-induced metabolic vulnerabilities in early-stage AR-negative prostate-cancer versus normal-prostate cell lines.Scientific reports · 2024Article
- Shining New Light on Biological Systems: Luminescent Transition Metal Complexes for Bioimaging and Biosensing Applications.Chemical reviews · 2024Review
- FACS-assisted single-cell lipidome analysis of phosphatidylcholines and sphingomyelins in cells of different lineages.Journal of lipid research · 2023Article
- Voltage-Controlled Divergent Cascade of Electrochemical Reactions for Characterization of Lipids at Multiple Isomer Levels Using Mass Spectrometry.Analytical chemistry · 2022Article
- Rhenium(I) conjugates as tools for tracking cholesterol in cells.Metallomics : integrated biometal science · 2022Article
- Label-Free Imaging of Lipid Droplets in Prostate Cells Using Stimulated Raman Scattering Microscopy and Multivariate Analysis.Analytical chemistry · 2022Article
- Ultrasensitive Detection of MCF-7 Cells with a Carbon Nanotube-Based Optoelectronic-Pulse Sensor Framework.ACS omega · 2022Article
- Determination of Glycerophospholipids in Biological Material Using High-Performance Liquid Chromatography with Charged Aerosol Detector HPLC-CAD-A New Approach for Isolation and Quantification.Molecules (Basel, Switzerland) · 2022Article
- Differential In Vitro Growth and Cell Killing of Cancer versus Benign Prostate Cells by Oncolytic Parainfluenza Virus.Pathogens (Basel, Switzerland) · 2022Article
- How cancer cells remodel lipid metabolism: strategies targeting transcription factors.Lipids in health and disease · 2021Review
- The phospholipid membrane compositions of bacterial cells, cancer cell lines and biological samples from cancer patients.Chemical science · 2021Review
- Article
- A Single-Organelle Optical Omics Platform for Cell Science and Biomarker Discovery.Analytical chemistry · 2021Article
- Identification of lipidomic profiles associated with drug-resistant prostate cancer cells.Lipids in health and disease · 2021Article
- Synthesis and fluorine-18 radiolabeling of a phospholipid as a PET imaging agent for prostate cancer.Nuclear medicine and biology · 2021Article
- Changes in phospholipid metabolism in exosomes of hormone-sensitive and hormone-resistant prostate cancer cells.Journal of Cancer · 2021Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lipids are important cellular components which can be significantly altered in a range of disease states including prostate cancer. Here, a unique systematic approach has been used to define lipid profiles of prostate cancer cell lines, using quantitative mass spectrometry (LC-ESI-MS/MS), FTIR spectroscopy and fluorescent microscopy. All three approaches identified significant difference in the lipid profiles of the three prostate cancer cell lines (DU145, LNCaP and 22RV1) and one non-malignant cell line (PNT1a). Specific lipid classes and species, such as phospholipids (e.g., phosphatidylethanolamine 18:1/16:0 and 18:1/18:1) and cholesteryl esters, detected by LC-ESI-MS/MS, allowed statistical separation of all four prostate cell lines. Lipid mapping by FTIR revealed that variations in these lipid classes could also be detected at a single cell level, however further investigation into this approach would be needed to generate large enough data sets for quantitation. Visualisation by fluorescence microscopy showed striking variations that could be observed in lipid staining patterns between cell lines allowing visual separation of cell lines. In particular, polar lipid staining by a fluorescent marker was observed to increase significantly in prostate cancer lines cells, when compared to PNT1a cells, which was consistent with lipid quantitation by LC-ESI-MS/MS and FTIR spectroscopy. Thus, multiple technologies can be employed to either quantify or visualise changes in lipid composition, and moreover specific lipid profiles could be used to detect and phenotype prostate cancer cells.
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