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Comparative Metabolomic and Lipidomic Analysis of Phenotype Stratified Prostate Cells.

Burch TC, Isaac G, Booher CL, Rhim JS, Rainville P, Langridge J, Baker A, Nyalwidhe JO - PLoS ONE (2015)

Bottom Line: We have identified potentially interesting species of different lipid subclasses including phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), glycerophosphoinositols (PIs) and other metabolites that are significantly upregulated in prostate cancer cells derived from distant metastatic sites.Transcriptomic and biochemical analysis of key enzymes that are involved in lipid metabolism demonstrate the significant upregulation of choline kinase alpha in the metastatic cells compared to the non-malignant and non-metastatic cells.This suggests that different de novo lipogenesis and other specific signal transduction pathways are activated in aggressive metastatic cells as compared to normal and non-metastatic cells.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, Virginia, United States of America; Leroy T. Canoles Jr. Cancer Research Center, Eastern Virginia Medical School, Norfolk, Virginia, United States of America.

ABSTRACT
Prostate cancer (PCa) is the most prevalent cancer amongst men and the second most common cause of cancer related-deaths in the USA. Prostate cancer is a heterogeneous disease ranging from indolent asymptomatic cases to very aggressive life threatening forms. The goal of this study was to identify differentially expressed metabolites and lipids in prostate cells with different tumorigenic phenotypes. We have used mass spectrometry metabolomic profiling, lipidomic profiling, bioinformatic and statistical methods to identify, quantify and characterize differentially regulated molecules in five prostate derived cell lines. We have identified potentially interesting species of different lipid subclasses including phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), glycerophosphoinositols (PIs) and other metabolites that are significantly upregulated in prostate cancer cells derived from distant metastatic sites. Transcriptomic and biochemical analysis of key enzymes that are involved in lipid metabolism demonstrate the significant upregulation of choline kinase alpha in the metastatic cells compared to the non-malignant and non-metastatic cells. This suggests that different de novo lipogenesis and other specific signal transduction pathways are activated in aggressive metastatic cells as compared to normal and non-metastatic cells.

No MeSH data available.


Related in: MedlinePlus

Analysis of lipids extracted from prostate cancer cell lines using UPLC/MS-MS.(A). A chromatogram acquired in high-energy mode. (B). A chromatogram acquired in low energy mode within the same experiment.
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pone.0134206.g001: Analysis of lipids extracted from prostate cancer cell lines using UPLC/MS-MS.(A). A chromatogram acquired in high-energy mode. (B). A chromatogram acquired in low energy mode within the same experiment.

Mentions: A novel UPLC/MSE data-independent method that provides molecular and structural information from every detectable component in a liquid chromatography separation was used to ensure maximizing data quality and coverage. This method provides informative mass spectrometry data that includes precursor exact ion mass in low energy and corresponding fragment ion spectra in high energy. This semi-quantitative approach requires little prior knowledge of the sample and is unbiased and reproducible. The results from comparing MSE with targeted MS/MS analysis have shown that the same metabolite structure was assigned in 95.7% of the cases [18]. Fig 1 shows the chromatogram for the separation of various lipid classes in the pooled sample by electrospray ionization in the negative ion mode. Both low and high energy data was acquired within the same run (MSE) and the data from the two experiments were subsequently aligned for structural elucidation. The analysis of the acquired data was accomplished using the novel Progenesis QI v1.0 (Nonlinear Dynamics, Newcastle, UK) data processing and statistical tool. Progenesis QI allows for the performance of differential analysis of high resolution UPLC-MS metabolomics data across different biological samples. This strategy allows for the identification and quantitation of potential biomarkers. Key to this data processing and analysis is the ability of Progenesis QI to distinguish biological variation and metabolic changes from analytical interferences. It is crucial that each sample is randomized and with a minimum of three technical replicates to ensure for statistical validity of the data.


Comparative Metabolomic and Lipidomic Analysis of Phenotype Stratified Prostate Cells.

Burch TC, Isaac G, Booher CL, Rhim JS, Rainville P, Langridge J, Baker A, Nyalwidhe JO - PLoS ONE (2015)

Analysis of lipids extracted from prostate cancer cell lines using UPLC/MS-MS.(A). A chromatogram acquired in high-energy mode. (B). A chromatogram acquired in low energy mode within the same experiment.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4526693&req=5

pone.0134206.g001: Analysis of lipids extracted from prostate cancer cell lines using UPLC/MS-MS.(A). A chromatogram acquired in high-energy mode. (B). A chromatogram acquired in low energy mode within the same experiment.
Mentions: A novel UPLC/MSE data-independent method that provides molecular and structural information from every detectable component in a liquid chromatography separation was used to ensure maximizing data quality and coverage. This method provides informative mass spectrometry data that includes precursor exact ion mass in low energy and corresponding fragment ion spectra in high energy. This semi-quantitative approach requires little prior knowledge of the sample and is unbiased and reproducible. The results from comparing MSE with targeted MS/MS analysis have shown that the same metabolite structure was assigned in 95.7% of the cases [18]. Fig 1 shows the chromatogram for the separation of various lipid classes in the pooled sample by electrospray ionization in the negative ion mode. Both low and high energy data was acquired within the same run (MSE) and the data from the two experiments were subsequently aligned for structural elucidation. The analysis of the acquired data was accomplished using the novel Progenesis QI v1.0 (Nonlinear Dynamics, Newcastle, UK) data processing and statistical tool. Progenesis QI allows for the performance of differential analysis of high resolution UPLC-MS metabolomics data across different biological samples. This strategy allows for the identification and quantitation of potential biomarkers. Key to this data processing and analysis is the ability of Progenesis QI to distinguish biological variation and metabolic changes from analytical interferences. It is crucial that each sample is randomized and with a minimum of three technical replicates to ensure for statistical validity of the data.

Bottom Line: We have identified potentially interesting species of different lipid subclasses including phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), glycerophosphoinositols (PIs) and other metabolites that are significantly upregulated in prostate cancer cells derived from distant metastatic sites.Transcriptomic and biochemical analysis of key enzymes that are involved in lipid metabolism demonstrate the significant upregulation of choline kinase alpha in the metastatic cells compared to the non-malignant and non-metastatic cells.This suggests that different de novo lipogenesis and other specific signal transduction pathways are activated in aggressive metastatic cells as compared to normal and non-metastatic cells.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, Virginia, United States of America; Leroy T. Canoles Jr. Cancer Research Center, Eastern Virginia Medical School, Norfolk, Virginia, United States of America.

ABSTRACT
Prostate cancer (PCa) is the most prevalent cancer amongst men and the second most common cause of cancer related-deaths in the USA. Prostate cancer is a heterogeneous disease ranging from indolent asymptomatic cases to very aggressive life threatening forms. The goal of this study was to identify differentially expressed metabolites and lipids in prostate cells with different tumorigenic phenotypes. We have used mass spectrometry metabolomic profiling, lipidomic profiling, bioinformatic and statistical methods to identify, quantify and characterize differentially regulated molecules in five prostate derived cell lines. We have identified potentially interesting species of different lipid subclasses including phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), glycerophosphoinositols (PIs) and other metabolites that are significantly upregulated in prostate cancer cells derived from distant metastatic sites. Transcriptomic and biochemical analysis of key enzymes that are involved in lipid metabolism demonstrate the significant upregulation of choline kinase alpha in the metastatic cells compared to the non-malignant and non-metastatic cells. This suggests that different de novo lipogenesis and other specific signal transduction pathways are activated in aggressive metastatic cells as compared to normal and non-metastatic cells.

No MeSH data available.


Related in: MedlinePlus