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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

Comparative analysis of metabolite profiles of the cell lines.(A) PCA scores plot of the metabolite profiles of the five prostate cell lines, RWPE-1, LNCAP, RC77N-E, RC77T-E, MDAPCa2b and pooled sample. (B) PCA scores plot of the metabolites of the three African American cell lines RC77N-E, RC77T-E and MDAPCa2b. (C) Corresponding loadings plot from PCA analysis of the three cell lines. (D) Corresponding OPLS-DA analysis of the two African American cell lines RC77N-E and MDAPCa2b.
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pone.0134206.g003: Comparative analysis of metabolite profiles of the cell lines.(A) PCA scores plot of the metabolite profiles of the five prostate cell lines, RWPE-1, LNCAP, RC77N-E, RC77T-E, MDAPCa2b and pooled sample. (B) PCA scores plot of the metabolites of the three African American cell lines RC77N-E, RC77T-E and MDAPCa2b. (C) Corresponding loadings plot from PCA analysis of the three cell lines. (D) Corresponding OPLS-DA analysis of the two African American cell lines RC77N-E and MDAPCa2b.

Mentions: The data from Progenesis QI analysis was exported to EZinfo for detailed multivariate statistical analysis such as Principal component analysis (PCA), orthogonal partial least squares—discriminant analysis (OPLS-DA) and S-plot. Using these multivariate statistical tools, regardless the complexity of the sample, it is easier to determine the features that change between the different cell lines for further identification and targeted analysis. PCA was performed for the acquired metabolomic data to identify whether the metabolite profiles of the different prostate cell lines could be used to differentiate tumorigenic phenotypes. The scores and loadings plot for the PCA model of the five different cell lines and the pooled samples for lipid metabolites in the positive mode is shown in Fig 3a. The clustering of the pooled samples at the origin of the PCA plot indicates the robustness of the analysis. Different comparative PCA analyses were performed amongst the 5 cell lines. As an example, the scores and loadings plot for the PCA model of the three cell lines RC77N-E, RC77T-E and MDAPCa2b with different tumorigenic phenotypes is shown in Fig 3b. Three groups were separated on the basis of the PCA analysis, reflecting the tumorigenic features of these cell lines. The loadings plot indicates the exact mass retention time pairs (EMRT’s) that contributed towards the groupings in the scores plot, Fig 3c. The major EMRT’s that contribute significantly in differentiating the three cell lines have m/z 760.5855, 876.800, 904.8315 (upregulated in MDAPCa2b), 758.5694, 411.2660, 732.5538 (upregulated in RC77N-E) and 808.7384, 794.7225, 822.7537 (upregulated in RC77T-E).


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)

Comparative analysis of metabolite profiles of the cell lines.(A) PCA scores plot of the metabolite profiles of the five prostate cell lines, RWPE-1, LNCAP, RC77N-E, RC77T-E, MDAPCa2b and pooled sample. (B) PCA scores plot of the metabolites of the three African American cell lines RC77N-E, RC77T-E and MDAPCa2b. (C) Corresponding loadings plot from PCA analysis of the three cell lines. (D) Corresponding OPLS-DA analysis of the two African American cell lines RC77N-E and MDAPCa2b.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0134206.g003: Comparative analysis of metabolite profiles of the cell lines.(A) PCA scores plot of the metabolite profiles of the five prostate cell lines, RWPE-1, LNCAP, RC77N-E, RC77T-E, MDAPCa2b and pooled sample. (B) PCA scores plot of the metabolites of the three African American cell lines RC77N-E, RC77T-E and MDAPCa2b. (C) Corresponding loadings plot from PCA analysis of the three cell lines. (D) Corresponding OPLS-DA analysis of the two African American cell lines RC77N-E and MDAPCa2b.
Mentions: The data from Progenesis QI analysis was exported to EZinfo for detailed multivariate statistical analysis such as Principal component analysis (PCA), orthogonal partial least squares—discriminant analysis (OPLS-DA) and S-plot. Using these multivariate statistical tools, regardless the complexity of the sample, it is easier to determine the features that change between the different cell lines for further identification and targeted analysis. PCA was performed for the acquired metabolomic data to identify whether the metabolite profiles of the different prostate cell lines could be used to differentiate tumorigenic phenotypes. The scores and loadings plot for the PCA model of the five different cell lines and the pooled samples for lipid metabolites in the positive mode is shown in Fig 3a. The clustering of the pooled samples at the origin of the PCA plot indicates the robustness of the analysis. Different comparative PCA analyses were performed amongst the 5 cell lines. As an example, the scores and loadings plot for the PCA model of the three cell lines RC77N-E, RC77T-E and MDAPCa2b with different tumorigenic phenotypes is shown in Fig 3b. Three groups were separated on the basis of the PCA analysis, reflecting the tumorigenic features of these cell lines. The loadings plot indicates the exact mass retention time pairs (EMRT’s) that contributed towards the groupings in the scores plot, Fig 3c. The major EMRT’s that contribute significantly in differentiating the three cell lines have m/z 760.5855, 876.800, 904.8315 (upregulated in MDAPCa2b), 758.5694, 411.2660, 732.5538 (upregulated in RC77N-E) and 808.7384, 794.7225, 822.7537 (upregulated in RC77T-E).

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