Limits...
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

Principal component and trend analyses.(A) Principal component analysis and (B) Trend Plots for metabolites that are upregulated in MDAPCa2b vs RC77N-E and RC77T-E.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4526693&req=5

pone.0134206.g005: Principal component and trend analyses.(A) Principal component analysis and (B) Trend Plots for metabolites that are upregulated in MDAPCa2b vs RC77N-E and RC77T-E.

Mentions: In an attempt to identify metabolic markers that differentiate most between the non-malignant, RC77N-E and the bone metastatic MDAPCa2b, a binary comparison was performed using Orthogonal partial least square discriminant analysis (OPLS-DA) modeling. The scores plot of the OPLS-DA data further separated the RC77N-E and MDAPCa2b cell lines (Fig 3d). The OPLS-DA data were visualized using an S-plot (Fig 4). The X-axis in the S-plot represents the reliability and magnitude of each EMRT to the group difference and the Y-axis represents the confidence of each EMRT contribution to the group difference. Similar binary comparison can be performed between the different cell lines to identify the EMRT’s that contribute the most for the group separation. The EMRT’s with the greatest magnitude and reliability for the RC77N-E and MDAPCa2b cell lines were identified as PC(16:0/18:1) (m/z 760.5855, ESI+), and PC(16:0/16:1) (m/z 731.5459, ESI+). The other most significantly upregulated compound with the highest fold increase has a neutral mass of 1519.1517. The MS/MS fragmentation data is not sufficient for the unambiguous identification of the compound. Some of the compounds that contribute to the separation of these cell lines are summarized in Table 2. Subsequent trend analysis of metabolite expression profiles amongst the three RC77N-E, RC77T-E and MDAPCa2b cell lines reveal a group of metabolites that are significantly upregulated in the bone metastatic MDAPCa2b cells compared to the non-malignant RC77N-E and the primary adenocarcinoma RC77T-E cell lines (data not shown). These metabolites are potential markers of prostate cancer metastasis. Fig 5 shows the PCA analysis and trend plots for these molecules amongst the 5 cell lines. Table 2 summarizes the identifications, molecular properties and statistical analysis parameters for the metabolites that are differentially expressed between the non-malignant RC77N-E and the bone metastatic MDAPCa2b cell lines. The identifications are for lipids and polar metabolites in both negative and positive acquisition modes. S1 Fig shows representative low- and high-energy spectra for the identification of a differentially expressed lipid between RC77N-E and MDAPCa2b. Similar analyses have been performed on the same samples using MS data acquired in the negative mode and the results of the lipid metabolites amongst the 5 cell lines are summarized in Tables 3 and 4.


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)

Principal component and trend analyses.(A) Principal component analysis and (B) Trend Plots for metabolites that are upregulated in MDAPCa2b vs RC77N-E and RC77T-E.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0134206.g005: Principal component and trend analyses.(A) Principal component analysis and (B) Trend Plots for metabolites that are upregulated in MDAPCa2b vs RC77N-E and RC77T-E.
Mentions: In an attempt to identify metabolic markers that differentiate most between the non-malignant, RC77N-E and the bone metastatic MDAPCa2b, a binary comparison was performed using Orthogonal partial least square discriminant analysis (OPLS-DA) modeling. The scores plot of the OPLS-DA data further separated the RC77N-E and MDAPCa2b cell lines (Fig 3d). The OPLS-DA data were visualized using an S-plot (Fig 4). The X-axis in the S-plot represents the reliability and magnitude of each EMRT to the group difference and the Y-axis represents the confidence of each EMRT contribution to the group difference. Similar binary comparison can be performed between the different cell lines to identify the EMRT’s that contribute the most for the group separation. The EMRT’s with the greatest magnitude and reliability for the RC77N-E and MDAPCa2b cell lines were identified as PC(16:0/18:1) (m/z 760.5855, ESI+), and PC(16:0/16:1) (m/z 731.5459, ESI+). The other most significantly upregulated compound with the highest fold increase has a neutral mass of 1519.1517. The MS/MS fragmentation data is not sufficient for the unambiguous identification of the compound. Some of the compounds that contribute to the separation of these cell lines are summarized in Table 2. Subsequent trend analysis of metabolite expression profiles amongst the three RC77N-E, RC77T-E and MDAPCa2b cell lines reveal a group of metabolites that are significantly upregulated in the bone metastatic MDAPCa2b cells compared to the non-malignant RC77N-E and the primary adenocarcinoma RC77T-E cell lines (data not shown). These metabolites are potential markers of prostate cancer metastasis. Fig 5 shows the PCA analysis and trend plots for these molecules amongst the 5 cell lines. Table 2 summarizes the identifications, molecular properties and statistical analysis parameters for the metabolites that are differentially expressed between the non-malignant RC77N-E and the bone metastatic MDAPCa2b cell lines. The identifications are for lipids and polar metabolites in both negative and positive acquisition modes. S1 Fig shows representative low- and high-energy spectra for the identification of a differentially expressed lipid between RC77N-E and MDAPCa2b. Similar analyses have been performed on the same samples using MS data acquired in the negative mode and the results of the lipid metabolites amongst the 5 cell lines are summarized in Tables 3 and 4.

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