Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression

Arun Sreekumar, Laila M Poisson, Thekkelnaycke M Rajendiran, Amjad P Khan, Qi Cao, Jindan Yu, Bharathi Laxman, Rohit Mehra, Robert J Lonigro, Yong Li, Mukesh K Nyati, Aarif Ahsan, Shanker Kalyana-Sundaram, Bo Han, Xuhong Cao, Jaeman Byun, Gilbert S Omenn, Debashis Ghosh, Subramaniam Pennathur, Danny C Alexander, Alvin Berger, Jeffrey R Shuster, John T Wei, Sooryanarayana Varambally, Christopher Beecher, Arul M Chinnaiyan, Arun Sreekumar, Laila M Poisson, Thekkelnaycke M Rajendiran, Amjad P Khan, Qi Cao, Jindan Yu, Bharathi Laxman, Rohit Mehra, Robert J Lonigro, Yong Li, Mukesh K Nyati, Aarif Ahsan, Shanker Kalyana-Sundaram, Bo Han, Xuhong Cao, Jaeman Byun, Gilbert S Omenn, Debashis Ghosh, Subramaniam Pennathur, Danny C Alexander, Alvin Berger, Jeffrey R Shuster, John T Wei, Sooryanarayana Varambally, Christopher Beecher, Arul M Chinnaiyan

Abstract

Multiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of critical biomarkers for cancer invasion and disease aggressiveness. Although gene and protein expression have been extensively profiled in human tumours, little is known about the global metabolomic alterations that characterize neoplastic progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we profiled more than 1,126 metabolites across 262 clinical samples related to prostate cancer (42 tissues and 110 each of urine and plasma). These unbiased metabolomic profiles were able to distinguish benign prostate, clinically localized prostate cancer and metastatic disease. Sarcosine, an N-methyl derivative of the amino acid glycine, was identified as a differential metabolite that was highly increased during prostate cancer progression to metastasis and can be detected non-invasively in urine. Sarcosine levels were also increased in invasive prostate cancer cell lines relative to benign prostate epithelial cells. Knockdown of glycine-N-methyl transferase, the enzyme that generates sarcosine from glycine, attenuated prostate cancer invasion. Addition of exogenous sarcosine or knockdown of the enzyme that leads to sarcosine degradation, sarcosine dehydrogenase, induced an invasive phenotype in benign prostate epithelial cells. Androgen receptor and the ERG gene fusion product coordinately regulate components of the sarcosine pathway. Here, by profiling the metabolomic alterations of prostate cancer progression, we reveal sarcosine as a potentially important metabolic intermediary of cancer cell invasion and aggressivity.

Figures

Figure 1. Metabolomic profiling of prostate cancer
Figure 1. Metabolomic profiling of prostate cancer
a, Venn diagram of the total metabolites detected across 42 prostate-related tissues and 110 matched plasma and urine samples. b, Venn diagram of 626 metabolites in tissues measured across 16 benign adjacent prostate, 12 clinically localized prostate cancers (PCA), and 14 metastatic prostate cancers (Mets). c, Heat map representation of unsupervised hierarchical clustering of b (rows) grouped by sample type (columns). Shades of yellow and blue represent elevation and decrease of a metabolite respectively relative to the median metabolite levels (see color scale). d, Z-score plots for b normalized to the mean of the benign prostate samples (truncated at 25 SD for clarity, see Supplementary Methods for procedural details).
Figure 2. Metabolomic alterations of prostate cancer…
Figure 2. Metabolomic alterations of prostate cancer progression
a, Heat map showing 87 differential metabolites in PCA relative to benign samples (Wilcoxon P ≤ 0.05). Localized PCA samples are grouped as i., low grade (Gleason<6) and ii., high grade (Gleason>=7). Metastatic samples are grouped by the site of tissue procurement namely iii., soft tissue, iv., rib/diaphragm or v., liver. b, Benign-based z-score plot of named metabolites from a. Each point represents one metabolite in one sample, colored by tissue type (jade=benign, yellow=PCA). c, As in b except for the comparison between Mets (red) and PCA (yellow), with data represented relative to the mean of the PCA samples. For clarity, the plots in b and c have been truncated at 15 standard deviations above the mean of the benign and PCA samples, respectively.
Figure 3. Sarcosine levels in prostate cancer…
Figure 3. Sarcosine levels in prostate cancer and its association with cell invasion
a, Sarcosine levels in prostate cancer related tissue specimens (n=89). b, Sarcosine levels in post-DRE urine sediments from men with biopsy-proven prostate cancer (n=49) and prostate biopsy negative controls (n=44). c, Elevated levels of sarcosine (black bars) were found in invasive prostate cancer cells compared to non-invasive benign prostate epithelial cell lines. Mean +/− s.e.m. of sarcosine levels (n=3, except for PrEC cells where n=2). Cell invasion (grey bars) was also measured (mean +/− s.e.m.). e, Assessment of cell invasiveness of prostate epithelial cells upon exogenous administration of alanine, glycine, or sarcosine (mean +/− s.e.m., n=3).
Figure 4. A role for sarcosine in…
Figure 4. A role for sarcosine in androgen signaling and prostate cancer cell invasion
a, Schematic of the sarcosine pathway and its potential link to prostate cancer. b, Assessment of sarcosine levels and cell invasiveness after knockdown of GNMT in DU145 cells by RNA interference. c, As in b except knockdown of SARDH in RWPE cells (n=6). d, QRT-PCR analysis of GNMT and SARDH mRNA expression in androgen stimulated VCaP cells. e, AR and ERG binding sites on the promoter of GNMT as determined by ChIP-seq. The Y axes display the number of reads in a 25 bp sliding window. f, As in e, except ERG binding sites in the promoter of SARDH. g, Left panel, overexpression of ERG or ETV1 in RWPE cells and measurement of sarcosine levels and cell invasiveness. Right panel, as in left, except knockdown of TMPRSS2-ERG in VCaP cells by RNA interference. All error bars represent mean +/− s.e.m., n=3 unless indicated otherwise.

Source: PubMed

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