Non-invasive detection and prognostic evaluation of cancer represents a formidable challenge. Studies of the entire metabolite composition of cells promise advances towards this objective for prostate cancer.
Prostate cancer — the most frequently diagnosed cancer in men — is a main cause of morbidity and mortality. Although it can be effectively diagnosed using a combination of digital rectal examination and measuring the levels of the enzyme PSA in the blood serum, its features are notoriously variable among patients. This makes it difficult to identify those at greatest risk of their disease progressing to advanced stages. Improved screening approaches to stratify patient populations could therefore allow selective application of more aggressive treatment strategies. On page 910 of this issue, Sreekumar et al.1 report applying metabolomics to discover biomarkers that could potentially be used for non-invasive diagnosis and prognostic evaluation of prostate cancer.
So, what is metabolomics? In the post-genomic era, cancer researchers survey not only the total genetic composition of cells and tissues (genome), but also their overall collection of gene transcripts (transcriptome), proteins (proteome) and other 'omes'. The goal of such investigations is to decipher molecular signatures that distinguish tumours from normal tissues. The metabolome is the latest 'ome' to capture the imagination of researchers, and corresponds to the metabolite content of cells or tissues. Analyses of the various 'omes' are complementary, but determining the metabolite content of cancer cells — cancer metabolomics — is particularly attractive because it can provide an accurate read-out of tumours' cellular physiology and biochemical activity, with individual metabolites representing end-points of the molecular pathways perturbed by events in the other 'omes'2,3 (Fig. 1a).
In practice, however, analysis of the metabolome is highly complex because of the broad range of detectable metabolites. Recent advances in the application of metabolomics to cancer have depended on technical improvements in the separation of various metabolites using enhanced spectrometric methods, as well as the use of systems-biology approaches for data analysis. But, despite several studies4,5,6 that have made initial inroads into using applied metabolomics for the detection or prognostic evaluation of kidney and colon cancers, until now cancer metabolomics has remained in its infancy.
Sreekumar and colleagues1 have embarked on the identification of metabolites that distinguish normal (benign) prostate from prostate cancer and its advanced metastatic form. Among the 1,126 metabolites they isolated from samples of prostate tissue, serum and urine, they identify 87 that distinguish prostate cancer from benign prostate tissue. Of these, six metabolites were of particular interest because their levels were even higher in metastatic cancer. The authors further pursued one of these metabolites as a possible biomarker for cancer progression: sarcosine — a derivative of the amino acid glycine — was the metabolite they chose owing to its elevated levels during cancer progression as well as its possible links to the disease mechanisms.
In vivo, sarcosine (N-methylglycine) is generated by the enzymatic transfer of a methyl group from S-adenosylmethionine to glycine (Fig. 1b). This reaction is catalysed by the enzyme glycine-N-methyltransferase (GNMT), which is expressed at high levels in the mammalian liver, exocrine pancreas and prostate. GNMT plays a central part in modulating the cellular pool of S-adenosylmethionine, which is the main methyl donor for several essential reactions that regulate gene expression and protein activity; these include cytosine methylation of DNA, lysine methylation of histone proteins and arginine methylation of histones and other proteins. In an earlier study7, this group1 found that the levels of the methyltransferase enzyme EZH2, which transfers methyl groups to lysine 27 of histone H3, are higher during the progression of prostate cancer and other tumours. Their latest data1 are suggestive of a transcriptional link between cancer progression and GNMT activity, through the binding of both the androgen receptor and the oncogene ERG to the promoter sequence of the GNMT gene in tumour cells.
Unexpectedly, Sreekumar et al. not only show that sarcosine is a biomarker for prostate-cancer progression, but also provide evidence, using cells maintained in culture, for its functional role in regulating the features of cancer cells. They find that the addition of sarcosine to benign prostate epithelial cells promotes invasive properties in these cells, whereas lowering GNMT levels in a prostate-cancer cell line reduces its invasiveness.
By contrast, however, a previous study8 showed that mice lacking GNMT develop liver cancer with age. Moreover, in a significant proportion of human prostate cancers, GNMT undergoes a phenomenon called loss of heterozygosity — in which one copy of the gene is lost — and the expression of this gene was documented to decrease with prostate-cancer progression9. Reconciling these earlier findings with those of Sreekumar et al. is necessary to determine the overall significance of sarcosine levels in assessing cancer progression.
At present, the greatest value of metabolomic approaches seems to be for the development of non-invasive screening procedures that can be used for effective cancer diagnosis and prognosis. Notably, Sreekumar and colleagues1 show that sarcosine levels in urine have a modest but significant predictive value for prostate-cancer diagnosis; this suggests that assessment of metabolite levels in urine might be an appropriate screening tool when applied together with examination of PSA levels and other approaches for monitoring disease progression. Furthermore, the authors identify several other metabolites that are more readily detected in cancer and metastases than sarcosine, although with no obvious mechanistic link to disease progression; these metabolites might therefore be more suitable for predictive screening tests.
It is not known whether metabolome changes similar to those Sreekumar et al. observe in prostate cancer occur in other tumours. It will also be of interest to learn how environmental factors such as diet (including intake of methionine — the precursor of S-adenosylmethionine) may affect the metabolome profile and thus the usefulness of metabolomic analysis in cancer screening. As a starting point, however, Sreekumar and colleagues' observations suggest that metabolomics has a promising future in aiding cancer diagnosis and treatment.
Sreekumar, A. et al. Nature 457, 910–914 (2009).
Griffin, J. L. & Shockcor, J. P. Nature Rev. Cancer 4, 551–561 (2004).
Spratlin, J. L., Serkova, N. J. & Eckhardt, S. G. Clin. Cancer Res. 15, 431–440 (2009).
Denkert, C. et al. Mol. Cancer 7, 72 (2008).
Ippolito, J. E. et al. Proc. Natl Acad. Sci. USA 102, 9901–9906 (2005).
Kind, T. et al. Anal. Biochem. 363, 185–195 (2007).
Varambally, S. et al. Nature 419, 624–629 (2002).
Martínez-Chantar, M. L. et al. Hepatology 47, 1191–1199 (2008).
Huang, Y.-C. et al. Clin. Cancer Res. 13, 1412–1420 (2007).
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