A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics
Background: Timely diagnosis and classification of colorectal cancer (CRC) are hindered by unsatisfactory clinical assays. Our aim was to construct a blood-based biomarker series using a single assay, suitable for CRC detection, prognostication and staging. Methods: Serum metabolomic profiles of ade...
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Veröffentlicht in: | British journal of cancer 2016-09, Vol.115 (7), p.848-857 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Background:
Timely diagnosis and classification of colorectal cancer (CRC) are hindered by unsatisfactory clinical assays. Our aim was to construct a blood-based biomarker series using a single assay, suitable for CRC detection, prognostication and staging.
Methods:
Serum metabolomic profiles of adenoma (
N
=31), various stages of CRC (
N
=320) and healthy matched controls (
N
=254) were analysed by gas chromatography-mass spectrometry (GC-MS). A diagnostic model for CRC was derived by orthogonal partial least squares-discriminant analysis (OPLS-DA) on a training set, and then validated on an independent data set. Metabolomic models suitable for identifying adenoma, poor prognosis stage II CRC and discriminating various stages were generated.
Results:
A diagnostic signature for CRC with remarkable multivariate performance (
R
2
Y
=0.46,
Q
2
Y
=0.39) was constructed, and then validated (sensitivity 85%; specificity 86%). Area under the receiver-operating characteristic curve was 0.91 (95% CI, 0.87–0.96). Adenomas were also detectable (
R
2
Y
=0.35,
Q
2
Y
=0.26, internal AUROC=0.81, 95% CI, 0.70–0.92). Also of particular interest, we identified models that stratified stage II by prognosis, and classified cases by stage.
Conclusions:
Using a single assay system, a suite of CRC biomarkers based on circulating metabolites enables early detection, prognostication and preliminary staging information. External population-based studies are required to evaluate the repeatability of our findings and to assess the clinical benefits of these biomarkers. |
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ISSN: | 0007-0920 1532-1827 |
DOI: | 10.1038/bjc.2016.243 |