| Autor: |
Farshad Farshidfar, Karen A. Kopciuk, Robert Hilsden, S. Elizabeth McGregor, Vera C. Mazurak, W. Donald Buie, Anthony MacLean, Hans J. Vogel, Oliver F. Bathe |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
BMC Cancer, Vol 18, Iss 1, Pp 1-12 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
1471-2407 |
| DOI: |
10.1186/s12885-017-3923-z |
| Popis: |
Abstract Background Early diagnosis of colorectal cancer (CRC) simplifies treatment and improves treatment outcomes. We previously described a diagnostic metabolomic biomarker derived from semi-quantitative gas chromatography-mass spectrometry. Our objective was to determine whether a quantitative assay of additional metabolomic features, including parts of the lipidome could enhance diagnostic power; and whether there was an advantage to deriving a combined diagnostic signature with a broader metabolomic representation. Methods The well-characterized Biocrates P150 kit was used to quantify 163 metabolites in patients with CRC (N = 62), adenoma (N = 31), and age- and gender-matched disease-free controls (N = 81). Metabolites included in the analysis included phosphatidylcholines, sphingomyelins, acylcarnitines, and amino acids. Using a training set of 32 CRC and 21 disease-free controls, a multivariate metabolomic orthogonal partial least squares (OPLS) classifier was developed. An independent set of 28 CRC and 20 matched healthy controls was used for validation. Features characterizing 31 colorectal adenomas from their healthy matched controls were also explored, and a multivariate OPLS classifier for colorectal adenoma could be proposed. Results The metabolomic profile that distinguished CRC from controls consisted of 48 metabolites (R2Y = 0.83, Q2Y = 0.75, CV-ANOVA p-value |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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