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000157754 0247_ $$2doi$$a10.1007/s10552-020-01312-1
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000157754 0247_ $$2ISSN$$a1573-7225
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000157754 041__ $$aeng
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000157754 1001_ $$aOse, Jennifer$$b0
000157754 245__ $$aMetabolomics profiling of visceral and abdominal subcutaneous adipose tissue in colorectal cancer patients: results from the ColoCare study.
000157754 260__ $$aDordrecht [u.a.]$$bSpringer Science + Business Media B.V.$$c2020
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000157754 520__ $$aUnderlying mechanisms of the relationship between body fatness and colorectal cancer remain unclear. This study investigated associations of circulating metabolites with visceral (VFA), abdominal subcutaneous (SFA), and total fat area (TFA) in colorectal cancer patients.Pre-surgery plasma samples from 212 patients (stage I-IV) from the ColoCare Study were used to perform targeted metabolomics. VFA, SFA, and TFA were quantified by computed tomography scans. Partial correlation and linear regression analyses of VFA, SFA, and TFA with metabolites were computed and corrected for multiple testing. Cox proportional hazards were used to assess 2-year survival.In patients with metastatic tumors, SFA and TFA were statistically significantly inversely associated with 16 glycerophospholipids (SFA: pFDR range 0.017-0.049; TFA: pFDR range 0.029-0.048), while VFA was not. Doubling of ten of the aforementioned glycerophospholipids was associated with increased risk of death in patients with metastatic tumors, but not in patients with non-metastatic tumors (phet range: 0.00044-0.049). Doubling of PC ae C34:0 was associated with ninefold increased risk of death in metastatic tumors (Hazard Ratio [HR], 9.05; 95% confidence interval [CI] 2.17-37.80); an inverse association was observed in non-metastatic tumors (HR 0.17; 95% CI 0.04-0.87; phet = 0.00044).These data provide initial evidence that glycerophospholipids in metastatic colorectal cancer are uniquely associated with subcutaneous adiposity, and may impact overall survival.
000157754 536__ $$0G:(DE-HGF)POF3-313$$a313 - Cancer risk factors and prevention (POF3-313)$$cPOF3-313$$fPOF III$$x0
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000157754 650_2 $$2MeSH$$aAdiposity
000157754 650_2 $$2MeSH$$aAdolescent
000157754 650_2 $$2MeSH$$aAdult
000157754 650_2 $$2MeSH$$aAged
000157754 650_2 $$2MeSH$$aAged, 80 and over
000157754 650_2 $$2MeSH$$aBody Mass Index
000157754 650_2 $$2MeSH$$aColorectal Neoplasms: diagnostic imaging
000157754 650_2 $$2MeSH$$aColorectal Neoplasms: metabolism
000157754 650_2 $$2MeSH$$aColorectal Neoplasms: pathology
000157754 650_2 $$2MeSH$$aFemale
000157754 650_2 $$2MeSH$$aHumans
000157754 650_2 $$2MeSH$$aIntra-Abdominal Fat: diagnostic imaging
000157754 650_2 $$2MeSH$$aIntra-Abdominal Fat: metabolism
000157754 650_2 $$2MeSH$$aMale
000157754 650_2 $$2MeSH$$aMetabolomics
000157754 650_2 $$2MeSH$$aMiddle Aged
000157754 650_2 $$2MeSH$$aNeoplasm Staging
000157754 650_2 $$2MeSH$$aSubcutaneous Fat, Abdominal: diagnostic imaging
000157754 650_2 $$2MeSH$$aSubcutaneous Fat, Abdominal: metabolism
000157754 650_2 $$2MeSH$$aTomography, X-Ray Computed
000157754 650_2 $$2MeSH$$aYoung Adult
000157754 7001_ $$aHolowatyj, Andreana N$$b1
000157754 7001_ $$aNattenmüller, Johanna$$b2
000157754 7001_ $$aGigic, Biljana$$b3
000157754 7001_ $$aLin, Tengda$$b4
000157754 7001_ $$aHimbert, Caroline$$b5
000157754 7001_ $$aHabermann, Nina$$b6
000157754 7001_ $$aAchaintre, David$$b7
000157754 7001_ $$aScalbert, Augustin$$b8
000157754 7001_ $$aKeski-Rahkonen, Pekka$$b9
000157754 7001_ $$aBöhm, Jürgen$$b10
000157754 7001_ $$0P:(DE-He78)01ef71f71b01a3ec3b698653fd43fe86$$aSchrotz-King, Petra$$b11$$udkfz
000157754 7001_ $$aSchneider, Martin$$b12
000157754 7001_ $$aUlrich, Alexis$$b13
000157754 7001_ $$aKampman, Ellen$$b14
000157754 7001_ $$aWeijenberg, Matty$$b15
000157754 7001_ $$aGsur, Andrea$$b16
000157754 7001_ $$aUeland, Per-Magne$$b17
000157754 7001_ $$aKauczor, Hans-Ulrich$$b18
000157754 7001_ $$aUlrich, Cornelia M$$b19
000157754 773__ $$0PERI:(DE-600)1496544-6$$a10.1007/s10552-020-01312-1$$gVol. 31, no. 8, p. 723 - 735$$n8$$p723 - 735$$tCancer causes & control$$v31$$x1573-7225$$y2020
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