Metabolite information |
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| HMDB ID | HMDB0011131 |
| Synonyms |
1,2,3-Propanetriol 1-octadecanoyl ester1,2,3-Propanetriol monooctadecanoate1,2,3-Propanetriol, homopolymer, isooctadecanoate1-Glyceryl stearate1-Monoacylglyceride1-Monoacylglycerol1-Monooctadecanoyl-rac-glycerol1-Monostearin1-Monostearoylglycerol1-O-Octadecanoylglycerol1-O-Stearoylglycerol1-Octadecanoyl-rac-glycerol1-Octadecanoyl-sn-glycerol1-Octadecanoylglycerol1-Stearoyl-glycerol1-Stearoyl-rac-glycerol1-Stearoylglycerol1-mono-Stearin2,3-Dihydroxypropyl stearate3-Stearoyloxy-1,2-propanediolCefatinCellular membraneDermagineDigestionExtracellular regionFEMA 2527FaecalFaecesFaunaFecalGlycerin 1-monostearateGlycerin 1-stearateGlycerol 1-monostearateGlycerol 1-octadecanoateGlycerol 1-octadecanoic acidGlycerol 1-stearateGlycerol alpha -monostearateGlycerol alpha -sterateGlycerol alpha-monostearateGlyceryl 1-monostearateGlyceryl monostearateGlyceryl monostearic acidGlyceryl-1-monostearateLipid metabolic processMAG[18:0/0:0]MAG[18:0]MG [18:0/0:0/0:0]MG[18:0/0:0]MG[18:0]Membrane integrity agentMembrane stability agentOctadecanoic acid 2,3-dihydroxypropyl esterOctadecanoic acid, 2,3-dihydroxypropyl esterOctadecanoic acid, ester with 1,2,3-propanetriolSignal transductionStearic acid 1-monoglycerideStearic acid alpha -monoglycerideStearic acid alpha-monoglycerideStoolSurface-active agent[1]-2,3-Dihydroxypropyl stearate[2S]-2,3-Dihydroxypropyl octadecanoate[2S]-2,3-Dihydroxypropyl octadecanoic acid[S]-1-Monostearin[S]-[+]-1-O-Stearoylglycerola-Monoacylglycerola-Monostearinalpha-Monoacylglycerolalpha-Monostearinsn-1-Octadecanoyl-monoglyceride |
| Chemical formula | C21H42O4 |
| IUPAC name | (2S)-2,3-dihydroxypropyl octadecanoate |
| CAS registry number | 22610-61-3 |
| Monisotopic molecular weight | 358.308309832 |
Chemical taxonomy |
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| Super class | Lipids and lipid-like molecules |
| Class | Glycerolipids |
| Sub class | Monoradylglycerols |
Biological properties |
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| Pahtways |
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| Author-emphasized biomarker in the paper(s) |
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| Reference | Country | Specimen | Marker function | Participants (Case) | Participants (Control) | |||||||||
| Cancer type | Stage | Number | Gender (M,F) | Age mean (range) (M/F) | Smoking status | Type | Number | Gender (M,F) | Age mean (range) (M/F) | Smoking status | ||||
| Miyamoto et al. 2015 | – | blood | diagnosis | adenocarcinoma | unknown (mostly late stage) | 18 | 10, 8 | 67 (50-85) / 62 (53-72) | former, current | healthy | 20 | 8, 12 | 64 (49-80) / 66 (58-82) | former, current |
| Fahrmann et al. 2015 | – | serum | diagnosis | adenocarcinoma | I, II, III, IV | 49 | 17, 32 | 65.9 ± 9.87 | – | healthy | 31 | 11, 20 | 64.1 ± 8.97 | – |
| Fahrmann et al. 2015 | – | plasma | diagnosis | adenocarcinoma | I, II, III, IV | 43 | 21, 22 | 67.3 ± 10.10 | – | healthy | 43 | 21, 22 | 65.9 ± 8.05 | – |
| Miyamoto et al. 2015 | – | blood | diagnosis | NSCLC, SCLC, mesothelioma, secondary metastasis to lung | I, II, III, IV | 11 | 4, 7 | 67 (61-73) / 67 (47-76) | smoker, non-smoker | healthy | 11 | 5, 6 | 69 (61-83) / 54 (44-61) | unknown |
| Mazzone et al. 2016 | – | serum | – | adenocarcinoma, squamous cell carcinoma | I, II, III | 94 | 55.3%, 44.7% | 68.7 | – | at-risk controls | 190 | 50.5%, 49.5% | 66.2 | – |
| Fahrmann et al. 2015 | – | plasma | diagnosis | adenocarcinoma | I, II, III, IV | 52 | 17, 35 | 65.9 ± 9.66 | – | healthy | 31 | 11, 20 | 64.1 ± 8.97 | – |
| Fahrmann et al. 2015 | – | serum | diagnosis | adenocarcinoma | I, II, III, IV | 43 | 21, 22 | 67.3 ± 10.10 | – | healthy | 43 | 21, 22 | 65.9 ± 8.05 | – |
| Moreno et al. 2018 | – | tissue | therapy, diagnosis | adenocarcinoma | I, II, III | 33 | 24, 9 | 62.11 ± 9.73 | – | tumor vs. adjacent normal tissue | 33 | 24, 9 | 62.11 ± 9.73 | – |
| Moreno et al. 2018 | – | tissue | therapy, diagnosis | squamous cell carcinoma | I, II, III | 35 | 35, 0 | 68.71 ± 7.46 | – | tumor vs. adjacent normal tissue | 35 | 35, 0 | 68.71 ± 7.46 | – |
| Wikoff et al. 2015b | – | tissue | diagnosis | adenocarcinoma | I | 39 | 15, 24 | 72.33 ± 8.78 | smoker, non-smoker | tumor vs. adjacent normal tissue | 39 | 15, 24 | 72.33 ± 8.78 | smoker, non-smoker |
| Reference | Chromatography | Ion source | Positive/Negative mode | Mass analyzer | Identification level |
| Miyamoto et al. 2015 | GC | EI | – | TOF | MS/MS |
| Fahrmann et al. 2015 | GC | EI | – | TOF | – |
| Fahrmann et al. 2015 | GC | EI | – | TOF | – |
| Miyamoto et al. 2015 | GC | EI | – | TOF | MS/MS |
| Mazzone et al. 2016 | GC | EI | – | quadrupole | MS/MS |
| Fahrmann et al. 2015 | GC | EI | – | TOF | – |
| Fahrmann et al. 2015 | GC | EI | – | TOF | – |
| Moreno et al. 2018 | LC, GC | ESI, EI | positive, negative | LC: linear ion‐trap, GC: single‐quadrupole | LC: MS/MS |
| Moreno et al. 2018 | LC, GC | ESI, EI | positive, negative | LC: linear ion‐trap, GC: single‐quadrupole | LC: MS/MS |
| Wikoff et al. 2015b | GC | EI | – | TOF | – |
| Reference | Data processing software | Database search |
| Miyamoto et al. 2015 | ChromaTOF software (Leco) | UC Davis Metabolomics BinBase database |
| Fahrmann et al. 2015 | – | UC Davis Metabolomics BinBase database |
| Fahrmann et al. 2015 | – | UC Davis Metabolomics BinBase database |
| Miyamoto et al. 2015 | ChromaTOF software (Leco) | UC Davis Metabolomics BinBase database |
| Mazzone et al. 2016 | Metabolon LIMS system | Metabolon LIMS system |
| Fahrmann et al. 2015 | – | UC Davis Metabolomics BinBase database |
| Fahrmann et al. 2015 | – | UC Davis Metabolomics BinBase database |
| Moreno et al. 2018 | – | KEGG, HMDB |
| Moreno et al. 2018 | – | KEGG, HMDB |
| Wikoff et al. 2015b | BinBase | NIST11, BinBase |
| Reference | Difference method | Mean concentration (case) | Mean concentration (control) | Fold change (case/control) | P-value | FDR | VIP |
| Miyamoto et al. 2015 | Analysis of Covariance | 604 | 597.8 | 1.01037136165942 | 0.996675362077527 | – | – |
| Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | 86 ± 74 | 89 ± 51 | 0.97 | 0.398 | 0.674 | – |
| Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | 88 ± 25 | 106 ± 85 | 0.83 | 0.347 | 0.633 | – |
| Miyamoto et al. 2015 | Analysis of Covariance | 652 | 549.727272727273 | 1.18604266578469 | 0.32647877616044 | – | – |
| Mazzone et al. 2016 | two- sample independent t test | 1.090807± 0.7430408 | 1.020861± 0.3377913 | 1.06851667367056 | 0.2757499 | 0.38954355 | – |
| Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | 63 ± 54 | 67 ± 29 | 0.93 | 0.056 | 0.387 | – |
| Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | 122 ± 32 | 142 ± 39 | 0.862 | 0.039 | 0.227 | – |
| Moreno et al. 2018 | paired two‐sample t‐test, PLS-DA | – | – | 1.32180798420764 | 0.00269970003273267 | 0.0060160828140591 | – |
| Moreno et al. 2018 | paired two‐sample t‐test, PLS-DA | – | – | 1.3182411477119 | 0.0000995133036754031 | 0.000180892064539799 | – |
| Wikoff et al. 2015b | OPLS-DA | – | – | 1.2 | – | 0.047 | – |
| Reference | Classification method | Cutoff value | AUROC 95%CI | Sensitivity (%) | Specificity (%) | Accuracy (%) |
| Miyamoto et al. 2015 | – | – | – | – | – | – |
| Fahrmann et al. 2015 | random forest | – | – | – | – | – |
| Fahrmann et al. 2015 | random forest | – | – | – | – | – |
| Miyamoto et al. 2015 | – | – | – | – | – | – |
| Mazzone et al. 2016 | – | – | – | – | – | – |
| Fahrmann et al. 2015 | random forest | – | – | – | – | – |
| Fahrmann et al. 2015 | random forest | – | – | – | – | – |
| Moreno et al. 2018 | – | – | – | – | – | – |
| Moreno et al. 2018 | – | – | – | – | – | – |
| Wikoff et al. 2015b | – | – | – | – | – | – |