Metabolite information |
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HMDB ID | HMDB0002712 |
Synonyms |
1,5-AG1,5-Anhydroglucitol1,5-anhydro-D-Glucitol1,5-anhydro-D-Sorbitol1-DeoxyglucoseAdult-onset diabetesCsfCytoplasmaNiddmNon-insulin-dependent diabetes mellitusProstate gland |
Chemical formula | C6H12O5 |
IUPAC name | (2R,3S,4R,5S)-2-(hydroxymethyl)oxane-3,4,5-triol |
CAS registry number | 154-58-5 |
Monisotopic molecular weight | 164.068473494 |
Chemical taxonomy |
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Super class | Organic oxygen compounds |
Class | Organooxygen compounds |
Sub class | Carbohydrates and carbohydrate conjugates |
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 | ||||
Roś-Mazurczyk et al. 2017 | – | serum | diagnosis | adenocarcinoma, squamous cell carcinoma | I, II, III | 31 | 17, 14 | 52-72 | – | healthy | 92 | 52, 40 | 52-73 | – |
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 | 49 | 17, 32 | 65.9 ± 9.87 | – | healthy | 31 | 11, 20 | 64.1 ± 8.97 | – |
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 |
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 |
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 | – |
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 | – | 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 | 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 | – |
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 | – |
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 |
Roś-Mazurczyk et al. 2017 | GC | – | – | TOF | In-source fragmentation |
Fahrmann et al. 2015 | GC | EI | – | TOF | – |
Fahrmann et al. 2015 | GC | EI | – | TOF | – |
Miyamoto et al. 2015 | GC | EI | – | TOF | MS/MS |
Miyamoto et al. 2015 | GC | EI | – | TOF | MS/MS |
Moreno et al. 2018 | LC, GC | ESI, EI | positive, negative | LC: linear ion‐trap, GC: single‐quadrupole | LC: MS/MS |
Mazzone et al. 2016 | GC | EI | – | quadrupole | MS/MS |
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 |
Fahrmann et al. 2015 | GC | EI | – | TOF | – |
Wikoff et al. 2015b | GC | EI | – | TOF | – |
Reference | Data processing software | Database search |
Roś-Mazurczyk et al. 2017 | Leco ChromaTOF-GC | Replib, Mainlib and Fiehn libraries |
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 |
Miyamoto et al. 2015 | ChromaTOF software (Leco) | UC Davis Metabolomics BinBase database |
Moreno et al. 2018 | – | KEGG, HMDB |
Mazzone et al. 2016 | Metabolon LIMS system | Metabolon LIMS system |
Fahrmann et al. 2015 | – | UC Davis Metabolomics BinBase database |
Moreno et al. 2018 | – | KEGG, HMDB |
Fahrmann et al. 2015 | – | UC Davis Metabolomics BinBase database |
Wikoff et al. 2015b | BinBase | NIST11, BinBase |
Reference | Difference method | Mean concentration (case) | Mean concentration (control) | Fold change (case/control) | P-value | FDR | VIP |
Roś-Mazurczyk et al. 2017 | two-sample T test, U Mann-Whitney test, Benjamini-Hochberg approach | 11.743 ± 7.108 | 11.998 ± 8.638 | 0.978746457742957 | 0.79547 | 0.85012 | – |
Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | 10848 ± 5435 | 11979 ± 5203 | 0.91 | 0.64 | 0.874 | – |
Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | 11324 ± 4806 | 13410 ± 5674 | 0.84 | 0.635 | 0.819 | – |
Miyamoto et al. 2015 | Analysis of Covariance | 92187.8181818182 | 88164 | 1.04564014996845 | 0.531017589459075 | – | – |
Miyamoto et al. 2015 | Analysis of Covariance | 95587.3888888889 | 85305.45 | 1.12053085575293 | 0.437208228389904 | – | – |
Moreno et al. 2018 | paired two‐sample t‐test, PLS-DA | – | – | 0.937942913871908 | 0.150430427248231 | 0.205728839756926 | – |
Mazzone et al. 2016 | two- sample independent t test | 1.0200968± 0.3469864 | 0.9498011± 0.3815291 | 1.07401096924398 | 0.1331728 | 0.230609873 | – |
Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | 12259 ± 6475 | 15142 ± 7933 | 0.81 | 0.053 | 0.265 | – |
Moreno et al. 2018 | paired two‐sample t‐test, PLS-DA | – | – | 0.933325701515037 | 0.0389948811741565 | 0.0506806436107116 | – |
Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | 6630 ± 3591 | 8125 ± 3432 | 0.82 | 0.017 | 0.102 | – |
Wikoff et al. 2015b | OPLS-DA | – | – | 1.2 | – | 0.037 | – |
Reference | Classification method | Cutoff value | AUROC 95%CI | Sensitivity (%) | Specificity (%) | Accuracy (%) |
Roś-Mazurczyk et al. 2017 | ROC curve | – | – | – | – | – |
Fahrmann et al. 2015 | random forest | – | – | – | – | – |
Fahrmann et al. 2015 | random forest | – | – | – | – | – |
Miyamoto et al. 2015 | – | – | – | – | – | – |
Miyamoto et al. 2015 | – | – | – | – | – | – |
Moreno et al. 2018 | – | – | – | – | – | – |
Mazzone et al. 2016 | – | – | – | – | – | – |
Fahrmann et al. 2015 | random forest | – | – | – | – | – |
Moreno et al. 2018 | – | – | – | – | – | – |
Fahrmann et al. 2015 | random forest | – | – | – | – | – |
Wikoff et al. 2015b | – | – | – | – | – | – |