Metabolite information |
|
| HMDB ID | HMDB0000872 |
| Synonyms |
1,12-Dodecanedicarboxylate1,12-Dodecanedicarboxylic acid1,14-Tetradecanedioate1,14-Tetradecanedioic acidDodecamethylenedicarboxylateDodecamethylenedicarboxylic acidNSC 9504Tetradecane-1,14-dioateTetradecane-1,14-dioic acidTetradecanedicarboxylateTetradecanedicarboxylic acidTetradecanedioate |
| Chemical formula | C14H26O4 |
| IUPAC name | tetradecanedioic acid |
| CAS registry number | 821-38-5 |
| Monoisotopic molecular weight | 258.18310932 |
Chemical taxonomy |
|
| Super class | Lipids and lipid-like molecules |
| Class | Fatty Acyls |
| Sub class | Fatty acids and conjugates |
Biological properties |
|
| Pathways (Pathway Details in HMDB) |
|
| 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 | ||||
| Mazzone et al. 2016 | US | 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 | – |
| Chen et al. 2015b | China | serum | – | lung cancer (postoperative) | – | 30 | – | 61.58 ± 10.67 | – | healthy | 30 | – | 60.35 ± 12.48 | – |
| Xiang et al. 2018 | China | plasma | diagnosis | squamous cell carcinoma | I, II, III, IV | 22 | 16, 6 | 60.5 (42-73) | former, current, non-smoker | healthy | 56 | 35, 21 | 59 (42-79) | former, current, non-smoker |
| Xiang et al. 2018 | China | plasma | diagnosis | squamous cell carcinoma | I, II, III, IV | 25 | 21, 4 | 59.8 (43-83) | former, current, non-smoker | healthy | 56 | 35, 21 | 58 (47-80) | former, current, non-smoker |
| Xiang et al. 2018 | China | plasma | diagnosis | adenocarcinoma | I, II, III, IV | 24 | 10, 14 | 59 (43-71) | former, current, non-smoker | healthy | 56 | 35, 21 | 59 (42-79) | former, current, non-smoker |
| Xiang et al. 2018 | China | plasma | diagnosis | adenocarcinoma | I, II, III, IV | 28 | 16, 12 | 59 (44-80) | former, current, non-smoker | healthy | 56 | 35, 21 | 58 (47-80) | former, current, non-smoker |
| Reference | Chromatography | Ion source | Positive/Negative mode | Mass analyzer | Identification level |
| Mazzone et al. 2016 | LC | ESI | negative | linear ion-trap | MS/MS |
| Chen et al. 2015b | LC | ESI | positive | Q-TOF | – |
| Xiang et al. 2018 | LC | ESI | both | LTQ-FT | – |
| Xiang et al. 2018 | LC | ESI | both | LTQ-FT | – |
| Xiang et al. 2018 | LC | ESI | both | LTQ-FT | – |
| Xiang et al. 2018 | LC | ESI | both | LTQ-FT | – |
| Reference | Data processing software | Database search |
| Mazzone et al. 2016 | Metabolon LIMS system | Metabolon LIMS system |
| Chen et al. 2015b | Mass Hunter Qualitative Analysis Software (Agilent Technologies) | METLIN |
| Xiang et al. 2018 | Analyst software | – |
| Xiang et al. 2018 | Analyst software | – |
| Xiang et al. 2018 | Analyst software | – |
| Xiang et al. 2018 | Analyst software | – |
| Reference | Difference method | Mean concentration (case) | Mean concentration (control) | Fold change (case/control) | P-value | FDR | VIP |
| Mazzone et al. 2016 | two- sample independent t test | 1.393862± 1.137943 | 1.309041± 1.765999 | 1.06 | 0.67 | 0.68 | – |
| Chen et al. 2015b | PCA, PLS-DA, independent t test | – | – | 1.14 | 3.00e-03 | – | 1.05 |
| Xiang et al. 2018 | independent sample t-tests, OPLS-DA | – | – | 26.60 | 1.18e-18 | – | 1.56 |
| Xiang et al. 2018 | independent sample t-tests, OPLS-DA | – | – | 21.20 | 5.23e-18 | – | 1.16 |
| Xiang et al. 2018 | independent sample t-tests, OPLS-DA | – | – | 20.99 | 6.62e-17 | – | 1.80 |
| Xiang et al. 2018 | independent sample t-tests, OPLS-DA | – | – | 11.28 | 6.47e-16 | – | 1.34 |
| Reference | Classification method | Cutoff value | AUROC 95%CI | Sensitivity (%) | Specificity (%) | Accuracy (%) |
| Mazzone et al. 2016 | – | – | – | – | – | – |
| Chen et al. 2015b | – | – | – | – | – | – |
| Xiang et al. 2018 | – | – | – | – | – | – |
| Xiang et al. 2018 | – | – | – | – | – | – |
| Xiang et al. 2018 | – | – | – | – | – | – |
| Xiang et al. 2018 | – | – | – | – | – | – |