Metabolite information |
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| HMDB ID | HMDB0000510 |
| Synonyms |
(+/-)-2-aminoadipate(+/-)-2-aminoadipic acid2 Aminoadipic acid2 Aminohexanedioic acid2-Aminoadipate2-Aminoadipic acidAadAcid, 2 aminoadipicAcid, 2-aminoadipicAcid, 2-aminohexanedioicAcid, alpha-aminoadipicAminoadipateAminoadipic acid, 2DL-2-AminoadipateDL-2-Aminoadipic acidDL-2-AminohexanedioateDL-2-Aminohexanedioic acidDL-a-AminoadipateDL-a-Aminoadipic acidDL-alpha-AminoadipateDL-alpha-Aminoadipic acidDL-α-aminoadipateDL-α-aminoadipic acidL-2-AminoadipateL-2-Aminoadipic acidL-2-AminohexanedioateL-2-Aminohexanedioic acidL-alpha-AminoadipateL-alpha-Aminoadipic acida-Aminoadipatea-Aminoadipic acidalpha Aminoadipic acidalpha-Aminoadipatealpha-Aminoadipic acidalpha-amino-Adipic acidα-aminoadipateα-aminoadipic acid |
| Chemical formula | C6H11NO4 |
| IUPAC name | 2-aminohexanedioic acid |
| CAS registry number | 542-32-5 |
| Monoisotopic molecular weight | 161.068807845 |
Chemical taxonomy |
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| Super class | Organic acids and derivatives |
| Class | Carboxylic acids and derivatives |
| Sub class | Amino acids, peptides, and analogues |
Biological properties |
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| Pathways (Pathway Details in HMDB) |
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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 | US | 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 |
| Miyamoto et al. 2015 | US | 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 |
| Klupczynska et al. 2016a | Poland | serum | diagnosis | adenocarcinoma, squamous cell carcinoma | I, II, III | 90 | 58, 32 | 64 (48-86) | current, non-smoker, unknown | healthy | 63 | 41, 22 | 62 (43-78) | smoker, non-smoker, unknown |
| Fahrmann et al. 2015 | US | 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 | US | plasma | diagnosis | adenocarcinoma | I, II, III, IV | 52 | 17, 35 | 65.9 ± 9.66 | – | healthy | 31 | 11, 20 | 64.1 ± 8.97 | – |
| Hori et al. 2011 | Japan | tissue | diagnosis | adenocarcinoma, squamous cell carcinoma, SCLC | – | 7 | 6, 1 | median: 61 (53-82) | smoker, non-smoker | tumor vs. adjacent normal tissue | 7 | 6, 1 | median: 61 (53-82) | smoker, non-smoker |
| Wikoff et al. 2015b | US | 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 |
| Fahrmann et al. 2015 | US | serum | diagnosis | adenocarcinoma | I, II, III, IV | 43 | 21, 22 | 67.3 ± 10.10 | – | healthy | 43 | 21, 22 | 65.9 ± 8.05 | – |
| Fahrmann et al. 2015 | US | plasma | 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 | Spain | 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 | – |
| Moreno et al. 2018 | Spain | 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 | – |
| Reference | Chromatography | Ion source | Positive/Negative mode | Mass analyzer | Identification level |
| Miyamoto et al. 2015 | GC | EI | – | TOF | MS/MS |
| Miyamoto et al. 2015 | GC | EI | – | TOF | MS/MS |
| Klupczynska et al. 2016a | LC | – | – | QTRAP | MS/MS |
| Fahrmann et al. 2015 | GC | EI | – | TOF | – |
| Fahrmann et al. 2015 | GC | EI | – | TOF | – |
| Hori et al. 2011 | GC | – | – | – | – |
| Wikoff et al. 2015b | GC | EI | – | TOF | – |
| Fahrmann et al. 2015 | GC | EI | – | TOF | – |
| Fahrmann et al. 2015 | GC | EI | – | TOF | – |
| Moreno et al. 2018 | LC, GC | ESI, EI | both | LC: linear ion-trap, GC: single-quadrupole | LC: MS/MS |
| Moreno et al. 2018 | LC, GC | ESI, EI | both | LC: linear ion-trap, GC: single-quadrupole | LC: MS/MS |
| Reference | Data processing software | Database search |
| Miyamoto et al. 2015 | ChromaTOF software (Leco) | UC Davis Metabolomics BinBase database |
| Miyamoto et al. 2015 | ChromaTOF software (Leco) | UC Davis Metabolomics BinBase database |
| Klupczynska et al. 2016a | – | – |
| Fahrmann et al. 2015 | – | UC Davis Metabolomics BinBase database |
| Fahrmann et al. 2015 | – | UC Davis Metabolomics BinBase database |
| Hori et al. 2011 | Shimadzu GCMSsolution software | commercially available GC/MS Metabolite Mass Spectral Database (Shimadzu Co.), NIST Mass Spectral Library (NIST 08) |
| Wikoff et al. 2015b | BinBase | NIST11, BinBase |
| 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 |
| Reference | Difference method | Mean concentration (case) | Mean concentration (control) | Fold change (case/control) | P-value | FDR | VIP |
| Miyamoto et al. 2015 | Analysis of Covariance | 378.388888888889 | 429 | 0.88 | 0.08 | – | – |
| Miyamoto et al. 2015 | Analysis of Covariance | 407.090909090909 | 403 | 1.01 | 0.50 | – | – |
| Klupczynska et al. 2016a | t-test, Welch’s t-test or the Mann-Whitney U test, one-way ANOVA | 0.86±0.48 ?M | 0.88±0.33 ?M | 0.98 | 0.26 | – | – |
| Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | 92 ± 52 | 98 ± 50 | 0.94 | 0.76 | 0.90 | – |
| Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | 94 ± 40 | 83 ± 32 | 1.14 | 0.30 | 0.69 | – |
| Hori et al. 2011 | student’s t-test, PLS-DA | – | – | 2.36 | 1.00e-02 | – | – |
| Wikoff et al. 2015b | OPLS-DA | – | – | 1.10 | – | 0.77 | – |
| Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | – | – | – | – | – | – |
| Fahrmann et al. 2015 | regress (by the covariates: age, gender and smoking history [packs per year]), permutation test | – | – | – | – | – | – |
| Moreno et al. 2018 | paired two-sample t-test, PLS-DA | – | – | 1.99 | 9.92e-08 | 3.06e-07 | – |
| Moreno et al. 2018 | paired two-sample t-test, PLS-DA | – | – | 1.64 | 9.14e-04 | 2.35e-03 | – |
| Reference | Classification method | Cutoff value | AUROC 95%CI | Sensitivity (%) | Specificity (%) | Accuracy (%) |
| Miyamoto et al. 2015 | – | – | – | – | – | – |
| Miyamoto et al. 2015 | – | – | – | – | – | – |
| Klupczynska et al. 2016a | ROC curve analysis (Monte-Carlo cross validation), discriminant function analysis | – | 0.554 | – | – | – |
| Fahrmann et al. 2015 | random forest | – | – | – | – | – |
| Fahrmann et al. 2015 | random forest | – | – | – | – | – |
| Hori et al. 2011 | – | – | – | – | – | – |
| Wikoff et al. 2015b | – | – | – | – | – | – |
| Fahrmann et al. 2015 | random forest | – | – | – | – | – |
| Fahrmann et al. 2015 | random forest | – | – | – | – | – |
| Moreno et al. 2018 | – | – | – | – | – | – |
| Moreno et al. 2018 | – | – | – | – | – | – |