Showing information for HMDB0000267 ('pyroglutamic acid', '5-oxoproline', '5-oxo-l-proline', 'oxoproline', 'pyroglutamate', 'L-pyroglutamic acid')

Metabolite information
HMDB ID HMDB0000267
Synonyms
2-L-Pyrrolidone-5-carboxylate
2-L-Pyrrolidone-5-carboxylic acid
2-Oxopyrrolidine-5[S]-carboxylate
2-Oxopyrrolidine-5[S]-carboxylic acid
2-Pyrrolidinone-5-carboxylate
2-Pyrrolidinone-5-carboxylic acid
5-Carboxy-2-pyrrolidinone
5-Ketoproline
5-L-Oxoproline
5-Oxoproline
5-Oxopyrrolidine-2-carboxylic acid
5-Pyrrolidinone-2-carboxylate
5-Pyrrolidinone-2-carboxylic acid
5-Pyrrolidone-2-carboxylate
5-Pyrrolidone-2-carboxylic acid
5-oxo-L-Proline
Ajidew a 100
Csf
Cucurbits
Cytoplasma
Digestion
Faecal
Faeces
Fauna
Fecal
Flora
Glutimate
Glutimic acid
Glutiminate
Glutiminic acid
Gourds
Gramineae
L-2-Pyrrolidone-5-carboxylate
L-2-Pyrrolidone-5-carboxylic acid
L-5-Carboxy-2-pyrrolidinone
L-5-Oxoproline
L-5-Pyrrolidone-2-carboxylate
L-5-Pyrrolidone-2-carboxylic acid
L-5-oxo-2-Pyrrolidinecarboxylate
L-5-oxo-2-Pyrrolidinecarboxylic acid
L-Glutamic acid g-lactam
L-Glutimate
L-Glutimic acid
L-Glutiminate
L-Glutiminic acid
L-Pyroglutamate
L-Pyroglutamic acid
L-Pyrrolidinonecarboxylate
L-Pyrrolidinonecarboxylic acid
L-Pyrrolidonecarboxylate
L-Pyrrolidonecarboxylic acid
Legume
Magnesium pidolate
Oxoproline
Oxopyrrolidinecarboxylate
Oxopyrrolidinecarboxylic acid
Papilionoideae
Pidolate
Pidolate, magnesium
Pidolic acid
Pidolidone
Prostate gland
Pyroglutamate
Pyrrolidinonecarboxylate
Pyrrolidinonecarboxylic acid
Pyrrolidone-5-carboxylate
Pyrrolidone-5-carboxylic acid
Pyrrolidonecarboxylic acid
Soy
Soya
Soya bean
Soybean
Stool
[-]-2-Pyrrolidone-5-carboxylate
[-]-2-Pyrrolidone-5-carboxylic acid
[-]-Pyroglutamate
[-]-Pyroglutamic acid
[5S]-2-Oxopyrrolidine-5-carboxylate
[5S]-2-Oxopyrrolidine-5-carboxylic acid
[S]-2-Pyrrolidone-5-carboxylate
[S]-2-Pyrrolidone-5-carboxylic acid
[S]-5-oxo-2-Pyrrolidinecarboxylate
[S]-5-oxo-2-Pyrrolidinecarboxylic acid
[S]-Pyroglutamate
[S]-Pyroglutamic acid
[S]-[-]-2-Pyrrolidone-5-carboxylate
[S]-[-]-2-Pyrrolidone-5-carboxylic acid
[S]-[-]-g-Butyrolactam-g-carboxylate
[S]-[-]-g-Butyrolactam-g-carboxylic acid
[S]-[-]-gamma-Butyrolactam-gamma-carboxylate
[S]-[-]-gamma-Butyrolactam-gamma-carboxylic acid
Chemical formula C5H7NO3
IUPAC name
(2S)-5-oxopyrrolidine-2-carboxylic acid
CAS registry number 98-79-3
Monisotopic molecular weight 129.042593095

Chemical taxonomy
Super class Organic acids and derivatives
Class Carboxylic acids and derivatives
Sub class Amino acids, peptides, and analogues

Biological properties
Pahtways
5-Oxoprolinuria
5-oxoprolinase deficiency
Gamma-Glutamyltransferase Deficiency
Gamma-glutamyl-transpeptidase deficiency
Glutathione Metabolism
Glutathione Synthetase Deficiency
Author-emphasized biomarker in the paper(s)

Lung cancer metabolomics studies that identify HMDB0000267 ('pyroglutamic acid', '5-oxoproline', '5-oxo-l-proline', 'oxoproline', 'pyroglutamate', 'L-pyroglutamic acid')

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
Mu et al. 2019 – serum diagnosis NSCLC I, II, III, IV 30 0, 30 60.4 ± 9.7 non-smoker healthy 30 0, 30 54.7 ± 14.3 non-smoker
Chen et al. 2015 – serum – lung cancer – 30 – 61.58 ± 10.67 – healthy 30 – 60.35 ± 12.48 –
Chen et al. 2015 – serum – lung cancer – 30 – 61.58 ± 10.67 – before vs. after treatment (operation) 30 – 61.58 ± 10.67 –
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 –
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
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 43 21, 22 67.3 ± 10.10 – healthy 43 21, 22 65.9 ± 8.05 –
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 –
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 –
Hori et al. 2011 – serum diagnosis adenocarcinoma, squamous cell carcinoma, SCLC I, II 11 – – – healthy 29 23, 6 median: 64 (34-78) smoker, non-smoker, unknown
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 –
Callejon-Leblic et al. 2016 – bronchoalveolar lavage fluid diagnosis lung cancer – 24 16, 8 66 ± 11 – noncancerous lung diseases 31 23, 8 56 ± 13 –
Chen et al. 2015 – serum – lung cancer (postoperative) – 30 – 61.58 ± 10.67 – healthy 30 – 60.35 ± 12.48 –
Hori et al. 2011 – serum diagnosis adenocarcinoma, squamous cell carcinoma, SCLC III, IV 22 – – – healthy 29 23, 6 median: 64 (34-78) smoker, non-smoker, unknown
Hori et al. 2011 – 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
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 –
Hori et al. 2011 – serum diagnosis adenocarcinoma, squamous cell carcinoma, SCLC I, II, III, IV 33 26, 7 median: 65 (55-81) smoker, non-smoker, unknown healthy 29 23, 6 median: 64 (34-78) smoker, non-smoker, unknown
Klupczynska et al. 2017 – serum diagnosis adenocarcinoma, squamous cell carcinoma I, II 50 28, 22 65 (53-86) – healthy 25 14, 11 64 (50-78) –
Huang et al. 2019 – plasma diagnosis lung cancer – 31 19, 12 28-64 – healthy 35 24, 11 23-60 –
Klupczynska et al. 2017 – serum diagnosis adenocarcinoma, squamous cell carcinoma I, II 50 28, 22 65 (53-86) – healthy 25 14, 11 64 (50-78) –
Huang et al. 2019 – plasma diagnosis lung cancer – 31 19, 12 28-64 – healthy 35 24, 11 23-60 –
Klupczynska et al. 2016b – serum diagnosis adenocarcinoma, squamous cell carcinoma I, II, III 90 58, 32 64 ± 6.9 smoker, non-smoker, unknown healthy 62 40, 22 62 ± 8.8 smoker, non-smoker, unknown
Yue et al. 2018 – plasma diagnosis SCLC – 20 – – – healthy 20 – – –
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
Mu et al. 2019 GC – – – –
Chen et al. 2015 GC EI – quadrupole –
Chen et al. 2015 GC EI – quadrupole –
Moreno et al. 2018 LC, GC ESI, EI positive, negative LC: linear ion‐trap, GC: single‐quadrupole LC: MS/MS
Miyamoto et al. 2015 GC EI – TOF MS/MS
Miyamoto et al. 2015 GC EI – TOF MS/MS
Mazzone et al. 2016 LC ESI negative linear ion-trap MS/MS
Fahrmann et al. 2015 GC EI – TOF –
Fahrmann et al. 2015 GC EI – TOF –
Fahrmann et al. 2015 GC EI – TOF –
Hori et al. 2011 GC – – – –
Moreno et al. 2018 LC, GC ESI, EI positive, negative LC: linear ion‐trap, GC: single‐quadrupole LC: MS/MS
Callejon-Leblic et al. 2016 DI ESI positive Q-TOF MS/MS
Chen et al. 2015 GC EI – quadrupole –
Hori et al. 2011 GC – – – –
Hori et al. 2011 GC – – – –
Fahrmann et al. 2015 GC EI – TOF –
Hori et al. 2011 GC – – – –
Klupczynska et al. 2017 LC ESI positive Quadrupole- Orbitrap MS/MS
Huang et al. 2019 LC ESI negative Q-Orbitrap MS/MS
Klupczynska et al. 2017 LC ESI positive Quadrupole- Orbitrap MS/MS
Huang et al. 2019 LC ESI positive Q-Orbitrap MS/MS
Klupczynska et al. 2016b LC ESI negative triple quadrupole MS/MS
Yue et al. 2018 LC ESI positive, negative QTRAP MS/MS
Wikoff et al. 2015b GC EI – TOF –
Reference Data processing software Database search
Mu et al. 2019 – –
Chen et al. 2015 ChemStation NIST
Chen et al. 2015 ChemStation NIST
Moreno et al. 2018 – KEGG, HMDB
Miyamoto et al. 2015 ChromaTOF software (Leco) 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
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)
Moreno et al. 2018 – KEGG, HMDB
Callejon-Leblic et al. 2016 Markerview HMDB, METLIN
Chen et al. 2015 ChemStation NIST
Hori et al. 2011 Shimadzu GCMSsolution software commercially available GC/MS Metabolite Mass Spectral Database (Shimadzu Co.), NIST Mass Spectral Library (NIST 08)
Hori et al. 2011 Shimadzu GCMSsolution software commercially available GC/MS Metabolite Mass Spectral Database (Shimadzu Co.), NIST Mass Spectral Library (NIST 08)
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)
Klupczynska et al. 2017 MZmine 2.19 software In-house library, HMDB
Huang et al. 2019 XCMS OSI-SMMS
Klupczynska et al. 2017 MZmine 2.19 software In-house library
Huang et al. 2019 XCMS OSI-SMMS
Klupczynska et al. 2016b Analyst software –
Yue et al. 2018 Analyst, MultiQuant –
Wikoff et al. 2015b BinBase NIST11, BinBase
Reference Difference method Mean concentration (case) Mean concentration (control) Fold change (case/control) P-value FDR VIP
Mu et al. 2019 PCA, PLS-DA, Mann-Whitney U test – – 0.77 < 0.001 < 0.001 1.467
Chen et al. 2015 PCA, PLS-DA, independent t test – – 0.823591017267573 <0.001 – 1.09
Chen et al. 2015 PCA, PLS-DA, independent t test – – 0.550952557938305 <0.001 – 1.35
Moreno et al. 2018 paired two‐sample t‐test, PLS-DA – – 1.00088539410156 0.987970498973134 0.990226139381748 –
Miyamoto et al. 2015 Analysis of Covariance 195323.272727273 203595.090909091 0.959371229704592 0.904847548842238 – –
Miyamoto et al. 2015 Analysis of Covariance 201697.888888889 197444.35 1.02154297597723 0.611078459281691 – –
Mazzone et al. 2016 two- sample independent t test 1.003324± 0.2046687 1.020258± 0.1668089 0.983402237473267 0.4566752 0.541767609 –
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 44799 ± 14621 46504 ± 12210 0.96 0.425 0.672 –
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 80594 ± 21724 83104 ± 16481 0.97 0.386 0.694 –
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 60393 ± 13891 56530 ± 11065 1.07 0.2 0.543 –
Hori et al. 2011 student’s t-test, PLS-DA – – 0.89 0.114 – –
Moreno et al. 2018 paired two‐sample t‐test, PLS-DA – – 1.16826516426701 0.064261399583493 0.0805032917859143 –
Callejon-Leblic et al. 2016 PLS-LDA, one-way ANOVA – – 0.83 0.042 – 1.01
Chen et al. 2015 PCA, PLS-DA, independent t test – – 0.823591017267573 0.02 – 1
Hori et al. 2011 student’s t-test, PLS-DA – – 0.83 0.0062 – –
Hori et al. 2011 student’s t-test, PLS-DA – – 2.06 0.005 – –
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 45736 ± 9536 39616 ± 8849 1.15 0.005 0.093 –
Hori et al. 2011 student’s t-test, PLS-DA – – 0.85 0.0019 – –
Klupczynska et al. 2017 t-test – – 0.78 0.00126 0.01002 –
Huang et al. 2019 OPLS-DA, Mann-Whitney U test – – 0.694724052 0.000946801 – 1.722675621
Klupczynska et al. 2017 t-test – – 0.79 0.00035 0.00454 –
Huang et al. 2019 OPLS-DA, Mann-Whitney U test – – 0.515379615 0.00000079959 – 2.070554307
Klupczynska et al. 2016b Mann-Whitney U test 26.99 ± 11.56 μmol/l 35.28 ± 10.22 μmol/l 0.765022675736961 0.0000000264363 – –
Yue et al. 2018 OPLS-DA, student’s t-test 2.91±0.84 ng/mL 1.71±0.92 ng/mL 6.36429187003935 0.00000000123 – 1.98
Wikoff et al. 2015b OPLS-DA – – 1.1 – 0.094 –
Reference Classification method Cutoff value AUROC 95%CI Sensitivity (%) Specificity (%) Accuracy (%)
Mu et al. 2019 – – – – – –
Chen et al. 2015 – – – – – –
Chen et al. 2015 – – – – – –
Moreno et al. 2018 – – – – – –
Miyamoto et al. 2015 – – – – – –
Miyamoto et al. 2015 – – – – – –
Mazzone et al. 2016 – – – – – –
Fahrmann et al. 2015 random forest – – – – –
Fahrmann et al. 2015 random forest – – – – –
Fahrmann et al. 2015 random forest – – – – –
Hori et al. 2011 – – – – – –
Moreno et al. 2018 – – – – – –
Callejon-Leblic et al. 2016 ROC curve analysis – 0.57 – – –
Chen et al. 2015 – – – – – –
Hori et al. 2011 – – – – – –
Hori et al. 2011 – – – – – –
Fahrmann et al. 2015 random forest – – – – –
Hori et al. 2011 – – – – – –
Klupczynska et al. 2017 ROC curve analysis (Monte-Carlo cross validation) – – – – –
Huang et al. 2019 – – – – – –
Klupczynska et al. 2017 ROC curve analysis (Monte-Carlo cross validation) – 0.705 (0.560–0.813) 0.63 0.72 –
Huang et al. 2019 – – – – – –
Klupczynska et al. 2016b ROC curve analysis stage I vs. control: 29.6; stage II vs. control: 29.6; stage III vs. control: 28 0.766; stage I vs. control: 0.752; stage II vs. control: 0.748; stage III vs. control: 0.799 stage I vs. control: 0.8; stage II vs. control: 0.8; stage III vs. control: 0.8 stage I vs. control: 0.7; stage II vs. control: 0.7; stage III vs. control: 0.7 –
Yue et al. 2018 – – – – – –
Wikoff et al. 2015b – – – – – –