Showing information for HMDB0002259 ('margaric acid', 'heptadecanoic acid', 'margarate', 'margarate (17:0)')

Metabolite information
HMDB ID HMDB0002259
Synonyms
17:0
Adipose
Body fat
C17:0
CH3-[CH2]15-COOH
Cellular membrane
Coffee
Coffee bean
Cucurbits
Cytoplasma
Digestion
Extracellular region
Faecal
Faeces
Fat tissue
Fauna
Fecal
Flora
Gourds
Gramineae
Heptadecanoate
Heptadecoate
Heptadecoic acid
Heptadecylate
Heptadecylic acid
Legume
Lipid body
Lipid droplet
Lipid metabolic process
Lipid particle
Margarate
Margaric acid
Margaric acid, 1-[11]C-labeled
Margaric acid, nickel [2+] salt
Margaric acid, potassium salt
Margaric acid, sodium salt
Margarinate
Margarinic acid
Margarinsaeure
Margaroate
Margaroic acid
Membrane integrity agent
Membrane stability agent
N-Heptadecanoate
N-Heptadecanoic acid
N-Heptadecoate
N-Heptadecoic acid
N-Heptadecylate
N-Heptadecylic acid
Normal-heptadecanoate
Normal-heptadecanoic acid
Omega I-123 heptadecanoic acid
Papilionoideae
Prostate gland
Signal transduction
Stool
Striated muscle
Surface-active agent
Chemical formula C17H34O2
IUPAC name
heptadecanoic acid
CAS registry number 506-12-7
Monisotopic molecular weight 270.255880332

Chemical taxonomy
Super class Lipids and lipid-like molecules
Class Fatty Acyls
Sub class Fatty acids and conjugates

Biological properties
Pahtways
Author-emphasized biomarker in the paper(s)

Lung cancer metabolomics studies that identify HMDB0002259 ('margaric acid', 'heptadecanoic acid', 'margarate', 'margarate (17:0)')

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
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
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
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 – 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
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 – 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 – plasma diagnosis adenocarcinoma I, II, III, IV 43 21, 22 67.3 ± 10.10 – healthy 43 21, 22 65.9 ± 8.05 –
Callejon-Leblic et al. 2019 – serum diagnosis NSCLC, SCLC – 32 22, 8 66 ± 12 former, current, non-smoker healthy 29 18, 11 56 ± 13 former, non-smoker
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 –
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 –
Reference Chromatography Ion source Positive/Negative mode Mass analyzer Identification level
Hori et al. 2011 GC – – – –
Fahrmann et al. 2015 GC EI – TOF –
Hori et al. 2011 GC – – – –
Roś-Mazurczyk et al. 2017 GC – – TOF In-source fragmentation
Fahrmann et al. 2015 GC EI – TOF –
Hori et al. 2011 GC – – – –
Hori et al. 2011 GC – – – –
Fahrmann et al. 2015 GC EI – TOF –
Fahrmann et al. 2015 GC EI – TOF –
Callejon-Leblic et al. 2019 GC EI – ion trap –
Moreno et al. 2018 LC, GC ESI, EI positive, negative LC: linear ion‐trap, GC: single‐quadrupole LC: MS/MS
Mazzone et al. 2016 LC ESI negative linear ion-trap MS/MS
Moreno et al. 2018 LC, GC ESI, EI positive, negative LC: linear ion‐trap, GC: single‐quadrupole LC: MS/MS
Reference Data processing software Database search
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)
Roś-Mazurczyk et al. 2017 Leco ChromaTOF-GC Replib, Mainlib and Fiehn libraries
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)
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
Fahrmann et al. 2015 – UC Davis Metabolomics BinBase database
Callejon-Leblic et al. 2019 XCMS NIST Mass Spectral Library
Moreno et al. 2018 – KEGG, HMDB
Mazzone et al. 2016 Metabolon LIMS system Metabolon LIMS system
Moreno et al. 2018 – KEGG, HMDB
Reference Difference method Mean concentration (case) Mean concentration (control) Fold change (case/control) P-value FDR VIP
Hori et al. 2011 student’s t-test, PLS-DA – – 0.99 0.923 – –
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 477 ± 287 527 ± 368 0.91 0.497 0.788 –
Hori et al. 2011 student’s t-test, PLS-DA – – 0.97 0.494 – –
Roś-Mazurczyk et al. 2017 two-sample T test, U Mann-Whitney test, Benjamini-Hochberg approach 1.2438 ± 0.6796 1.2944 ± 0.57039 0.960908529048208 0.44367 0.69016 –
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 420 ± 266 501 ± 372 0.84 0.374 0.671 –
Hori et al. 2011 student’s t-test, PLS-DA – – 0.95 0.373 – –
Hori et al. 2011 student’s t-test, PLS-DA – – 0.22 0.345 – –
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 429 ± 165 501 ± 217 0.856 0.057 0.265 –
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 327 ± 99 399 ± 252 0.82 0.035 0.15 –
Callejon-Leblic et al. 2019 PLS-LDA, one-way ANOVA – – 0.42 0.012 – 2.24
Moreno et al. 2018 paired two‐sample t‐test, PLS-DA – – 1.36760943062056 0.000337677144483211 0.000950258118129036 –
Mazzone et al. 2016 two- sample independent t test 1.2574511± 0.5272238 0.9636958± 0.5179013 1.30482160449387 0.000011 0.015006832 –
Moreno et al. 2018 paired two‐sample t‐test, PLS-DA – – 1.30162644311311 0.00000175476557614322 0.0000042822719564596 –
Reference Classification method Cutoff value AUROC 95%CI Sensitivity (%) Specificity (%) Accuracy (%)
Hori et al. 2011 – – – – – –
Fahrmann et al. 2015 random forest – – – – –
Hori et al. 2011 – – – – – –
Roś-Mazurczyk et al. 2017 ROC curve – – – – –
Fahrmann et al. 2015 random forest – – – – –
Hori et al. 2011 – – – – – –
Hori et al. 2011 – – – – – –
Fahrmann et al. 2015 random forest – – – – –
Fahrmann et al. 2015 random forest – – – – –
Callejon-Leblic et al. 2019 ROC curve analysis – 0.78 – – –
Moreno et al. 2018 – – – – – –
Mazzone et al. 2016 – – – – – –
Moreno et al. 2018 – – – – – –