Metabolite page

Showing information for HMDB0000192 ('cystine')

Metabolite information
HMDB ID	HMDB0000192
Synonyms	2-amino-3-[2-amino-2-Carboxy-ethyl]disulfanyl-propanoate 2-amino-3-[2-amino-2-Carboxy-ethyl]disulfanyl-propanoic acid 2-amino-3-[[2-amino-2-Carboxyethyl]dithio]propanoate 2-amino-3-[[2-amino-2-Carboxyethyl]dithio]propanoic acid 3,3'-Dithiobis 3,3'-Dithiobis-L-alanine 3,3'-Dithiobis[2-amino-[R-[r,r]]-propanoate 3,3'-Dithiobis[2-amino-[R-[r,r]]-propanoic acid 3,3'-Dithiodialanine Acute seizures Acute tonic clonic seizure Bis[b-amino-b-carboxyethyl] disulfide Bis[b-amino-b-carboxyethyl] disulphide Bis[b-amino-beta-carboxyethyl] disulfide Bis[beta-amino-beta-carboxyethyl] disulfide Bis[beta-amino-beta-carboxyethyl] disulphide Bis[β-amino-β-carboxyethyl] disulfide Bis[β-amino-β-carboxyethyl] disulphide Coffee Coffee bean Copper cystinate Csf Cucurbits Cysteine disulfide Cystin Cystine Cystine acid Cytoplasma D[+]-3,3'-Dithiobis[2-aminopropanoate D[+]-3,3'-Dithiobis[2-aminopropanoic acid Dicysteine Digestion Extracellular region Faecal Faeces Fauna Fecal Flora Gelucystine Gourds Gramineae Gran mal seizure Grand mal seizure Janz syndrome Jme L Cystine L-Cysteine disulfide L-Cystin L-Dicysteine L-[-]-Cystine L-a-diamino-b-Dithiolactate L-a-diamino-b-Dithiolactic acid L-alpha-diamino-beta-Dithiolactate L-alpha-diamino-beta-Dithiolactic acid L-α-diamino-β-dithiolactate L-α-diamino-β-dithiolactic acid Legume Oxidized L-cysteine Papilionoideae Rle Soy Soya Soya bean Soybean Stool [-]-Cystine [R,R]-3,3'-Dithiobis[2-aminopropanoate] [R,R]-3,3'-Dithiobis[2-aminopropanoic acid] [R-[R,r]]-3,3'-dithiobis [R-[R,r]]-3,3'-dithiobis [R-[R,r]]-3,3'-dithiobis[2-aminopropanoate] [R-[R,r]]-3,3'-dithiobis[2-aminopropanoic acid] b,B'-diamino-b,b'-dicarboxydiethyl disulfide b,B'-dithiodialanine b,Beta'-diamino-b,beta'-dicarboxydiethyl disulfide b,Beta'-diamino-b,beta'-dicarboxydiethyl disulphide b,Beta'-dithiodialanine beta,Beta'-diamino-beta,beta'-dicarboxydiethyl disulfide beta,Beta'-diamino-beta,beta'-dicarboxydiethyl disulphide beta,Beta'-dithiobisalanine beta,Beta'-dithiodialanine e921 β,beta'-diamino-β,beta'-dicarboxydiethyl disulfide β,beta'-diamino-β,beta'-dicarboxydiethyl disulphide β,beta'-dithiodialanine
Chemical formula	C6H12N2O4S2
IUPAC name	(2R)-2-amino-3-{[(2R)-2-amino-2-carboxyethyl]disulfanyl}propanoic acid
CAS registry number	56-89-3
Monisotopic molecular weight	240.023848262
Chemical taxonomy
Super class	Organic acids and derivatives
Class	Carboxylic acids and derivatives
Sub class	Amino acids, peptides, and analogues
Biological properties
Pahtways
Author-emphasized biomarker in the paper(s)	Fahrmann et al. 2015

Lung cancer metabolomics studies that identify HMDB0000192 ('cystine')

Reference	Country	Specimen	Marker function	Participants (Case)						Participants (Control)
Reference	Country	Specimen	Marker function	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	–	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	–
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
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	–
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	–
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	–
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	–
Sun et al. 2019	–	serum	diagnosis	lung cancer	I, II, III, IV	31	21, 10	54.1 ± 9.9	smoker, non-smoker	healthy	29	15, 14	52.1 ± 14.6	smoker, non-smoker
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	–
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	52	17, 35	65.9 ± 9.66	–	healthy	31	11, 20	64.1 ± 8.97	–
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
Miyamoto et al. 2015	GC	EI	–	TOF	MS/MS
Mazzone et al. 2016	LC	ESI	positive	linear ion-trap	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
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	–
Mazzone et al. 2016	GC	EI	–	quadrupole	MS/MS
Sun et al. 2019	GC	–	–	–	–
Fahrmann et al. 2015	GC	EI	–	TOF	–
Fahrmann et al. 2015	GC	EI	–	TOF	–
Fahrmann et al. 2015	GC	EI	–	TOF	–
Wikoff et al. 2015b	GC	EI	–	TOF	–

Reference	Data processing software	Database search
Miyamoto et al. 2015	ChromaTOF software (Leco)	UC Davis Metabolomics BinBase database
Mazzone et al. 2016	Metabolon LIMS system	Metabolon LIMS system
Miyamoto et al. 2015	ChromaTOF software (Leco)	UC Davis Metabolomics BinBase database
Moreno et al. 2018	–	KEGG, HMDB
Moreno et al. 2018	–	KEGG, HMDB
Fahrmann et al. 2015	–	UC Davis Metabolomics BinBase database
Mazzone et al. 2016	Metabolon LIMS system	Metabolon LIMS system
Sun et al. 2019	–	BinBase, KEGG
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
Wikoff et al. 2015b	BinBase	NIST11, BinBase

Differential analysis
Classification analysis

Reference	Difference method	Mean concentration (case)	Mean concentration (control)	Fold change (case/control)	P-value	FDR	VIP
Miyamoto et al. 2015	Analysis of Covariance	24613	23835.05	1.03263890782692	0.95770813540115	–	–
Mazzone et al. 2016	two- sample independent t test	0.7780394± 0.4150007	0.7981379± 0.5462263	0.974818261355588	0.7530882	0.728411991	–
Miyamoto et al. 2015	Analysis of Covariance	24883.3636363636	23523.7272727273	1.05779850904889	0.593087487212968	–	–
Moreno et al. 2018	paired two‐sample t‐test, PLS-DA	–	–	0.859552742375417	0.509856380329975	0.546862085353924	–
Moreno et al. 2018	paired two‐sample t‐test, PLS-DA	–	–	1.17308572397089	0.329088855036987	0.392581541742493	–
Fahrmann et al. 2015	regress (by the covariates: age, gender and smoking history [packs per year]), permutation test	3886 ± 1676	4929 ± 1579	0.79	0.052	0.201	–
Mazzone et al. 2016	two- sample independent t test	0.911183± 0.3725111	1.050226± 0.4464398	0.867606591343197	0.009638	0.033570032	–
Sun et al. 2019	Student t test, PLS-DA	–	–	0.717290784120464	0.004624	0.033975	1.047
Fahrmann et al. 2015	regress (by the covariates: age, gender and smoking history [packs per year]), permutation test	6358 ± 2545	8312 ± 2735	0.77	0.001	0.091	–
Fahrmann et al. 2015	regress (by the covariates: age, gender and smoking history [packs per year]), permutation test	8704 ± 2504	10376 ± 2341	0.839	0.001	0.016	–
Fahrmann et al. 2015	regress (by the covariates: age, gender and smoking history [packs per year]), permutation test	3044 ± 2748	5050 ± 2468	0.6	0	0.002	–
Wikoff et al. 2015b	OPLS-DA	–	–	1.3	–	0.178	–

Reference	Classification method	Cutoff value	AUROC 95%CI	Sensitivity (%)	Specificity (%)	Accuracy (%)
Miyamoto et al. 2015	–	–	–	–	–	–
Mazzone et al. 2016	–	–	–	–	–	–
Miyamoto et al. 2015	–	–	–	–	–	–
Moreno et al. 2018	–	–	–	–	–	–
Moreno et al. 2018	–	–	–	–	–	–
Fahrmann et al. 2015	random forest	–	maltose+maltotriose+cystine+3-Phosphoglycerate+citrulline=0.699 (0.583, 0.815) maltose+maltotriose+cystine+3-Phosphoglycerate+citrulline+pyrophosphate+tryptophan+adenosine-5-Phosphate=0.670 (0.552, 0.789)	58.1 maltose+maltotriose+cystine=69.8	79.1 maltose+maltotriose+cystine=69.8	68.6 maltose+maltotriose+cystine=69.8
Mazzone et al. 2016	–	–	–	–	–	–
Sun et al. 2019	ROC curve analysis	–	–	–	–	–
Fahrmann et al. 2015	random forest	–	–	–	–	–
Fahrmann et al. 2015	random forest	–	–	–	–	–
Fahrmann et al. 2015	random forest	–	maltose+maltotriose+cystine+3-Phosphoglycerate+citrulline=0.880 (0.805, 0.954) maltose+maltotriose+cystine+3-Phosphoglycerate+citrulline+pyrophosphate+tryptophan+adenosine-5-Phosphate=0.883 (0.812, 0.955)	–	–	66.3 maltose+maltotriose+cystine=75.9
Wikoff et al. 2015b	–	–	–	–	–	–