#METABOLOMICS WORKBENCH Linyan_20231218_233331 DATATRACK_ID:4537 STUDY_ID:ST003025 ANALYSIS_ID:AN004960 PROJECT_ID:PR001876
VERSION             	1
CREATED_ON             	December 22, 2023, 12:01 am
#PROJECT
PR:PROJECT_TITLE                 	NMR- and MS-based omics reveal characteristic metabolome atlas and optimize
PR:PROJECT_TITLE                 	biofluid earlydiagnostic biomarkers for esophageal squamous cell carcinoma
PR:PROJECT_SUMMARY               	Metabolic changes precede malignant histology. However, it remains unclear
PR:PROJECT_SUMMARY               	whether detectable characteristic metabolome exists in esophageal squamous cell
PR:PROJECT_SUMMARY               	carcinoma (ESCC) tissues and biofluids for early diagnosis. We conducted NMR-
PR:PROJECT_SUMMARY               	and MS-based metabolomics on 1,153 matched ESCC tissues, normal mucosae, pre-
PR:PROJECT_SUMMARY               	and one-week post-operative sera and urines from 560 participants across three
PR:PROJECT_SUMMARY               	hospitals, with machine learning, logistic regression and WGCNA. Aberrations in
PR:PROJECT_SUMMARY               	'alanine, aspartate and glutamate metabolism' proved to be prevalent throughout
PR:PROJECT_SUMMARY               	the ESCC evolution, and were reflected in 16 serum and 10 urine metabolic
PR:PROJECT_SUMMARY               	signatures that were consistently identified by NMR and MS in both discovery and
PR:PROJECT_SUMMARY               	validation sets. NMR-based simplified panels of any five serum or urine
PR:PROJECT_SUMMARY               	metabolites outperformed clinical serological tumor markers (AUC = 0.984 and
PR:PROJECT_SUMMARY               	0.930, respectively), and were effective in distinguishing early-stage ESCC in
PR:PROJECT_SUMMARY               	test set (serum accuracy = 0.994, urine accuracy = 0.879). Collectively,
PR:PROJECT_SUMMARY               	NMR-based biofluid screening can reveal characteristic metabolic events of ESCC
PR:PROJECT_SUMMARY               	and be feasible for early detection (ChiCTR2300073613).
PR:INSTITUTE                     	Radiology Department, Second Affiliated Hospital, Shantou University Medical
PR:INSTITUTE                     	College, Shantou
PR:LAST_NAME                     	Lin
PR:FIRST_NAME                    	Yan
PR:ADDRESS                       	No. 69, Dongxia North Road, Shantou, Guangdong, China
PR:EMAIL                         	994809889@qq.com
PR:PHONE                         	+86 18823992148
#STUDY
ST:STUDY_TITLE                   	NMR- and MS-based omics reveal characteristic metabolome atlas and optimize
ST:STUDY_TITLE                   	biofluid earlydiagnostic biomarkers for esophageal squamous cell carcinoma
ST:STUDY_TITLE                   	(part-Ⅴ)
ST:STUDY_SUMMARY                 	Metabolic changes precede malignant histology. However, it remains unclear
ST:STUDY_SUMMARY                 	whether detectable characteristic metabolome exists in esophageal squamous cell
ST:STUDY_SUMMARY                 	carcinoma (ESCC) tissues and biofluids for early diagnosis. We conducted NMR-
ST:STUDY_SUMMARY                 	and MS-based metabolomics on 1,153 matched ESCC tissues, normal mucosae, pre-
ST:STUDY_SUMMARY                 	and one-week post-operative sera and urines from 560 participants across three
ST:STUDY_SUMMARY                 	hospitals, with machine learning, logistic regression and WGCNA. Aberrations in
ST:STUDY_SUMMARY                 	'alanine, aspartate and glutamate metabolism' proved to be prevalent throughout
ST:STUDY_SUMMARY                 	the ESCC evolution, and were reflected in 16 serum and 10 urine metabolic
ST:STUDY_SUMMARY                 	signatures that were consistently identified by NMR and MS in both discovery and
ST:STUDY_SUMMARY                 	validation sets. NMR-based simplified panels of any five serum or urine
ST:STUDY_SUMMARY                 	metabolites outperformed clinical serological tumor markers (AUC = 0.984 and
ST:STUDY_SUMMARY                 	0.930, respectively), and were effective in distinguishing early-stage ESCC in
ST:STUDY_SUMMARY                 	test set (serum accuracy = 0.994, urine accuracy = 0.879). Collectively,
ST:STUDY_SUMMARY                 	NMR-based biofluid screening can reveal characteristic metabolic events of ESCC
ST:STUDY_SUMMARY                 	and be feasible for early detection (ChiCTR2300073613).
ST:INSTITUTE                     	Radiology Department, Second Affiliated Hospital, Shantou University Medical
ST:INSTITUTE                     	College, Shantou
ST:LAST_NAME                     	Lin
ST:FIRST_NAME                    	Yan
ST:ADDRESS                       	No. 69, Dongxia North Road, Shantou, Guangdong, China
ST:EMAIL                         	994809889@qq.com
ST:PHONE                         	+86 18823992148
#SUBJECT
SU:SUBJECT_TYPE                  	Human
SU:SUBJECT_SPECIES               	Homo sapiens
SU:TAXONOMY_ID                   	9606
#SUBJECT_SAMPLE_FACTORS:         	SUBJECT(optional)[tab]SAMPLE[tab]FACTORS(NAME:VALUE pairs separated by |)[tab]Raw file names and additional sample data
SUBJECT_SAMPLE_FACTORS           	-	1	Fator:Early stage ESCC	RAW_FILE_NAME=1.CDF
SUBJECT_SAMPLE_FACTORS           	-	2	Fator:Early stage ESCC	RAW_FILE_NAME=2.CDF
SUBJECT_SAMPLE_FACTORS           	-	3	Fator:Early stage ESCC	RAW_FILE_NAME=3.CDF
SUBJECT_SAMPLE_FACTORS           	-	4	Fator:Early stage ESCC	RAW_FILE_NAME=4.CDF
SUBJECT_SAMPLE_FACTORS           	-	5	Fator:Early stage ESCC	RAW_FILE_NAME=5.CDF
SUBJECT_SAMPLE_FACTORS           	-	6	Fator:Early stage ESCC	RAW_FILE_NAME=6.CDF
SUBJECT_SAMPLE_FACTORS           	-	7	Fator:Early stage ESCC	RAW_FILE_NAME=7.CDF
SUBJECT_SAMPLE_FACTORS           	-	8	Fator:Early stage ESCC	RAW_FILE_NAME=8.CDF
SUBJECT_SAMPLE_FACTORS           	-	9	Fator:Early stage ESCC	RAW_FILE_NAME=9.CDF
SUBJECT_SAMPLE_FACTORS           	-	10	Fator:Early stage ESCC	RAW_FILE_NAME=10.CDF
SUBJECT_SAMPLE_FACTORS           	-	11	Fator:Early stage ESCC	RAW_FILE_NAME=11.CDF
SUBJECT_SAMPLE_FACTORS           	-	12	Fator:Early stage ESCC	RAW_FILE_NAME=12.CDF
SUBJECT_SAMPLE_FACTORS           	-	13	Fator:Early stage ESCC	RAW_FILE_NAME=13.CDF
SUBJECT_SAMPLE_FACTORS           	-	14	Fator:Early stage ESCC	RAW_FILE_NAME=14.CDF
SUBJECT_SAMPLE_FACTORS           	-	15	Fator:Early stage ESCC	RAW_FILE_NAME=15.CDF
SUBJECT_SAMPLE_FACTORS           	-	16	Fator:Early stage ESCC	RAW_FILE_NAME=16.CDF
SUBJECT_SAMPLE_FACTORS           	-	17	Fator:Normal tissue	RAW_FILE_NAME=17.CDF
SUBJECT_SAMPLE_FACTORS           	-	18	Fator:Normal tissue	RAW_FILE_NAME=18.CDF
SUBJECT_SAMPLE_FACTORS           	-	19	Fator:Normal tissue	RAW_FILE_NAME=19.CDF
SUBJECT_SAMPLE_FACTORS           	-	20	Fator:Normal tissue	RAW_FILE_NAME=20.CDF
SUBJECT_SAMPLE_FACTORS           	-	21	Fator:Normal tissue	RAW_FILE_NAME=21.CDF
SUBJECT_SAMPLE_FACTORS           	-	22	Fator:Normal tissue	RAW_FILE_NAME=22.CDF
SUBJECT_SAMPLE_FACTORS           	-	23	Fator:Normal tissue	RAW_FILE_NAME=23.CDF
SUBJECT_SAMPLE_FACTORS           	-	24	Fator:Normal tissue	RAW_FILE_NAME=24.CDF
SUBJECT_SAMPLE_FACTORS           	-	25	Fator:Normal tissue	RAW_FILE_NAME=25.CDF
SUBJECT_SAMPLE_FACTORS           	-	26	Fator:Normal tissue	RAW_FILE_NAME=26.CDF
SUBJECT_SAMPLE_FACTORS           	-	27	Fator:Normal tissue	RAW_FILE_NAME=27.CDF
SUBJECT_SAMPLE_FACTORS           	-	28	Fator:Normal tissue	RAW_FILE_NAME=28.CDF
SUBJECT_SAMPLE_FACTORS           	-	29	Fator:Normal tissue	RAW_FILE_NAME=29.CDF
SUBJECT_SAMPLE_FACTORS           	-	30	Fator:Normal tissue	RAW_FILE_NAME=30.CDF
SUBJECT_SAMPLE_FACTORS           	-	31	Fator:Normal tissue	RAW_FILE_NAME=31.CDF
SUBJECT_SAMPLE_FACTORS           	-	32	Fator:Normal tissue	RAW_FILE_NAME=32.CDF
#COLLECTION
CO:COLLECTION_SUMMARY            	Tissue samples, including tumor and normal areas 5 cm away, were obtained under
CO:COLLECTION_SUMMARY            	the guidance of experienced pathologists without compromising the patients'
CO:COLLECTION_SUMMARY            	pathology examinations. The collected tissue was rinsed with PBS to avoid
CO:COLLECTION_SUMMARY            	contamination, excess moisture was removed, and it was rapidly frozen in liquid
CO:COLLECTION_SUMMARY            	nitrogen to arrest enzymatic or chemical reactions. Samples were stored at
CO:COLLECTION_SUMMARY            	−80°C until metabolite extraction.
CO:SAMPLE_TYPE                   	Tissue
#TREATMENT
TR:TREATMENT_SUMMARY             	None
#SAMPLEPREP
SP:SAMPLEPREP_SUMMARY            	GC-MS Analysis mainly detects seven short-chain and four medium-chain fatty
SP:SAMPLEPREP_SUMMARY            	acids. Qualitative and quantitative analysis was also performed using internal
SP:SAMPLEPREP_SUMMARY            	standard method. Metabolic extracts were analyzed using the SHIMADZU
SP:SAMPLEPREP_SUMMARY            	GC2030-QP2020 NX gas chromatography-mass spectrometer. The system employed an
SP:SAMPLEPREP_SUMMARY            	HP-FFAP capillary column, and a 1 μL aliquot of the analyte was injected in
SP:SAMPLEPREP_SUMMARY            	split mode (5:1). Helium was used as the carrier gas with a front inlet purge
SP:SAMPLEPREP_SUMMARY            	flow of 3 mL/min and a gas flow rate of 1 mL/min through the column. The initial
SP:SAMPLEPREP_SUMMARY            	temperature was maintained at 50 °C for 1 min, then increased to 150 °C at a
SP:SAMPLEPREP_SUMMARY            	rate of 50 °C/min for 1 min. Subsequently, it was raised to 170 °C at a rate
SP:SAMPLEPREP_SUMMARY            	of 10 °C/min for 1 min, further increased to 210 °C at a rate of 20 °C/min
SP:SAMPLEPREP_SUMMARY            	for 1 min, and finally raised to 240 °C at a rate of 40 °C/min for 1 min. The
SP:SAMPLEPREP_SUMMARY            	injection, transfer line, quad, and ion source temperatures were set at 220 °C,
SP:SAMPLEPREP_SUMMARY            	240 °C, 150 °C, and 200 °C, respectively. The energy used was -70 eV in
SP:SAMPLEPREP_SUMMARY            	electron impact mode. Mass spectrometry data were acquired in Scan/SIM mode
SP:SAMPLEPREP_SUMMARY            	within the m/z range of 33-150 after a solvent delay of 3 min. Metabolite
SP:SAMPLEPREP_SUMMARY            	identification was performed using an in-house MS database. The pre-processing
SP:SAMPLEPREP_SUMMARY            	of MS raw data involved filtering individual metabolites to retain those with no
SP:SAMPLEPREP_SUMMARY            	more than 50% missing values. Missing values in the original data were simulated
SP:SAMPLEPREP_SUMMARY            	by multiplying the minimum value by a random number between 0.1 and 0.5.
#CHROMATOGRAPHY
CH:CHROMATOGRAPHY_TYPE           	GC
CH:INSTRUMENT_NAME               	SHIMADZU GC2030
CH:COLUMN_NAME                   	Agilent HP5-MS (30m x 0.25mm, 0.25 um)
CH:SOLVENT_A                     	-
CH:SOLVENT_B                     	-
CH:FLOW_GRADIENT                 	-
CH:FLOW_RATE                     	350-400
CH:COLUMN_TEMPERATURE            	475°C
#ANALYSIS
AN:ANALYSIS_TYPE                 	MS
#MS
MS:INSTRUMENT_NAME               	SHIMADZU
MS:INSTRUMENT_TYPE               	GC2030-QP2020
MS:MS_TYPE                       	EI
MS:ION_MODE                      	POSITIVE
MS:MS_COMMENTS                   	The quantitative results are calculated from the following formula: Calculation
MS:MS_COMMENTS                   	formula: C（con）= (Cs∗V1∗V3)/(M∗V2) *1000 C (con) : content of the
MS:MS_COMMENTS                   	target compound in the sample, μg/g; Cs: target compound concentration in
MS:MS_COMMENTS                   	extract, mg/l; V1: Volume of extract solution added, ML; V2: Take Out pure water
MS:MS_COMMENTS                   	supernatant volume, ML; V3: Volume of pure water added, ML; M: weighing sample,
MS:MS_COMMENTS                   	MG.
#MS_METABOLITE_DATA
MS_METABOLITE_DATA:UNITS	m/z
MS_METABOLITE_DATA_START
Samples	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32
Factors	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Early stage ESCC	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue	Fator:Normal tissue
Acetic acid	16895	80995	255764	10518	117763	10413	5307	34952	19611	9695	22833	7365	7084	4847	11695	5257	11368	42027	20423	26580	6538	10384	8111	34435	9820	16873	26484	17005	13256	14265	28791	11242
Propionic acid	3385	19211	64168	995	3666	1110	703	20656	3560	1017	5613	781	681	778	1214	551	791	6376	1768	2220	705	902	505	12686	1156	1055	1652	710	1002	824	3729	899
Isobutyric acid	6929	104452	88054	1806	75887	2015	1401	17212	14398	1074	1704	1270	2388	578	2819	931	1910	31477	4183	2600	1612	1756	1099	10107	2506	2668	1416	1149	673	1011	5728	1430
Butyric acid	10941	164552	203846	3362	199655	2694	2088	21228	18153	2898	8593	3152	2332	1743	3659	1806	2243	28588	3148	1726	2260	1347	1190	6552	2188	1484	1549	1261	1304	1097	3582	1166
Isovaleric acid	5797	17218	17173	1319	43283	1169	1080	4458	3311	877	1478	866	641	592	967	682	1294	3871	1131	699	1150	725	545	1822	1405	806	668	648	517	505	1662	534
Valeric acid	8977	20915	10773	2280	10343	1892	2116	2596	3558	1894	1568	1469	1157	1184	1105	1089	2100	2817	1399	1188	1642	1177	1030	1112	1838	1252	963	884	1398	963	944	902
Hexanoic acid	15077	14516	5440	6322	8707	10865	11776	16160	31713	34469	21949	14021	16129	7766	3761	8985	3119	11061	10860	5157	13142	13676	5739	3366	14741	6746	3478	2929	15351	3264	3230	5037
Heptanoic acid	963	1062	825	801	1012	1022	1115	1022	1385	1293	1237	877	968	836	729	878	624	949	966	966	992	803	919	1041	868	951	848	818	944	869	789	625
Octanoic acid	6344	5133	10934	7572	13973	18720	15324	8405	6115	6526	6128	9875	9290	8707	8767	5295	12558	7139	8367	5752	15894	13355	15437	12763	12029	7420	8173	16634	14296	12824	10801	7824
Nonanoic acid	11760	15327	13127	12420	14763	9587	12042	12641	12876	19080	19060	16608	17542	13228	13691	10947	11535	14449	13879	14271	12426	12961	19458	15004	15581	13604	11455	15545	11617	14744	10058	17788
Decanoic acid	2943	2484	4657	3467	5535	5084	5763	5058	3029	2989	3038	5929	4328	4665	5733	2234	5381	4138	3258	3842	7305	2799	5922	9201	7135	4006	3715	10139	6929	6949	6483	2744
MS_METABOLITE_DATA_END
#METABOLITES
METABOLITES_START
metabolite_name	CAS	molecular formula	quantitated m/z	HMDB ID	KEGG ID	PubChem ID
Acetic acid	64-19-7	CH3COOH	60.05	HMDB0000042	C00033	176
Propionic acid	1979/9/4	CH3CH2COOH	74.08	HMDB0000237	C00163	1032
Isobutyric acid	79-31-2	C4H8O2	88.11	HMDB0001873	C02632	6590
Butyric acid	107-92-6	C4H8O2	88.11	HMDB0000039	C00246	264
Isovaleric acid	503-74-2	C5H10O2	102.12	HMDB0000718	C08262	10430
Valeric acid	109-52-4	C5H10O2	102.13	HMDB0000892	C00803	7991
Hexanoic acid	142-62-1	C6H12O2	116.16	HMDB0000535	C01585	8892
Heptanoic acid	111-14-8	C7H14O2	130.18	HMDB0000666	C17714	8094
Octanoic acid	124-07-2	C8H16O2	144.21	HMDB0000482	C06423	379
Nonanoic acid	112-05-0	C9H18O2	158.24	HMDB0000847	C01601	8158
Decanoic acid	334-48-5	C10H20O2	172.26	HMDB0000511	C01571	2969
METABOLITES_END
#END