Summary of Study ST003025

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001876. The data can be accessed directly via it's Project DOI: 10.21228/M87426 This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

Study ID	ST003025
Study Title	NMR- and MS-based omics reveal characteristic metabolome atlas and optimize biofluid earlydiagnostic biomarkers for esophageal squamous cell carcinoma (part-Ⅴ)
Study Summary	Metabolic changes precede malignant histology. However, it remains unclear whether detectable characteristic metabolome exists in esophageal squamous cell carcinoma (ESCC) tissues and biofluids for early diagnosis. We conducted NMR- and MS-based metabolomics on 1,153 matched ESCC tissues, normal mucosae, pre- and one-week post-operative sera and urines from 560 participants across three hospitals, with machine learning, logistic regression and WGCNA. Aberrations in 'alanine, aspartate and glutamate metabolism' proved to be prevalent throughout the ESCC evolution, and were reflected in 16 serum and 10 urine metabolic signatures that were consistently identified by NMR and MS in both discovery and validation sets. NMR-based simplified panels of any five serum or urine metabolites outperformed clinical serological tumor markers (AUC = 0.984 and 0.930, respectively), and were effective in distinguishing early-stage ESCC in test set (serum accuracy = 0.994, urine accuracy = 0.879). Collectively, NMR-based biofluid screening can reveal characteristic metabolic events of ESCC and be feasible for early detection (ChiCTR2300073613).
Institute	Radiology Department, Second Affiliated Hospital, Shantou University Medical College
Last Name	Lin
First Name	Yan
Address	No. 69, Dongxia North Road, Shantou, Guangdong, China
Email	994809889@qq.com
Phone	+86 18823992148
Submit Date	2023-12-18
Raw Data Available	Yes
Raw Data File Type(s)	cdf
Analysis Type Detail	GC-MS
Release Date	2024-02-08
Release Version	1

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Sample Preparation:

Sampleprep ID:	SP003145
Sampleprep Summary:	GC-MS Analysis mainly detects seven short-chain and four medium-chain fatty acids. Qualitative and quantitative analysis was also performed using internal standard method. Metabolic extracts were analyzed using the SHIMADZU GC2030-QP2020 NX gas chromatography-mass spectrometer. The system employed an HP-FFAP capillary column, and a 1 μL aliquot of the analyte was injected in split mode (5:1). Helium was used as the carrier gas with a front inlet purge flow of 3 mL/min and a gas flow rate of 1 mL/min through the column. The initial temperature was maintained at 50 °C for 1 min, then increased to 150 °C at a rate of 50 °C/min for 1 min. Subsequently, it was raised to 170 °C at a rate of 10 °C/min for 1 min, further increased to 210 °C at a rate of 20 °C/min for 1 min, and finally raised to 240 °C at a rate of 40 °C/min for 1 min. The injection, transfer line, quad, and ion source temperatures were set at 220 °C, 240 °C, 150 °C, and 200 °C, respectively. The energy used was -70 eV in electron impact mode. Mass spectrometry data were acquired in Scan/SIM mode within the m/z range of 33-150 after a solvent delay of 3 min. Metabolite identification was performed using an in-house MS database. The pre-processing of MS raw data involved filtering individual metabolites to retain those with no more than 50% missing values. Missing values in the original data were simulated by multiplying the minimum value by a random number between 0.1 and 0.5.

Sampleprep ID:

SP003145

Sampleprep Summary:

GC-MS Analysis mainly detects seven short-chain and four medium-chain fatty acids. Qualitative and quantitative analysis was also performed using internal standard method. Metabolic extracts were analyzed using the SHIMADZU GC2030-QP2020 NX gas chromatography-mass spectrometer. The system employed an HP-FFAP capillary column, and a 1 μL aliquot of the analyte was injected in split mode (5:1). Helium was used as the carrier gas with a front inlet purge flow of 3 mL/min and a gas flow rate of 1 mL/min through the column. The initial temperature was maintained at 50 °C for 1 min, then increased to 150 °C at a rate of 50 °C/min for 1 min. Subsequently, it was raised to 170 °C at a rate of 10 °C/min for 1 min, further increased to 210 °C at a rate of 20 °C/min for 1 min, and finally raised to 240 °C at a rate of 40 °C/min for 1 min. The injection, transfer line, quad, and ion source temperatures were set at 220 °C, 240 °C, 150 °C, and 200 °C, respectively. The energy used was -70 eV in electron impact mode. Mass spectrometry data were acquired in Scan/SIM mode within the m/z range of 33-150 after a solvent delay of 3 min. Metabolite identification was performed using an in-house MS database. The pre-processing of MS raw data involved filtering individual metabolites to retain those with no more than 50% missing values. Missing values in the original data were simulated by multiplying the minimum value by a random number between 0.1 and 0.5.