Summary of Study ST002113
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 PR001339. The data can be accessed directly via it's Project DOI: 10.21228/M8N405 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 | ST002113 |
Study Title | Metabolomic analyses redefine the biological classification of pancreatic cancer: From clinical stage to metabolic subtype |
Study Summary | Pancreatic ductal adenocarcinoma (PDAC) is characterized by high heterogeneity, and the postoperative prognosis of different patients often varies greatly. Therefore, the classification of pancreatic cancer patients and precise treatment becomes particularly important. In this study, 1H NMR spectroscopy was used to analyze the 76 PDAC serum samples and identify the potential metabolic subtypes. The metabolic characteristics of each metabolic subtype were screened out and the relationship between metabolic subtype and the long-term prognosis was further identified. The clinical stages of PDAC did not show the metabolic differences at the serum metabolomic level. And three metabolic subtypes, basic, choline-like and amino acid-enriched types, were defined by the HCA of the serum metabolites and the disturbed metabolic pathways. The characteristic metabolites of each PDAC subtype were identified, and the metabolite model was established to distinguish the PDAC patients in the different subtypes. Among the three metabolic subtypes, choline-like type displayed better long-term prognosis compared with the other two types of patients. Metabolic subtypes are of clinical importance and can fully express the heterogeneity in the actual life activities of pancreatic cancer. The excavation of metabolic subtypes based on this will be more accurate and in line with clinical reality, so as to guide clinical precision individualization treatment. |
Institute | Xiamen University |
Last Name | Guo |
First Name | Pengfei |
Address | Zengcuoan street |
451965557@qq.com | |
Phone | 18965187376 |
Submit Date | 2022-03-04 |
Raw Data Available | Yes |
Raw Data File Type(s) | fid |
Analysis Type Detail | NMR |
Release Date | 2022-03-22 |
Release Version | 1 |
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Collection:
Collection ID: | CO002191 |
Collection Summary: | Before the first-diagnosed patient is admitted to the hospital for treatment and before the blood is drawn from the healthy controls, all the subjects were fasted overnight. The blood samples were taken through a clinical standard procedure, and 3-5 mL of venous blood was collected in the early morning and placed at 4 ºC for 2 hours. The serum was separated through a centrifugation at 3000 g for 10 minutes, and 500 μL of the supernatant was transferred into a 1.5-mL EP tube. The serum samples were snap-frozen with liquid nitrogen to stop the metabolic activity and then kept at -80 ºC. |
Collection Protocol Filename: | NMR_serum collection.docx |
Sample Type: | Blood (serum) |
Storage Conditions: | -80℃ |