Efficient plasma metabolic fingerprinting as a novel tool for diagnosis and prognosis of gastric cancer: a large-scale, multicenter study
| Title | Efficient plasma metabolic fingerprinting as a novel tool for diagnosis and prognosis of gastric cancer: a large-scale, multicenter study |
|---|---|
| Description | We conducted a large-scale, multicenter study comprising 1944 participants from 7 centers in retrospective cohort. Discovery and verification phases of diagnostic and prognostic models were conducted in retrospective cohort through machine learning and Cox regression of plasma metabolic fingerprints (PMFs) obtained by nanoparticle-enhanced laser desorption/ionization-mass spectrometry (NPELDI-MS). |
| Organism | Homo sapiens |
| Data Type | Metabolome Data by Mass Spectrometry (MS) |
| Data Accessibility | Controlled-access |
| BioProject | PRJCA016944 |
| Release Date | 2023-06-20 |
| Submitter | Xiangdong Cheng (chengxd@zjcc.org.cn) |
| Organization | Zhejiang Cancer Hospital |
| Submission Date | 2023-05-12 |
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| File ID | File Title | Number/Samples | File Type | File Size | File Suffix | Download Times | Download |
|---|---|---|---|---|---|---|---|
| OMIX004022-01 | PMFs | 1944 | Metabolome Data by Mass Spectrometry (MS) | 8.0 MB | xlsx | 0 | Controlled |