OMIX004318

1Summary
Title Metabolic Signature Subtypes of Transcriptomic in Gastric Cancer
Description Recent studies highlighted the clinicopathologic importance of tumor metabolic reprogramming in delineating molecular attributes and therapeutic potentials. However, the overall metabolic features in gastric cancer (GC) have not been comprehensively recognized. Here, consensus NMF clustering algorithm is employed to determine the tumor metabolism patterns in GC. The SDPH in-house dataset with paired transcriptomic and metabolomic identifies three distinct cluster (termed as MSC1, MSC2, MSC3) with substantial differences in metabolic pathways and oncology signaling.
Organism Homo sapiens
Data Type Expression Profiling
Data Accessibility Open-access
BioProject PRJCA017614
Release Date 2025-07-01
Submitter Wei Chong (chongwei@sdfmu.edu.cn)
Organization Shandong Provincial Hospital
Submission Date 2023-06-11
2Files & Download

The data cannot be downloaded as it has not yet been registered in the Human Genetic Resource Management Platform of MOST.

File ID File Title Number/Samples File Type File Size File Suffix Download
OMIX004318-01 Transcriptomic Data of FPKM 1 Expression Profiling 35.2 MB xls Unavailable
3Relevant Publications
Paper Title Journal Name Publish Time Accession Citing Type
Molecular characterization and clinical relevance of metabolic signature subtypes in gastric cancer Cell Reports 2024-07 OMIX004318 OMIX004317 Deposit
Molecular characterization and clinical relevance of metabolic signature subtypes in gastric cancer World Congress of Gastroenterology and Digestive Diseases 2024-12 OMIX004318 OMIX004317 Deposit

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