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Updated: Aug 5, 2026
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Multiomics Analysis of TMEM200A as a Pan-Cancer Biomarker
Published on: September 15, 2023
Integrated Elementomics-Genomics-Metabolomics Analysis Reveals Plasma Biomarker Networks and Diagnostic Potential for
Ruoyu Li1,2,3, Guofeng Li1,2,3, Shilin Chen1,2,3
1Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou 350108, China.
Metabolites
|July 27, 2026
Summary
Nine plasma elements show high diagnostic accuracy for gastric cancer (GC). These elements link to genes and metabolites involved in cancer pathways, offering potential biomarkers for early detection and understanding GC mechanisms.
Area of Science:
- Biochemistry
- Genomics
- Oncology
Background:
- Gastric cancer (GC) is a major global cause of cancer mortality.
- Despite advancements, the molecular underpinnings of GC require further elucidation.
- A comprehensive multi-omics approach is essential for understanding GC's molecular landscape.
Purpose of the Study:
- To systematically analyze the molecular characteristics of gastric cancer using a multi-omics strategy.
- To explore the regulatory axis of elements, genes, and metabolites in GC.
- To identify potential circulating biomarkers for GC diagnosis.
Main Methods:
- A case-control study involving 218 GC patients and 218 healthy controls.
- Utilized inductively coupled plasma mass spectrometry (ICP-MS) for elemental analysis.
- Employed element-related genome-wide association studies (eGWAS) and untargeted metabolomics.
Main Results:
- Identified nine plasma differential elements with a combined diagnostic accuracy of 0.918 for GC.
- Found significant correlations between elements (e.g., Fe, Co, Li) and 63 genes in pathways like MAPK, SMAD, and Wnt.
- Metabolomic analysis revealed associations between 20 elements and 94 metabolites, enriched in pyrimidine and glutathione metabolism.
Conclusions:
- The nine identified plasma elements demonstrate high diagnostic efficacy for GC.
- These elements are linked to genes and metabolites involved in cancer signaling, metabolic reprogramming, and DNA damage response.
- Findings suggest multi-level interactions between elemental changes, genetic variations, and metabolic dysregulation in GC, offering mechanistic insights and biomarker candidates.
