ArticleFrontiers in cell and developmental biology2022
Identification of 14 Differentially-Expressed Metabolism-Related Genes as Potential Targets of Gastric Cancer by Integrated Proteomics and Transcriptomics.
Article in Frontiers in cell and developmental biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Amino Acid Metabolic Enzymes in Gastric Cancer: Roles and Mechanisms in Tumorigenesis and Progression.Oncology research · 2026Review
- Branched-chain amino acid transaminases as promising targets in tumor therapy.Frontiers in cell and developmental biology · 2026Review
- Identification and validation of tumor microenvironment-related therapeutic targets in gastric cancer using integrated multi-omics and molecular docking approaches.Frontiers in bioinformatics · 2025Article
- Multi-omics analysis identifies BCAT2 as a potential pan-cancer biomarker for tumor progression and immune microenvironment modulation.Scientific reports · 2024Article
- Multi-omics analysis identifies BCAT2 as a potential pan-cancer biomarker for tumor progression and immune microenvironment modulation.Scientific reports · 2024Article
- Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer.International journal of molecular sciences · 2024Review
- Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer.Current medicinal chemistry · 2024Review
- Research progress on branched-chain amino acid aminotransferases.Frontiers in genetics · 2023Review
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although research on the metabolism related to gastric cancer (GC) is gradually gaining increasing interest, there are few studies regarding metabolism-related genes in GC. Understanding the characteristic changes of metabolism-related genes at the transcriptional and protein levels in GC will help us to identify new biomarkers and novel therapeutic targets. We harvested six pairs of samples from GC patients and evaluated the differentially expressed proteins using mass spectrometry-based proteomics. RNA sequencing was conducted simultaneously to detect the corresponding expression of mRNAs, and bioinformatics analysis was used to reveal the correlation of significant differentially expressed genes. A total of 57 genes were observed to be dysregulated both in proteomics and transcriptomics. Bioinformatics analysis showed that these differentially expressed genes were significantly associated with regulating metabolic activity. Further, 14 metabolic genes were identified as potential targets for GC patients and were related to immune cell infiltration. Moreover, we found that dysregulation of branched-chain amino acid transaminase 2 (BCAT2), one of the 14 differentially expressed metabolism-related genes, was associated with the overall survival time in GC patients. We believe that this study provides comprehensive information to better understand the mechanism underlying the progression of GC metastasis and explores the potential therapeutic and prognostic metabolism-related targets for GC.
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