ArticleMolecular biotechnology2023
Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients.
Article in Molecular biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Methyltransferase 3 promotes v-set and transmembrane domain-containing 2-like protein expression to intensify ferroptosis-mediated prostate adenocarcinoma progression through the m6A methylation modification.Histology and histopathology · 2026Article
- VSTM2L mediates the release of extracellular vimentin to drive lymph node metastasis in gastric cancer.Biology direct · 2026Article
- Integrating multiple key molecules in uveal melanoma to uncover metastatic and immune microenvironment-related gene signatures.International journal of ophthalmology · 2026Article
- Identification of a novel gene signature related to prognosis and metastasis in gastric cancer.Cellular oncology (Dordrecht, Netherlands) · 2024Article
- The function of the inter-alpha-trypsin inhibitors in the development of disease.Frontiers in medicine · 2024Review
- The uniqueness of ABCB5 as a full transporter ABCB5FL and a half-transporter-like ABCB5β.Cancer drug resistance (Alhambra, Calif.) · 2024Review
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5 authors.
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Abstract
Gastric cancer (GC) has been a common tumor type with high mortality. Distal metastasis is one of the main causes of death in GC patients, which is also related to poor prognosis. The mRNA profiles and clinical information of GC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Univariate Cox and LASSO Cox analyses were used to screen the optimal metastasis-related genes (MRGs) to establish a prognostic Risk Score model for GC patients. The nomogram was used to visualize the Risk Score and predict the 1-, 3-, 5-year survival rate. The immune cell infiltration was analyzed by CIBERSORT and the ratio of immune-stromal component was calculated by the ESTIMATE algorithm. A total of 142 differentially expressed genes were identified between metastatic and non-metastatic GC samples. The optimal 8 genes, comprising GAMT (guanidinoacetate N-methyltransferase), ABCB5 (ATP-binding cassette subfamily B member 5), ITIH3 (inter-alpha-trypsin inhibitor heavy chain 3), GDF3 (growth differentiation factor 3), VSTM2L (V-set and transmembrane domain-containing 2 like), CIDEA (cell death inducing DFFA like effector a), NPTX1 (neuronal pentraxin-1), and UMOD (uromodulin), were further screened to establish a prognostic Risk Score, which proved to be an independent prognostic factor. Patients in high-risk group had a poor prognosis. There were significant differences in the proportion of 11 tumor-infiltrating immune cells between high-risk and low-risk subgroups. In addition, the StromalScore, ImmuneScore, and ESTIMATEScore in high-risk group were higher than those in low-risk group, indicating that the tumor microenvironment of the high-risk group was more complex. A Risk Score model based on eight metastasis-related genes could clearly distinguish the prognosis of GC patients. The poor prognosis of patients with high-Risk Score might be associated with the complex tumor microenvironments.
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