ArticleCancer biomarkers : section A of Disease markers2020
Six-gene-based prognostic model predicts overall survival in patients with uveal melanoma.
Article in Cancer biomarkers : section A of Disease markers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Translating Data Into Clinical Tools: An Integrative Strategy for Precision Biomarker Identification in Soft Tissue Sarcoma Diagnosis and Prognosis.Cancer informatics · 2026Article
- Maintenance of magnesium homeostasis by NUF2 promotes protein synthesis and anaplastic thyroid cancer progression.Cell death & disease · 2024Article
- Transcriptome-Wide Association Study Reveals New Molecular Interactions Associated with Melanoma Pathogenesis.Cancers · 2024Article
- Development of a Macrophage-Related Risk Model for Metastatic Melanoma.International journal of molecular sciences · 2023Article
- Article
- Tumor subtypes and signature model construction based on chromatin regulators for better prediction of prognosis in uveal melanoma.Pathology oncology research : POR · 2023Article
- MiR-762 regulates the activation of PI3K/AKT and Hippo pathways involved in the development of gastric cancer by targeting LZTS1.American journal of translational research · 2022Article
- Prognostic Biomarkers in Uveal Melanoma: The Status Quo, Recent Advances and Future Directions.Cancers · 2021Review
- Identification of subgroups along the glycolysis-cholesterol synthesis axis and the development of an associated prognostic risk model.Human genomics · 2021Article
- Prognostic Implications of Novel Ten-Gene Signature in Uveal Melanoma.Frontiers in oncology · 2020Article
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Abstract
backgroundUveal melanoma (UM) is the most common primary intraocular tumor in adults, which has a high mortality rate and worse prognosis. Therefore, early potential molecular detection and prognostic evaluation seem more important for early diagnosis and treatment.
methodsGene expression data were obtained from The Cancer Genome Atlas-Uveal melanomas database. Survival genes were identified by univariate analysis and were regarded to be associated with the overall survival of UM patients. Then, pathway enrichment analysis of these survival genes was performed. Robust likelihood-based survival model and multivariate survival analysis were conducted to identify more reliable genes and the prognostic signature for UM survival prediction. Two internal datasets and another two UM datasets from Gene Expression Omnibus (GEO) were used for the validation of prognostic signature.
resultsFirstly, 2,010 survival genes were screened by univariate survival analysis. GO and KEGG analysis revealed that these genes were mainly involved in pathways such as mRNA processing, RNA splicing, spliceosome and ubiquitin mediated proteolysis. Secondly, a six-gene signature was identified by Robust likelihood-based survival model approach. The gene expression of the six genes can successfully divide UM samples into high- and low-risk groups and have strong survival prediction ability. What's more, the expression of six genes was compared in 80 healthy adipose tissue samples obtained from GTEx (Genotype-Tissue Expression) database and further validated in internal datasets and GEO datasets, which also can predict UM patient survival.
conclusionsThe six genes (SH2D3A, TMEM201, LZTS1, CREG1, NIPA1 and HIST1H4E) model might play a vital role in prognosis of UM, which should be helpful for further insight into the treatment of uveal melanoma.
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