Six-gene-based prognostic model predicts overall survival in patients with uveal melanoma

Autor:	Yaru Su, Yaqi Cheng, Chaoyang Li, Shoubi Wang, Ying Liu, Lin Jin, Jing Tang, Qi Wan, Jianqun Lu, Zhichong Wang
Rok vydání:	2020
Předmět:	0301 basic medicine Oncology Male Uveal Neoplasms Cancer Research medicine.medical_specialty Biology 03 medical and health sciences 0302 clinical medicine Internal medicine Gene expression Databases Genetic Genetics medicine Humans KEGG Gene Melanoma Survival analysis Neoplasm Staging Univariate analysis Base Sequence Mortality rate Gene Expression Profiling General Medicine Middle Aged medicine.disease Prognosis Survival Analysis 030104 developmental biology 030220 oncology & carcinogenesis RNA splicing Female
Zdroj:	Cancer biomarkers : section A of Disease markers. 27(3)
ISSN:	1875-8592
Popis:	BACKGROUND Uveal 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. METHODS Gene 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. RESULTS Firstly, 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. CONCLUSIONS The 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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::413e145cae1c8667d79a4aa0bf5c394d https://pubmed.ncbi.nlm.nih.gov/31903983 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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