ABSTRACT
Uveal melanoma (UM) is the most common primary intraocular malignancy in adults, and its metastases are known to be fatal. It is critical to identify molecular markers to be used in potential prognostic evaluation for early diagnosis, treatment, and metastasis or to investigate all aspects of known genetic anomalies. Therefore, this study aimed to analyze the eight genes (GNAQ, GNA11, BAP1, SF3B1, SRSF2, EIF1AX, PLCB4, and CYSLTR2) that are associated with the most common genetic anomalies in UM from a molecular perspective. The genome sequences and expression profiles of 108 UM patients were obtained via bioinformatics tools that provide data from TCGA. The overall mutational load and the mutation patterns for eight genes, in particular, were thoroughly determined. Moreover, PolyPhen2 and SNAP2 tools were used to estimate the oncogenic/pathogenic properties of identified mutations for UM. In addition to the mutation profile, the effects of the presence of a mutation on gene expression and survival were determined. Finally, STRING network analysis was performed to better understand the functional relationships of mutated proteins in cellular processes. There were 27 missense mutations, 16 frameshift mutations, six nonsense mutations, and three splice region mutations among the 52 mutations found in eight genes, and 26 of them had pathogenic properties. BAP1 m-RNA expression was significantly lower in tumors with the mutant genotype (p = .001). The impact of gene expression, which has poor prognostic importance, on survival is statistically significant for high-expressed BAP1 (p = .0015) and low-expressed CYSLTR2 (p = .0021). To assess the current state of this potentially devastating disease, a molecular perspective has been evaluated. Defining this molecular perspective can be useful in developing targeted drug therapies and personalized medicine.
Acknowledgments
The data used in our study are obtained from public database the TCGA Research Network: https://www.cancer.gov/tcga. We thank the TCGA, GEPIA, cbio Portal, TIMER-2 and STRING databases for the availability of the data.
Authorship contribution
D.F.A.B carried out the conceptualization of the study, conducted bioinformatics analyses and analyzed the data; wrote the manuscript.
Availability of data and materials
The datasets generated and analyzed during the current study are available in TCGA database (https://www.cancer.gov/tcga), The cbio cancer genomics portal (http://www.cbioportal.org/).
Declaration of interest
The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article.
Ethical approval and ethical standards
The data used in our study were obtained from public database TCGA, therefore, ethical approval was not required.