Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases
Background. The aim of this study was to apply bioinformatic analysis to develop a robust miRNA signature and construct a nomogram model in uveal melanoma (UM) to improve prognosis prediction. Methods. miRNA and mRNA sequencing data for 80 UM patients were obtained from The Cancer Genome Atlas (TCGA...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Journal of Ophthalmology |
| Online Access: | http://dx.doi.org/10.1155/2022/9724160 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832548845176750080 |
|---|---|
| author | Jun Zuo Hongquan Ye Jing Tang Jianqun Lu Qi Wan |
| author_facet | Jun Zuo Hongquan Ye Jing Tang Jianqun Lu Qi Wan |
| author_sort | Jun Zuo |
| collection | DOAJ |
| description | Background. The aim of this study was to apply bioinformatic analysis to develop a robust miRNA signature and construct a nomogram model in uveal melanoma (UM) to improve prognosis prediction. Methods. miRNA and mRNA sequencing data for 80 UM patients were obtained from The Cancer Genome Atlas (TCGA) database. The patients were further randomly assigned to a training set (n = 40, used to identify key miRNAs) and a testing set (n = 40, used to internally verify the signature). Then, miRNAs data of GSE84976 and GSE68828 were downloaded from Gene Expression Omnibus (GEO) database for outside verification. Combining univariate analysis and LASSO methods for identifying a robust miRNA biomarker in training set and the signature was validated in testing set and outside dataset. A prognostic nomogram was constructed and combined with decision curve as well as reduction curve analyses to assess the application of clinical usefulness. Finally, we constructed a miRNA-mRNA regulator network in UM and conducted pathway enrichment analysis according to the mRNAs in the network. Results. In total, a 3-miRNA was identified and validated that can robustly predict UM patients’ survival. According to univariate and multivariate cox analyses, age at diagnosis, tumor node metastasis (TNM) classification, stage, and the 3-miRNA signature significantly correlated with the survival outcomes. These characteristics were used to establish nomogram. The nomogram worked well for predicting 1 and 3 years of overall survival time. The decision curve of nomogram revealed a good clinical usefulness of our nomogram. What’s more, a miRNA-mRNA network was constructed. Pathway enrichment showed that this network was largely involved in mRNA processing, the mRNA surveillance pathway, the spliceosome, and so on. Conclusions. We developed a 3-miRNA biomarker and constructed a prognostic nomogram, which may afford a quantitative tool for predicting the survival of UM. Our finding also provided some new potential targets for the treatment of UM. |
| format | Article |
| id | doaj-art-c6c838051c6f4390b5fabf32ff712b0c |
| institution | Kabale University |
| issn | 2090-0058 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Ophthalmology |
| spelling | doaj-art-c6c838051c6f4390b5fabf32ff712b0c2025-02-03T06:13:03ZengWileyJournal of Ophthalmology2090-00582022-01-01202210.1155/2022/9724160Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO DatabasesJun Zuo0Hongquan Ye1Jing Tang2Jianqun Lu3Qi Wan4Department of OphthalmologyDepartment of OphthalmologyDepartment of OphthalmologyDepartment of OphthalmologyDepartment of OphthalmologyBackground. The aim of this study was to apply bioinformatic analysis to develop a robust miRNA signature and construct a nomogram model in uveal melanoma (UM) to improve prognosis prediction. Methods. miRNA and mRNA sequencing data for 80 UM patients were obtained from The Cancer Genome Atlas (TCGA) database. The patients were further randomly assigned to a training set (n = 40, used to identify key miRNAs) and a testing set (n = 40, used to internally verify the signature). Then, miRNAs data of GSE84976 and GSE68828 were downloaded from Gene Expression Omnibus (GEO) database for outside verification. Combining univariate analysis and LASSO methods for identifying a robust miRNA biomarker in training set and the signature was validated in testing set and outside dataset. A prognostic nomogram was constructed and combined with decision curve as well as reduction curve analyses to assess the application of clinical usefulness. Finally, we constructed a miRNA-mRNA regulator network in UM and conducted pathway enrichment analysis according to the mRNAs in the network. Results. In total, a 3-miRNA was identified and validated that can robustly predict UM patients’ survival. According to univariate and multivariate cox analyses, age at diagnosis, tumor node metastasis (TNM) classification, stage, and the 3-miRNA signature significantly correlated with the survival outcomes. These characteristics were used to establish nomogram. The nomogram worked well for predicting 1 and 3 years of overall survival time. The decision curve of nomogram revealed a good clinical usefulness of our nomogram. What’s more, a miRNA-mRNA network was constructed. Pathway enrichment showed that this network was largely involved in mRNA processing, the mRNA surveillance pathway, the spliceosome, and so on. Conclusions. We developed a 3-miRNA biomarker and constructed a prognostic nomogram, which may afford a quantitative tool for predicting the survival of UM. Our finding also provided some new potential targets for the treatment of UM.http://dx.doi.org/10.1155/2022/9724160 |
| spellingShingle | Jun Zuo Hongquan Ye Jing Tang Jianqun Lu Qi Wan Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases Journal of Ophthalmology |
| title | Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases |
| title_full | Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases |
| title_fullStr | Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases |
| title_full_unstemmed | Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases |
| title_short | Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases |
| title_sort | development of a 3 microrna signature and nomogram for predicting the survival of patients with uveal melanoma based on tcga and geo databases |
| url | http://dx.doi.org/10.1155/2022/9724160 |
| work_keys_str_mv | AT junzuo developmentofa3micrornasignatureandnomogramforpredictingthesurvivalofpatientswithuvealmelanomabasedontcgaandgeodatabases AT hongquanye developmentofa3micrornasignatureandnomogramforpredictingthesurvivalofpatientswithuvealmelanomabasedontcgaandgeodatabases AT jingtang developmentofa3micrornasignatureandnomogramforpredictingthesurvivalofpatientswithuvealmelanomabasedontcgaandgeodatabases AT jianqunlu developmentofa3micrornasignatureandnomogramforpredictingthesurvivalofpatientswithuvealmelanomabasedontcgaandgeodatabases AT qiwan developmentofa3micrornasignatureandnomogramforpredictingthesurvivalofpatientswithuvealmelanomabasedontcgaandgeodatabases |