Nomogram of uveal melanoma as prediction model of metastasis risk

• DOI: 10.1016/j.heliyon.2023.e18956
• Publication Date: 2023-08-07T00:35:55Z
• Authors: Yimin Wang; Minyue Xie; Feng Lin; Xiaonan Sheng; Xiaohuan Zhao; Xinyue Zhu; Yuwei Wang; Bing Lu; Jieqiong Chen; Ting Zhang; Xiaoling Wan; Wenjia Liu; Xiaodong Sun
• Keywords: Social sciences (General); H1-99; Q1-390; Uveal melanoma; Science (General); Nomogram; 3. Good health; Research Article

Since the poor prognosis of uveal melanoma with distant metastasis, we intended to screen out possible biomarkers for uveal melanoma metastasis risk and establish a nomogram model for predicting the risk of uveal melanoma (UVM) metastasis.Two datasets of UVM (GSE84976, GSE22138) were selected. Data was analyzed by R language, CTD database and GEPIA.The co-upregulated genes of two datasets, HTR2B, CHAC1, AHNAK2, and PTP4A3 were identified using a Venn diagram. These biomarkers are combined with clinical characteristics, and Lasso regression was conducted to filter the metastasis-related biomarkers. HTR2B, CHAC1, AHNAK2, PTP4A3, tumor thickness, and retinal detachment (RD) were selected to establish the nomogram.Our study provides a comprehensive predictive model and personalized risk estimation tool for assessment of 3-year metastasis risk of UVM with a better accuracy.