Nomogram of uveal melanoma as prediction model of metastasis risk
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
Affiliations
Yimin Wang
Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine, China; National Clinical Research Center for Eye Disease, China; Shanghai Key Laboratory of Ocular Fundus Diseases, China; Shanghai Engineering Center for Visual Science and Photomedicine, China; Department of Ophthalmology, Zhongshan Hospital, Fudan University, Shanghai, China
Minyue Xie
Beijing Tongren Hospital, Capital Medical University, China
Feng Lin
Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, China
Xiaonan Sheng
Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, PR China
Xiaohuan Zhao
Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine, China; National Clinical Research Center for Eye Disease, China; Shanghai Key Laboratory of Ocular Fundus Diseases, China; Shanghai Engineering Center for Visual Science and Photomedicine, China
Xinyue Zhu
Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine, China; National Clinical Research Center for Eye Disease, China; Shanghai Key Laboratory of Ocular Fundus Diseases, China; Shanghai Engineering Center for Visual Science and Photomedicine, China
Yuwei Wang
Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine, China; National Clinical Research Center for Eye Disease, China; Shanghai Key Laboratory of Ocular Fundus Diseases, China; Shanghai Engineering Center for Visual Science and Photomedicine, China
Bing Lu
Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine, China; National Clinical Research Center for Eye Disease, China; Shanghai Key Laboratory of Ocular Fundus Diseases, China; Shanghai Engineering Center for Visual Science and Photomedicine, China
Jieqiong Chen
Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine, China; National Clinical Research Center for Eye Disease, China; Shanghai Key Laboratory of Ocular Fundus Diseases, China; Shanghai Engineering Center for Visual Science and Photomedicine, China
Ting Zhang
Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine, China; National Clinical Research Center for Eye Disease, China; Shanghai Key Laboratory of Ocular Fundus Diseases, China
Xiaoling Wan
Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine, China; National Clinical Research Center for Eye Disease, China; Shanghai Key Laboratory of Ocular Fundus Diseases, China
Wenjia Liu
Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine, China; National Clinical Research Center for Eye Disease, China; Shanghai Key Laboratory of Ocular Fundus Diseases, China; Shanghai Engineering Center for Visual Science and Photomedicine, China; Corresponding author. Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Hai Ning Road, Shanghai 200080, PR China.
Xiaodong Sun
Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine, China; National Clinical Research Center for Eye Disease, China; Shanghai Key Laboratory of Ocular Fundus Diseases, China; Shanghai Engineering Center for Visual Science and Photomedicine, China
Background: 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. Methods: Two datasets of UVM (GSE84976, GSE22138) were selected. Data was analyzed by R language, CTD database and GEPIA. Results: 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. Conclusion: 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.
