Development and Validation of a Novel Metabolic Signature-Based Prognostic Model for Uveal Melanoma.
Development and Validation of a Novel Metabolic Signature-Based Prognostic Model for Uveal Melanoma.
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基于代谢特征的新型葡萄膜黑色素瘤预后模型的开发和验证
DOI：
10.1167/tvst.11.5.9
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发表时间：
2022-05-02
影响因子：
3
通讯作者：
Sun, Xiaodong
中科院分区：
文献类型：
--
作者：
Shi, Ke;Li, Xinxin;Zhang, Jingfa;Sun, Xiaodong
葡萄膜黑色素瘤(UM)是最常见的原发恶性肿瘤，预后不良。代谢相关基因在UM预后中的作用尚不清楚。本研究旨在建立并验证基于代谢相关基因的UM预后预测模型。基因表达谱和临床病理信息从癌症基因组图谱和基因表达总库下载。采用单变量Cox回归、最小绝对收缩和选择算子Cox回归、逐步回归等方法建立模型。采用Kaplan-Meier生存分析、受试者工作特征(ROC)曲线分析、校正和判别分析对模型进行评价。3个代谢相关基因(碳酸氢酶12、酰辅酶A合成酶长链家族成员3和突触素2)和3个临床病理参数(即年龄、性别和转移分期)被确定为建立该模型的基础。风险评分被发现是UM生存的独立预后因素。高危患者的预后明显比低危患者差。ROC分析表明，该模型具有良好的预测效果。校正曲线表明，预测的风险与观察到的风险之间有令人满意的一致性。开发了诺模图和在线生存计算器来预测生存概率。新的基于代谢的预后模型能够准确地预测UM患者的预后，便于眼科医生和患者使用在线动态诺模图预测生存概率。动态诺模图将基因表达谱与UM的临床预后联系起来，有助于评估UM的生存概率。
Uveal melanoma (UM) is the most common primary malignant tumor with poor prognosis. The role of metabolism-related genes in the prognosis of UM remains unrevealed. This study aimed to establish and validate a prognostic prediction model for UM based on metabolism-related genes. Gene expression profiles and clinicopathological information were downloaded from The Cancer Genome Atlas, and the Gene Expression Omnibus database. Univariable Cox regression, least absolute shrinkage and selection operator Cox regression, and stepwise regression were performed to establish the model. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve analysis, and calibration and discrimination analyses were used to evaluate the prognostic model. Three metabolism-related genes, carbonic anhydrase 12, acyl-CoA synthetase long-chain family member 3, and synaptojanin 2, and three clinicopathological parameters (i.e., age, gender, and metastasis staging) were identified to establish the model. The risk score was found to be an independent prognostic factor for UM survival. High-risk patients demonstrated significantly poorer prognosis than low-risk patients. ROC analysis suggested the promising prognostic efficiency of the model. The calibration curve manifested satisfactory agreement between the predicted and observed risk. A nomogram and online survival calculator were developed to predict the survival probability. The novel metabolism-based prognostic model could accurately predict the prognosis of UM patients, which facilitates the prediction of the survival probability by both ophthalmologists and patients with the online dynamic nomogram. The dynamic nomogram links gene expression profiles to clinical prognosis of UM and is useful to evaluate the survival probability.
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影响因子：
6.6
作者：
Fernández LP;Merino M;Colmenarejo G;Moreno-Rubio J;Sánchez-Martínez R;Quijada-Freire A;Gómez de Cedrón M;Reglero G;Casado E;Sereno M;Ramírez de Molina A
通讯作者：
Ramírez de Molina A
DOI：
10.3390/diagnostics11020219
发表时间：
2021-02-02
期刊：
Diagnostics (Basel, Switzerland)
影响因子：
--
作者：
Luo H;Ma C
通讯作者：
Ma C
影响因子：
--
作者：
Shields, Carol L.;Furuta, Minoru;Shields, Jerry A.
通讯作者：
Shields, Jerry A.
影响因子：
45.3
作者：
Rietschel, P;Panageas, KS;Chapman, PB
通讯作者：
Chapman, PB
影响因子：
21.3
作者：
Boroughs LK;DeBerardinis RJ
通讯作者：
DeBerardinis RJ