Li Ping, Ren He, Zhang Yan, Zhou Zhaoli
Shanghai University of Medicine & Health Sciences School of Optical-electrical and Computer Engineer of University of Shanghai for Science and Technology Shanghai Key Laboratory for Molecular Imaging, Collaborative Research Center, Shanghai University of Medicine & Health Science Department of Pharmacology, School of Pharmacy, Shanghai University of Medicine & Health Science, Shanghai, China.
Medicine (Baltimore). 2018 Aug;97(33):e11839. doi: 10.1097/MD.0000000000011839.
Clear-cell renal cell carcinoma (ccRCC) is the major renal cell carcinoma subtype, but its postsurgical prognosis varies among individual patients.We used gene expression, machine learning (random forest variable hunting), and Cox regression analysis to develop a risk score model based on 15 genes to predict survival of patients with ccRCC in the The Cancer Genome Atlas dataset (N = 533). We validated this model in another cohort, and analyzed correlations between risk score and other clinical indicators.Patients in the high-risk group had significantly worse overall survival (OS) than did those in the low-risk group (P = 5.6e-16); recurrence-free survival showed a similar pattern. This result was reproducible in another dataset, E-MTAB-1980 (N = 101, P = .00029). We evaluated correlations between risk score and other clinical indicators. Risk was independent of age and sex, but was significantly associated with hemoglobin level, primary tumor size, and grade. Radiation therapy also had no effect on the prognostic value of the risk score. Cox multivariate regression showed risk score to be an important indicator for ccRCC prognosis. We plotted a nomogram for 3-year OS to facilitate use of risk score and other indicators.The risk score model based on expression of the 15 selected genes can predict survival of patients with ccRCC.
透明细胞肾细胞癌（ccRCC）是肾细胞癌的主要亚型，但其术后预后在个体患者中存在差异。我们使用基因表达、机器学习（随机森林变量筛选）和Cox回归分析，基于15个基因开发了一个风险评分模型，以预测癌症基因组图谱数据集（N = 533）中ccRCC患者的生存率。我们在另一个队列中验证了该模型，并分析了风险评分与其他临床指标之间的相关性。高风险组患者的总生存期（OS）明显低于低风险组（P = 5.6e-16）；无复发生存期也呈现类似模式。这一结果在另一个数据集E-MTAB-1980（N = 101，P = 0.00029）中具有可重复性。我们评估了风险评分与其他临床指标之间的相关性。风险与年龄和性别无关，但与血红蛋白水平、原发肿瘤大小和分级显著相关。放射治疗对风险评分的预后价值也没有影响。Cox多因素回归显示风险评分是ccRCC预后的重要指标。我们绘制了一个3年总生存期的列线图，以方便使用风险评分和其他指标。基于15个选定基因表达的风险评分模型可以预测ccRCC患者的生存率。
