Predictive value of single-nucleotide polymorphism signature for recurrence in localised renal cell carcinoma: a retrospective analysis and multicentre validation study
Predictive value of single-nucleotide polymorphism signature for recurrence in localised renal cell carcinoma: a retrospective analysis and multicentre validation study
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单核苷酸多态性特征对局限性肾细胞癌复发的预测价值：回顾性分析和多中心验证研究
DOI：
10.1016/s1470-2045(18)30932-x
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发表时间：
2019-04-01
期刊：
影响因子：
51.1
通讯作者：
Luo, Jun-Hang
中科院分区：
文献类型：
--
作者：
Wei, Jin-Huan;Feng, Zi-Hao;Luo, Jun-Hang
背景：确定高风险的局部肾细胞癌是选择复发风险较高的患者进行辅助治疗的关键。我们开发了一个基于单核苷酸多态性（snp）的分类器，以提高对肾癌复发的预测准确性，并研究肿瘤内异质性是否影响分类器的准确性。方法在这项回顾性分析和多中心验证研究中，我们使用来自中山大学（中国广东广州）227例局部透明细胞肾细胞癌患者的石蜡包埋标本，通过对癌症基因组图谱（TCGA）肾透明细胞癌（KIRC）数据集（n=114）的全基因组关联研究进行探索性生物信息学分析，检测44个潜在的复发相关snp。906600个snp)。基于SNP状态与患者无复发生存之间的关系，我们使用LASSO Cox回归开发了一个基于6个SNP的分类器。从训练集中同一肿瘤的两个其他区域研究肿瘤内的异质性。基于6 - snp的分类器在内部测试集（n=226）、独立验证集（中国多中心研究，2004年1月1日至2012年12月31日在中国三家医院接受治疗的428例患者）和TCGA集（441例回顾性鉴定的1998年至2010年在美国接受局部透明细胞肾细胞癌切除术的患者）中进行了验证。主要终点为无复发生存期；次要终点是总生存期。虽然在具有完整SNP信息的206例内部测试集中发现48例（23%）存在肿瘤内异质性，但基于6个SNP的分类器在训练集的三个不同区域（5年曲线下面积[AUC]：区域1为0.749 [95% CI 0.660-0.826]，区域2为0.734[0.651-0.814]，区域3为0.736[0.649-0.824]）的预测准确性相似。基于6个snp的分类器在3个验证集中精确预测患者无复发生存（内部测试集的风险比[HR] 5.32 [95% CI 2.81-10.07]，独立验证集的风险比[HR] 5.39 [3.38-8.59]， TCGA集的风险比[HR] 4.62 [2.48-8.61]）
Background Identification of high-risk localised renal cell carcinoma is key for the selection of patients for adjuvant treatment who are at truly higher risk of reccurrence. We developed a classifier based on single-nucleotide polymorphisms (SNPs) to improve the predictive accuracy for renal cell carcinoma recurrence and investigated whether intratumour heterogeneity affected the precision of the classifier.Methods In this retrospective analysis and multicentre validation study, we used paraffin-embedded specimens from the training set of 227 patients from Sun Yat-sen University (Guangzhou, Guangdong, China) with localised clear cell renal cell carcinoma to examine 44 potential recurrence-associated SNPs, which were identified by exploratory bioinformatics analyses of a genome-wide association study from The Cancer Genome Atlas (TCGA) Kidney Renal Clear Cell Carcinoma (KIRC) dataset (n=114, 906 600 SNPs). We developed a six-SNP-based classifier by use of LASSO Cox regression, based on the association between SNP status and patients' recurrence-free survival. Intratumour heterogeneity was investigated from two other regions within the same tumours in the training set. The six-SNP-based classifier was validated in the internal testing set (n=226), the independent validation set (Chinese multicentre study; 428 patients treated between Jan 1, 2004 and Dec 31, 2012, at three hospitals in China), and TCGA set (441 retrospectively identified patients who underwent resection between 1998 and 2010 for localised clear cell renal cell carcinoma in the USA). The main outcome was recurrence-free survival; the secondary outcome was overall survival.Findings Although intratumour heterogeneity was found in 48 (23%) of 206 cases in the internal testing set with complete SNP information, the predictive accuracy of the six-SNP-based classifier was similar in the three different regions of the training set (areas under the curve [AUC] at 5 years: 0.749 [95% CI 0.660-0.826] in region 1,0.734 [0.651-0.814] in region 2, and 0.736 [0.649-0.824] in region 3). The six-SNP-based classifier precisely predicted recurrence-free survival of patients in three validation sets (hazard ratio [HR] 5.32 [95% CI 2.81-10.07] in the internal testing set, 5.39 [3.38-8.59] in the independent validation set, and 4.62 [2.48-8.61] in the TCGA set; all p