Improving needle biopsy accuracy in small renal mass using tumor-specific DNA methylation markers.
Improving needle biopsy accuracy in small renal mass using tumor-specific DNA methylation markers.
复制标题
DOI：
10.18632/oncotarget.12276
复制
发表时间：
2017-01-17
期刊：
影响因子：
--
通讯作者：
Siegmund KD
中科院分区：
文献类型：
--
作者：
Chopra S;Liu J;Alemozaffar M;Nichols PW;Aron M;Weisenberger DJ;Collings CK;Syan S;Hu B;Desai M;Aron M;Duddalwar V;Gill I;Liang G;Siegmund KD
肾小肿块(SRM)的临床处理具有挑战性，因为目前区分良性肿块和恶性肾细胞癌(RCC)的方法往往不准确或不确定。此外，肾癌亚型也有不同的治疗方法和结果。高的假阴性率增加了癌症进展的风险，不确定的诊断导致了不必要的和潜在的病态外科手术。我们使用来自六个不同亚组的697个DNA甲基化图谱建立了一个肾脏肿瘤的预测分类模型：透明细胞、乳头状和嫌色肾细胞癌、良性血管多米脂肪瘤、嗜酸细胞瘤和正常肾组织。此外，DNA甲基化依赖的分类器已经在来自100个肾肿块(71%的SRM)的272个体外针刺活检样本中得到验证。总的来说，从活检中预测相同的恶性亚型的结果具有很高的重复性(89%，n=70)。总体上，98%的邻近正常组织(n=102)被正确归类为正常，92%(n=71)的肿瘤被正确归类为恶性，86%的良性肿瘤(n=29)被正确归类为良性。总体而言，本研究为使用常规针吸活检确定SRM的肿瘤分类提供了分子基础支持，并支持临床决策。
The clinical management of small renal masses (SRMs) is challenging since the current methods for distinguishing between benign masses and malignant renal cell carcinomas (RCCs) are frequently inaccurate or inconclusive. In addition, renal cancer subtypes also have different treatments and outcomes. High false negative rates increase the risk of cancer progression and indeterminate diagnoses result in unnecessary and potentially morbid surgical procedures. We built a predictive classification model for kidney tumors using 697 DNA methylation profiles from six different subgroups: clear cell, papillary and chromophobe RCC, benign angiomylolipomas, oncocytomas, and normal kidney tissues. Furthermore, the DNA methylation-dependent classifier has been validated in 272 ex vivo needle biopsy samples from 100 renal masses (71% SRMs). In general, the results were highly reproducible (89%, n=70) in predicting identical malignant subtypes from biopsies. Overall, 98% of adjacent-normals (n=102) were correctly classified as normal, while 92% of tumors (n=71) were correctly classified malignant and 86% of benign (n=29) were correctly classified benign by this classification model. Overall, this study provides molecular-based support for using routine needle biopsies to determine tumor classification of SRMs and support the clinical decision-making.