Barocas D A, Rohan S M, Kao J, Gurevich R D, Del Pizzo J J, Vaughan E D, Akhtar M, Chen Y-T, Scherr D S
Department of Urology of New York Presbyterian Hospital-Weill Cornell Medical Center, New York, New York 10021, USA.
J Urol. 2006 Nov;176(5):1957-62. doi: 10.1016/j.juro.2006.07.038.
We diagnosed the subtypes of renal cell carcinoma on needle core biopsies using a combination of histopathology and a molecular diagnostic algorithm.
Core biopsies were taken of renal tumors following nephrectomy. RNA was extracted and quantitative real-time polymerase chain reaction was performed for 4 gene products to differentiate among renal cell carcinoma subtypes. Histopathological diagnosis was achieved on a second core before and after obtaining the molecular diagnostic algorithm results.
Based on the nephrectomy diagnosis 6 of 77 renal masses were nonneoplastic and 71 were tumors, including 65 renal cell carcinoma/oncocytomas. The overall diagnostic accuracy using histology and our molecular diagnostic algorithm combined was 90.0% (70 of 77). Side by side comparison of histology vs molecular diagnostic algorithm was feasible for 60 classifiable renal cell carcinoma/oncocytomas (31 clear cell, 14 papillary renal cell carcinoma, 6 chromophobe renal cell carcinoma, 2 mucinous tubular and spindle cell carcinoma, and 7 oncocytoma). In this group histology correctly predicted the final histological subtype in 83.3% (50 of 60) of cores. Addition of the molecular diagnostic algorithm to histology improved the subtyping accuracy to 95% (57 of 60), whereas the molecular diagnostic algorithm alone was accurate in 50 of 60 cases (83.3%). Dividing these 60 specimens into clear cell and nonclear cell neoplasms, the addition of the molecular diagnostic algorithm improved the sensitivity for the diagnosis of clear cell carcinoma from 87.1% (27 of 31) to 100% and the negative predictive value from 87.5% to 100%.
Core biopsies of renal tumors provide adequate material for diagnosing and subtyping renal cell carcinoma. The addition of our molecular diagnostic algorithm to histology improved the diagnostic accuracy of core biopsies of renal masses.
我们使用组织病理学和分子诊断算法相结合的方法,对针芯活检的肾细胞癌亚型进行诊断。
肾切除术后对肾肿瘤进行针芯活检。提取RNA,并对4种基因产物进行定量实时聚合酶链反应,以区分肾细胞癌亚型。在获得分子诊断算法结果之前和之后,对第二根针芯进行组织病理学诊断。
根据肾切除术诊断,77个肾肿块中有6个为非肿瘤性,71个为肿瘤,其中包括65个肾细胞癌/嗜酸细胞瘤。组织学和我们的分子诊断算法相结合的总体诊断准确率为90.0%(77个中的70个)。对于60个可分类的肾细胞癌/嗜酸细胞瘤(31个透明细胞癌、14个乳头状肾细胞癌、6个嫌色肾细胞癌、2个黏液性管状和梭形细胞癌以及7个嗜酸细胞瘤),组织学与分子诊断算法的并行比较是可行的。在这组病例中,组织学在83.3%(60个中的50个)的针芯中正确预测了最终的组织学亚型。将分子诊断算法添加到组织学中可将亚型分类准确率提高到95%(60个中的57个),而单独的分子诊断算法在60个病例中的50个(83.3%)是准确的。将这60个标本分为透明细胞和非透明细胞肿瘤,添加分子诊断算法可将透明细胞癌诊断的敏感性从87.1%(31个中的27个)提高到100%,阴性预测值从87.5%提高到100%。
肾肿瘤的针芯活检为诊断肾细胞癌及其亚型提供了足够的材料。将我们的分子诊断算法添加到组织学中可提高肾肿块针芯活检的诊断准确率。