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基于微阵列的基因表达测试在确定低分化和未分化癌症组织来源方面的实验室间性能。

Interlaboratory performance of a microarray-based gene expression test to determine tissue of origin in poorly differentiated and undifferentiated cancers.

作者信息

Dumur Catherine I, Lyons-Weiler Maureen, Sciulli Christin, Garrett Carleton T, Schrijver Iris, Holley Tara K, Rodriguez-Paris Juan, Pollack Jonathan R, Zehnder James L, Price Melissa, Hagenkord Jill M, Rigl C Ted, Buturovic Ljubomir J, Anderson Glenda G, Monzon Federico A

机构信息

Department of Pathology, Virginia Commonwealth University, Richmond, Virginia, USA.

出版信息

J Mol Diagn. 2008 Jan;10(1):67-77. doi: 10.2353/jmoldx.2008.070099. Epub 2007 Dec 13.

Abstract

Clinical workup of metastatic malignancies of unknown origin is often arduous and expensive and is reported to be unsuccessful in 30 to 60% of cases. Accurate classification of uncertain primary cancers may improve with microarray-based gene expression testing. We evaluated the analytical performance characteristics of the Pathwork tissue of origin test, which uses expression signals from 1668 probe sets in a gene expression microarray, to quantify the similarity of tumor specimens to 15 known tissues of origin. Sixty archived tissue specimens from poorly and undifferentiated tumors (metastatic and primary) were analyzed at four laboratories representing a wide range of preanalytical conditions (eg, personnel, reagents, instrumentation, and protocols). Cross-laboratory comparisons showed highly reproducible results between laboratories, with correlation coefficients between 0.95 to 0.97 for measurements of similarity scores, and an average 93.8% overall concordance between laboratories in terms of final tissue calls. Bland-Altman plots (mean coefficients of reproducibility of 32.48+/-3.97) and kappa statistics (kappa >0.86) also indicated a high level of agreement between laboratories. We conclude that the Pathwork tissue of origin test is a robust assay that produces consistent results in diverse laboratory conditions reflecting the preanalytical variations found in the everyday clinical practice of molecular diagnostics laboratories.

摘要

对原发灶不明的转移性恶性肿瘤进行临床检查往往既费力又昂贵,据报道,在30%至60%的病例中检查结果并不理想。基于微阵列的基因表达检测可能会改善对不确定原发癌的准确分类。我们评估了Pathwork组织来源检测的分析性能特征,该检测利用基因表达微阵列中1668个探针集的表达信号,来量化肿瘤标本与15种已知组织来源的相似性。在四个代表广泛分析前条件(如人员、试剂、仪器和方案)的实验室中,对60份来自低分化和未分化肿瘤(转移性和原发性)的存档组织标本进行了分析。实验室间比较显示,各实验室结果具有高度可重复性,相似性评分测量的相关系数在0.95至0.97之间,各实验室在最终组织分类方面的总体一致性平均为93.8%。Bland-Altman图(平均重复性系数为32.48±3.97)和kappa统计(kappa>0.86)也表明各实验室之间具有高度一致性。我们得出结论,Pathwork组织来源检测是一种可靠的检测方法,在反映分子诊断实验室日常临床实践中所发现的分析前差异的不同实验室条件下,能产生一致的结果。

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