Analytical validity of a microRNA-based assay for diagnosing indeterminate thyroid FNA smears from routinely prepared cytology slides

基于microRNA的检测方法在诊断常规制备的细胞学涂片中不确定甲状腺细针穿刺涂片结果时的分析有效性

阅读:1

Abstract

BACKGROUND: The majority of thyroid nodules are diagnosed using fine-needle aspiration (FNA) biopsies. The authors recently described the clinical validation of a molecular microRNA-based assay, RosettaGX Reveal, which can diagnose thyroid nodules as benign or suspicious using a single stained FNA smear. This paper describes the analytical validation of the assay. METHODS: More than 800 FNA slides were tested, including slides stained with Romanowsky-type and Papanicolaou stains. The assay was examined for the following features: intranodule concordance, effect of stain type, minimal acceptable RNA amounts, performance on low numbers of thyroid cells, effect of time since sampling, and analytical sensitivity, specificity, and reproducibility. RESULTS: The assay can be run on FNA slides for which as little as 1% of the cells are thyroid epithelial cells or from which only 5 ng of RNA have been extracted. Samples composed entirely of blood failed quality control and were not classified. Stain type did not affect performance. All slides were stored at room temperature. However, the length of time between FNA sampling and processing did not affect assay performance. There was a high level of concordance between laboratories (96%), and the concordance for slides created from the same FNA pass was 93%. CONCLUSIONS: The microRNA-based assay was robust to various physical processing conditions and to differing sample characteristics. Given the assay's performance, robustness, and use of routinely prepared FNA slides, it has the potential to provide valuable aid for physicians in the diagnosis of thyroid nodules. Cancer Cytopathol 2016;124:711-21. © 2016 Rosetta Genomics. Cancer Cytopathology published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。