Division of Bioinformatics & Biostatistics, NCTR, US FDA, Jefferson, AR 72079, USA.
Division of Biochemical Toxicology, NCTR, US FDA, Jefferson, AR 72079, USA.
Biomark Med. 2020 Sep;14(13):1255-1263. doi: 10.2217/bmm-2019-0599.
Recent studies have revealed that circulating microRNAs are promising biomarkers for detecting toxicity or disease. Quantitative real-time polymerase chain reaction (qPCR) is often used to measure the levels of microRNAs. Besides complete and certain data, investigators inevitably have observed technically incomplete or uncertain qPCR data. Investigators usually set incomplete observations equal to the maximum quality number of qPCR cycles, apply the complete-observation method, or choose not to analyze targets with incomplete observations. Using biostatistical knowledge and published studies, we show that three commonly applied methods tend to cause biased inference and decrease reproducibility in biomarker detection. More efforts are needed to address the challenges to identify and detect reliable, novel circulating biomarkers in liquid biopsies.
最近的研究表明，循环 microRNAs 是检测毒性或疾病的有前途的生物标志物。实时定量聚合酶链反应（qPCR）常用于测量 microRNAs 的水平。除了完整和确定的数据外，研究人员不可避免地观察到技术上不完整或不确定的 qPCR 数据。研究人员通常将不完整的观察值设置为 qPCR 循环的最大质量数，应用完整观察值方法，或选择不分析具有不完整观察值的目标。利用生物统计学知识和已发表的研究，我们表明，三种常用的方法往往会导致偏倚推断，并降低生物标志物检测的可重复性。需要进一步努力解决在液体活检中识别和检测可靠、新颖的循环生物标志物的挑战。
