Ren Annie H, Fiala Clare A, Diamandis Eleftherios P, Kulasingam Vathany
Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada.
Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
Cancer Epidemiol Biomarkers Prev. 2020 Dec;29(12):2568-2574. doi: 10.1158/1055-9965.EPI-20-0074. Epub 2020 Apr 10.
Despite significant investment of funds and resources, few new cancer biomarkers have been introduced to the clinic in the last few decades. Although many candidates produce promising results in the laboratory, deficiencies in sensitivity, specificity, and predictive value make them less than desirable in a patient setting. This review will analyze these challenges in detail as well as discuss false discovery, problems with reproducibility, and tumor heterogeneity. Circulating tumor DNA (ctDNA), an emerging cancer biomarker, is also analyzed, particularly in the contexts of assay specificity, sensitivity, fragmentation, lead time, mutant allele fraction, and clinical relevance. Emerging artificial intelligence technologies will likely be valuable tools in maximizing the clinical utility of ctDNA which is often found in very small quantities in patients with early-stage tumors. Finally, the implications of challenging false discoveries are examined and some insights about improving cancer biomarker discovery are provided.
尽管投入了大量资金和资源,但在过去几十年里,很少有新的癌症生物标志物被引入临床。虽然许多候选物在实验室中产生了有希望的结果,但敏感性、特异性和预测价值方面的不足使得它们在患者环境中不尽人意。本综述将详细分析这些挑战,并讨论假发现、可重复性问题和肿瘤异质性。循环肿瘤DNA(ctDNA)作为一种新兴的癌症生物标志物也将被分析,特别是在检测特异性、敏感性、片段化、提前期、突变等位基因分数和临床相关性方面。新兴的人工智能技术可能会成为最大化ctDNA临床效用的有价值工具,ctDNA在早期肿瘤患者中通常含量极少。最后,研究了具有挑战性的假发现的影响,并提供了一些关于改进癌症生物标志物发现的见解。