癌症患者全基因組無細胞DNA片段分析
作者：
小柯機器人發布時間：2019/7/25 14:23:08
美國約翰霍普金斯大學醫學院Victor E. Velculescu團隊對癌症患者全基因組無細胞DNA片段進行了分析，該研究成果發表在2019年6月出版的《自然》雜誌上。
該課題組開發了一種方法來評估基因組中無細胞DNA的碎裂譜，並發現健康個體的特徵反映了白細胞的核小體模式，而癌症患者則改變了片段模式。研究人員採用該方法分析了236例乳腺癌、結直腸癌、肺癌、卵巢癌、胰腺癌、胃癌或膽管癌患者和245例健康人的碎片特徵。結合了全基因組片段特徵的機器學習模型在7種癌症類型中的檢測靈敏度從57%到99%以上，特異性為98%，總曲線下面積為0.94。在75%的病例中，碎裂譜可將癌症起源組織鑑定到有限幾個位點。將此方法與基於突變的無細胞DNA分析相結合，檢測出91%的癌症患者。這些分析結果強調了無細胞DNA的重要特性，並為篩選、早期檢測和監測人類癌症提供了一種原理驗證方法。
研究人員表示，血液中的無細胞DNA為癌症患者提供了非侵入性的診斷途徑。然而目前對無細胞DNA的起源和分子特點的特徵知之甚少。
附：英文原文
Title: Genome-wide cell-free DNA fragmentation in patients with cancer
Author: Stephen Cristiano, Alessandro Leal, Jillian Phallen, Jacob Fiksel, Vilmos Adleff, Daniel C. Bruhm, Sarah strup Jensen, Jamie E. Medina, Carolyn Hruban, James R. White, Doreen N. Palsgrove, Noushin Niknafs, Valsamo Anagnostou, Patrick Forde, Jarushka Naidoo, Kristen Marrone, Julie Brahmer, Brian D. Woodward, Hatim Husain, Karlijn L. van Rooijen, Mai-Britt Worm rntoft, Anders Husted Madsen, Cornelis J. H. van de Velde, Marcel Verheij, Annemieke Cats, Cornelis J. A. Punt, Geraldine R. Vink, Nicole C. T. van Grieken, Miriam Koopman, Remond J. A. Fijneman, Julia S. Johansen, Hans Jrgen Nielsen, Gerrit A. Meijer, Claus Lindbjerg Andersen, Robert B. Scharpf, Victor E. Velculescu
Issue&Volume: Volume 570 Issue 7761, 20 June 2019
Abstract: Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer1. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.
DOI: 10.1038/s41586-019-1272-6
Source:https://www.nature.com/articles/s41586-019-1272-6