亚型
胎儿游离DNA
计算生物学
肿瘤科
核小体
医学
内科学
染色质
癌症研究
DNA
生物
计算机科学
遗传学
程序设计语言
胎儿
产前诊断
怀孕
作者
Anna-Lisa Doebley,Minjeong Ko,Hanna Liao,Aimee E Cruikshank,Katheryn Santos,Caroline Kikawa,Joseph Hiatt,Robert D. Patton,Navonil De Sarkar,Katharine A. Collier,Anna C. H. Hoge,Katharine Chen,Anat Zimmer,Zachary Weber,Mohamed Adil,Jonathan Reichel,Paz Polak,Viktor A. Adalsteinsson,Peter S. Nelson,David MacPherson,Heather A. Parsons,Daniel G. Stover,Gavin Ha
标识
DOI:10.1038/s41467-022-35076-w
摘要
Abstract Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we develop Griffin, a framework for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing data. Griffin employs a GC correction procedure tailored to variable cfDNA fragment sizes, which generates a better representation of chromatin accessibility and improves the accuracy of cancer detection and tumor subtype classification. We demonstrate estrogen receptor subtyping from cfDNA in metastatic breast cancer. We predict estrogen receptor subtype in 139 patients with at least 5% detectable circulating tumor DNA with an area under the receive operator characteristic curve (AUC) of 0.89 and validate performance in independent cohorts (AUC = 0.96). In summary, Griffin is a framework for accurate tumor subtyping and can be generalizable to other cancer types for precision oncology applications.
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