Wang Yunze, Hou Yuying, Xiong Zhankun, Lu Libo, Zong Zhanxiang, Wang Bo, Chen Hebing, Zhang Wen, Zhou Xionghui
Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P.R. China; Key Laboratory of Smart Farming for Agricultural Animals, Ministry of Agriculture and Rural Affairs, Beijing, P.R. China; College of Informatics, Huazhong Agricultural University, No. 1, Shizishan Street, Wuhan 430070, P.R. China.
College of Informatics, Huazhong Agricultural University, No. 1, Shizishan Street, Wuhan 430070, P.R. China.
Cell Rep Methods. 2025 Jul 21;5(7):101083. doi: 10.1016/j.crmeth.2025.101083. Epub 2025 Jun 18.
We introduce a cell-free DNA (cfDNA) fragmentation pattern: the fragment dispersity index (FDI), which integrates information on the distribution of cfDNA fragment ends with the variation in fragment coverage, enabling precise characterization of chromatin accessibility in specific regions. The FDI shows a strong correlation with chromatin accessibility and gene expression, and regions with high FDI are enriched in active regulatory elements. Using whole-genome cfDNA data from five datasets, we developed and validated the FDI-oncology model, which demonstrates robust performance in early cancer diagnosis, subtyping, and prognosis. Case studies reveal that key cancer genes such as HER2 and TP53 exhibit significantly different FDIs between cancer and control samples. Simulation experiments suggest that deep targeted sequencing of a small number of regions can achieve high diagnostic efficiency.
我们引入了一种游离DNA(cfDNA)片段化模式:片段分散指数(FDI),它整合了cfDNA片段末端分布信息与片段覆盖度变化,能够精确表征特定区域的染色质可及性。FDI与染色质可及性和基因表达呈现出强烈的相关性,且FDI高的区域富含活性调控元件。利用来自五个数据集的全基因组cfDNA数据,我们开发并验证了FDI肿瘤学模型,该模型在早期癌症诊断、亚型分类和预后评估方面表现出强大的性能。案例研究表明,HER2和TP53等关键癌症基因在癌症样本与对照样本之间表现出显著不同的FDI。模拟实验表明,对少数区域进行深度靶向测序可实现高诊断效率。