基于捕获的低通量测序数据的整合片段组学图谱和5-羟甲基胞嘧啶能够通过cfDNA进行泛癌检测。

Integrated fragmentomic profile and 5-Hydroxymethylcytosine of capture-based low-pass sequencing data enables pan-cancer detection via cfDNA.

作者信息

Zhang Zhidong, Pi Xuenan, Gao Chang, Zhang Jun, Xia Lin, Yan Xiaoqin, Hu Xinlei, Yan Ziyue, Zhang Shuxin, Wei Ailin, Guo Yuer, Liu Jingfeng, Li Ang, Liu Xiaolong, Zhang Wei, Liu Yanhui, Xie Dan

机构信息

Laboratory of Omics Technology and Bioinformatics, Frontiers Science Center for Disease-related Molecular Network, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, Sichuan Province, P. R. China.

Tailai Inc., Shanghai 200233, P. R. China.

出版信息

Transl Oncol. 2023 Aug;34:101694. doi: 10.1016/j.tranon.2023.101694. Epub 2023 May 18.

DOI:10.1016/j.tranon.2023.101694

PMID:37209526

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10209323/

Abstract

BACKGROUND

Using epigenetic markers and fragmentomics of cell-free DNA for cancer detection has been proven applicable.

METHODS

We further investigated the diagnostic potential of combining two features (epigenetic markers and fragmentomic information) of cell-free DNA for detecting various types of cancers. To do this, we extracted cfDNA fragmentomic features from 191 whole-genome sequencing data and studied them in 396 low-pass 5hmC sequencing data, which included four common cancer types and control samples.

RESULTS

In our analysis of 5hmC sequencing data from cancer samples, we observed aberrant ultra-long fragments (220-500 bp) that differed from normal samples in terms of both size and coverage profile. These fragments played a significant role in predicting cancer. Leveraging the ability to detect cfDNA hydroxymethylation and fragmentomic markers simultaneously in low-pass 5hmC sequencing data, we developed an integrated model that incorporated 63 features representing both fragmentomic features and hydroxymethylation signatures. This model achieved high sensitivity and specificity for pan-cancer detection (88.52% and 82.35%, respectively).

CONCLUSION

We showed that fragmentomic information in 5hmC sequencing data is an ideal marker for cancer detection and that it shows high performance in low-pass sequencing data.

摘要

背景

利用表观遗传标记和游离DNA片段组学进行癌症检测已被证明是可行的。

方法

我们进一步研究了结合游离DNA的两个特征（表观遗传标记和片段组学信息）用于检测各种类型癌症的诊断潜力。为此，我们从191个全基因组测序数据中提取了游离DNA片段组学特征，并在396个低通量5hmC测序数据中进行研究，这些数据包括四种常见癌症类型和对照样本。

结果

在对癌症样本的5hmC测序数据进行分析时，我们观察到异常的超长片段（220 - 500 bp），其大小和覆盖图谱与正常样本不同。这些片段在预测癌症方面发挥了重要作用。利用在低通量5hmC测序数据中同时检测游离DNA羟甲基化和片段组学标记的能力，我们开发了一个整合模型，该模型纳入了代表片段组学特征和羟甲基化特征的63个特征。该模型在泛癌检测中实现了高灵敏度和特异性（分别为88.52%和82.35%）。