美国斯坦福大学医学院Ash A. Alizadeh和Maximilian Diehn团队合作从细胞游离DNA (cfDNA)片段化谱推断基因表达。该项研究成果发表在2022年3月31日出版的《自然—生物技术》上。

他们将启动子片段化熵描述为一种表观基因组 cfDNA 特征，可预测单个基因的 RNA 表达水平。他们开发了“来自无细胞 DNA 测序的表观遗传表达推断”（EPIC-seq），一种使用目标基因启动子测序的方法。他们分析了来自 201 名癌症患者和 87 名健康成人的 329 份血液样本，展示了肺癌和弥漫性大 B 细胞淋巴瘤亚型的分类。将 EPIC-seq 应用于接受 PD-(L)1 免疫检查点抑制剂治疗的患者的系列血液样本，他们表明 EPIC-seq 推断的基因表达谱与临床反应相关。他们的结果表明，EPIC-seq 可以实现具有诊断、预后和治疗潜力的无创、高通量的起源组织表征。

据介绍，血流中循环肿瘤 DNA (ctDNA) 的分析显示了非侵入性癌症检测的前景。此前已探索染色质片段化特征以从cfDNA推断基因表达谱，但目前的片段组学方法需要高浓度的肿瘤衍生 DNA 并提供有限的分辨率。

附：英文原文

Title: Inferring gene expression from cell-free DNA fragmentation profiles

Author: Esfahani, Mohammad Shahrokh, Hamilton, Emily G., Mehrmohamadi, Mahya, Nabet, Barzin Y., Alig, Stefan K., King, Daniel A., Steen, Chlo B., Macaulay, Charles W., Schultz, Andre, Nesselbush, Monica C., Soo, Joanne, Schroers-Martin, Joseph G., Chen, Binbin, Binkley, Michael S., Stehr, Henning, Chabon, Jacob J., Sworder, Brian J., Hui, Angela B-Y, Frank, Matthew J., Moding, Everett J., Liu, Chih Long, Newman, Aaron M., Isbell, James M., Rudin, Charles M., Li, Bob T., Kurtz, David M., Diehn, Maximilian, Alizadeh, Ash A.

Issue&Volume: 2022-03-31

Abstract: Profiling of circulating tumor DNA (ctDNA) in the bloodstream shows promise for noninvasive cancer detection. Chromatin fragmentation features have previously been explored to infer gene expression profiles from cell-free DNA (cfDNA), but current fragmentomic methods require high concentrations of tumor-derived DNA and provide limited resolution. Here we describe promoter fragmentation entropy as an epigenomic cfDNA feature that predicts RNA expression levels at individual genes. We developed ‘epigenetic expression inference from cell-free DNA-sequencing’ (EPIC-seq), a method that uses targeted sequencing of promoters of genes of interest. Profiling 329 blood samples from 201 patients with cancer and 87 healthy adults, we demonstrate classification of subtypes of lung carcinoma and diffuse large B cell lymphoma. Applying EPIC-seq to serial blood samples from patients treated with PD-(L)1 immune-checkpoint inhibitors, we show that gene expression profiles inferred by EPIC-seq are correlated with clinical response. Our results indicate that EPIC-seq could enable noninvasive, high-throughput tissue-of-origin characterization with diagnostic, prognostic and therapeutic potential.

DOI: 10.1038/s41587-022-01222-4

Source: https://www.nature.com/articles/s41587-022-01222-4