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从 bulk tumor ATAC-Seq 数据中稳健估计癌症和免疫细胞类型比例。

Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data.

机构信息

Department of Oncology, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.

Agora Cancer Research Center, Lausanne, Switzerland.

出版信息

Elife. 2024 Oct 9;13:RP94833. doi: 10.7554/eLife.94833.

Abstract

Assay for Transposase-Accessible Chromatin sequencing (ATAC-Seq) is a widely used technique to explore gene regulatory mechanisms. For most ATAC-Seq data from healthy and diseased tissues such as tumors, chromatin accessibility measurement represents a mixed signal from multiple cell types. In this work, we derive reliable chromatin accessibility marker peaks and reference profiles for most non-malignant cell types frequently observed in the microenvironment of human tumors. We then integrate these data into the EPIC deconvolution framework (Racle et al., 2017) to quantify cell-type heterogeneity in bulk ATAC-Seq data. Our EPIC-ATAC tool accurately predicts non-malignant and malignant cell fractions in tumor samples. When applied to a human breast cancer cohort, EPIC-ATAC accurately infers the immune contexture of the main breast cancer subtypes.

摘要

转座酶可及染色质测序(ATAC-Seq)分析是一种广泛用于探索基因调控机制的技术。对于大多数来自健康和患病组织(如肿瘤)的 ATAC-Seq 数据,染色质可及性测量代表了来自多种细胞类型的混合信号。在这项工作中,我们为人类肿瘤微环境中经常观察到的大多数非恶性细胞类型推导出可靠的染色质可及性标记峰和参考图谱。然后,我们将这些数据整合到 EPIC 去卷积框架(Racle 等人,2017)中,以量化批量 ATAC-Seq 数据中的细胞类型异质性。我们的 EPIC-ATAC 工具可准确预测肿瘤样本中非恶性和恶性细胞的分数。当应用于人类乳腺癌队列时,EPIC-ATAC 可准确推断主要乳腺癌亚型的免疫结构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5178/11464006/3b76e5902ff8/elife-94833-fig1.jpg

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