Single-cell signatures identify microenvironment factors in tumors associated with patient outcomes.

IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Cell Reports Methods Pub Date : 2024-06-17 DOI:10.1016/j.crmeth.2024.100799
Yuanqing Xue, Verena Friedl, Hongxu Ding, Christopher K Wong, Joshua M Stuart
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引用次数: 0

Abstract

The cellular components of tumors and their microenvironment play pivotal roles in tumor progression, patient survival, and the response to cancer treatments. Unveiling a comprehensive cellular profile within bulk tumors via single-cell RNA sequencing (scRNA-seq) data is crucial, as it unveils intrinsic tumor cellular traits that elude identification through conventional cancer subtyping methods. Our contribution, scBeacon, is a tool that derives cell-type signatures by integrating and clustering multiple scRNA-seq datasets to extract signatures for deconvolving unrelated tumor datasets on bulk samples. Through the employment of scBeacon on the The Cancer Genome Atlas (TCGA) cohort, we find cellular and molecular attributes within specific tumor categories, many with patient outcome relevance. We developed a tumor cell-type map to visually depict the relationships among TCGA samples based on the cell-type inferences.

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单细胞特征识别出与患者预后相关的肿瘤微环境因素。
肿瘤的细胞成分及其微环境在肿瘤进展、患者生存和对癌症治疗的反应中起着关键作用。通过单细胞 RNA 测序(scRNA-seq)数据揭示大块肿瘤内的全面细胞特征至关重要,因为它揭示了传统癌症亚型鉴定方法无法识别的肿瘤细胞内在特征。我们的成果 scBeacon 是一种通过整合和聚类多个 scRNA-seq 数据集来提取细胞类型特征的工具,用于解构大样本中不相关的肿瘤数据集。通过在癌症基因组图谱(TCGA)队列中使用 scBeacon,我们发现了特定肿瘤类别中的细胞和分子属性,其中许多与患者预后相关。我们开发了肿瘤细胞类型图,根据细胞类型推断直观地描述了 TCGA 样本之间的关系。
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来源期刊
Cell Reports Methods
Cell Reports Methods Chemistry (General), Biochemistry, Genetics and Molecular Biology (General), Immunology and Microbiology (General)
CiteScore
3.80
自引率
0.00%
发文量
0
审稿时长
111 days
期刊最新文献
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