SCISSOR™:用于肿瘤微环境关联研究的单细胞特异性位点组学资源。

NAR Cancer Pub Date : 2021-09-09 eCollection Date: 2021-09-01 DOI:10.1093/narcan/zcab037
Xiang Cui, Fei Qin, Xuanxuan Yu, Feifei Xiao, Guoshuai Cai
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引用次数: 1

摘要

肿瘤微环境中肿瘤组织具有异质性,细胞类型不同,在肿瘤发生和发展中起着重要作用。已经开发了几种计算算法和工具来从大量转录组谱中推断细胞组成。然而,它们忽略了组织特异性,因此需要一种新的组织特异性细胞转录组参考资源来推断肿瘤微环境中的细胞组成,并探索它们与临床结果和肿瘤组学的关联。在这项研究中,我们开发了在线开放资源SCISSOR™(https://thecailab.com/scissor/),通过整合5个正交组学数据,包括6031个大规模样本、患者临床结果和451 917个16种癌症类型的高粒度组织特异性单细胞转录组学图谱,来满足这一需求。SCISSOR™提供了五个主要的分析模块,使灵活的建模与可调参数和动态可视化方法。通过描绘组织特异性肿瘤微环境中的细胞并表征其与肿瘤组学和临床结果的关联,SCISSOR™作为促进肿瘤异质性和肿瘤-肿瘤微环境细胞相互作用研究的新资源是有价值的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

SCISSOR™: a single-cell inferred site-specific omics resource for tumor microenvironment association study.

SCISSOR™: a single-cell inferred site-specific omics resource for tumor microenvironment association study.

SCISSOR™: a single-cell inferred site-specific omics resource for tumor microenvironment association study.

SCISSOR™: a single-cell inferred site-specific omics resource for tumor microenvironment association study.

Tumor tissues are heterogeneous with different cell types in tumor microenvironment, which play an important role in tumorigenesis and tumor progression. Several computational algorithms and tools have been developed to infer the cell composition from bulk transcriptome profiles. However, they ignore the tissue specificity and thus a new resource for tissue-specific cell transcriptomic reference is needed for inferring cell composition in tumor microenvironment and exploring their association with clinical outcomes and tumor omics. In this study, we developed SCISSOR™ (https://thecailab.com/scissor/), an online open resource to fulfill that demand by integrating five orthogonal omics data of >6031 large-scale bulk samples, patient clinical outcomes and 451 917 high-granularity tissue-specific single-cell transcriptomic profiles of 16 cancer types. SCISSOR™ provides five major analysis modules that enable flexible modeling with adjustable parameters and dynamic visualization approaches. SCISSOR™ is valuable as a new resource for promoting tumor heterogeneity and tumor-tumor microenvironment cell interaction research, by delineating cells in the tissue-specific tumor microenvironment and characterizing their associations with tumor omics and clinical outcomes.

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