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从空间解析的转录组学数据绘制细胞相互作用的地图.

James Zhu1, Yunguan Wang1,2,3, Woo Yong Chang1

  • 1Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.

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概括
此摘要是机器生成的。

我们开发了spacia,这是一个新的贝叶斯框架,用于使用空间转录学分析细胞细胞通信 (CCC). Spacia精确地绘制了细胞之间的基因表达相互作用,克服了现有工具的局限性,并揭示了对癌症和免疫力的新见解.

关键词:
这是GeoMXX的.这就是MERSCOPE的目的.细胞相互作用 细胞相互作用斯帕西亚 (Spaciacia) 是一个空间.空间分辨率的转录学

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科学领域:

  • 计算生物学 计算生物学
  • 基因组学就是基因组学.
  • 系统生物学 系统生物学

背景情况:

  • 细胞-细胞通信 (CCC) 是生物系统的基础.
  • 空间解析的转录组学 (SRT) 能够在单细胞分辨率下对基因表达进行高通量映射.
  • 对CCC分析复杂的SRT数据仍然具有挑战性,现有的方法存在局限性.

研究的目的:

  • 介绍spacia,贝叶斯的多实例学习框架,用于从SRT数据中检测CCC.
  • 利用SRTs的空间模式来克服当前CCC分析工具的局限性.
  • 为推进细胞通信的定量理论提供一个强大的计算框架.

主要方法:

  • 开发了spacia,这是一个贝叶斯的多实例学习框架.
  • 利用SRT数据中固有的空间信息.
  • 在多个商业SRT平台 (MERSCOPE/Vizgen,CosMx/Nanostring,Xenium/10X) 上验证了空间.

主要成果:

  • Spacia准确地检测到CCC,克服了像分辨率损失和高假阳性率这样的局限性.
  • 鉴定了内皮细胞,纤维细胞和B细胞对前列腺癌上皮质-介质细胞过渡的贡献.
  • 在泛癌数据集中揭示了B细胞参与PDL1/PD1信号传递.
  • 开发了一种CD8+T细胞/PDL1有效性特征,与患者的存活率和免疫治疗反应相关.
  • 在健康和癌症肝脏组织中发现了 γδ T 细胞和肝细胞之间的差异空间相互作用.

结论:

  • Spacia提供了一种强大的新方法,可以从SRT数据中推断CCC.
  • 该框架解决了现有的CCC分析工具的关键局限性.
  • Spacia为癌症,免疫和组织相互作用提供了新的生物学见解,推进了细胞通信的定量理论.