从和到不和:组织中的多细胞协调及其在癌症中的重新连接
Merve Dede1, Vakul Mohanty1, Ken Chen2
1The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Cancer research
|July 23, 2025
概括
研究人员开发了CoVarNet,这是一个计算框架,可以在人体组织中映射多细胞模块 (CM). 癌症的进展破坏了这些CM,形成了一个新的癌症相关生态系统,提供了诊断和治疗的见解.
科学领域:
- 计算生物学是一种计算生物学.
- 系统生物学 系统生物学
- 翻译性瘤学是指翻译性瘤学.
背景情况:
- 组织功能依赖于复杂的细胞相互作用,但它们的组织和疾病中的变化不明.
- 当前的研究往往集中在单个细胞上,忽视了多细胞协调.
- 了解组织组织水平对于疾病诊断和治疗至关重要.
研究的目的:
- 引入CoVarNet,这是一个用于在人体组织中映射多细胞模块 (CM) 的计算框架.
- 研究CM如何在生物转变和疾病期间组织和动态变化.
- 探索组织生态系统重新连接对癌症进展的影响.
主要方法:
- 利用来自35个人体组织的单细胞和空间转录组学数据.
- 开发了CoVarNet以识别可复制的多细胞模块 (CM).
- 在衰老,更年期和癌症进展中分析了CM动态.
主要成果:
- 识别了功能性多细胞模块 (CMs),包括免疫,树皮和内皮细胞.
- 在衰老和更年期期间,CMs的动态变化得到证明.
- 在癌症进展过程中揭示了组织特异性CM的分解和融合癌症相关生态系统 (cCM02) 的出现.
结论:
- CoVarNet提供了一个可通用的框架,用于使用多式联络数据剖析组织层面的协调.
- 癌症的进展涉及到生态系统层面的组织架构的根本性重组.
- 确定的与癌症相关的生态系统为瘤诊断和治疗提供了新的机会.
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