Suppr超能文献

肿瘤细胞状态:单细胞 RNA 测序研究人类肿瘤十年的启示。

Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors.

机构信息

Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 761001, Israel.

Department of Pathology and Krantz Family Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.

出版信息

Cancer Cell. 2024 Sep 9;42(9):1497-1506. doi: 10.1016/j.ccell.2024.08.005. Epub 2024 Aug 29.

Abstract

Human tumors are intricate ecosystems composed of diverse genetic clones and malignant cell states that evolve in a complex tumor micro-environment. Single-cell RNA-sequencing (scRNA-seq) provides a compelling strategy to dissect this intricate biology and has enabled a revolution in our ability to understand tumor biology over the last ten years. Here we reflect on this first decade of scRNA-seq in human tumors and highlight some of the powerful insights gleaned from these studies. We first focus on computational approaches for robustly defining cancer cell states and their diversity and highlight some of the most common patterns of gene expression intra-tumor heterogeneity (eITH) observed across cancer types. We then discuss ambiguities in the field in defining and naming such eITH programs. Finally, we highlight critical developments that will facilitate future research and the broader implementation of these technologies in clinical settings.

摘要

人类肿瘤是由多种遗传克隆和恶性细胞状态组成的复杂生态系统,这些克隆和状态在复杂的肿瘤微环境中不断进化。单细胞 RNA 测序 (scRNA-seq) 提供了一种强大的策略来剖析这种复杂的生物学,并在过去十年中极大地提高了我们理解肿瘤生物学的能力。在这里,我们回顾了人类肿瘤中 scRNA-seq 的第一个十年,并强调了从这些研究中获得的一些有影响力的见解。我们首先关注用于稳健定义癌症细胞状态及其多样性的计算方法,并强调了在不同癌症类型中观察到的一些最常见的肿瘤内异质性 (eITH) 基因表达模式。然后,我们讨论了在定义和命名此类 eITH 程序方面存在的歧义。最后,我们强调了将促进未来研究以及更广泛地将这些技术应用于临床环境的关键进展。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验