Nickason Cole C, Khaitan Vanshika, Clark-Baba Connor, Torrez Alberto G, Salnikov Mikhail Y, Siraj Kabir, Cariba Solsa, Chowdhury Fuad, Han Hong
Centre for Discovery in Cancer Research, McMaster University, Hamilton, ON, Canada.
Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada.
Methods Mol Biol. 2025;2944:227-237. doi: 10.1007/978-1-0716-4654-0_18.
Glioblastoma (GBM) is the most common and lethal primary adult brain tumor. It represents a rapidly evolving ecosystem, including heterogeneous tumor cells and an immunosuppressive tumor microenvironment (TME) with diverse non-malignant cells. High-throughput single-cell omics profiling, such as single-cell and single-nucleus RNA sequencing (scRNA-seq and snRNA-seq, respectively), is an emerging powerful tool to deconvolute diverse cell types and states as well as intricate cellular and molecular functions and interactions that underlie the complex GBM ecosystem. snRNA-seq is a methodology that profiles the transcriptome using isolated nuclei instead of intact cells. It is an alternative to scRNA-seq and is compatible with frozen samples and difficult-to-dissociate tissues, such as brain or brain tumor tissues. However, efficient, optimized procedures are instrumental in preparing high-quality single nuclei from clinical GBM specimens and patient-derived GBM cell lines across different conditions for snRNA-seq. Here, we provide a toolkit of detailed protocols for nucleus isolation, counting, and quality control, enabling a streamlined single-nucleus preparation for snRNA-seq characterization.
胶质母细胞瘤（GBM）是成人中最常见且致命的原发性脑肿瘤。它代表了一个快速演变的生态系统，包括异质性肿瘤细胞以及具有多种非恶性细胞的免疫抑制性肿瘤微环境（TME）。高通量单细胞组学分析，如单细胞和单细胞核RNA测序（分别为scRNA-seq和snRNA-seq），是一种新兴的强大工具，可用于解析构成复杂GBM生态系统的各种细胞类型和状态，以及复杂的细胞和分子功能与相互作用。snRNA-seq是一种使用分离的细胞核而非完整细胞来分析转录组的方法。它是scRNA-seq的替代方法，并且与冷冻样本以及诸如脑或脑肿瘤组织等难以解离的组织兼容。然而，高效、优化的程序对于在不同条件下从临床GBM标本和患者来源的GBM细胞系中制备用于snRNA-seq的高质量单细胞核至关重要。在此，我们提供了一套详细的方案工具包，用于细胞核分离、计数和质量控制，从而实现用于snRNA-seq表征的简化单细胞核制备。
