Bone Marrow Transplantation Center of the First Affiliated Hospital, and Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Liangzhu Laboratory, Zhejiang University, Hangzhou, 311121, China.
Adv Sci (Weinh). 2024 Feb;11(5):e2304755. doi: 10.1002/advs.202304755. Epub 2023 Nov 27.
Tumor heterogeneity and its drivers impair tumor progression and cancer therapy. Single-cell RNA sequencing is used to investigate the heterogeneity of tumor ecosystems. However, most methods of scRNA-seq amplify the termini of polyadenylated transcripts, making it challenging to perform total RNA analysis and somatic mutation analysis.Therefore, a high-throughput and high-sensitivity method called snHH-seq is developed, which combines random primers and a preindex strategy in the droplet microfluidic platform. This innovative method allows for the detection of total RNA in single nuclei from clinically frozen samples. A robust pipeline to facilitate the analysis of full-length RNA-seq data is also established. snHH-seq is applied to more than 730 000 single nuclei from 32 patients with various tumor types. The pan-cancer study enables it to comprehensively profile data on the tumor transcriptome, including expression levels, mutations, splicing patterns, clone dynamics, etc. New malignant cell subclusters and exploring their specific function across cancers are identified. Furthermore, the malignant status of epithelial cells is investigated among different cancer types with respect to mutation and splicing patterns. The ability to detect full-length RNA at the single-nucleus level provides a powerful tool for studying complex biological systems and has broad implications for understanding tumor pathology.
肿瘤异质性及其驱动因素会影响肿瘤的进展和癌症治疗。单细胞 RNA 测序用于研究肿瘤生态系统的异质性。然而,大多数 scRNA-seq 方法都扩增了多聚腺苷酸化转录本的末端,这使得进行总 RNA 分析和体细胞突变分析具有挑战性。因此,开发了一种称为 snHH-seq 的高通量和高灵敏度方法,它结合了随机引物和液滴微流控平台中的预索引策略。这种创新方法允许从临床冷冻样本中的单个核中检测总 RNA。还建立了一个强大的管道来促进全长 RNA-seq 数据的分析。snHH-seq 应用于来自 32 名患有各种肿瘤类型的患者的超过 730,000 个单个核。泛癌研究使它能够全面分析肿瘤转录组的数据,包括表达水平、突变、剪接模式、克隆动态等。确定了新的恶性细胞亚群,并在癌症之间探索了它们的特定功能。此外,还研究了不同癌症类型中上皮细胞的恶性状态,根据突变和剪接模式进行研究。在单细胞水平检测全长 RNA 的能力为研究复杂的生物系统提供了强大的工具,并对理解肿瘤病理学具有广泛的意义。