Single Nucleus Total RNA Sequencing of Formalin‐Fixed Paraffin‐Embedded Gliomas

核糖核酸 核心 生物 神经科学 遗传学 基因
作者
Ziye Xu,Lingchao Chen,Xin Lin,Yuexiao Lyu,Mofei Zhou,Haide Chen,Heng Zhang,Tianyu Zhang,Yu Chen,Yuanzhen Suo,Qian Liang,Zhiyong Qin,Yongcheng Wang
出处
期刊:Small methods [Wiley]
被引量:2
标识
DOI:10.1002/smtd.202301801
摘要

Gliomas, the predominant form of brain cancer, comprise diverse malignant subtypes with limited curative therapies available. The insufficient understanding of their molecular diversity and evolutionary processes hinders the advancement of new treatments. Technical complexities associated with formalin-fixed paraffin-embedded (FFPE) clinical samples hinder molecular-level analyses of gliomas. Current single-cell RNA sequencing (scRNA-seq) platforms are inadequate for large-scale clinical applications. In this study, automated snRandom-seq is developed, a high-throughput single-nucleus total RNA sequencing platform optimized for archival FFPE samples. This platform integrates automated single-nucleus isolation and droplet barcoding systems with the random primer-based scRNA-seq chemistry, accommodating a broad spectrum of sample types. The automated snRandom-seq is applied to analyze 116 492 single nuclei from 17 FFPE samples of various glioma subtypes, including rare clinical samples and matched primary-recurrent glioblastomas (GBMs). The study provides comprehensive insights into the molecular characteristics of gliomas at the single-cell level. Abundant non-coding RNAs (ncRNAs) with distinct expression profiles across different glioma clusters and uncovered promising recurrence-related targets and pathways in primary-recurrent GBMs are identified. These findings establish automated snRandom-seq as a robust tool for scRNA-seq of FFPE samples, enabling exploration of molecular diversities and tumor evolution. This platform holds significant implications for large-scale integrative and retrospective clinical research.
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