An automated archival single-nucleus total RNA sequencing platform mapping integrative and retrospective cell atlas of gliomas

Abstract

Single-cell RNA sequencing (scRNA-seq) has dramatically transformed biomedical research within laboratory settings. It has been extensively employed to investigate the heterogeneity and plasticity of glioma, the most prevalent brain tumor. However, the clinical diagnosis and treatment of glioma remain complex and challenging, highlighting the need for comprehensive cancer research. Currently available scRNA-seq platforms are insufficient to fulfill the demands posed by large-scale clinical applications. Here, we present an automated high-throughput single-nucleus total RNA sequencing platform, known as AAsnRandom-seq. This platform integrates automated single-nucleus isolation and droplet barcoding systems with the random primer-based scRNA-seq chemistry, designed to accommodate a diverse range of sample types. The performance and versatility of AAsnRandom-seq are validated using over one hundred clinical FFPE and frozen samples. AAsnRandom-seq was applied to archival FFPE samples of various glioma subtypes, including rare clinical samples, and matched primary-recurrent glioblastomas (GBMs), delving into the comprehensive molecular characteristic of glioma at single-cell level. Abundant non-coding RNAs (ncRNAs) with distinct expression profiles within different glioma clusters are detected. Promising recurrence-related targets and pathways are identified from the matched primary-recurrent GBMs. AAsnRandom-seq holds significant application value on large-scale integrative and retrospective clinical research using archived specimens.