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

Ziye Xu1, Lingchao Chen2, Xin Lin1

  • 1Department of Laboratory Medicine of The First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310003, China.

Small Methods
|July 3, 2024
PubMed

Insights

A new automated single-nucleus RNA sequencing method (snRandom-seq) analyzes formalin-fixed paraffin-embedded (FFPE) glioma samples. This advances understanding of brain cancer molecular diversity and evolution.

Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Gliomas are diverse brain cancers with limited treatment options.
  • Understanding glioma molecular diversity and evolution is crucial for new therapies.
  • Analyzing formalin-fixed paraffin-embedded (FFPE) clinical samples is challenging for molecular studies.

Purpose of the Study:

  • To develop a high-throughput single-nucleus RNA sequencing platform for FFPE samples.
  • To analyze the molecular characteristics of various glioma subtypes, including primary-recurrent glioblastomas (GBMs).
  • To identify non-coding RNAs and recurrence-related targets in gliomas.

Main Methods:

  • Development of automated snRandom-seq, a platform integrating automated single-nucleus isolation and droplet barcoding.
  • Application of snRandom-seq to 116,492 single nuclei from 17 FFPE glioma samples.
  • Analysis of non-coding RNA expression and identification of recurrence-related pathways.

Main Results:

  • Automated snRandom-seq effectively analyzes FFPE samples, accommodating diverse glioma subtypes.
  • Distinct non-coding RNA expression profiles were identified across glioma clusters.
  • Promising recurrence-related targets and pathways were uncovered in primary-recurrent GBMs.

Conclusions:

  • Automated snRandom-seq is a robust tool for single-cell RNA sequencing of FFPE samples.
  • The platform enables exploration of glioma molecular diversity and tumor evolution.
  • This technology has significant implications for large-scale integrative and retrospective clinical research in brain cancer.