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Pan-Cancer Single-Nucleus Total RNA Sequencing Using snHH-Seq.
Haide Chen1,2,3, Xiunan Fang4, Jikai Shao1,2
1Bone Marrow Transplantation Center of the First Affiliated Hospital, and Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|November 27, 2023
Summary
A new method, snHH-seq, analyzes total RNA in single nuclei, overcoming limitations of standard scRNA-seq for tumor heterogeneity studies. This enables comprehensive pan-cancer analysis of mutations and splicing patterns.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Tumor heterogeneity significantly impacts cancer progression and treatment efficacy.
- Current single-cell RNA sequencing (scRNA-seq) methods primarily analyze polyadenylated transcripts, limiting comprehensive analysis of total RNA and somatic mutations.
- Investigating tumor ecosystems requires advanced techniques to capture diverse cellular and molecular features.
Purpose of the Study:
- To develop a high-throughput, high-sensitivity method for total RNA analysis in single nuclei.
- To enable comprehensive profiling of tumor transcriptomes, including mutations, splicing, and clone dynamics.
- To advance the understanding of tumor pathology and heterogeneity across various cancer types.
Main Methods:
- Development of snHH-seq, a novel droplet microfluidic method combining random primers and a preindex strategy.
- Application of snHH-seq to over 730,000 single nuclei from 32 diverse cancer patients.
- Establishment of a robust bioinformatics pipeline for analyzing full-length RNA-seq data.
Main Results:
- snHH-seq successfully detected total RNA in single nuclei from frozen clinical samples.
- Pan-cancer analysis revealed novel malignant cell subclusters and their functions.
- Comprehensive profiling identified mutation and splicing patterns associated with malignant epithelial cells across different cancer types.
Conclusions:
- snHH-seq provides a powerful tool for single-nucleus, full-length RNA analysis, overcoming previous technical limitations.
- The method facilitates in-depth exploration of tumor heterogeneity, including clonal dynamics and molecular alterations.
- This approach has broad implications for understanding cancer biology and developing targeted therapies.
