This technology uncovers heterogeneity in drug-resistant lung cancer cells, suggesting pathways for personalized medicine.
sc-rDSeq is a scalable, full-length total RNA droplet-based technology that captures both polyadenylated and nonpolyadenylated RNAs, including histone RNAs, small and long non-coding RNAs, and enhancer RNAs. It achieves a 10-fold increase in UMIs per cell compared to conventional scRNAseq like 10× Chromium and inDrops, while remaining simple and cost-efficient. Applied to lung cancer cells, sc-rDSeq uncovered hidden heterogeneity, divergent signaling pathways, and non-polyA RNA variations undetectable by 3' end-based methods. Following EGFR inhibitor treatment, cell cycle arrest was detected through non-polyA histone messenger RNA expression, revealing seven distinct subpopulations of cells with upregulation of different persister-related programs, like migration, sterol synthesis and matrix formation. Additionally, by leveraging single-cell expression variability and pseudo-bulk analyses, sc-rDSeq unveiled alternative splicing events and single nucleotide variations that distinguished the drug resistant subsets. sc-rDSeq therefore opens the way for in-depth personalized medicine applications through massive-scale and multifaceted analysis of different RNA species, splicing events, and sequence variations.
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Sun et al. (2026) studied this question.
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