Single-cell third-generation sequencing-based multi-omics uncovers gene expression changes governed by ecDNA and structural variants in cancer cells

BackgroundCancer cells often exhibit large-scale genomic variations, such as circular extrachromosomal DNA (ecDNA) and structural variants (SVs), which have been highly correlated with the initiation and progression of cancer. Currently, no adequate method exists to unveil how these variations regulate gene expression in heterogeneous cancer cell populations at a single-cell resolution. MethodsHere, we developed a single-cell multi-omics sequencing method, scGTP-seq, to analyse ecDNA and SVs using long-read sequencing technologies. Results and ConclusionsWe demonstrated that our method can efficiently detect ecDNA and SVs and illustrated how these variations affect transcriptomic changes in various cell lines. Finally, we applied and validated this method in a clinical sample of hepatocellular carcinoma (HCC), demonstrating a feasible way to monitor the evolution of ecDNA and SVs during cancer progression.

Automated summary

Researchers developed a single-cell multi-omics sequencing method called scGTP-seq to analyze ecDNA and SVs, and demonstrated how these variations affect transcriptomic changes in different cell lines. The application of this method in a clinical sample of hepatocellular carcinoma (HCC) validated its feasibility in monitoring the evolution of ecDNA and SVs during cancer progression.