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基于单细胞第三代测序的多组学揭示了 ecDNA 和结构变异在癌细胞中调控的基因表达变化。

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

机构信息

GMU-GIBH Joint School of Life Sciences, Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, Guangdong Province, P. R. China.

Innovation centre for Advanced Interdisciplinary Medicine, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, P. R. China.

出版信息

Clin Transl Med. 2023 Aug;13(8):e1351. doi: 10.1002/ctm2.1351.

DOI:10.1002/ctm2.1351
PMID:37517066
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10387328/
Abstract

BACKGROUND

Cancer 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.

METHODS

Here, we developed a single-cell multi-omics sequencing method, scGTP-seq, to analyse ecDNA and SVs using long-read sequencing technologies.

RESULTS AND CONCLUSIONS

We 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.

摘要

背景

癌细胞经常表现出大规模的基因组变异,如环状染色体外 DNA(ecDNA)和结构变异(SVs),这些变异与癌症的发生和发展高度相关。目前,尚无充分的方法可以揭示这些变异如何以单细胞分辨率调节异质癌细胞群体中的基因表达。

方法

在这里,我们开发了一种单细胞多组学测序方法 scGTP-seq,使用长读测序技术分析 ecDNA 和 SVs。

结果与结论

我们证明了我们的方法可以有效地检测 ecDNA 和 SVs,并说明了这些变异如何影响不同细胞系中转录组的变化。最后,我们在肝细胞癌(HCC)的临床样本中应用和验证了该方法,证明了在癌症进展过程中监测 ecDNA 和 SVs 演变的可行方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/636dcf64835c/CTM2-13-e1351-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/fde9e7a71fc9/CTM2-13-e1351-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/98e20dedba7d/CTM2-13-e1351-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/8e779d40eb0f/CTM2-13-e1351-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/10afda818d8f/CTM2-13-e1351-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/636dcf64835c/CTM2-13-e1351-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/fde9e7a71fc9/CTM2-13-e1351-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/98e20dedba7d/CTM2-13-e1351-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/8e779d40eb0f/CTM2-13-e1351-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/10afda818d8f/CTM2-13-e1351-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29ae/10387328/636dcf64835c/CTM2-13-e1351-g004.jpg

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