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Single cell DNA sequencing reveals punctuated and gradual clonal evolution in hepatocellular carcinoma (by Prof. Zhang Ning)

Abstract:

BACKGROUND & AIMS: Copy number alterations (CNAs), elicited by genome instability, are a major source of intratumor heterogeneity. How CNAs evolve in hepatocellular carcinoma (HCC) remains unknown. METHODS: We performed single-cell DNA sequencing (scDNA-seq) on 1275 cells isolated from 10 patients with HCC, ploidy-resolved scDNA-seq on 356 cells from 1 additional patient, and single-cell RNA sequencing on 27,344 cells from 3 additional patients. Three statistical fitting models were compared to investigate the CNA accumulation pattern. RESULTS: Cells in the tumor were categorized into the following 3 subpopulations: euploid, pseudoeuploid, and aneuploid. Our scDNA-seq analysis revealed that CNA accumulation followed a dual-phase copy number evolution model, that is, a punctuated phase followed by a gradual phase. Patients who exhibited prolonged gradual phase showed higher intratumor heterogeneity and worse disease-free survival. Integrating bulk RNA sequencing of 17 patients with HCC, published datasets of 1196 liver tumors, and immunohistochemical staining of 202 HCC tumors, we found that high expression of CAD, a gene involved in pyrimidine synthesis, was correlated with rapid tumorigenesis and reduced survival. The dual-phase copy number evolution model was validated by our single-cell RNA sequencing data and published scDNA-seq datasets of other cancer types. Furthermore, ploidy-resolved scDNA-seq revealed the common clonal origin of diploid- and polyploid-aneuploid cells, suggesting that polyploid tumor cells were generated by whole genome doubling of diploid tumor cells. CONCLUSIONS: Our work revealed a novel dual-phase copy number evolution model, showed HCC with longer gradual phase was more severe, identified CAD as a promising biomarker for early recurrence of HCC, and supported the diploid origin of polyploid HCC.

(Link: https://www.sciencedirect.com/science/article/pii/S0016508521034715?via%3Dihub)

 

北京大学科研部张宁 的图像结果

                                 Prof. Zhang Ning

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