Integrative single-cell transcriptome analysis reveals a subpopulation of fibroblasts associated with favorable prognosis of liver cancer patients

综合单细胞转录组分析揭示成纤维细胞亚群与肝癌患者良好预后相关

阅读:5
作者:Haiyang Wang, Chao Feng, Meixin Lu, Biao Zhang, Yingchen Xu, Quan Zeng, Jiafei Xi, Junnian Zhou, Xiaomin Ying, Jian Zhang, Wen Yue, Xuetao Pei

Abstract

Single-cell transcriptome analysis has provided detailed insights into the ecosystem of liver cancer. However, the changes of the cellular and molecular components of liver tumors in comparison with normal livers have not been described at single-cell level. Here, we performed an integrative single-cell analysis of both normal livers and liver cancers. Principal component analysis was firstly performed to delineate the cell lineages in liver tissues. Differential gene expression within major cell types were then analyzed between tumor and normal samples, thus resolved the cell type-specific molecular alterations in liver cancer development. Moreover, a comparison between liver cancer derived versus normal liver derived cell components revealed that two subpopulations of fibroblasts were exclusively expanded in liver cancer tissues. By further defining subpopulation-specific gene signatures, characterizing their spatial distribution in tumor tissues and investigating their clinical significance, we found that the SPARCL1 positive fibroblasts, representing a group of tumor vessel associated fibroblasts, were related to reduced vascular invasion and prolonged survival of liver cancer patients. Through establishing an in-vitro endothelial-to-mesenchymal transition model, we verified the conversion of the fetal liver sinusoidal endothelial cells into the fibroblast-like cells, demonstrating a possible endothelial cell origination of the SPARCL1 positive fibroblasts. Our study provides new insights into the cell atlas alteration, especially the expanded fibroblasts in liver cancers.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。