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Single‐Cell RNA‐seq Reveals a Developmental Hierarchy Super‐Imposed Over Subclonal Evolution in the Cellular Ecosystem of Prostate Cancer

Authors :
Guangzhe Ge
Yang Han
Jianye Zhang
Xinxin Li
Xiaodan Liu
Yanqing Gong
Zhentao Lei
Jie Wang
Weijie Zhu
Yangyang Xu
Yiji Peng
Jianhua Deng
Bao Zhang
Xuesong Li
Liqun Zhou
Huiying He
Weimin Ci
Source :
Advanced Science, Vol 9, Iss 15, Pp n/a-n/a (2022)
Publication Year :
2022
Publisher :
Wiley, 2022.

Abstract

Abstract Prostate cancer (PCa) is a complex disease. An ongoing accumulation of mutations results in increased genetic diversity, with the tumor acquiring distinct subclones. However, non‐genetic intra‐tumoral heterogeneity, the cellular differentiation state and the interplay between subclonal evolution and transcriptional heterogeneity are poorly understood. Here, the authors perform single‐cell RNA sequencing from 14 untreated PCa patients. They create an extensive cell atlas of the PCa patients and mapped developmental states onto tumor subclonal evolution. They identify distinct subclones across PCa patients and then stratify tumor cells into four transcriptional subtypes, EMT‐like (subtype 0), luminal A‐like (subtype 1), luminal B/C‐like (subtype 2), and basal‐like (subtype 3). These subtypes are hierarchically organized into stem cell‐like and differentiated status. Strikingly, multiple subclones within a single primary tumor present with distinct combinations of preferential subtypes. In addition, subclones show different communication strengths with other cell types within the tumor ecosystem, which may modulate the distinct transcriptional subtypes of the subclones. Notably, by integrating TCGA data, they discover that both tumor cell transcriptional heterogeneity and cellular ecosystem diversity correlate with features of a poor prognosis. Collectively, their study provides the analysis of subclonal and transcriptional heterogeneity and its implication for patient prognosis.

Details

Language :
English
ISSN :
21983844
Volume :
9
Issue :
15
Database :
Directory of Open Access Journals
Journal :
Advanced Science
Publication Type :
Academic Journal
Accession number :
edsdoj.01377a71593447d99e493ff59cc8a27a
Document Type :
article
Full Text :
https://doi.org/10.1002/advs.202105530