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

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.

Single‐cell RNA sequencing of human prostate basal epithelial cells reveals zone‐specific cellular populations and gene expression signatures

“…Overall, there was little cell population variability between PZ and TZ samples; however, clusters 7 and 9 appeared to be CZ-specific (Figure 1B,C). Utilizing literature-based cell population markers, we identified each PrEC cluster as basal, basal/dividing, basal/transit-amplifying, basal/intermediate, or basal/stem; two CZ-specific clusters; and three SVEC clusters (Figure 1D) [13,[37][38][39][40]. Interestingly, at least one basal marker was present in every cluster, in some cases coexpressing with markers for transit-amplifying, stem, luminal, or proliferating cells (Figure 1D and supplementary material, Figure S2).…”

Single-cell transcriptomic analysis of the tumor ecosystem of adenoid cystic carcinoma

“…We determined the range of Euclidean distances (median ± 2 SD) by assuming that most epithelial cells (95%) in the carcinoma samples were “malignant” in the true sense, whereas cells whose distance from the baseline was not within this range were considered pre-M cells. The signature genes used to distinguish subtypes of epithelial cells or to calculate the score of stemness of different class of epithelial cells are as follows ( 60 – 62 ): intercalated duct cells (KIT or AQP5), myoepithelial cell genes (ACTA2, MYH11, CNN1), and stemness genes (ALDH1A1, CD44, PROM1, NANOG, KIT, NES, KLF4, CD55, ALCAM, NOTCH4, WNT7A, PDPN). Each cell was scored for stemness activity using the function AddModuleScore in Seurat with default settings.…”

Meta-analyses of mouse and human prostate single-cell transcriptomes reveal widespread epithelial plasticity in tissue regression, regeneration, and cancer

“…To examine the alterations of the human prostate due to disease, we combined the normal prostate scRNA-seq datasets with those from patients with benign prostate hyperplasia (BPH) (Joseph et al, 2020), and treatment-naïve prostate cancer (Chen et al, 2021;Ge et al, 2022;Hirz et al, 2023;Karthaus et al, 2020;Song et al, 2022). In these aggregated data of 99,611 cells from 66 datasets, we observed heterogeneous gene expression profiles across treatment-naïve tumors, which was particularly apparent in LumAcinar cells from prostatectomy samples.…”

“…Finally, we have investigated changes in cell states that occur during progression to prostate adenocarcinoma. We have analyzed the dynamic changes in profiles of each cell type in homeostasis, hyperplasia (Joseph et al, 2020), and adenocarcinoma (Chen et al, 2021;Ge et al, 2022;Hirz et al, 2023;Karthaus et al, 2020;Song et al, 2022). Notably, we have found that Luminal Acinar (LumAcinar) cells display the greatest transcriptomic changes during progression to adenocarcinoma.…”