Single-cell and bulk RNA sequencing reveal cancer-associated fibroblast heterogeneity and a prognostic signature in prostate cancer

Abstract

Cancer-associated fibroblasts (CAFs), the central players in the tumor microenvironment (TME), can promote tumor progression and metastasis via various functions. However, the properties of CAFs in prostate cancer (PCa) have not been fully assessed. Therefore, we aimed to examine the CAF characteristics in PCa and construct a CAF-derived signature to predict PCa prognosis. CAFs were identified using single-cell RNA sequencing (scRNA-seq) data from 3 studies. We performed the FindAllMarkers function to extract CAF marker genes and constructed a signature to predict the biochemical relapse-free survival (bRFS) of PCa in the Cancer Genome Atlas (TCGA) cohort. Subsequently, different algorithms were applied to reveal the differences of the TME, immune infiltration, treatment responses in the high- and low-risk groups. Additionally, the CAF heterogeneity was assessed in PCa, which were confirmed by the functional enrichment analysis, gene set enrichment analysis (GSEA), and AUCell method. The scRNA-seq analysis identified a CAF cluster with 783 cells and determined 183 CAF marker genes. Cell-cell communication revealed extensive interactions between fibroblasts and immune cells. A CAF-related prognostic model, containing 7 genes (ASPN, AEBP1, ALDH1A1, BGN, COL1A1, PAGE4 and RASD1), was developed to predict bRFS and validated by 4 independent bulk RNA-seq cohorts. Moreover, the high-risk group of the signature score connected with an immunosuppressive TME, such as a higher level of M2 macrophages and lower levels of plasma cells and CD8+ T cells, and a reduced reaction rate for immunotherapy compared with low-risk group. After re-clustering CAFs via unsupervised clustering, we revealed 3 biologically distinct CAF subsets, namely myofibroblast-like CAFs (myCAFs), immune and inflammatory CAFs (iCAFs) and antigen-presenting CAFs (apCAFs). In conclusion, the CAF-derived signature, the first of its kind, can effectively predict PCa prognosis and serve as an indicator for immunotherapy. Furthermore, our study identified 3 CAF subpopulations with distinct functions in PCa.

Exploring the diversity of cancer-associated fibroblasts: insights into mechanisms of drug resistance

“…With the advent of scRNA-seq, the existence of multiple phenotypically and functionally distinct CAF populations has become apparent ( Figure 1 ) ( Galbo et al, 2021 ; Cords et al, 2023 ; Ma et al, 2023 ). Currently, there is growing evidence supporting the existence of another CAF population in each tumor type—antigen-presenting CAFs (apCAFs) ( Figure 1 ) ( Zhang et al, 2020 ; Kieffer et al, 2020 ; Wang et al, 2021 ; Hu et al, 2022 ; Luo et al, 2022 ; Liu et al, 2023 ; Cords et al, 2023 ). Moreover, scRNA-seq studies have identified other rarely occurring CAF populations in the microenvironment of different tumor types ( Figure 1 ) ( Zhang et al, 2020 ; Galbo et al, 2021 ; Li et al, 2022 ; Cords et al, 2023 ; Ma et al, 2023 ).…”

“…In the first category, myCAFs are distinguished as a distinct cell population typified by elevated expression of the blood vessel wall gene RGS5 , contractility genes ( MYH11 , ACTA2 , TAGLN , MYL9 ), and other pericyte markers ( NDUFA4L2 , ADIRF ) ( Elyada et al, 2019 ; Chen et al, 2020 ; Galbo et al, 2021 ; Pu et al, 2021 ; Li t al., 2022 ; Chen et al, 2022 ; Hu et al, 2022 ; Luo et al, 2022 ; Obradovic et al, 2022 ; Yang et al, 2022 ; Zhao et al, 2022 ; Liu et al, 2023 ; Qin et al, 2023 ). Functionally, these cells are implicated in processes such as angiogenesis, smooth muscle contraction, and vascular wound healing.…”

“…Among the diverse CAF subtypes, iCAFs stand out for their distinct immunomodulatory secretory profile ( Figure 1 ). iCAFs are characterized by their expression of various genes, including members of the chemokine ligand family ( CXCL12 and CXCL14 ), the insulin-like growth factor family ( IGF1 and IGFBP6 ), complement-regulatory genes ( C3 , C7, and CFD), and some other genes ( APOD , FBLN1 , PTGDS , DPT, and GSN ) ( Elyada et al, 2019 ; Zhang et al, 2020 ; Chen et al, 2020 ; Wang et al, 2021 ; Galbo et al, 2021 ; Pu et al, 2021 ; Li et al, 2022 ; Chen et al, 2022 ; Li et al, 2022 ; Hu et al, 2022 ; Loret et al, 2022 ; Obradovic et al, 2022 ; Yang et al, 2022 ; Liu et al, 2023 ; Cords et al, 2023 ; Ma et al, 2023 ; Pan et al, 2023 ; Werba et al, 2023 ).…”

“…Nevertheless, the heterogeneity inherent to CAF populations poses a formidable challenge in delineating their precise functional roles and devising tailored therapeutic strategies ( Zhang et al, 2023 ). Recent advancements in single-cell transcriptomic profiling, notably through technologies such as single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics, have unveiled a spectrum of CAF subpopulations characterized by distinct gene expression profiles, functional attributes, and spatial distribution within the TME ( Zhang et al, 2020 ; Kieffer et al, 2020 ; Wang et al, 2021 ; Hu et al, 2022 ; Luo et al, 2022 ; Liu et al, 2023 ; Cords et al, 2023 ). These discrete CAF subsets exhibit nuanced phenotypic characteristics and exert context-dependent effects on tumor progression, necessitating a nuanced approach towards therapeutic targeting.…”

“…In this review, we systematically interrogate the landscape of CAF heterogeneity by leveraging scRNA-seq data encompassing diverse malignancies. In total, we reviewed and systematized data from 36 scRNA-seq studies, encompassing 17 types of human malignant tumors ( Elyada et al, 2019 ; Zhang et al, 2020 ; Chen et al, 2020 ; Dominguez et al, 2020 ; Kieffer et al, 2020 ; Lin et al, 2020 ; Wang et al, 2021 ; Zhang et al, 2021 ; Che et al, 2021 ; Chen et al, 2021 ; Galbo et al, 2021 ; Hornburg et al, 2021 ; Olbrecht et al, 2021 ; Pu et al, 2021 ; Li et al, 2022 ; Bischoff et al, 2022 ; Li et al, 2022 ; Chen et al, 2022 ; Li et al, 2022 ; Deng et al, 2022 ; Giguelay et al, 2022 ; Hu et al, 2022 ; Loret et al, 2022 ; Luo et al, 2022 ; Obradovic et al, 2022 ; Yang et al, 2022 ; Zhao et al, 2022 ; Liu et al, 2023 ; Qin et al, 2023 ; Liu et al, 2023 ; Zhang et al, 2023 ; Cords et al, 2023 ; Ma et al, 2023 ; Pan et al, 2023 ; Wang et al, 2023 ; Werba et al, 2023 ). As a result, we identified and characterized three primary CAFs populations: myofibroblast-like CAFs, inflammatory CAFs, and antigen-presenting CAFs.…”