RESUMO
Background: Ovarian cancer, as a highly malignant tumor, features the critical involvement of tumor-associated fibroblasts in the ovarian cancer tissue microenvironment. However, due to the apparent heterogeneity within fibroblast subpopulations, the specific functions of these subpopulations in the ovarian cancer tissue microenvironment remain insufficiently elucidated. Methods: In this study, we integrated single-cell sequencing data from 32 ovarian cancer samples derived from four distinct cohorts and 3226 bulk RNA-seq data from GEO and TCGA-OV cohorts. Utilizing computational frameworks such as Seurat, Monocle 2, Cellchat, and others, we analyzed the characteristics of the ovarian cancer tissue microenvironment, focusing particularly on fibroblast subpopulations and their differentiation trajectories. Employing the CIBERSORTX computational framework, we assessed various cellular components within the ovarian cancer tissue microenvironment and evaluated their associations with ovarian cancer prognosis. Additionally, we conducted Mendelian randomization analysis based on cis-eQTL to investigate causal relationships between gene expression and ovarian cancer. Results: Through integrative analysis, we identified 13 major cell types present in ovarian cancer tissues, including CD8+ T cells, malignant cells, and fibroblasts. Analysis of the tumor microenvironment (TME) cell proportions revealed a significant increase in the proportion of CD8+ T cells and CD4+ T cells in tumor tissues compared to normal tissues, while fibroblasts predominated in normal tissues. Further subgroup analysis of fibroblasts identified seven subgroups, with the MMP11+Fib subgroup showing the highest activity in the TGFß signaling pathway. Single-cell analysis suggested that oxidative phosphorylation could be a key pathway driving fibroblast differentiation, and the ATRNL1+KCN + Fib subgroup exhibited chromosomal copy number variations. Prognostic analysis using a large sample size indicated that high infiltration of MMP11+ fibroblasts was associated with poor prognosis in ovarian cancer. SMR analysis identified 132 fibroblast differentiation-related genes, which were linked to pathways such as platinum drug resistance. Conclusions: In the context of ovarian cancer, fibroblasts expressing MMP11 emerge as the primary drivers of the TGF-beta signaling pathway. Their presence correlates with an increased risk of adverse ovarian prognoses. Additionally, the genetic regulation governing the differentiation of fibroblasts associated with ovarian cancer correlates with the emergence of drug resistance.
RESUMO
Cancer-associated fibroblast (CAF) is an essential risk factor for ovarian cancer. Exosomes can mediate cellular communication in the tumour microenvironment, but the interaction of tumour cell exosomes with CAF is less studied in Ovarian cancer. This study identified H19/miR-29c-3p/LOXL2-COL1A1 as a ceRNA regulatory network involved in regulating tumour matrix-associated signaling pathways associated with CAF. Cellular assays demonstrated that exosomes from ovarian cancer cell line SKOV3 significantly promoted the proliferation and migration of CAF. The results of mixed transplantation tumour experiments in nude mice showed that exosomes of SKOV3 significantly promoted tumour growth. Ovarian cancer tumour-derived exosomes can regulate CAF proliferation and migration through H19/miR-29c-3p/LOXL2-COL1A1. This study reveals the regulatory role of tumour exosomes on CAF, which may provide a theoretical basis for the development of therapeutic regimens targeting fibroblasts in ovarian cancer.