The Relationship Between Programmed Death-Ligand 1 and Cancer Stem Cells in Ovarian Cancer: Implications for Immunotherapy

Abstract

Objective: To review the relationship between programmed death-ligand 1 (PD-L1) expression and cancer stem cells (CSCs) in ovarian cancer and to explore their implications for tumor progression, immune evasion, therapeutic resistance, and immunotherapy strategies. Materials and Methods: A narrative review was conducted using major electronic databases, including PubMed, Scopus, Web of Science, and Google Scholar, focusing on studies investigating PD-L1 expression, CSC biology, tumor microenvironment interactions, and key signaling pathways in ovarian cancer. Results: Emerging evidence indicates that CSCs play a pivotal role in tumor progression, recurrence, and resistance to conventional therapies in ovarian cancer. PD-L1 has been suggested to contribute not only to immune suppression but also to the maintenance of stem-like properties through activation of multiple signaling pathways, including Notch signaling and epithelial mesenchymal transition-related mechanisms. Components of the tumor microenvironment, particularly myeloid-derived suppressor cells, further enhance CSC phenotypes and PD-L1 expression via cytokine-mediated signaling. Elevated PD-L1 expression in CSC populations may partly explain the limited efficacy of immune checkpoint inhibitors in ovarian cancer, although further clinical validation is still required. Conclusion: The interplay between PD-L1 and cancer stem cells represents a key mechanism underlying immune evasion, tumor progression, and therapeutic resistance in ovarian cancer. Current evidence suggests that CSC-associated PD-L1 expression is closely linked to stemness maintenance and immunosuppressive tumor microenvironment dynamics. Although most findings are derived from preclinical studies, targeting the PD-L1–CSC axis, particularly in combination with CSC-directed or microenvironment-modulating strategies, may enhance the effectiveness of immunotherapy and improve clinical outcomes.