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Applications of single-cell transcriptomics: updated insights in endometrial cancer.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico 2026 Vol.28(3) p. 729-745

Xiao S, Li H, Liu J, Xie X, Xu H, Gong Z, Zhong S

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Endometrial cancer (EC) presents a major global health challenge due to its heterogeneity and complex pathophysiology.

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APA Xiao S, Li H, et al. (2026). Applications of single-cell transcriptomics: updated insights in endometrial cancer.. Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 28(3), 729-745. https://doi.org/10.1007/s12094-025-04032-7
MLA Xiao S, et al.. "Applications of single-cell transcriptomics: updated insights in endometrial cancer.." Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, vol. 28, no. 3, 2026, pp. 729-745.
PMID 40903692

Abstract

Endometrial cancer (EC) presents a major global health challenge due to its heterogeneity and complex pathophysiology. The tumor microenvironment (TME), comprising stromal cells, immune cells, endothelial cells, and non-cellular components, critically influences EC progression. Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of EC by revealing TME cellular heterogeneity and interactions. This review synthesizes recent scRNA-seq applications in EC, focusing on two key areas: ① Mapping transcriptional heterogeneity across major cellular components (epithelial, stromal, endothelial, and immune cells); ② Elucidating the factors driving tumor evolution, immune evasion, and differential immunotherapy response. Collectively, these scRNA-seq-derived insights into the dynamic TME ecosystem provide the foundation for translating basic discoveries toward clinical applications. Such advances could thereby promote TME-based personalized therapies and more accurate prognostic predictions.

MeSH Terms

Humans; Endometrial Neoplasms; Female; Single-Cell Analysis; Tumor Microenvironment; Transcriptome; Gene Expression Profiling; Sequence Analysis, RNA; Immunotherapy

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