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Dissecting endometriosis by single-cell transcriptomic and genomic analysis

Endometriosis affects around 10% of individuals born with a uterus, yet we know remarkably little about its underlying biology. Our single-cell transcriptional profiling of endometrial-type epithelial and stromal cells is shedding light on the cells and processes that contribute to endometriosis, which opens up new avenues for diagnostics and therapeutics.

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Fig. 1: Transcriptional profiling of epithelial components of lesions from patients with endometriosis.


  1. Fonseca, M. A. S. et al. Single cell transcriptomic analysis of endometriosis. Nat. Genet. (2022). A paper that reports single-cell transcriptomic analysis of ~50 tissues from 17 patients with endometriosis and four individuals who are unaffected.

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  2. Tan, Y. et al. Single-cell analysis of endometriosis reveals a coordinated transcriptional programme driving immunotolerance and angiogenesis across eutopic and ectopic tissues. Nat. Cell Biol. 24, 1306–1318 (2022). This paper reports single-cell transcriptomic analyses of endometriosis in patients taking exogenous hormones, with a focus on the perivascular niche, and immune signatures of the peritoneum in affected individuals.

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  3. Garcia-Alonso, L. et al. Mapping the temporal and spatial dynamics of the human endometrium in vivo and in vitro. Nat. Genet. 53, 1698–1711 (2021). This study performed scRNA-seq and spatial profiling of endometrium and endometrial organoids that were exposed to ovarian hormones, and relates epithelial signatures to endometrial cancer and endometriosis.

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  4. Wang, W. et al. Single-cell transcriptomic atlas of the human endometrium during the menstrual cycle. Nat. Med. 26, 1644–1653 (2020). A single-cell transcriptomic study of the endometrium throughout the menstrual cycle, with a focus on the window of implantation.

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This is a summary of: Fonseca, M. A. S. et al. Single-cell transcriptomic analysis of endometriosis. Nat. Genet. (2022).

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Dissecting endometriosis by single-cell transcriptomic and genomic analysis. Nat Genet 55, 168–169 (2023).

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