Single-cell and spatially resolved omics reveal transcriptional and metabolic signatures of ovarian endometriomas

Endometriosis involves ectopic growth of endometrial-like tissue, yet the spatial transcriptomic and metabolic landscape of ovarian endometriomas remains poorly understood. This investigation presents a comprehensive multi-omics analysis of ovarian endometriomas incorporating single-cell RNA sequencing in conjunction with Digital Spatial Profiler-Whole Transcriptome Atlas for spatial transcriptomics, and non-targeted Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging for spatially resolved metabolomics. Our integrated analysis confirms the importance of cell adhesion, ECM-receptor interaction, and focal adhesion pathways in disease context. We identify XBP1, VCAN, and CLDN7 as key markers in epithelial cells, and THBS1 in perivascular cells. Spatially resolved metabolomics further reveals altered activity of cytochrome P450 enzymes, lipoprotein particles, and cholesterol metabolism in mesenchymal regions, along with several undefined metabolites enriched in epithelial areas of endometriomas compared to ovarian cortex controls. These findings reveal potential markers and metabolic pathways linked to ovarian endometriomas, offering a foundation for future diagnostic and therapeutic strategies.

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Publication Details

Journal
Nature Communications
Published
2025-11-22
DOI
https://doi.org/10.1038/s41467-025-66706-8
Citations
3
Primary Topic
Endometriosis Research and Treatment
Type
article
Field-Weighted Citation Impact
5.09
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article

Single-cell and spatially resolved omics reveal transcriptional and metabolic signatures of ovarian endometriomas

Juan Gu, Xinda Wang, Yuqi Huang, Xinyuan Zhao et al.
3 citations
Nature Communications
Endometriosis Research and Treatment
5.09
article

Single-cell and spatially resolved omics reveal transcriptional and metabolic signatures of ovarian endometriomas

Juan Gu, Xinda Wang, Yuqi Huang, Xinyuan Zhao, Xue Cao, Zhenbei Li, Qingqing Sun, Bo Zheng, Jie Cheng, Qiuru Huang, Chen Qiao, Qingqing Hu, Yujuan Qi, Xinhui Yang, Lei He, Jiaxin Li, Chenyu Wang, Yi Zhang, Xia Chen, Ning Chen, Yanting Wang, Tao Wei, Sen Zheng, Weiyi Qian, Ying Zheng, Mei Xu, Ling‐Yi Kong, Jun Yu, Qiushi Xia, Yijuan Cao, Tiantian Wu, Jiangming Reng
article en
3 citations

Abstract

Endometriosis involves ectopic growth of endometrial-like tissue, yet the spatial transcriptomic and metabolic landscape of ovarian endometriomas remains poorly understood. This investigation presents a comprehensive multi-omics analysis of ovarian endometriomas incorporating single-cell RNA sequencing in conjunction with Digital Spatial Profiler-Whole Transcriptome Atlas for spatial transcriptomics, and non-targeted Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging for spatially resolved metabolomics. Our integrated analysis confirms the importance of cell adhesion, ECM-receptor interaction, and focal adhesion pathways in disease context. We identify XBP1, VCAN, and CLDN7 as key markers in epithelial cells, and THBS1 in perivascular cells. Spatially resolved metabolomics further reveals altered activity of cytochrome P450 enzymes, lipoprotein particles, and cholesterol metabolism in mesenchymal regions, along with several undefined metabolites enriched in epithelial areas of endometriomas compared to ovarian cortex controls. These findings reveal potential markers and metabolic pathways linked to ovarian endometriomas, offering a foundation for future diagnostic and therapeutic strategies.

Nature CommunicationsVol. 16(1)
Jiangsu University (CN), Xuzhou Medical College (CN), Nantong University (CN), Affiliated Hospital of Nantong University (CN), Affiliated Hospital of Jiangsu University (CN), Suzhou Municipal Hospital (CN), Xuzhou Central Hospital (CN), Yangzhou University (CN), Nanjing Medical University (CN)
Openalex Percentile: Top 4%
Endometriosis Research and Treatment
5.09
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