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<p>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 <i>XBP1</i>, <i>VCAN</i>, and <i>CLDN7</i> as key markers in epithelial cells, and <i>THBS1</i> 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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月22日

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

摘要

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.