Unraveling immunotherapeutic targets for endometriosis: a transcriptomic and single-cell analysis

Front Immunol. 2023 Nov 16:14:1288263. doi: 10.3389/fimmu.2023.1288263. eCollection 2023.

Abstract

Background: Endometriosis (EMs), a common gynecological disorder, adversely affects the quality of life of females. The pathogenesis of EMs has not been elucidated and the diagnostic methods for EMs have limitations. This study aimed to identify potential molecular biomarkers for the diagnosis and treatment of EMs.

Methods: Differential gene expression (DEG) and functional enrichment analyses were performed using the R language. WGCNA, Random Forest, SVM-REF and LASSO methods were used to identify core immune genes. The CIBERSORT algorithm was then used to analyse the differences in immune cell infiltration and to explore the correlation between immune cells and core genes. In addition, the extent of immune cell infiltration and the expression of immune core genes were investigated using single-cell RNA (scRNA) sequencing data. Finally, we performed molecular docking of three core genes with dienogest and goserelin to screen for potential drug targets.

Results: DEGs enriched in immune response, angiogenesis and estrogen processes. CXCL12, ROBO3 and SCG2 were identified as core immune genes. RT-PCR confirmed that the expression of CXCL12 and SCG2 was significantly upregulated in 12Z cells compared to hESCs cells. ROC curves showed high diagnostic value for these genes. Abnormal immune cell distribution, particularly increased macrophages, was observed in endometriosis. CXCL12, ROBO3 and SCG2 correlated with immune cell levels. Molecular docking suggested their potential as drug targets.

Conclusion: This study investigated the correlation between EMs and the immune system and identified potential immune-related biomarkers. These findings provided valuable insights for developing clinically relevant diagnostic and therapeutic strategies for EMs.

Keywords: endometriosis; CIBERSORT; immune; molecular docking; single-cell RNA sequencing.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers
  • Endometriosis* / drug therapy
  • Endometriosis* / genetics
  • Female
  • Humans
  • Immunotherapy
  • Molecular Docking Simulation
  • Quality of Life
  • Receptors, Cell Surface
  • Single-Cell Analysis
  • Transcriptome*

Substances

  • Biomarkers
  • ROBO3 protein, human
  • Receptors, Cell Surface

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by grants from the Foshan Transnatural Cavity Surgery Development and Innovation Engineering Technology Research Center (2020001003507) and the 2021 Foshan Self-funded Science and Technology Innovation Projects (2220001004062).