Scientific Reports (Dec 2024)

Causal relationship between inflammatory factors and gynecological cancer: a Bayesian Mendelian randomization study

  • Chunxiao Dang,
  • Mengmeng Liu,
  • Pengfei Liu,
  • Jinxing Liu,
  • Xiao Yu,
  • Yan Dong,
  • Junde Zhao

DOI
https://doi.org/10.1038/s41598-024-80747-x
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 8

Abstract

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Abstract Background: Cervical cancer, ovarian cancer, and endometrial cancer are the three most common cancers in gynecology. Understanding their respective pathology is currently incomplete. Inflammatory factors play an important role in the pathophysiology of these three cancers, but the causal relationship between inflammatory factors and these three cancers is unclear. Methods: Based on publicly available genetic databases, relevant instrumental variables were extracted according to predefined thresholds, and causal analyses of CRP, 41 circulating inflammatory factors, and three gynecological cancers were performed, mainly using the inverse variance weighted method, while bayesian analysis was performed to improve the accuracy of the results. Finally, heterogeneity, horizontal pleiotropy test, and MR Steiger test were carried out to evaluate the reliability of the findings and the causal inference strength. Results: One inflammatory factor (PDGF-BB) and four inflammatory factors (CXCL9, IL-6, CXCL1, and G-CSF) were identified as significantly associated with the risk of ovarian and endometrial cancers, respectively. In comparison, cervical cancer was found to have a negative causal association with one inflammatory factor (G-CSF) and endometrial cancer with two inflammatory factors (CXCL10 and CCL11). Conclusions: Our MR study suggests potential causal relationships between circulating inflammatory regulators and three gynecological cancers from a genetic perspective, which contributes to further understanding of the pathomechanisms of cervical, ovarian and endometrial cancers and highlights the potential of targeting inflammatory factors as therapeutic interventions and predictors

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