Discover Oncology (Mar 2024)

High-throughput metabolomics identifies new biomarkers for cervical cancer

  • Xue Li,
  • Liyi Zhang,
  • Xuan Huang,
  • Qi Peng,
  • Shoutao Zhang,
  • Jiangming Tang,
  • Jing Wang,
  • Dingqing Gui,
  • Fanxin Zeng

DOI
https://doi.org/10.1007/s12672-024-00948-8
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 11

Abstract

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Abstract Background Cervical cancer (CC) is a danger to women’s health, especially in many developing countries. Metabolomics can make the connection between genotypes and phenotypes. It provides a wide spectrum profile of biological processes under pathological or physiological conditions. Method In this study, we conducted plasma metabolomics of healthy volunteers and CC patients and integratively analyzed them with public CC tissue transcriptomics from Gene Expression Omnibus (GEO). Result Here, we screened out a panel of 5 metabolites to precisely distinguish CC patients from healthy volunteers. Furthermore, we utilized multi-omics approaches to explore patients with stage I-IIA1 and IIA2-IV4 CC and comprehensively analyzed the dysregulation of genes and metabolites in CC progression. We identified that plasma levels of trimethylamine N-oxide (TMAO) were associated with tumor size and regarded as a risk factor for CC. Moreover, we demonstrated that TMAO could promote HeLa cell proliferation in vitro. In this study, we delineated metabolic profiling in healthy volunteers and CC patients and revealed that TMAO was a potential biomarker to discriminate between I-IIA1 and IIA2-IV patients to indicate CC deterioration. Conclusion Our study identified a diagnostic model consisting of five metabolites in plasma that can effectively distinguish CC from healthy volunteers. Furthermore, we proposed that TMAO was associated with CC progression and might serve as a potential non-invasive biomarker to predict CC substage. Impact These findings provided evidence of the important role of metabolic molecules in the progression of cervical cancer disease, as well as their ability as potential biomarkers.

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