Multi-omics analysis reveals the alterations in the tumor microbiome and metabolome associated with cervical cancer
Ting Zhang1,2,3, Yiduo Yu1, Chunyan Zhang1,2,3
1Department of Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Abstract:
Lymph node metastasis (LNM) is the primary mode of cervical cancer (CC) metastasis and is associated with a poorer prognosis. A comprehensive understanding of the underlying mechanisms driving LNM is critical to improving CC patient outcomes. Previous studies have demonstrated that alterations in the intratumor microbiome contribute to tumor progression, with metabolic regulation as a key mechanism. This study aims to investigate the role of intratumor microbiota and tumor metabolism in CC LNM. The microbiome analysis revealed significant differences in the diversity and composition of the intratumor microbiome between CC with and without LNM. Caulobacter and Porphyromonas were the most prominent genus markers for CC with LNM and CC without LNM, respectively. Alterations in tumor metabolism were also observed through global untargeted metabolomics and high-resolution spatial metabolomics, with pathways such as breast cancer, prolactin signaling, histidine metabolism, ovarian steroidogenesis, cysteine and methionine metabolism, and estrogen signaling being significantly altered in CC with LNM. Correlation analysis identified a strong association between specific intratumor microbes (especially Porphyromonas and Virgibacillus) and tumor metabolism. Additionally, our findings suggest a potential trend of phospholipid upregulation in tumor tissues during CC LNM. In summary, our findings underscore the critical role of intratumor microbiota and tumor metabolism in CC LNM, providing valuable insights for developing novel diagnostic markers and therapeutic strategies to address this challenging aspect of cervical cancer.
Importance:
This study comprehensively characterized the intratumor microbiota and tumor metabolism associated with lymph node metastasis (LNM) of cervical cancer (CC) by performing 16S ribosomal RNA sequencing, global untargeted metabolomics, and high-resolution spatial metabolomics on surgical CC specimens. Our findings revealed distinct compositions and diversities of intratumor microbiota between CC with and without LNM. Each group exhibited specific bacterial genera that could potentially serve as diagnostic tools for CC LNM, and Caulobacter and Porphyromonas were the most prominent biomarkers for CC with and without LNM, respectively. The significantly different distribution trend of metabolites was also observed between CC with and without LNM. Correlation analysis identified a strong association between specific intratumor microbes (especially Porphyromonas and Virgibacillus) and tumor metabolism. This study not only provides valuable insights for developing novel diagnostic markers and therapeutic strategies for CC LNM but also contributes to a deeper understanding of the underlying molecular mechanisms of it.
