Diagnostic and prognostic potential of the intra-tumoral microbiota profile in HPV-independent endocervical adenocarcinoma.

Front Cell Infect Microbiol

Departments of Pathology, The International Peace Maternal and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

Published: September 2024

AI Article Synopsis

  • Microbial community dynamics are linked to various diseases, including cancer, yet the diversity of the microbiota in HPV-independent endocervical adenocarcinoma (HPVI ECA) remains underexplored.
  • The study analyzed 45 HPVI ECA cases using advanced sequencing techniques, revealing significant differences in microbial profiles between cancerous and adjacent noncancerous tissues, with gastric-type ECA showing more variability.
  • Two unique microbial signatures were identified as potential biomarkers for predicting HPVI ECA outcomes, highlighting the relationship between certain microbial abundances and poorer clinical results, suggesting a role for microbiome-based interventions in treatment strategies.

Article Abstract

Background: Microbial community dynamics have been involved in numerous diseases, including cancer. The diversity of intertumoral microbiota in human papillomavirus independent endocervical adenocarcinoma (HPVI ECA) is not well-characterized.

Objective: Our objective is to delineate the intratumoral microbiota profile in HPVI ECA and investigate its potential influence on oncogenesis.

Methods: We analyzed 45 HPVI ECA cases, comprising 36 gastric-type ECA (GEA) and 9 clear cell carcinomas (CCC). We compared the microbial composition within cancerous and adjacent noncancerous tissue samples using 5R-16S ribosomal DNA sequencing. Further, we investigated the correlation between specific microbes and clinical-pathological metrics as well as patient outcomes.

Results: Our findings demonstrate notable differences in the microbial spectra between cancerous and adjacent noncancerous tissues. Amongst HPVI ECA subtypes, GEAs exhibit more microbial variations compared to CCCs. Using the Random Forest algorithm, we identified two distinct microbial signatures that could act as predictive biomarkers for HPVI ECA and differentiate between GEA and CCC. Varied microbial abundances was related to clinical characteristics of HPVI ECA patients. In addition, high levels of and low levels of family were associated with poorer outcomes in HPVI ECA patients. Similarly, an abundance of correlated with reduced overall survival (OS), and a high presence of family microbes was linked to reduced recurrence-free survival (RFS) in GEA patients. Intriguingly, a high abundance of was also associated with a worse OS in GEA patients.

Conclusion: The study reveals distinct microbial signatures in HPVI ECA, which have potential as biomarkers for disease prognosis. The correlation between these tumor-associated microbiota features and clinicopathological characteristics underscores the possibility of microbiome-based interventions. Our research provides a foundation for more in-depth studies into the cervical microbiome's role in HPVI ECA.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11362085PMC
http://dx.doi.org/10.3389/fcimb.2024.1440017DOI Listing

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