From Dysbiosis to Malignancy: The Female Genital Tract Microbiome in Endometrial Cancer; Insights from a Systematic Review and Meta-Analysis.

Clin TerJan 1, 2026

Ahmed Mohamed Fahmy Selim, Mazed Mohamed Labib Ghonemy Ibrahim, Mohamed Selim Mohamed Elbrolosy et al.

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In 30 seconds

This systematic review and meta-analysis examined genital tract microbiome patterns across benign, premalignant, and malignant endometrial conditions. It included 10 observational studies comprising 775 women, including 325 with endometrial cancer (EC). EC was associated with significant microbiome alterations: several commensal taxa were reduced, while potentially pathogenic or infection-associated genera were increased (p < 0.001). The pooled analysis found a significant association between microbial dysbiosis and EC, but the observational evidence does not establish causality.

Key findings

  • Across 10 observational studies, 775 women were included: 329 with benign conditions, 121 with hyperplasia, and 325 with EC.
  • Lactobacillus, Bacteroides, Prevotella, Staphylococcus, and Enterococcus were decreased in malignant cases.
  • Stenotrophomonas, Streptococcus, and Porphyromonas were increased in malignant cases (p < 0.001).
  • The pooled analysis found a significant association between genital tract microbial dysbiosis and EC.

Why it matters

The findings identify microbiome differences associated with EC that may help guide research into risk stratification and early detection. However, the review does not show that dysbiosis causes cancer, and it does not establish that microbiome-based testing improves clinical outcomes. The reported patterns therefore remain investigational rather than a basis for diagnostic or therapeutic decisions.

What to keep in mind

The evidence is observational and does not establish causality. The authors call for prospective studies with standardized sampling, sequencing, and analytical methods.

Source

Published in Clin Ter. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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