Microbial community profiles in breast cancer and normal adjacent tissues: associations with clinicopathological characteristics.

Background: The microorganisms in breast tissue and its surrounding environment play a critical role in the development and progression of breast cancer (BC). This study aims to characterize BC-associated microbiota via 16S ribosomal RNA (rRNA) sequencing to explore potential pathogenic mechanisms and support early diagnosis and personalized treatment. Methods: Tumor and normal adjacent tissue (NAT) samples from 31 BC patients were analyzed by 16S rRNA sequencing targeting five variable regions. Microbial composition was analyzed via the Short MUltiple Regions Framework (SMURF) pipeline. Alpha and beta diversity analyses were conducted to compare the microbial communities between the BC and NAT groups, and among different BC subgroups stratified by the molecular subtype, clinical stage, histological grade, and proliferation index (Ki-67). Differential microbial taxa were identified using the Wilcoxon signed-rank test and linear discriminant analysis effect size (LEfSe). Functional pathways were predicted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results: No significant differences in alpha or beta diversity were observed between the BC and NAT groups (P>0.05). The LEfSe revealed that Conclusions: Overall, microbial diversity was similar between the BC and NAT groups; however, distinct microbial profiles were identified in the BC tissue group and among the clinicopathological subgroups. Brevundimonas was the predominant genus in the H-Ki-67 group. This study provides novel insights and potential targets that may extend our understanding of BC-related microbial mechanisms and advance microbiota-based therapies.