Abstract PS4-02-22: Dynamics of the Intratumoral Microbiome Across Malignant Transformation and Treatment in Breast Cancer

Abstract Introduction While breast cancer (BC) remains the most prevalent malignancy among women worldwide, the dynamics of the intratumoral microbiome during tumor initiation, progression, and treatment have been largely overlooked. Prior studies are predominantly cross-sectional and limited by indirect microbial inference from RNA-seq data. Method: This study presents the first comprehensive longitudinal analysis of intratumoral microbiota across breast tissue samples using high-depth 16S rRNA sequencing (11W tags). Samples included: 165 benign nodules (82 non-transforming, 83 that later progressed to cancer with matched malignant tissues); 180 primary BC tissues and 165 benign controls; and 101 neoadjuvant therapy (NAT) specimens (15 pCR, 86 non-pCR, with paired pre/post-treatment samples). Microbial diversity, differential taxa, functional predictions, network structures, and correlations with clinical characteristics were systematically analyzed. In addition, two predictive models were developed to malignancy transformation and NAT response. Results Compared to NNT group, NDT group exhibited lower microbial diversity, with a relative enrichment of genera such as Bacteroides, Weissella, Paenibacillus, and Methyloversatilis, whereas the NNT group showed higher abundances of Halomonas, Dietzia, Nesterenkonia, and Aeromicrobium (P0.05). Functional analysis revealed that amino acid and vitamin metabolism-related pathways were significantly more active in the NNT group, while lipid metabolism pathways were enriched in the NDT group (P0.05). During the malignant transformation of nodules, the abundances of Aeromicrobium, Dietzia, Halomonas, and Nesterenkonia markedly increased, whereas Paenibacillus and Faecalibacterium significantly decreased (P0.05). Second, in comparisons between BC tissues and benign lesions, genera such as Methyloversatilis, Weissella, Caulobacter, and Bosea were enriched in tumor tissues, while Delftia, Dietzia, Halomonas, Aeromicrobium, Nesterenkonia, and Acinetobacter were notably reduced (P0.05). Furthermore, with advancing tumor stages, the relative abundances of Dietzia, Aeromicrobium, Delftia, Nesterenkonia, Halomonas, and Nitriliruptor gradually declined, suggesting that these taxa may be associated with the early-stage tumor microenvironment (P0.05). Finally, following NAT, microbial diversity significantly increased, and the microbial community composition underwent a notable reconstruction. After treatment, alpha diversity rose, with genera such as Aeromicrobium, Halomonas, Dietzia, Nesterenkonia, and Nitriliruptor showing significant increases in abundance (P0.05). Functional prediction analysis indicated enhanced activities in pathways related to amino acid metabolism, lipid metabolism, and terpene metabolism, while pathways involved in glycan metabolism were diminished (P0.05). Importantly, we developed two predictive models with high clinical relevance: one stratifying malignancy risk in nodules (AUC=1.0), and another predicting NAT response (AUC=0.82). Conclusion Our findings highlight the clinical relevance of microbial signatures in early diagnosis, malignancy prediction, and response to therapy, offering novel insights for precision oncology and microbiome-based interventions in breast cancer. Citation Format: l. quan, R. Huiteng, y. jian, y. peng. Dynamics of the Intratumoral Microbiome Across Malignant Transformation and Treatment in Breast Cancer abstract. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS4-02-22.