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March 22, 2024Cancer Research0 citations

Abstract 6698: Tumor microbiota associated with immune enrichment in breast tumor

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LYLi-Fang YeoBLBernard KB LimTITania Islam

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Abstract

Abstract Asian cancer patients have enriched immune profiles when compared to Caucasians. This is associated with improved overall survival and potentially better response to immunotherapy. Yet the reason behind enriched Asian immune profiles is unclear. This study investigated microbes found in Malaysian breast tumors in association with immune profiles. We used an existing dataset of RNA-seq data from fresh frozen breast tumor tissue (n=978). Sequencing reads were trimmed and filtered to remove human reads. Non-human reads were mapped to Kraken2 and relative abundance was estimated using Bracken. Microbiome analysis was conducted on R following Microbiome OMA guidebook. The top five genera found in the Malaysian Breast Cancer (MyBrCa) cohort were Pseudomonas, Siphoviridae, Bacillus, Escherichia and Klebsiella. Alpha diversity of basal subtype microbiota was significantly higher than Her2 subtype (Shannon index, p=0. 027) whilst the other subtypes were more homogenous. MyBrCa patients with low immune scores were significantly different from high immune scores while controlling for age, stage, grade, ethnicity and PAM50 subtype (PERMANOVA, F-statistic = 1. 656, p=0. 05). Differential abundance analysis revealed Sulfidibacter and Priestia to be significantly different in abundance between high vs low IFNg groups (FDR-adjusted p-value 0. 05) using ALDEx2, ANCOM-BC2 and ZicoSeq and LinDA algorithms. Sulfidibacter was significantly different between high vs low immune group for Bindea combined immune score and ESTIMATE score groups (FDR-adjusted p-value 0. 05). An independent breast cancer cohort (n=419) was used as validation where Sulfidibacter and Priestia were also significantly different in abundance for immune high vs low groups. Machine learning using Random Forest model predicted immune group with an AUC of 0. 79 (CI = 0. 74, 0. 83; p-value 0. 01). The top five most important features contributing to the random forest model were Sulfidibacter, Prestia, Cutibacterium, Acinetobacter and Rhizobium. This study is the largest to date that characterize the tumor microbiota of an Asian cohort of breast cancers, where Sulfidibacter and Priestia, both relatively new and uncharacterized bacteria, were differentially abundant among patients with high vs low immune scores. Citation Format: Li-Fang Yeo, Bernard KB Lim, Tania Islam, Li-Ying Teoh, Suniza Jamaris, Mee-Hoong See, Lai-Meng Looi, Nur Aishah Mohd Taib, Cheng-Har Yip, Pathmanathan Rajadurai, Soo-Hwang Teo, Jia Wern Pan. Tumor microbiota associated with immune enrichment in breast tumor abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 6698.

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Yeo et al. (2024) studied this question.

synapsesocial.com/papers/68e72f4bb6db6435876a883fhttps://doi.org/10.1158/1538-7445.am2024-6698
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Abstract PS3-12-12: Association between Intratumoral Microbiota and Immune Microenvironment in Breast Cancer2026
  2. 2Characterization of intra-tumoral microbiota from transcriptomic sequencing of Asian breast cancer2025
  3. 3Detection of intra-tumoral microbiota from transcriptomic sequencing of Asian breast cancer2024
  4. 4Abstract 4889: Distinct tumor microbiome profiles in triple negative breast cancer compared to other breast cancer subtypes: A pilot study2026
  5. 5Abstract PS4-02-22: Dynamics of the Intratumoral Microbiome Across Malignant Transformation and Treatment in Breast Cancer2026