Vívian D'Afonseca, Elizabeth Valdés Muñoz, Alan López Leal, Patricio Maximiliano Adrián Suazo Soto, Cristóbal Parra-Cid
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引用次数: 0
Abstract
The breast microbiome presents a diverse microbial community that could affects health and disease states, in the context of breast cancer. Sequencing technologies have allowed describing the diversity and abundance of microbial communities among individuals. The complex tumoral microenvironment that includes the microbial composition could influence tumor growth. The imbalance of diversity and abundance inside the microbial community, known as dysbiosis plays a crucial role in this context. One the most prevalent bacterial genera described in breast invasive carcinoma are Bacillus, Pseudomonas, Brevibacillus, Mycobacterium, Thermoviga, Acinetobacter, Corynebacterium, Paenibacillus, Ensifer, and Bacteroides. Paenibacills genus shows a relation with patient survival. When the Paenibacills genus increases its abundance in patients with breast cancer, the survival probability decreases. Within this dysbiotic environment, various bacterial metabolites could play a pivotal role in the progression and modulation of breast cancer. Key bacterial metabolites, such as cadaverine, lipopolysaccharides (LPS), and trimethylamine N-oxide (TMAO), have been found to exhibit potential interactions within breast tissue microenvironments. Understanding the intricate relationships between dysbiosis and these metabolites in breast cancer may open new avenues for diagnostic biomarkers and therapeutic targets. Further research is essential to unravel the specific roles and mechanisms of these microbial metabolites in breast cancer progression.
期刊介绍:
Genetics and Molecular Biology (formerly named Revista Brasileira de Genética/Brazilian Journal of Genetics - ISSN 0100-8455) is published by the Sociedade Brasileira de Genética (Brazilian Society of Genetics).
The Journal considers contributions that present the results of original research in genetics, evolution and related scientific disciplines. Manuscripts presenting methods and applications only, without an analysis of genetic data, will not be considered.