J Cancer 2021; 12(16):4841-4848. doi:10.7150/jca.58986
Tumor-related Microbiome in the Breast Microenvironment and Breast Cancer
1. Department of Breast Medicine, Cancer Hospital of China Medical University, Liaoning Cancer Hospital, Shenyang, China, 110042.
2. Department of Pharmacology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital, Shenyang, China, 110042.
3. Key Laboratory of Liaoning Breast Cancer Research, Shenyang, Liaoning, China.
Wang N, Sun T, Xu J. Tumor-related Microbiome in the Breast Microenvironment and Breast Cancer. J Cancer 2021; 12(16):4841-4848. doi:10.7150/jca.58986. Available from https://www.jcancer.org/v12p4841.htm
Despite the significant progress in diagnosis and treatment over the past years in the understanding of breast cancer pathophysiology, it remains one of the leading causes of mortality worldwide among females. Novel technologies are needed to improve better diagnostic and therapeutic approaches, and to better understand the role of tumor-environment microbiome players involved in the progression of this disease. The gut environment is enriched with over 100 trillion microorganisms, which participate in metabolic diseases, obesity, and inflammation, and influence the response to therapy. In addition to the direct metabolic effects of the gut microbiome, accumulating evidence has revealed that a microbiome also exists in the breast and in breast cancer tissue. This microbiome enriched in the breast environment and the tumor microenvironment may modulate effects potentially associated with carcinogenesis and therapeutic interventions in breast tissue, which to date have not been properly acknowledged. Herein, we review the most recent works associated with the population dynamics of breast microbes and explore the significance of the microbiome on diagnosis, tumor development, response to chemotherapy, endocrine therapy, and immunotherapy. To overcome the low reproducibility of evaluations of tumor-related microbiome, sequencing technical escalation and machine deep learning algorithms may be valid for standardization of assessment for breast-related microbiome and their applications as powerful biomarkers for prognosis and predictive response in the future.
Keywords: microbiome, breast cancer, gut microbiota, diversity