Microbiome relevance in tumor tissue of breast cancer patients.

PENAS-STEINHARDT A.; CARBALLO MP.; WERNICKE A; SIDLIK S.; MARENCO P.; ALSINA MF.; CHASSEING NA.; DANDEU L. ; LACHOVSKI J. ; VÁZQUEZ MP.; LABOVSKY V.

CABA

Congreso; Reunión Conjunta de la Sociedad Argentina de Investigación Clínica (SAIC), la Sociedad Argentina de Inmunología (SAI) y la Sociedad Argentina de Fisiología (SAFIS) 2020.; 2020

Sociedad Argentina de Investigación Clínica (SAIC), la Sociedad Argentina de Inmunología (SAI) y la Sociedad Argentina de Fisiología (SAFIS) .

Microbiome composition reflects the host´s genetic and lifestyle variables, contributing it´s dysbiosis to the risk of developing breast cancer. Patients from diverse countries show different microbial profiles, thus led us to analyze the microbiota in breast cancer patients in Argentina. In order to study the prognostic relevance of the microbiota in the evolution of early breast cancer, a study was carried out including biopsies of frozen/fresh breast tumor tissues (Hospital Roffo, n=7 and Hospital Italiano, n=1, respectively). Inclusion criteria: women with invasive ductal breast carcinoma, clinicopathological stage I/II with a 5-year follow-up minimum. Exclusion criteria: patients with prior treatment, underlying immune disease or another prior tumor. Samples were processed and DNA was extracted using the QIAamp-DNA-Mini-Kit. The bacterial profile was identified studying V4-V4 hypervariable regions of the 16S rRNA gene. OTUs classification and Alpha and Beta diversity analysis were performed, in order to study possible associations with parameters such as age, tumor size, histological grade, Ki-67, Her2/neu, ER, PR, axillary lymph nodes and tumor evolution. Taxonomic analysis of these samples indicated that Firmicutes (34.6%) and Proteobacteria (30.8%) are the most representative phyla. We observed that the sample from the H. Italiano presented greater diversity (165k) than the ones from the H. Roffo (43k-96k), therefore the first was not taken into account for the analysis. Alpha diversity analysis showed a significant difference between tumor dimensions, showing a decrease in diversity with the tumor size increase (p-value