Dataset Information

The Microbiota of Breast Tissue and Its Association with Breast Cancer.

ABSTRACT: In the United States, 1 in 8 women will be diagnosed with breast cancer in her lifetime. Along with genetics, the environment contributes to disease development, but what these exact environmental factors are remains unknown. We have previously shown that breast tissue is not sterile but contains a diverse population of bacteria. We thus believe that the host's local microbiome could be modulating the risk of breast cancer development. Using 16S rRNA amplicon sequencing, we show that bacterial profiles differ between normal adjacent tissue from women with breast cancer and tissue from healthy controls. Women with breast cancer had higher relative abundances of Bacillus, Enterobacteriaceae and Staphylococcus Escherichia coli (a member of the Enterobacteriaceae family) and Staphylococcus epidermidis, isolated from breast cancer patients, were shown to induce DNA double-stranded breaks in HeLa cells using the histone-2AX (H2AX) phosphorylation (?-H2AX) assay. We also found that microbial profiles are similar between normal adjacent tissue and tissue sampled directly from the tumor. This study raises important questions as to what role the breast microbiome plays in disease development or progression and how we can manipulate this for possible therapeutics or prevention.This study shows that different bacterial profiles in breast tissue exist between healthy women and those with breast cancer. Higher relative abundances of bacteria that had the ability to cause DNA damage in vitro were detected in breast cancer patients, as was a decrease in some lactic acid bacteria, known for their beneficial health effects, including anticarcinogenic properties. This study raises important questions as to the role of the mammary microbiome in modulating the risk of breast cancer development.

SUBMITTER: Urbaniak C

PROVIDER: S-EPMC4968547 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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The Microbiota of Breast Tissue and Its Association with Breast Cancer.

Urbaniak Camilla C Gloor Gregory B GB Brackstone Muriel M Scott Leslie L Tangney Mark M Reid Gregor G

Applied and environmental microbiology 20160729 16

<h4>Unlabelled</h4>In the United States, 1 in 8 women will be diagnosed with breast cancer in her lifetime. Along with genetics, the environment contributes to disease development, but what these exact environmental factors are remains unknown. We have previously shown that breast tissue is not sterile but contains a diverse population of bacteria. We thus believe that the host's local microbiome could be modulating the risk of breast cancer development. Using 16S rRNA amplicon sequencing, we sh ...[more]

PMID: 27342554

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Project description:BackgroundMicrobial dysbiosis has emerged as an important element in the development and progression of various cancers, including breast cancer. However, the microbial composition of the breast from healthy individuals, even relative to risk of developing breast cancer, remains unclear. Here, we performed a comprehensive analysis of the microbiota of the normal breast tissue, which was analyzed in relation to the microbial composition of the tumor and adjacent normal tissue.MethodsThe study cohorts included 403 cancer-free women (who donated normal breast tissue cores) and 76 breast cancer patients (who donated tumor and/or adjacent normal tissue samples). Microbiome profiling was obtained by sequencing the nine hypervariable regions of the 16S rRNA gene (V1V2, V2V3, V3V4, V4V5, V5V7, and V7V9). Transcriptome analysis was also performed on 190 normal breast tissue samples. Breast cancer risk score was assessed using the Tyrer-Cuzick risk model.ResultsThe V1V2 amplicon sequencing resulted more suitable for the analysis of the normal breast microbiome and identified Lactobacillaceae (Firmicutes phylum), Acetobacterraceae, and Xanthomonadaceae (both Proteobacteria phylum) as the most abundant families in the normal breast. However, Ralstonia (Proteobacteria phylum) was more abundant in both breast tumors and histologically normal tissues adjacent to malignant tumors. We also conducted a correlation analysis between the microbiome and known breast cancer risk factors. Abundances of the bacterial taxa Acetotobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp. were associated with age (p < 0.0001), racial background (p < 0.0001), and parity (p < 0.0001). Finally, transcriptome analysis of normal breast tissues showed an enrichment in metabolism- and immune-related genes in the tissues with abundant Acetotobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp., whereas the presence of Ralstonia in the normal tissue was linked to dysregulation of genes involved in the carbohydrate metabolic pathway.ConclusionsThis study defines the microbial features of normal breast tissue, thus providing a basis to understand cancer-related dysbiosis. Moreover, the findings reveal that lifestyle factors can significantly affect the normal breast microbial composition.

Project description:Automated methods are needed to facilitate high-throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large-scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37-0.87) and study (kappa range = 0.39-0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p-value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000-4,500 cells: kappa = 0.78) than those with lower counts (50-500 cells: kappa = 0.41; p-value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre- and post-analytical quality control procedures are necessary in order to ensure satisfactory performance.

Project description:BackgroundBreast cancer ranks first in women, and is the second cause of death in this gender. In addition to genetics, the environment contributes to the development of the disease, although the factors involved are not well known. Among the latter is the influence of microorganisms and, therefore, attention is recently being paid to the mammary microbiota. We hypothesize that the risk of breast cancer could be associated with the composition and functionality of the mammary/gut microbiota, and that exposure to environmental contaminants (endocrine disruptors, EDCs) might contribute to alter these microbiota.MethodsWe describe a case-control clinical study that will be performed in women between 25 and 70 years of age. Cases will be women diagnosed and surgically intervened of breast cancer (stages I and II). Women with antecedents of cancer or advanced tumor stage (metastasis), or who have received antibiotic treatment within a period of 3 months prior to recruitment, or any neoadjuvant therapy, will be excluded. Controls will be women surgically intervened of breast augmentation or reduction. Women with oncological, gynecological or endocrine history, and those who have received antibiotic treatment within a period of 3 months prior to recruitment will also be excluded. Blood, urine, breast tissue and stool samples will be collected. Data regarding anthropometric, sociodemographic, reproductive history, tumor features and dietary habits will be gathered. Metabolomic studies will be carried out in stool and breast tissue samples. Metagenomic studies will also be performed in stool and breast tissue samples to ascertain the viral, fungal, bacterial and archaea populations of the microbiota. Quantitation of estrogens, estrogen metabolites and EDCs in samples of serum, urine and breast tissue will also be performed.DiscussionThis is the first time that the contribution of bacteria, archaea, viruses and fungi together with their alteration by environmental contaminants to the risk of breast cancer will be evaluated in the same study. Results obtained could contribute to elucidate risk factors, improve the prognosis, as well as to propose novel intervention studies in this disease.Trial registrationClinicalTrials.gov NCT03885648 , 03/25/2019. Retrospectively registered.

Dataset Information

The Microbiota of Breast Tissue and Its Association with Breast Cancer.

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The Microbiota of Breast Tissue and Its Association with Breast Cancer.

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