| Literature DB >> 30110974 |
Mariana F Fernández1,2,3, Iris Reina-Pérez4, Juan Manuel Astorga5, Andrea Rodríguez-Carrillo6, Julio Plaza-Díaz7,8,9, Luis Fontana10,11,12.
Abstract
The microorganisms that live symbiotically in human beings are increasingly recognized as important players in health and disease. The largest collection of these microorganisms is found in the gastrointestinal tract. Microbial composition reflects both genetic and lifestyle variables of the host. This microbiota is in a dynamic balance with the host, exerting local and distant effects. Microbial perturbation (dysbiosis) could contribute to the risk of developing health problems. Various bacterial genes capable of producing estrogen-metabolizing enzymes have been identified. Accordingly, gut microbiota is capable of modulating estrogen serum levels. Conversely, estrogen-like compounds may promote the proliferation of certain species of bacteria. Therefore, a crosstalk between microbiota and both endogenous hormones and estrogen-like compounds might synergize to provide protection from disease but also to increase the risk of developing hormone-related diseases. Recent research suggests that the microbiota of women with breast cancer differs from that of healthy women, indicating that certain bacteria may be associated with cancer development and with different responses to therapy. In this review, we discuss recent knowledge about the microbiome and breast cancer, identifying specific characteristics of the human microbiome that may serve to develop novel approaches for risk assessment, prevention and treatment for this disease.Entities:
Keywords: breast cancer; estrobolome; estrogens; microbiota
Mesh:
Substances:
Year: 2018 PMID: 30110974 PMCID: PMC6121903 DOI: 10.3390/ijerph15081747
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Human studies dealing with microbiota and breast cancer.
| Study | Sampling Materials and Site | Microbiota Detection and OTU Picking Method * | Sample Size | Main Findings |
|---|---|---|---|---|
| Fuhrman et al., 2014 [ | Urine and feces of healthy postmenopausal women | Pyrosequencing V1-V2 16S rRNA amplicons, QIIME: Ribosomal Data Project Bayesian classifier, specific method not disclosed | 60 healthy postmenopausal women | The composition and diversity of the gut microbiota were associated with patterns of estrogen metabolism. |
| Xuan et al., 2014 [ | Breast tumor tissue and paired normal adjacent tissue from the same women | Pyrosequencing gDNA amplified 16S V4 rDNA, QIIME: Greengenes database, specific method not disclosed | 20 patients with ER+ BC | |
| Urbaniak et al., 2014 [ | Breast tumor tissue from lumpectomies, mastectomies and breast reductions | Ion Torrent V6 16S rRNA sequencing, UCLUST: Taxonomic assignments for each OTU were made by the Ribosomal Database Project SeqMatch tool. The 16S rRNA sequences obtained in this study have been deposited in the Short Read Archive at NCBI. | 81 Canadian and Irish women [43 Canadian (11 benign, 27 BC, 5 healthy) and 38 Irish (33 BC, 5 healthy)] | |
| Bard et al., 2015 [ | Feces from women with breast cancer | PCR targeting 16S rRNA gene sequences, not specified | 32 women with BC [invasive ductal (81%), stage 0 (46.9%), grade II (62.5%), ER/PgR + (80%), HER2 + (15%)] | Absolute numbers of |
| Goedert et al., 2015 [ | Urine and feces of cases and control women | Illumina sequencing and taxonomy V3-V4 16S rRNA genes, QIIME: OTUs were assigned to taxa by matching to the Ribosomal Data Project naïve Bayesian classifier, specific method not disclosed | 48 BC postmenopausal women [ER+ (n = 42), PR+ (n = 37) and HER2+ (n = 5)] and 48 paired control women | Compared with control women, case patients had an altered fecal microbiota composition (β-diversity) and a lower α-diversity, which was estrogen-independent. Relative abundance of several taxa differed between cases and control: case patients had higher levels of |
| Banerjee et al., 2015 [ | Breast tissue from TNBC cases, and from matched and non-matched controls. Controls samples obtained from the adjacent non-cancerous breast tissue of the same patient, and from healthy individuals (non-matched) | PathoChip array | TNBC (n = 100) and matched controls (n = 17) and non-matched controls (n = 20), from the Abramson Cancer Center Tumor Tissue and Biosample. | TNBC samples presented a specific microbial signature of viruses, bacteria, fungi and parasites which was underrepresented in normal tissue. This signature was significantly associated with the cancer samples. In the viral signatures |
| Chan et al., 2016 [ | Nipple aspirate fluid (NAF) and aerolar breast skin | 16S-V4 rRNA gene amplicon sequencing, Mothur: sequences were aligned to SILVA v119, specific method not disclosed | Women with breast ductal cancer (25 cases), and healthy women (23 controls) | The NAF microbial community composition was different in women with BC. These microbes showed β-glucuronidase activity. The most abundant bacteria in NAF samples were those belonging to |
| Hieken et al., 2016 [ | Breast tissue and breast skin from patients undergoing non-mastectomy breast surgery for cancer or benign disease | 16S V3-V5 rDNA hypervariable taq sequencing, IM-TORNADO: Taxonomy was assigned against a Greengenes reference database, specific method not disclosed | Patients with benign breast disease (n = 13) and invasive breast cancer (n = 15); all ER/PR+, HER-2+ (29%) | Breast tissue had its own microbiome, different from the overlying breast skin. Moreover, breast microbiome in women with cancer was notably different from the breast microbiome of women with benign disease. The microbiome from breast tissue was differentially abundant of phyla |
| Urbaniak et al., 2016 [ | Breast tissue from women with breast cancer (lumpectomies or mastectomies) or healthy women (breast reductions or enhancements) | 16S V6 rRNA amplicon sequencing, QIIME: OTU were made by extracting the best hits from the SILVA database. The 16S rRNA sequences obtained in this study have been deposited in the Short Read Archive at NCBI. | 58 women with benign (n = 13) or BC (n = 45), and 23 controls (n = 23) | Bacterial profiles were statistically different in normal adjacent tissue from BC women compared with control tissue. The comparison showed significantly higher relative abundance of |
| Yazdi et al., 2016 [ | Sentinel lymph nodes and normal adjacent breast tissue | RT-PCR and pyrosequencing | 123 sentinel lymph nodes and 123 normal adjacent breast tissue specimens | There were significant differences between lymph cancer nodes and normal samples according to the presence of |
| Luu et al., 2017 [ | Feces from women with early-stage breast cancer | Real-time qPCR | 31 women with BC [ER/PgR+ (90%), HER2+ (15%)] | In the fecal samples, |
| Wang et al., 2017 [ | Urine, and right and left breast tissue from each control patient, and tumor and ipsilateral adjacent normal breast tissue for cases | Illumina 16S V3-V4 rRNA amplification, UCLUST: OTUs were assigned using Greengenes, specific method not disclosed | 50 BC patients and 20 healthy controls | Neither significant difference in overall diversity (Shannon diversity) nor in microbiota content (number of observed OTUs) was detected in breast tissue from cancer or control women. However, significantly decreased relative richness of |
| Thompson et al., 2017 [ | Breast tumor tissues and normal adjacent tissues from The Cancer Genome Atlas | 16S-V3-V5 rRNA amplified, metagenomeSeq package, specific method not disclosed | 668 tumor tissues (HER2+, ER+ and TNC BC) and 72 normal adjacent tissues | The most abundant phyla in breast tissues were |
| Goedert et al., 2018 [ | Urine and feces from postmenopausal BC cases and control women | 16S V4 rRNA gene amplicon sequencing, DADA2 package and SILVA. The 16S rRNA gene sequence data and case–control status have been deposited and are available in the Sequence Read Archive under BioProject ID PRJNA383849 | 48 BC postmenopausal women [ER+ (n = 42), PR+ (n = 37) and HER2+ (n = 5)] and 48 paired control women | Cases had reduced richness (number of species) and α-diversity, significantly more marked in the IgA-positive gut microbiota. Cases showed higher levels of |
| Banerjee et al., 2018 [ | BC tissues (cases), breast control tissues from healthy individuals (reduction surgeries) | PathoChips array | BC [ER+ (n = 50), HER2+ (n = 34), triple positive (n = 24), TNBC (n = 40)], and normal breast tissue (n = 20) | Unique viral, bacterial, fungal and parasitic signatures were found for each of the BC types. The triple negative and positive samples showed distinct microbial signature patterns than the ER and HER2 positive breast cancer samples. The most prevalent bacterial signatures were for |
BC: breast cancer; DADA2: Divisive Amplicon Denoising Algorithm; EM: estrogens metabolites; ER+: estrogen receptor-positive; HC: healthy control; HER2+: human epidermal growth factor receptor 2-positive; NAF: nipple aspirate fluid; OTUs: operational taxonomic units; PR+: progesterone receptor-positive; QIIME: Quantitative Insights Into Microbial Ecology; TNB: triple negative breast cancer. * All studies with OTU picking method have rarefaction curves assays.