Table 1. Studies that examined microbiota and its association with benign and malignant breast tumors.

AM: Akkermansia muciniphila, BaiH: bile acid induction 7α/β-hydroxysteroid dehydroxylase, BIA-ALCL: breast implant-associated anaplastic large cell lymphoma, BMI: body mass index, ER: estrogen receptor, HAM: high Akkermansia muciniphila, IgA: immunoglobulin A, LAM: low Akkermansia muciniphila, LCA: lithocholic acid, NAF: nipple aspirate fluid, NTM: nontuberculous mycobacterial lung disease, NTM-BCa: nontuberculous mycobacterial lung disease and breast cancer, PGEM: prostaglandin E metabolite, PUFA: polyunsaturated fatty acid, qPCR: quantitative polymerase chain reaction, RT-PCR: reverse transcription-polymerase chain reaction, TIL: tumor-infiltrating lymphocyte, TNBC: triple-negative breast cancer, TPBC: triple-positive breast cancer.

Reference	Type of study	Aim	Sample size	Sample site within the breast	Sample assessment methods	Main findings
Xuan et al. [18]	Cross-sectional	To investigate the potential role of microbiota in breast cancer	20 patients with estrogen receptor-positive breast cancer	Normal adjacent tissue and tumor tissue	16S rDNA pyrosequencing	The most numerous phyla in breast tissue are Firmicutes, Actinobacteria, Bacteroidetes, and Proteobacteria. Sphingomonas yanoikuyae was more prevalent in the normal surrounding tissue, while Methylobacterium radiotolerans were more numerous in tumor tissue. The breast cancer stage was shown to be inversely associated with bacterial burden in tumor tissue.
Urbaniak et al. [19]	Cross-sectional	To investigate the presence of microbiome within the mammary gland	Canadian samples: 11 benign, 27 cancer, 5 healthy Irish samples: 33 cancer, 5 healthy	From the patients, Samples were taken from outside the tumor marginal zone	16S rRNA sequencing and culture	Bacillus species, Micrococcus luteus, Propionibacterium acnes, and Propionibacterium granulosum were the most abundant species in the case as well as control tissue.
Goedert et al. [20]	Cross-sectional	To investigate the difference in gut microbiota among patients with breast cancer with regard to menopausal status.	48 postmenopausal patients with breast cancer, pretreatment, vs 48 control patients. Urine (without preservative) and feces	NA	16S rRNA and Fecal DNA gene sequencing	Faecalibacterium, Clostridiaceae, and Ruminococcaceae were found in higher concentrations in breast cancer patients. On the other hand, Lachnospiraceae and Dorea species were found in lower concentrations in breast cancer patients.
Banerjee et al. [21]	Case-control, cross-sectional	To discover the microbiota linked to TNBC.	100 TNBC, as well as 20 non-matched and 17 matched controls	TNBC, cancer tissue samples were collected. Matched-controls were collected from the same patient's normal neighboring tissue. Breast tissues from healthy people were used as non-matched controls.	PathoChip technology	When compared to other samples, the microbial profile observed in TNBC samples was strongly related to cancer samples.
Yazdi et al. [22]	Cross-sectional	To evaluate bacterial dysbiosis in sentinel lymph nodes from breast cancer patients	123 frozen sentinel lymph nodes from breast cancer patients were collected, as well as 123 normal neighboring breast tissue and 5 normal mastectomies.	Normal adjacent breast tissue	RT-PCR and pyrosequencing	Increased presence of Methylobacterium radiotolerans in sentinel lymph nodes.
Chan et al. [23]	Experimental	To characterize the microbiome present in NAF	23 healthy control women and 25 with a history of breast cancer NAF, nipple/areola skin swap	NA	16S rRNA gene sequencing	Alistipes species was present only in NAF from breast cancer, while Sphingomonadaceae was found to be more prevalent in healthy samples.
Urbaniak et al. [6]	Case-control, cross-sectional	To investigate the possible involvement of breast microbiota in the development of breast cancer	71 fresh breast tissue samples were collected from women, 13 of whom were benign, 45 were cancer, and 23 were healthy.	From women with cancer, tissue samples were taken from outside the marginal zone	16S rRNA gene sequencing	Patients with cancer have a higher compositional abundance of Bacillus, Enterobacteriaceae, Staphylococcus, Comamonadaceae, and Bacteroidaceae species. No significant difference across stages.
Hieken et al. [24]	Cross-sectional	To evaluate the role of breast microbiota in breast cancer development	33 patients: 16 benign, 17 cancer for breast tissue, buccal swap, skin swap, full-thickness skin biopsy	From women with tumors, the tissue was obtained from normal adjacent breast tissue.	16S rRNA sequencing	The microbiome of breast tissue is different from the microbiota of breast skin tissue, skin swap, and buccal swap. In malignant samples, Atopobium, Fusobacterium, Hydrogenophaga, Gluconacetobacter, and Lactobacillus genera were more abundant.
Luu et al. [25]	Cross-sectional	To investigate the association between microbiota composition and clinical and biological parameters of breast cancer patients	A stool sample from 31 with early-stage breast cancer: 23 patients had a normal body mass index (BMI), and 8 were overweight or obese	NA	Quantitative PCR (qPCR) targeting 16S rRNA	The amount of Faecalibacterium, Firmicutes, Blautia species, prausnitzii, and Eggerthella lenta bacteria was considerably lower in overweight and obese individuals compared to the normal BMI group. The number of Blautia species grew significantly with grade.
Wang et al. [26]	Case-control, cross-sectional	To explore the microbiome of breast tissue and its relationship to breast cancer	78 patients: 57 with invasive breast cancer, 21 healthy controls mid-stream clean-catch urine samples, a saline mouth rinse samples, and samples of tumor and nearby normal breast tissue were obtained.	Control breast tissue samples were taken on the right and left sides. In addition, tumor tissue and ipsilateral neighboring normal tissue were taken from patients.	DNA extraction 16S rRNA gene sequencing	Methylobacteriaceae species were significantly decreased in patients with cancer, while Alcaligenaceae species were increased in cancer samples relative to non-cancer samples. No significant difference in oral rinse microbiome between cancer patients and healthy controls. The difference in the urine microbiome was largely driven by menopausal status.
Thompson et al. [5]	Cross-sectional	To study the breast microbiota and its association with the tumor expression profile	668 breast tumor tissues 72 normal adjacent tissue	Tumor tissue and non-cancerous adjacent tissue	16S rRNA gene sequencing	Actinobacteria, Proteobacteria, and Firmicutes were the most numerous phyla in breast tissue. Actinobacteria species were plentiful in non-cancerous tissue nearby. Proteobacteria were found in greater abundance in tumor tissue. Mycobacterium phlei and Mycobacterium fortuitum were found in higher concentrations in tumor samples.
Goedert et al. [27]	Case-control, cross-sectional	To study the postmenopausal breast cancer associations with urinary levels of estrogens and estrogen metabolites, inflammation marker PGE-M, and finally, with IgA positive and IgA negative fecal microbiota	48 postmenopausal breast cancer cases and 48 postmenopausal controls Urine (without preservative) and stool samples	NA	16S rRNA gene sequencing	Alpha diversity is drastically diminished in breast cancer patients. Furthermore, the makeup of their IgA-positive and IgA-negative fecal microbiota has changed.
Mikó et al. [28]	Experimental	To investigate the association between changes in the microbiome, microbiome-derived metabolites, and breast cancer	Serum and stool samples from 56 patients and 56 healthy controls Fecal samples from 46 patients and 48 healthy controls	NA	DNA extraction from fecal samples and qPCR	Patients with early-stage breast cancer versus control women had reduced serum LCA levels, a reduced chenodeoxycholic acid to LCA ratio, and a lower abundance of BaiH of Clostridium sordellii, Staphylococcus aureus and Pseudomonas putida.
Banerjee et al. [29]	Cross-sectional	To explore the microbiome diversity among the different types of breast cancer.	50 ER positive, 34 HER2/neu positive, 24 TPBC, 40 TNBC, 20 healthy controls	Breast cancer tissues and control breast samples from healthy individuals	Pan-pathogen microarray (PathoChip) strategy	TNBC and TPBC exhibit unique microbial patterns, but ER-positive and HER2/neu-positive breast cancer samples have comparable microbial profiles.
Zhu et al. [30]	Case-control, cross-sectional	To compare the gut microbial community and its functional capabilities between patients with breast cancer and healthy controls	Fecal samples from 18 premenopausal patients with breast cancer, 25 premenopausal healthy controls 44 postmenopausal patients with breast cancer, 46 postmenopausal healthy controls	NA	DNA sequencing	Gut bacterial species composition seems to be different between postmenopausal patients and postmenopausal healthy control.
Meng et al. [31]	Cross-sectional	To examine the microbiome of breast tissue from individuals with benign and cancers of various histological grades.	22 benign, 72 patients with invasive breast cancer	Samples were taken from either benign or malignant tumor tissue	16S rRNA gene amplicon sequencing	Micrococcaceae, Propionicimonas, Rhodobacteraceae, Caulobacteraceae, Methylobacteriaceae, and Nocardioidaceae familes were found in breast tissues from patients with malignant tumors.
Costantini et al. [32]	Cross-sectional	To examine the 16S-rRNA gene for the hypervariable region that best represents the microbiome in breast tissue.	Normal and tumor tissues were obtained from 9 core needle biopsies and 6 surgical excisional biopsies.	Paired normal and tumor tissues	16S rRNA gene (V3) sequencing	Proteobacteria was the most numerous phylum among all areas, followed by Firmicutes, Actinobacteria, and Bacteroidetes.
Kovács et al. [33]	Experimental	To assess the ability of cadaverine to influence breast cancer cell behavior	48 postmenopausal patients with breast cancer, and 48 control	NA	Fecal DNA samples	DNAs from Enterobacter cloacae, CadA E. coli, and LdcC E. coli, were identified less often in cancer patients. In stage 0 breast cancer patients, levels of CadA and LdcC were found to be lower than their levels in other individuals. In stage 1 breast cancer patients, fecal samples showed lower levels of E. coli LdcC protein as compared to healthy females.
Shi et al. [34]	Cross-sectional	To assess the association between the diversity of the gastrointestinal microbiome with the patterns of expression TILs in patients with breast cancer	80 patients with breast cancer	Tumor tissues	Fresh fecal samples, 16S ribosomal RNA genes	Among different TIL expression groups in a patient with breast cancer, the gut microbiome diversity was distinct and compositionally different.
Philley et al. [35]	Cross-sectional	To identify the population of pathogenic microbes residing with the Mycobacterium avium complex species in NTM-infected women	Total of 29 samples Sputum samples from 5 healthy women, 5 women with NTM, and 15 women with both -NTM and breast cancer (NTM-BCa); sera extracellular vesicles from 4 of 15 NTM-BCa cases	NA	16S rDNA sequencing	Presence of diverse microbial community in the sputum and the extracellular vesicles in women with NTM and in women with NTM-BCa. These microbiota were dominated by Fusobacterium, Bacteroides, and Allistipes, which have estrobolome activity and are associated with breast and other type of cancers.
Walker et al. [36]	Cross-sectional	To study the difference in bacterial species colonizing the implanted breast with BIA-ALCL and those colonizing the contralateral control breast	7 patients with BIA-ALCL and contralateral controls	Specimens obtained from (implant, capsule, skin, and parenchyma)	16S rRNA microbiome sequencing and culture	No significant difference was found in Shannon and alpha diversity metrics between samples from BIA-ALCL and contralateral control.
Horigome et al. [37]	Cross-sectional	To study the association of blood PUFAs with the gastrointestinal microbiota in breast cancer survivors	The drop of capillary blood for PUFAs and fecal samples from 126 participants who had been diagnosed with invasive breast cancer over 1 year ago	NA	16S rRNA sequencing	An increased level of docosahexaenoic acid was associated with the increased relative abundance of Bifidobacterium, which belongs to the Actinobacteria phylum. A positive association was found between the relative abundance of Actinobacteria and Bifidobacterium and the levels of eicosapentaenoic acid.
Chiba et al. [38]	Retrospective cohort	To evaluate whether neoadjuvant chemotherapy modulates the tumor microbiome and the potential impact of microbes on breast cancer signaling	Neoadjuvant chemotherapy-treated patients (n = 15) Women with no prior therapy at the time of operation (n = 18)	Tumor tissues	Breast tissue 16S rRNA sequencing	Chemotherapy administration significantly increased breast tumor Pseudomonas spp. Primary breast tumors from patients who developed distant metastases displayed an increased tumoral abundance of Brevundimonas and Staphylococcus.
Frugé et al. [39]	Secondary analysis of pooled participants in a randomized controlled trial	To examine characteristics of overweight and obese female patients with early-stage breast cancer in relation to Akkermansia muciniphila relative abundance in the gut microbiome	32 women with stage 0 to II breast cancer, fecal samples, phlebotomy	NA	16s rRNA sequencing	In females with higher body fat, AM number was lower. Alpha diversity was higher in females with HAM. Prevotella and Lactobacillus were higher, and Clostridium, Campylobacter, and Helicobacter genera were lower in HAM vs. LAM.