The Breast Microbiome in Breast Cancer Risk and Progression: A Narrative Review

Breast cancer is the most commonly diagnosed cancer in women in the United States and globally, and is the leading cause of cancer-associated death in women globally (second leading cause for women in the United States after lung cancer; refs. 1, 2). Breast cancer incidence rates have continued to increase over time, while long-term declines in mortality from breast cancer have slowed (2). One model of breast cancer natural history posits that it develops as a result of histopathologic progression from normal breast tissue through stages of benign breast disease, carcinoma in situ, and invasive cancer, ultimately leading to distant metastasis (3, 4). Though there are established risk factors for breast cancer (5, 6), underlying mechanisms of breast cancer development and progression are incompletely understood, hindering the development of novel prevention and treatment strategies.

Study of the microbes inhabiting the human body, known collectively as the human microbiome, has expanded markedly over the past two decades (7), uncovering extensive diversity (8) and revealing a significant role for the microbiome in human health, not only in the high biomass communities of the orodigestive tract, but also in the lower biomass communities of tissues historically viewed as sterile, such as the breast. It has been postulated that understanding the role of the breast microbiota in breast cancer might generate new opportunities for prevention and treatment (9). The purpose of this review is to summarize the current evidence for the existence of a breast microbiome and its association with breast cancer, as well as to highlight areas for future research.

The search strategy used Medline-indexed journals of human studies published in English. We searched for studies which included the term “breast” in the title or abstract, one of “microbiome”, “microbiomes”, “microbiota”, “microbial”, or “bacterial” in the title, and one of “cancer”, “malignancy”, “tumor”, or “tissue” in the title. Studies were not restricted to a minimum sample size, country of origin, or date of publication. A total of 324 items were accessed through this search strategy and manually reviewed to determine relevance.

The existence of an indigenous breast microbiome was first reported in 2014 by two independent studies (10, 11), indicating that the breast harbors a distinct microbiome. One of these studies, which characterized the microbiome in breast tissue from 81 women undergoing breast surgery for benign or malignant tumors or for cosmetic reasons in Canada and Ireland, found variable microbial diversity across the samples, with Proteobacteria being the most abundant phylum followed by Firmicutes (specifically class Bacilli; ref. 11). In addition, it was found that these breast tissue samples had substantially higher sequencing read counts than paired environmental controls (i.e., sterile PBS left open during surgery and processed alongside samples), and that the breast tissue samples were culturable while the environmental controls were not, suggesting the existence of a true bacterial community in breast tissue (11). The second study, which included 20 U.S. patients diagnosed with breast cancer, also observed that breast tissue samples were dominated by the presence of Proteobacteria, followed by Firmicutes (10).

It has been hypothesized that the breast microbiome is colonized through the nipple (i.e., from the surrounding skin, or nipple-oral contact during breastfeeding or sexual activity) or through translocation from other body sites such as the gut or oral cavity (12). The former of these possibilities is supported by the similarity in composition of paired breast tissue and skin microbiome samples (12, 13), as well as the influence of infant lactation on the breast milk microbiota (14). With regard to gut origins, there is a growing literature on the connection of the gut microbiome with the breast microbiome and breast cancer (15), which may reflect direct (i.e., translocation) or systemic effects of the gut microbiome on inflammation, immunity, and metabolism. Several lines of evidence point to the influence of gut-mammary signaling axis, first proposed in the context of lactation, on breast cancer. For example, fecal transplants from mice on high-fat diets to mice on low-fat diets were shown to alter the gut and breast tumor microbiota and increase breast tumor incidence (16), while indicators of gut permeability were related to the composition of the breast microbiome in a non-human primate model (17). Further, murine models have revealed protective effects of probiotic supplementation on breast tumor development, and a number of human studies have described differences in the gut microbiome between women with and without breast cancer, or for women with varying stages of breast cancer (15). While the gut microbiome is not the main focus of this review, it is important to note its potential influence on the breast microbiome and breast carcinogenesis.

Since the early studies characterizing the breast microbiota for the first time and investigating their origins, research has expanded with more intricate studies that have compared the microbiome of healthy, benign, and cancerous breast tissues, with some of these studies listed in Table 1 and described in detail in later sections of this review.

The breast microbiome is considered to be a low biomass community, meaning that the microbial quantity is low relative to other human microbiome communities such as those of the gut and the oral cavity. Due to the low biomass nature of breast tissue, technical challenges arise in regards to assessment of the microbiome resulting from the significant potential for external contamination from the sampling environment, laboratory processing environment, and reagents, which may all interfere with true biological signals. Hence, standards of practice have been established for studies of biospecimens with low biomass (18). Specifically, study of low biomass biospecimens such as breast tissues necessitate utilization of approaches to reduce contamination (e.g., wearing clean suits, face masks, gloves, decontaminating work areas, working in controlled and sterile environments), to monitor contamination (i.e., inclusion of sampling/environmental controls, DNA extraction controls, PCR controls, reagent controls), and to remove contamination post-sequencing using bioinformatic tools designed to detect contaminants, which should be equally distributed in samples and controls (18). In practice, some studies of the breast microbiome have used rigorous methods to monitor and, if needed, remove contamination from breast tissue microbiome sequencing data (13, 19–22), while others have either not considered or incompletely considered contamination to varying degrees in their experimental design or analysis (Table 1). However, the degree to which contamination is addressed is an important consideration when weighing evidence on the breast microbiome. Table 1 lists quality control measures undertaken by each study included in this review; studies employing forms of environmental controls, extraction controls, and bioinformatic decontamination are considered to have undertaken appropriate quality control measures, which are expected to improve the robustness of results. For example, Nejman and colleagues profiled 1,526 tissue samples across seven cancer types, alongside ∼800 (∼50%) control samples representing each medical center, DNA extraction batch and date, PCR amplification batch, and sequencing library number, and conducted an extensive decontamination procedure featuring six filters to identify true species present in cancer or adjacent normal tissues (22). The ratio of environmental and laboratory controls to tissue samples makes this the most highly controlled cancer microbiome study to date, and also may set an example for future studies of the breast microbiome and cancer microbiome in general (22).

Regarding microbiome sequencing methods, the low biomass of the breast microbiome has typically led investigators to use 16S rRNA gene sequencing rather than shotgun sequencing (23). 16S sequencing involves PCR amplification of one or more hypervariable regions of the bacterial 16S rRNA gene, which thereby amplifies the bacterial signal in breast tissue. On the other hand, shotgun sequencing involves sequencing the entire DNA present in a sample, which in the case of breast tissue is primarily human DNA; the dominance of human DNA over microbial DNA dampens the microbial signal, and thus this method requires very deep sequencing to detect sufficient microbial DNA. Consequently, the majority of breast microbiome studies have employed 16S sequencing, with exceptions being studies using The Cancer Genome Atlas (TCGA) whole-genome sequencing (WGS) and RNA sequencing (RNA-seq) datasets to detect microbial DNA/RNA (24–26), and studies using a microarray specific to microbial pathogens (refs. 27, 28; Table 1). The TCGA shotgun sequencing data have been used extensively to characterize not only bacterial (26, 29) but also viral (30, 31) and fungal components (32) of cancer tissues including breast. These studies highlight the utility of shotgun sequencing for characterizing multiple microbial domains (i.e., bacterial, viral, fungal), as well as allowing assembly of full microbial genomes (32). It should be noted that, given the lack of experimental controls, the use of TCGA for microbiome research has generated some controversy due to human DNA/RNA contamination interfering with the results (23); recent cancer microbiome studies using TCGA have employed different methods to detect and remove contamination, including filtering contaminants by using paired blood samples that were collected alongside tissue samples (29), and identifying taxa that overlap between tissues from TCGA and other cohorts (32). Lastly, one study to date has used fungal-specific internal transcribed spacer 2 (ITS2) amplicon sequencing to study fungal presence in cancer tissues including breast (32).

Among breast microbiome studies using 16S sequencing, some have sequenced multiple hypervariable regions of the 16S gene, either to increase the coverage and resolution of bacterial detection (21, 22), or to determine which region(s) may be ideally suited for measuring the different bacterial species present in the breast microbiome (20, 33). German and colleagues sequenced all nine regions of the 16S gene in fresh frozen breast tissue samples, and found that the V2V3 region resulted in a distinctly different composition compared with the other regions (V1V2, V4V5, V5V7, V7V9), and also had the lowest read counts and diversity (20). After excluding the V2V3 region, their results comparing the microbiomes of breast cancer tissues to normal breast tissues from women without cancer (i.e., healthy controls) were generally similar across the other 16S regions (20). Costantini and colleagues sequenced the V2, V3, V4, V6, V7, V8, and V9 hypervariable regions of the 16S gene in breast samples, and reported that the V3 region yielded the most reads (45% of all reads) while the V9 region yielded the least (<0.1%; ref. 33). All of the regions except V9 showed similar proportions of the major phyla (33). Given these conflicting results, it is not yet clear which 16S gene hypervariable region, if any, provides ideal bacterial detection of the breast microbiome.

Benign breast disease is a risk factor for breast cancer, and some histologic subtypes are considered to be potential breast cancer precursors (3, 4). Some studies have sought to determine whether the breast microbiome is perturbed on the trajectory of healthy breast tissue to benign disease and ultimately to cancer (Table 1). Urbaniak and colleagues observed that normal adjacent tissue of benign breast disease (n = 13) was more similar to normal adjacent tissue of breast cancer (n = 45) than to normal breast tissue from women without breast disease or cancer (i.e., healthy controls; n = 23), indicating that the breast microbiome in benign breast disease may become dysbiotic early, in a manner similar to that of breast cancer (19). Indeed, normal adjacent tissue from breast cancer had higher abundance of Bacillus, Staphylococcus, and Enterobacteriaceae, and lower abundance of Prevotella, Lactococcus, and Streptococcus compared with healthy control tissue, while normal adjacent tissue from benign breast disease had similar enrichment of Bacillus and Staphylococcus and depletion of Prevotella and Lactococcus compared with healthy control tissue (19). Four other studies reported comparisons of breast tissue from patients with benign breast disease and breast cancer (either tumor or normal adjacent tissues), but did not include healthy control tissue; all of these observed similar within-sample diversity for the benign breast disease and breast cancer samples, though some observed differences in overall composition between benign breast disease and breast cancer samples (12, 34), and all reported differences in taxon abundance (12, 34–36). In one of the largest studies of breast cancer and benign breast disease patients, Li and colleagues found increased abundance of Staphylococcus and Proteobacteria genera in normal adjacent tissue from patients with breast cancer (n = 79) compared with normal adjacent tissue from benign breast disease patients (n = 15; ref. 34). In another large study, Meng and colleagues found enrichment of Proteobacteria, Bacillales, and Methylobacteriaceae, and depletion of Prevotella, Veillonella, and Clostridia, in needle biopsies from breast cancer (n = 72) versus benign breast disease (n = 22; ref. 35). Taken together, this limited evidence may suggest that the microbiome in benign breast disease differs from both healthy and cancerous breast tissue, and that the carcinogenic process from healthy tissue to benign disease to cancer might involve species from Proteobacteria and Bacilli. However, all of these studies had very small sample sizes of benign breast disease patients, increasing the potential for false discoveries and lack of generalizability. These few small studies of the microbiome in benign breast disease to date indicate a critical gap in understanding the microbiota of this important intermediate of breast cancer, and the role that benign breast disease microbiota may play in the development of breast cancer.

Many studies have examined the microbiome in invasive breast cancers, either in relation to adjacent normal breast tissue, benign breast disease tissue (reviewed above), healthy control breast tissue, or tissues from other cancers, and in relation to tumor characteristics such as tumor stage, grade, histologic subtype, and hormone receptor status (Table 1). These studies have varied widely in terms of the quality of their evidence, based on sample sizes, steps taken to prevent/remove contamination, and consideration of potential confounders during statistical analysis. While all studies chose healthy controls from the same hospital(s) as the breast cancer cases, healthy controls in most studies were patients undergoing cosmetic breast surgery, or healthy volunteers contributing to research; thus, healthy controls may differ from patients with breast cancer in age, race/ethnicity, and other sociodemographic and behavioural traits. Nearly every study [except one (21)] comparing breast cancer cases to healthy controls did not control for potential confounders in their analysis, sometimes due to small sample size (Table 1). In addition, some but not all studies excluded participants based on recent use of antibiotics (Table 1). Considering that the breast microbiome may be affected by age, race/ethnicity (37–39), diet (16, 40), lactation (14), and antibiotic use, it is possible that some differences identified in the breast microbiome between patients with breast cancer and healthy controls could be due to uncontrolled confounding.

Some studies suggest that no or few differences exist between the microbiome of breast tumor tissue and paired adjacent normal tissue, with far greater differences between breast cancer tissue (tumor or adjacent normal) and healthy control tissue, suggesting a global dysbiosis of the breast tissue during breast carcinogenesis, which extends beyond the tumor geography (19, 20, 33, 41, 42). In contrast, other studies have identified prominent differences between the microbiomes of breast tumors and their adjacent normal tissues (10, 13, 21, 24, 43, 44). When considering some of the largest and most rigorous studies of the breast microbiome in breast cancer to date, it is evident that the tumor microbiome differs from healthy control tissue and likely from adjacent normal tissue as well (20–22, 24), but consistent patterns have not yet been elucidated. Tzeng and colleagues found lower diversity and greater abundance of Pseudomonadaceae and Enterobacteriaceae in breast tumors (n = 221) compared with paired adjacent normal tissue (n = 221) and healthy control tissue (n = 87), and also found differences by stage, grade, subtype, and metastatic potential (21). Notably, Tzeng and colleagues was the only breast microbiome case-control study to adjust for potentially confounding factors (age, race, and hospital) in their statistical analysis (Table 1).

Thompson and colleagues used TCGA whole transcriptome breast cancer data (668 tumor and 72 adjacent normal tissues) to find that Proteobacteria were enriched in tumors, and that 9 species were concordantly differentially abundant for Basal, HER2+, and ER+ tumors when compared with the microbiomes of adjacent normal tissues (24).

Nejman and colleagues reported that the microbiome of breast tumors (n = 355) was richer and more diverse than those of all other tumor types examined (e.g., lung, ovary, pancreas, melanoma), with the diversity of the microbiome of adjacent normal breast tissue (n = 256) intermediate between that of tumors and healthy control tissue (n = 59; ref. 22). Breast tumor and adjacent normal tissue were quite similar in bacterial profiles, and distinct from the bacterial profiles of other tumor types, though breast tumors had higher prevalence of class Bacteroidia, family Prevotellaceae, and genera Streptococcus and Lactococcus than adjacent normal tissue, and microbiome differences were also observed by tumor subtype (HER2+, ER+, triple negative; ref. 22). Moreover, using immunohistochemistry, FISH, and transmission electron microscopy, Nejman and colleagues determined that bacteria and lipopolysaccharide (LPS, a component of gram-negative bacterial cell walls) were indeed present in breast tumors, but were mostly located intra-cellularly in both cancer and immune cells, rather than extra-cellularly, as may have been assumed in previous studies (22). The same research team, subsequently led by Narunsky-Haziza and colleagues, later analyzed fungal presence in breast tissue using the same cohort as Nejman and colleagues as well as TCGA data (32). They found that breast tumors had higher fungal load than most other tumor types, with fungi located intracellularly; that bacterial and fungal richness in breast tumors were positively correlated; and that fungal composition was similar for breast tumor and adjacent normal tissues (32). In addition, species from Malassezia were significantly more prevalent in breast tumors than healthy control tissue (32).

Finally, German and colleagues compared breast tissue from 403 healthy controls to tumor or adjacent normal tissue from 76 patients with breast cancer, reporting that Lactobacillaceae (L. vini and L. paracasei), Acetobacterraceae (A. aceti), and Xanthomonadaceae had lower abundance, while Ralstonia had higher abundance in tumor and normal adjacent samples from patients with breast cancer compared with breast tissue from healthy controls (20).

Taken together, these studies provide evidence of a distinct microbiome in breast cancer differing from healthy breast tissue, and possibly normal tissue adjacent to tumor tissue as well. However, the differentially abundant taxa between cancer and healthy control tissue are largely study-specific. This heterogeneity may in part be due to variation in the breast microbiome across study populations, as breast microbiome composition may differ by country of origin (11) and other population-specific characteristics such as age, race/ethnicity (37–39), diet (16, 40), lactation practices (14), and frequency of antibiotic use. In addition, study heterogeneity may have arisen due to different stringency of contaminant removal procedures (Nejman and colleagues (22) had the most stringent contaminant removal), and confounder control in statistical analysis [only Tzeng and colleagues (21) adjusted for potential confounders].

Relatively few studies have examined the association of the breast microbiota with breast cancer prognosis (Table 1). Chiba and colleagues reported that primary breast tumors from patients who subsequently develop distant metastases within 5 years of tumor resection (n = 9) had an elevated abundance of Brevundimonas and Staphylococcus compared with tumors from patients with no recurrence within 5 years (n = 24; ref. 45). Banerjee and colleagues used a pathogen microarray method to identify bacterial, fungal, viral, and parasitic signatures of recurrence specific to different breast cancer subtypes; for example, in ER+ breast tumors (n = 96), bacterial genera Klebsiella and Stenotrophomonas were associated with longer disease-free survival, while Brevundimonas, Proteus, Eikenella, Pseudomonas, and others were associated with shorter survival (27). Kim and colleagues classified 47 patients with breast cancer into two clusters based on their breast tumor microbiome, and found that the cluster enriched for Enterococcus, Cutibacterium, and Escherichia had worse regional recurrence-free survival, but did not differ from the other cluster with respect to local or distant recurrence (46). Narunsky-Haziza and colleagues reported that presence of the fungus Malassezia globosa in breast tumors was associated with shorter overall survival among 80 patients (32). Notably, these studies did not account for indicators of disease severity such as tumor stage and grade, which could be important confounders. In a large analysis, Mao and colleagues used TCGA whole transcriptome breast cancer data (n = 1,070) to identify 15 microbes independently related to overall survival, which together significantly improved prediction of prognosis at 5, 10, and 20 years, above the predictive ability of clinical risk factors alone (e.g., age, stage, ER/PR status, molecular subtype; ref. 25). This latter study suggests that the breast tumor microbiome may play an independent role in the recurrence of breast cancer, though the quality of microbiome data from TCGA has recently come under scrutiny due to heavy contamination with human reads (23).

Breast microbiota are hypothesized to contribute to carcinogenic processes via direct DNA damage, immune and inflammatory interactions, and metabolic activity (i.e., production of metabolites). Some breast cancer microbiome studies have investigated these potential mechanisms, lending plausibility to the breast microbiome having a local influence on breast cancer development and progression.

Damage of DNA leading to somatic mutations is a classic mechanism of cancer development. In this regard, cultured isolates of Escherichia coli and Staphylococcus epidermidis from adjacent normal breast tissue of patients with breast cancer have been shown to induce DNA double-strand breaks in a human cell line (19).

Bacterial proteins have been shown to elicit pro-tumor immune responses in breast tissue. For example, gram-negative bacteria-derived LPS stimulates TLR4 signaling in breast cancer, resulting in production of inflammatory cytokines and enhanced invasiveness of human breast cancer cells, and greater tumor growth and metastasis in mice (47). In addition, expression of TLR4 in human breast tumors was higher in patients with lymph node metastasis, suggesting that LPS may influence patient prognosis and survival (47). Pseudomonas aeruginosa conditioned media has been shown to stimulate cell growth in breast cancer cell lines, possibly related to secretion of LPS (45). Fusobacterium nucleatum has been shown to colonize breast cancer through binding of its surface protein Fap2 to Gal-GalNAc sugars in breast tissue, which then accelerates tumor growth by suppressing tumor-infiltrating T-cells (48). Studies correlating the breast microbiome with host breast tissue gene expression support a potential influence of the breast microbiome on the breast immune environment and tumorigenic processes (20, 21, 24). For example, Tzeng and colleagues posited that breast tumors may lack important homeostatic microbiome-immune cross-talk, as correlation networks among breast bacteria and host immune gene expression/cytokines were more sparse in breast tumors compared with adjacent normal and healthy breast tissue (21). They showed that abundance of Propionibacterium, which was depleted in breast tumors compared with healthy control tissue, was inversely associated with oncogenic immune genes and positively associated with T-cell activation-related genes (21). Thompson and colleagues found that Haemophilus influenza abundance was positively associated with proliferative gene pathways in breast tumors (24). In addition, German and colleagues reported that healthy control breast tissues more abundant in Acetobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp. were enriched for immune-related genes (20). Altogether, this evidence suggests that breast microbiome species may alter the immune milieu of the tumor environment, potentially facilitating tumor growth and metastasis.

Microbial-derived metabolites may play important roles in breast cancer. Lipid profiles have been shown to differ for normal adjacent breast tissue from patients with breast cancer versus healthy control breast tissue, with several potential microbial-lipid interactions (e.g., Acinetobacter and Lactococcus, enriched in healthy control tissue, were positively associated with diacylglycerols and ceramides, and inversely associated with lysophosphatidylcholines and oxidized cholesteryl esters); microbial synthesis of lipids may underlie these associations (49). Low bile acid metabolism in breast tumors was associated with worse survival and higher abundance of Lactobacillus, Ruegeria, and Marichromatium, suggesting an interaction of the breast microbiome and bile acid metabolism that may be related to breast cancer prognosis (50). Carbohydrate metabolism by the breast microbiota has also been suggested to influence breast cancer, as breast tissues with more abundant Ralstonia (enriched in breast cancer vs. healthy controls) had upregulation of carbohydrate metabolism-related genes (20). Finally, microbial metabolism of conjugated estrogens, facilitating their reabsorption and retention (i.e., the “estrobolome”), has been hypothesized to contribute to estrogen receptor–positive breast cancers (51), however experimental or human evidence has yet to support the connection of either gut or breast “estrobolome” microbiota with breast cancer.

While the body of research on the role of the breast microbiome in breast cancer has grown considerably over the last few years, the majority of research studies feature small sample sizes, cross-sectional designs, and lack of adjustment for potential confounders. When summarizing the results of the available studies at the family taxonomic level, only a few patterns (i.e., results replicated across 2 or more studies) emerge: (i) breast tissue from patients with breast cancer harbors greater abundance of Bacillaceae (19, 42) and Burkholderiaceae (20, 42), and lower abundance of Corynebacteriaceae (19, 21, 42) and Streptococcaceae (19, 21), than breast tissue from healthy controls; and (ii) breast tumor tissue harbors greater abundance of Methylobacteriaceae (10, 13) and lower abundance of Pseudomonadaceae (13, 44) than normal adjacent tissue (Fig. 1; Supplementary Table S1). No patterns could be identified for comparisons of tissue from breast cancer and benign breast disease patients (Fig. 1; Supplementary Table S1). Cross-sectional designs pose a challenge to causal inference, because they preclude distinguishing whether bacteria are drivers or opportunistic passengers in the carcinogenic process. Further, the sample sizes of existing studies have generally been insufficient to support meaningful sub-group analyses by tumor characteristics such as hormone receptor status, which may be important factors in the relationship of the breast microbiome with breast cancer. There have been no prospective studies of the association of the breast microbiome with breast cancer incidence, and the only large prospective study of the breast microbiome and breast cancer patient survival used TCGA RNA-seq data (25), which have been criticized for their predominance of human contamination (23). For the field to move forward, sufficiently large and well-characterized study populations, with appropriate environmental and laboratory negative controls and decontamination procedures, and prospective follow-up for breast cancer incidence (e.g., in the case of benign breast disease) or breast cancer progression, are clearly needed. Large prospective studies would greatly improve our knowledge regarding breast microbiome compositions that precede and potentially contribute to carcinogenesis. Such studies would also allow for stratification by tumor characteristics to examine whether breast microbiome associations with cancer are universal or apply only to specific sub-types.

The state of the science regarding the role of the breast microbiome in breast cancer is still in its early stages. The few large, rigorous cross-sectional studies on the breast microbiome and breast cancer (20–22, 24) provide key evidence of an altered microbiome in breast tumor compared with normal adjacent and healthy control tissue; however, whether such differences are the cause or consequence of the tumor remains unclear. In addition, inconsistent results across studies has limited the identification of taxa that are reproducibly associated with tumor versus adjacent normal or healthy control breast tissue. The only large, prospective study of the breast tumor microbiome identified a significant association of the breast microbiota with patient survival, and found that breast microbiota substantially improved prediction of prognosis above standard clinical risk factors (25); yet, this study used TCGA RNA-seq data which may be contaminated (23). Though existing studies suggest there is great promise in researching the breast microbiome and its involvement in breast carcinogenesis and cancer progression, there is a critical need for large prospective cohort studies to enable more definitive conclusions to be drawn regarding the role of the breast microbiome in breast cancer. Given the modifiable nature of the microbiome, breast microbiota may serve as future targets for primary prevention of breast cancer and improved survival of patients with breast cancer (52, 53).

No disclosures were reported.