The human microbiome is a significant community, with an estimated ratio of one microbial cell per human cell  and nearly 500-fold more microbial genes than host genes . This community is dynamically shaped alongside human development from birth through adolescence. It has coevolved with humans to the degree that it plays an integral role in normal, healthy human functioning . Experiments generating and assessing gnotobiotic and germ-free (GF) mice suggest that, while not a requisite component of physiology, this “hidden organ” provides critical functions that allow for normal metabolic and immune functioning . The role of microbiota as a key functional regulator of metabolic homeostasis [5, 6], drug detoxification and metabolism [7,8,9], and metabolite biosynthesis  has been established only recently, and new findings are emerging on a regular basis. Just as microbiota are important in healthy functioning, it has a hand in dysfunction and disorder. Microbial dysbiosis may be loosely described as a human microbiome that does not fulfill all the necessary functions required for health. It has been implicated in metabolic disorders, obesity [5, 11], and immune development, as well as a wide array of disease states [12, 13]. While microbial communities are functionally similar between individuals, they can be wildly dissimilar phylogenetically, a phenomenon that presents unique challenges in studying the microbiome and its role in health and disease . Research on the microbiome has expanded dramatically in the last decade, with increasing interest in microbial community interactions with cancer.
As an emerging field, challenges must be overcome at all facets of research to ensure robust and rigorous science, and these challenges are only exacerbated by the diversity of the human microbiome. Multiple and concerted efforts have been made to identify and provide solutions to these challenges. The MicroBiome Quality Control project (MBQC) attempted to identify the most critical aspects in microbiome studies to improve reproducibility , and the International Human Microbiome Standards consortium (IHMS) attempted to address reproducibility concerns by providing standard workflows for microbiome studies . Several reviews have covered issues and solutions for various levels of microbiology research, including fecal DNA extraction , 16S rRNA gene analysis and study design , and host-microbe multi-omic analyses . These approaches are eminently worthwhile; though it is important to note, they are continuously evolving as the technology and our understanding of the underlying biology improve. In this review, we address current research and issues in targeting cancer as a disease influenced by the microbiome, which includes the issues of microbial studies addressed above but also specific to correlating microbial analyses with cancer pathology or treatment.
Historical relationships between the microbiome and cancer
Various microbial populations have been implicated in cancer. In 2002, 17.8% of all cancers were attributed to microbial action . An early causal relationship between a specific bacterial species and human cancer is Helicobacter pylori and gastric cancer. H. pylori was discovered and later found to be implicated in ulcers by Warren . The development from an H. pyloriinfection to eventual carcinogenesis has been codified in the Correa pathway. H. pylori can drive chronic inflammation, which leads to atrophic gastritis and eventual dysplasia. CagA-positive H. pylori is especially carcinogenic [21, 22]. More recently, a possible relationship between H. pylori in the gut and increased risk of pancreatic cancer has been explored, although it remains controversial . Curiously, H. pylori may have a protective effect with respect to esophageal adenocarcinomas . Gastroesophageal reflux disease (GERD) can potentially lead to Barrett’s esophagus—that is, a development of scar tissue, cellular dysplasia, and alteration of the cells lining the esophagus from squamous cells to those resembling columnar mucosal cells. These are contributing factors to the development of esophageal adenocarcinoma. There is an inverse correlation between patients with H. pylori infections and Barrett’s esophagus, and thus with esophageal adenocarcinoma, likely due to the reduction in GERD symptoms as a result of H. pylori reducing the local pH in the subregions of the stomach; thereby, the hypothesis goes, reducing the severity of GERD . Thus, a single microbe may have both tumor-suppressing and tumorigenic effects, and deeper research into the host and microbiome relationship is necessary to understand the mechanisms that permit these differing phenotypes.
Transformation-competent viruses have also been shown to cause or be associated with cancer, as was first elucidated through the involvement of Rous sarcoma virus (RSV) in avian sarcoma. RSV is a retrovirus that contains a slightly modified src gene that causes the gene product to be unregulated, which modifies intracellular processes and eventually causes sarcomas in chickens . Human papillomavirus (HPV) has been found to cause cancer by producing the transforming proteins E6 and E7, which prevent Rb from binding E2F and lead to cell cycle dysregulation . Epstein-Barr virus (EBV), a common dsDNA herpesvirus, has been shown to be associated with carcinogenesis, especially Burkitt’s lymphomas. EBV infection alone is not sufficient to cause cancer but may lead to carcinogenesis in tandem with genetic and environmental factors . In the case of breast cancer, there was early suspicion that breast cancer in humans may be driven in part by a mammary tumor virus . While this is a known phenomenon in mice, no such virus has been conclusively identified in humans.
Modern research on the microbiome
Assessing studies of microbial communities and their interactions with cancer can be difficult as there are many methods to look at these interactions, and, occasionally, the approach used in a given study is not entirely clear. Here, we will describe studies by differentiating the relationship between cancer and microbial communities into three categories: primary, secondary, and tertiary interactions. We are proposing this descriptive nomenclature as a means of clarifying exactly what a given study is assessing, as the relationships can occasionally be unclear. We will define the primary interaction as the interaction between a tumor of interest and the microbiota in the local tumor microenvironment (Fig. 1a). Studies done at this resolution are likely looking for direct mechanistic or causal relationships between the microbiota and the tumor, or therapies within the tumor environment, and often require the use of animal models. Recent mouse studies demonstrating that localized bacteria may modulate chemotherapy efficacy are examples of a primary relationship between the microbiota and tumor [30, 31]. Secondary interactions are defined as those between the microbiota involved with the more general tissue or organ environment and the tumor of interest (Fig. 1b), such as the relationship between the gut microbiota from stool and colorectal cancer (CRC). The distinction between primary and secondary interactions is important because, while studies relying on the primary microbiota may elucidate causal relationships, studies of the secondary microbiota might be less capable in this regard due to the relative dilution of cancer-specific interactions in the more generalized microbial population being evaluated. The secondary microbial communities from these sources may contain some signal in the form of traces and residues from the tumor microenvironment and the primary microbiota, but these signals are inherently noisy since they interact with other tissues besides the neoplasm. However, since samples containing the secondary microbiota are much easier to obtain (e.g., stool), this interaction is critical to study in order to identify biomarkers for disease. Tertiary interactions are those where the effect on a tumor or tumor outcome occurs while the tumor is in an entirely different bodily location than that of the microbial community of interest (Fig. 1c). In the vast majority of cases of tertiary interactions, the microbial community is the gut or stool microbiota and the tumors are those outside the digestive tract—for instance, the interactions seen between breast cancer and the stool microbiota or melanoma and the gut microbiota [32,33,34,35,36]. Tertiary interactions often provide strong clinical implications for treatment options but may also afford insight into systemic relationships between the tumor and a physiologically remote microbial community.
Human tumor microbiota primary interactions
The standard starting place for a study of the microbiota associated with a particular disease state is basic characterization. A first-pass characterization needs to be done to identify the specific taxa that are present in normal and disease states and determine what the potential biomarkers or targets for intervention might be. Thus far, this topic has been studied most commonly through cross-sectional clinical studies, which have identified the microbes or sets of microbes that are differentially present/absent or increased/decreased as a function of the disease once all the potentially confounding patient metadata variables have been accounted for. Most of these types of studies have been restricted to cancers in tissues where there is a resident microbial community. However, one interesting side effect of this line of research is the investigation of tissue sites such as the breast, uterus, prostate, and bladder, among others, that were not previously thought to harbor resident microbial communities [37,38,39,40,41,42,43,44,45].
Regarding biomarkers, primary tumors are not necessarily a good place to begin a study (i.e., looking at the microbes directly on a tumor to detect if a tumor is present poses some logical challenges). However, there are instances where the primary microbiota can provide useful information. One can discern information about the microbes at the tumor and make predictions about patient outcomes, as is done in parallel research on personalized cancer treatments where a tumor genome is sequenced or specific levels of relevant genes measured as a means of identifying how best to proceed in the clinic. For instance, in some cases, pancreatic cancer can be protected from the immune system by the presence of specific cancer-associated microbial communities and is correlated with patient mortality [46, 47].
Tumors provide a unique hypoxic environment for bacterial growth. In 1955, Malmgren and Flanigan demonstrated in a mouse model that the growth of Clostridium tetani is favored in the tumor microenvironment . Tumors can develop hypoxic conditions due to the outgrowth of oxygen supply as a result of poor vascularization by tumor-stimulated angiogenesis [49, 50]. This hypoxic and necrotic environment allows for the selective growth of anaerobic bacteria, an important characteristic of the tumor microbiome [51, 52].
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