The microbiome and human cancer

Abstract

Microbial roles in cancer formation, diagnosis, prognosis, and treatment have been disputed for centuries. Recent studies have provocatively claimed that bacteria, viruses, and/or fungi are pervasive among cancers, key actors in cancer immunotherapy, and engineerable to treat metastases. Despite these findings, the number of microbes known to directly cause carcinogenesis remains small. Critically evaluating and building frameworks for such evidence in light of modern cancer biology is an important task. In this Review, we delineate between causal and complicit roles of microbes in cancer and trace common themes of their influence through the host's immune system, herein defined as the immuno-oncology-microbiome axis. We further review evidence for intratumoral microbes and approaches that manipulate the host's gut or tumor microbiome while projecting the next phase of experimental discovery.

Fig. 1.. Examples by which microbial mechanisms intersect with key cancer pathways (10, 11).

Microbiota-derived metabolites, genotoxins, and antigens influence host antitumor immunity, inflammation, energetics, cellular signaling, and metastasis. Abbreviations: MMP=matrix metalloproteinases; SCFAs=short-chain fatty acids; mAb=monoclonal antibody.

Fig. 2.. Defining the immuno-oncology-microbiome (IOM) axis.

Gut and TME microbiota regulate host metabolism and immunity, which ultimately influence antitumor immunity. (A) Gut microbial metabolites and byproducts influence host lympho- and myelopoiesis, including during allogeneic HSCT and radiotherapy (59, 63). (B) Cyclophosphamide (CTX)-derived gut epithelial damage enables E. hirae translocation and antitumor immunity (68, 69). (C) Gut translocation of Bifidobacterium species or its antigens can increase IFN-I signaling and antitumor immunity (73, 76). (D) Microbes within the tumor microenvironment (TME) can be either immunosuppressive (often PRR-mediated) or immunogenic, including shaping response to immunotherapy (12, 23). Cancer (neo)antigens may share epitopes with microbes through molecular mimicry (73, 83). Microbial hematogenous spread (117, 171, 172) or colonized micrometastases (19) may complete this feedback loop that originated in the gut. Abbreviations: MAMPs=microbe-associated molecular pattern; SCFAs=short-chain fatty acids; GALT=gut-associated lymphoid tissue; mLN=mesenteric lymph node; DC=dendritic cell; OMVs=bacterial outer membrane vesicles; NK=natural killer cell; PRR=pattern recognition receptor; TIL=tumor-infiltrating lymphocytes.

Fig. 3.. Current landscape of the cancer microbiome.

(A) Body diagram of all cancers currently linked to microbiota, where the colored dots reflect reference numbers and are colored according to the major theme of the referenced paper (diagnosis, mechanism, prognosis, treatment). Dots are included based on existing preclinical and clinical data. (B) Representative histology, immunohistochemistry (IHC) for lipopolysaccharide (LPS) and lipoteichoic acid (LTA), and immunofluorescence (IF) for bacterial 16S rRNA in six cancers. (C) Representative transmission electron microscopy (TEM) images with overlaid 16S rRNA immunofluorescence of intracellular bacteria (arrows) in breast cancer. (D) Estimation of tumor percent bacterial composition across seven cancer types assuming tissue homogeneity and 8 picograms of DNA per cancer cell. Black lines depict distributional quantiles (25%–50%–75%); white dots reflect averages. (B-D) Adapted from Nejman et al. (12)

Fig. 4.. Considerations when modulating the endogenous cancer microbiome.

Diet, medications, and prebiotics, postbiotics, probiotics, and antibiotics all have the capacity to modify the gut and tumor microbiomes. Bi-directional influences may exist between these microbiomes and cancer therapies (chemotherapy and immunotherapy). For instance, chemotherapy can cause compositional changes in the gut microbiome, which in turn enhance treatment efficacy (75); in other cases, chemotherapy may be degraded by microbes (14). Thus, modification of the gut and/or tumor microbiomes may be advantageous for one modality of therapy while disadvantageous for another. Dotted arrows denote gaps in the literature.

Fig. 5.. Synthetic biology for exogenous cancer therapeutics.

(A) Regulatory considerations for engineering bacteria against cancer (151). (B) Diverse sources of intratumoral bacteria include organ-specific commensals (18, 19, 25, 46, 112), gut communication (15, 20, 23), hematogenous spread (171, 172), and intra-metastatic spread (19). (C) Some probiotics, such as E. coli Nissle 1917, possess strong safety records (173), have been shown to naturally migrate to solid tumors in animal models, and can be programmed to produce and deliver therapies from within solid tumors (155). (D) Complex population dynamics can be engineered to generate the cyclical delivery of therapeutics (155, 156, 174). (E) Future efforts will likely center on engineering and testing strains that are found naturally in patient-specific tumors. (F) Engineered ecologies can be designed to create tailored, tumor-specific therapeutic cocktails (175, 176). (G) Multiple drug payloads can be encoded by one or more engineered strains against tumors.

Fig. 6.. Study design for characterizing cancer-associated microbiota and their functional impacts.

Opportunities exist to perform large-scale identification of the presence and function of cancer-associated microbiota, beginning with longitudinal cohorts and multi-region sampling. Existing tools can be used to gather multi-omic information on host immune cells, cancer cells, microbiota, and metabolites (51, 177, 178). In vitro and in vivo disease models of a patient’s tumor and intestine can then be used to verify or rebut the predicted functional impact and mechanism(s) of a given microbe (or its metabolites) and its causality in carcinogenesis (160, 170).