Host and gut bacteria share metabolic pathways for anti-cancer drug metabolism

Framework for exploring the sensory repertoire of the human gut microbiota

Bacteria sense changes in their environment and transduce signals to adjust their cellular functions accordingly. For this purpose, bacteria employ various sensors feeding into multiple signal transduction pathways. Signal recognition by bacterial sensors is studied mainly in a few model organisms, but advances in genome sequencing and analysis offer new ways of exploring the sensory repertoire of many understudied organisms. The human gut is a natural target of this line of study: it is a nutrient-rich and dynamic environment and is home to thousands of bacterial species whose activities impact human health. Many gut commensals are also poorly studied compared to model organisms and are mainly known through their genome sequences. To begin exploring the signals human gut commensals sense and respond to, we have designed a framework that enables the identification of sensory domains, prediction of signals that they recognize, and experimental verification of these predictions. We validate this framework's functionality by systematically identifying amino acid sensors in selected bacterial genomes and metagenomes, characterizing their amino acid binding properties, and demonstrating their signal transduction potential.IMPORTANCESignal transduction is a central process governing how bacteria sense and respond to their environment. The human gut is a complex environment with many living organisms and fluctuating streams of nutrients. One gut inhabitant, Escherichia coli, is a model organism for studying signal transduction. However, E. coli is not representative of most gut microbes, and signaling pathways in the thousands of other organisms comprising the human gut microbiota remain poorly understood. This work provides a foundation for how to explore signals recognized by these organisms.

Anaerostipes hadrus, a butyrate-producing bacterium capable of metabolizing 5-fluorouracil

Anaerostipes hadrus (A. hadrus) is a dominant species in the human gut microbiota and considered a beneficial bacterium for producing probiotic butyrate. However, recent studies have suggested that A. hadrus may negatively affect the host through synthesizing fatty acid and metabolizing the anticancer drug 5-fluorouracil, indicating that the impact of A. hadrus is complex and unclear. Therefore, comprehensive genomic studies on A. hadrus need to be performed. We integrated 527 high-quality public A. hadrus genomes and five distinct metagenomic cohorts. We analyzed these data using the approaches of comparative genomics, metagenomics, and protein structure prediction. We also performed validations with culture-based in vitro assays. We constructed the first large-scale pan-genome of A. hadrus (n = 527) and identified 5-fluorouracil metabolism genes as ubiquitous in A. hadrus genomes as butyrate-producing genes. Metagenomic analysis revealed the wide and stable distribution of A. hadrus in healthy individuals, patients with inflammatory bowel disease, and patients with colorectal cancer, with healthy individuals carrying more A. hadrus. The predicted high-quality protein structure indicated that A. hadrus might metabolize 5-fluorouracil by producing bacterial dihydropyrimidine dehydrogenase (encoded by the preTA operon). Through in vitro assays, we validated the short-chain fatty acid production and 5-fluorouracil metabolism abilities of A. hadrus. We observed for the first time that A. hadrus can convert 5-fluorouracil to α-fluoro-β-ureidopropionic acid, which may result from the combined action of the preTA operon and adjacent hydA (encoding bacterial dihydropyrimidinase). Our results offer novel understandings of A. hadrus, exceptionally functional features, and potential applications.

IMPORTANCE

This work provides new insights into the evolutionary relationships, functional characteristics, prevalence, and potential applications of Anaerostipes hadrus.

Emerging clinical relevance of microbiome in cancer: promising biomarkers and therapeutic targets

The profound influence of microbiota in cancer initiation and progression has been under the spotlight for years, leading to numerous researches on cancer microbiome entering clinical evaluation. As promising biomarkers and therapeutic targets, the critical involvement of microbiota in cancer clinical practice has been increasingly appreciated. Here, recent progress in this field is reviewed. We describe the potential of tumor-associated microbiota as effective diagnostic and prognostic biomarkers, respectively. In addition, we highlight the relationship between microbiota and the therapeutic efficacy, toxicity, or side effects of commonly utilized treatments for cancer, including chemotherapy, radiotherapy, and immunotherapy. Given that microbial factors influence the cancer treatment outcome, we further summarize some dominating microbial interventions and discuss the hidden risks of these strategies. This review aims to provide an overview of the applications and advancements of microbes in cancer clinical relevance.

Effects of probiotic supplementation on chronic inflammatory process modulation in colorectal carcinogenesis

The current study investigated the potential effects of probiotic supplementation on colorectal carcinogenesis chemically induced with 1,2-dimethylhydrazine (DMH) and treated with 5-fluorouracil (5FU)-based chemotherapy in mice. Animals were randomly allocated in five different groups: Control: which not receive any treatment throughout the experimental course; Colitis model group (DMH): treated with DMH; DMH+ 5FU: animals received I.P. (intraperitoneal) dose of chemotherapy on a weekly basis; DMH+PROB: animals received daily administrations (via gavage) of probiotics (Lactobacillus: acidophilus and paracasei, Bifidobacterium lactis and bifidum); and DMH+ PROB+ 5FU: animals received the same treatment as the previous groups. After ten-week treatment, mice's large intestine was collected and subjected to colon length, histopathological, periodic acid-schiff (PAS) staining and immunohistochemistry (TLR2, MyD88, NF-κB, IL-6, TLR4, TRIF, IRF-3, IFN-γ, Ki-67, KRAS, p53, IL-10, and TGF-β) analyzes. Variance (ANOVA) and Kruskal-Wallis tests were used for statistical analysis, at significance level p 0.05. Probiotics' supplementation has increased the production of Ki-67 cell-proliferation marker, reduced body weight, and colon shortening, as well as modulated the chronic inflammatory process in colorectal carcinogenesis by inhibiting NF-κB expression and mitigating mucin depletion. Thus, these findings lay a basis for guide future studies focused on probiotics' action mechanisms in tumor microenvironment which might have implications in clinical practice.

Identification of consensus head and neck cancer-associated microbiota signatures: a systematic review and meta-analysis of 16S rRNA and The Cancer Microbiome Atlas datasets

Introduction. Multiple reports have attempted to describe the tumour microbiota in head and neck cancer (HNSC).Gap statement. However, these have failed to produce a consistent microbiota signature, which may undermine understanding the importance of bacterial-mediated effects in HNSC.Aim. The aim of this study is to consolidate these datasets and identify a consensus microbiota signature in HNSC.Methodology. We analysed 12 published HNSC 16S rRNA microbial datasets collected from cancer, cancer-adjacent and non-cancer tissues to generate a consensus microbiota signature. These signatures were then validated using The Cancer Microbiome Atlas (TCMA) database and correlated with the tumour microenvironment phenotypes and patient's clinical outcome.Results. We identified a consensus microbial signature at the genus level to differentiate between HNSC sample types, with cancer and cancer-adjacent tissues sharing more similarity than non-cancer tissues. Univariate analysis on 16S rRNA datasets identified significant differences in the abundance of 34 bacterial genera among the tissue types. Paired cancer and cancer-adjacent tissue analyses in 16S rRNA and TCMA datasets identified increased abundance in Fusobacterium in cancer tissues and decreased abundance of Atopobium, Rothia and Actinomyces in cancer-adjacent tissues. Furthermore, these bacteria were associated with different tumour microenvironment phenotypes. Notably, high Fusobacterium signature was associated with high neutrophil (r=0.37, P<0.0001), angiogenesis (r=0.38, P<0.0001) and granulocyte signatures (r=0.38, P<0.0001) and better overall patient survival [continuous: HR 0.8482, 95 % confidence interval (CI) 0.7758-0.9273, P=0.0003].Conclusion. Our meta-analysis demonstrates a consensus microbiota signature for HNSC, highlighting its potential importance in this disease.

Microbiome metabolite quantification methods enabling insights into human health and disease

Many of the health-associated impacts of the microbiome are mediated by its chemical activity, producing and modifying small molecules (metabolites). Thus, microbiome metabolite quantification has a central role in efforts to elucidate and measure microbiome function. In this review, we cover general considerations when designing experiments to quantify microbiome metabolites, including sample preparation, data acquisition and data processing, since these are critical to downstream data quality. We then discuss data analysis and experimental steps to demonstrate that a given metabolite feature is of microbial origin. We further discuss techniques used to quantify common microbial metabolites, including short-chain fatty acids (SCFA), secondary bile acids (BAs), tryptophan derivatives, N-acyl amides and trimethylamine N-oxide (TMAO). Lastly, we conclude with challenges and future directions for the field.

High-throughput transcriptomics of 409 bacteria-drug pairs reveals drivers of gut microbiota perturbation

Many drugs can perturb the gut microbiome, potentially leading to negative health consequences. However, mechanisms of most microorganism-drug responses have not been elucidated at the genetic level. Using high-throughput bacterial transcriptomics, we systematically characterized the gene expression profiles of prevalent human gut bacteria exposed to the most frequently prescribed orally administered pharmaceuticals. Across >400 drug-microorganism pairs, significant and reproducible transcriptional responses were observed, including pathways involved in multidrug resistance, metabolite transport, tartrate metabolism and riboflavin biosynthesis. Importantly, we discovered that statin-mediated upregulation of the AcrAB-TolC efflux pump in Bacteroidales species enhances microbial sensitivity to vitamin A and secondary bile acids. Moreover, gut bacteria carrying acrAB-tolC genes are depleted in patients taking simvastatin, suggesting that drug-efflux interactions generate collateral toxicity that depletes pump-containing microorganisms from patient microbiomes. This study provides a resource to further understand the drivers of drug-mediated microbiota shifts for better informed clinical interventions.

Integrating the gut microbiome and pharmacology

The gut microbiome harbors trillions of organisms that contribute to human health and disease. These bacteria can also affect the properties of medical drugs used to treat these diseases, and drugs, in turn, can reshape the microbiome. Research addressing interdependent microbiome-host-drug interactions thus has broad impact. In this Review, we discuss these interactions from the perspective of drug bioavailability, absorption, metabolism, excretion, toxicity, and drug-mediated microbiome modulation. We survey approaches that aim to uncover the mechanisms underlying these effects and opportunities to translate this knowledge into new strategies to improve the development, administration, and monitoring of medical drugs.

INTEDE 2.0: the metabolic roadmap of drugs

The metabolic roadmap of drugs (MRD) is a comprehensive atlas for understanding the stepwise and sequential metabolism of certain drug in living organisms. It plays a vital role in lead optimization, personalized medication, and ADMET research. The MRD consists of three main components: (i) the sequential catalyses of drug and its metabolites by different drug-metabolizing enzymes (DMEs), (ii) a comprehensive collection of metabolic reactions along the entire MRD and (iii) a systematic description on efficacy & toxicity for all metabolites of a studied drug. However, there is no database available for describing the comprehensive metabolic roadmaps of drugs. Therefore, in this study, a major update of INTEDE was conducted, which provided the stepwise & sequential metabolic roadmaps for a total of 4701 drugs, and a total of 22 165 metabolic reactions containing 1088 DMEs and 18 882 drug metabolites. Additionally, the INTEDE 2.0 labeled the pharmacological properties (pharmacological activity or toxicity) of metabolites and provided their structural information. Furthermore, 3717 drug metabolism relationships were supplemented (from 7338 to 11 055). All in all, INTEDE 2.0 is highly expected to attract broad interests from related research community and serve as an essential supplement to existing pharmaceutical/biological/chemical databases. INTEDE 2.0 can now be accessible freely without any login requirement at: http://idrblab.org/intede/.

Mechanisms and Potential Clinical Implications of Oral Microbiome in Oral Squamous Cell Carcinoma

Microorganisms in the oral cavity are abundant in the human body. At present, more than 700 species of oral microorganisms have been identified. Recently, a lot of literature has indicated that the oral microbiota plays an important role in the occurrence, development, and prognosis of oral squamous cell carcinoma (OSCC) through various mechanisms. And researchers are now trying to utilize oral microbiota in cancer diagnosis and treatment. However, few articles systematically summarize the effects of oral microbes in the diagnosis, treatment, and disease outcomes of oral cancer. Herein, we made a summary of the microbial changes at cancerous sites and placed more emphasis on the mechanisms by which the oral microbiome promotes cancerization. Moreover, we aimed to find out the clinical value of the oral microbiome in OSCC.

Getting off tract: contributions of intraorgan microbiota to cancer in extraintestinal organs

The gastrointestinal ecosystem has received the most attention when examining the contributions of the human microbiome to health and disease. This concentration of effort is logical due to the overwhelming abundance of microbes in the gut coupled with the relative ease of sampling compared with other organs. However, the intestines are intimately connected to multiple extraintestinal organs, providing an opportunity for homeostatic microbial colonisation and pathogenesis in organs traditionally thought to be sterile or only transiently harbouring microbiota. These habitats are challenging to sample, and their low microbial biomass among large amounts of host tissue can make study challenging. Nevertheless, recent findings have shown that many extraintestinal organs that are intimately linked to the gut harbour stable microbiomes, which are colonised from the gut in selective manners and have highlighted not just the influence of the bacteriome but that of the mycobiome and virome on oncogenesis and health.

The new epoch of structural insights into radical SAM enzymology

The Radical SAM (RS) superfamily of enzymes catalyzes a wide array of enzymatic reactions. The majority of these enzymes employ an electron from a reduced [4Fe-4S]+1 cluster to facilitate the reductive cleavage of S-adenosyl-l-methionine, thereby producing a highly reactive 5'-deoxyadenosyl radical (5'-dA⋅) and l-methionine. Typically, RS enzymes use this 5'-dA⋅ to extract a hydrogen atom from the target substrate, starting the cascade of an expansive and impressive variety of chemical transformations. While a great deal of understanding has been gleaned for 5'-dA⋅ formation, because of the chemical diversity within this superfamily, the subsequent chemical transformations have only been fully elucidated in a few examples. In addition, with the advent of new sequencing technology, the size of this family now surpasses 700,000 members, with the number of uncharacterized enzymes and domains also rapidly expanding. In this review, we outline the history of RS enzyme characterization in what we term "epochs" based on advances in technology designed for stably producing these enzymes in an active state. We propose that the state of the field has entered the fourth epoch, which we argue should commence with a protein structure initiative focused solely on RS enzymes to properly tackle this unique superfamily and uncover more novel chemical transformations that likely exist.

Pharmacomicrobiomics of cell-cycle specific anti-cancer drugs - is it a new perspective for personalized treatment of cancer patients?

Intestinal bacteria are equipped with an enzyme apparatus that is involved in the active biotransformation of xenobiotics, including drugs. Pharmacomicrobiomics, a new area of pharmacology, analyses interactions between bacteria and xenobiotics. However, there is another side to the coin. Pharmacotherapeutic agents can significantly modify the microbiota, which consequently affects their efficacy. In this review, we comprehensively gathered scientific evidence on the interplay between anticancer therapies and gut microbes. We also underlined how such interactions might impact the host response to a given therapy. We discuss the possibility of modulating the gut microbiota to increase the effectiveness/decrease the incidence of adverse events during tumor therapy. The anticipation of the future brings new evidence that gut microbiota is a target of interest to increase the efficacy of therapy.

Biotransformation research advances - 2022 year in review

This annual review is the eighth of its kind since 2016 (Baillie et al. 2016, Khojasteh et al. 2017, Khojasteh et al. 2018, Khojasteh et al. 2019, Khojasteh et al. 2020, Khojasteh et al. 2021, Khojasteh et al. 2022). Our objective is to explore and share articles which we deem influential and significant in the field of biotransformation.

TARO: tree-aggregated factor regression for microbiome data integration

Motivation

Although the human microbiome plays a key role in health and disease, the biological mechanisms underlying the interaction between the microbiome and its host are incompletely understood. Integration with other molecular profiling data offers an opportunity to characterize the role of the microbiome and elucidate therapeutic targets. However, this remains challenging to the high dimensionality, compositionality, and rare features found in microbiome profiling data. These challenges necessitate the use of methods that can achieve structured sparsity in learning cross-platform association patterns.

Results

We propose Tree-Aggregated factor RegressiOn (TARO) for the integration of microbiome and metabolomic data. We leverage information on the phylogenetic tree structure to flexibly aggregate rare features. We demonstrate through simulation studies that TARO accurately recovers a low-rank coefficient matrix and identifies relevant features. We applied TARO to microbiome and metabolomic profiles gathered from subjects being screened for colorectal cancer to understand how gut microrganisms shape intestinal metabolite abundances.

Availability and implementation

The R package TARO implementing the proposed methods is available online at https://github.com/amishra-stats/taro-package .

Exploring New Dimensions of Tumor Heterogeneity: The Application of Single Cell Analysis to Organoid-Based 3D In Vitro Models

Modeling the heterogeneity of the tumor microenvironment (TME) in vitro is essential to investigating fundamental cancer biology and developing novel treatment strategies that holistically address the factors affecting tumor progression and therapeutic response. Thus, the development of new tools for both in vitro modeling, such as patient-derived organoids (PDOs) and complex 3D in vitro models, and single cell omics analysis, such as single-cell RNA-sequencing, represents a new frontier for investigating tumor heterogeneity. Specifically, the integration of PDO-based 3D in vitro models and single cell analysis offers a unique opportunity to explore the intersecting effects of interpatient, microenvironmental, and tumor cell heterogeneity on cell phenotypes in the TME. In this review, the current use of PDOs in complex 3D in vitro models of the TME is discussed and the emerging directions in the development of these models are highlighted. Next, work that has successfully applied single cell analysis to PDO-based models is examined and important experimental considerations are identified for this approach. Finally, open questions are highlighted that may be amenable to exploration using the integration of PDO-based models and single cell analysis. Ultimately, such investigations may facilitate the identification of novel therapeutic targets for cancer that address the significant influence of tumor-TME interactions.

Associations between the Gut Microbiota, Race, and Ethnicity of Patients with Colorectal Cancer: A Pilot and Feasibility Study

BACKGROUND

Colorectal cancer (CRC) is more prevalent among some racial and ethnic minority and low socioeconomic status populations. Although the gut microbiota is a risk factor for CRC and varies with race and ethnicity, its role in CRC disparities remains poorly understood.

METHODS

We examined the feasibility of recruiting sociodemographically diverse CRC patients for a microbiome study involving a home stool collection. We also explored whether race and ethnicity were associated with gut microbiome composition. We recruited Black/African American, Hispanic/Latino, and non-Hispanic White patients who were receiving care for active CRC to complete a comprehensive dietary and lifestyle survey, self-collect a stool sample, and complete an exit interview. Gut microbial diversity and composition were analyzed using 16S rRNA gene sequencing.

RESULTS

30 individuals consented (of 35 who were eligible and contacted) with 5 (17%) Black/African American, 11 (37%) Hispanic/Latino, and 14 (46%) non-Hispanic White. A total of 22 (73%) completed the dietary and lifestyle survey; 18 (63%) returned a stool sample. Even after controlling for socioeconomic, dietary, or treatment-related covariates, microbiome composition was associated with race and ethnicity. Fusobacteriota (a phylum associated with the development and progression of CRC) was significantly higher in the Black/African American group compared to others, and microbial diversity was higher in samples from non-Hispanic White individuals compared to Hispanic/Latino individuals.

CONCLUSION

Our study shows that it is feasible to recruit and collect stool samples from diverse individuals with CRC and found significant associations in gut microbial structure with race and ethnicity.

Variety of Fruit and Vegetables and Alcohol Intake are Associated with Gut Microbial Species and Gene Abundance in Colorectal Cancer Survivors

BACKGROUND

Adherence to the American Cancer Society (ACS) guidelines of avoiding obesity, maintaining physical activity, and consuming a diet rich in fruits, vegetables, and whole grains is associated with longer survival in colorectal cancer (CRC) survivors. Dietary components of the ACS guidelines may act in part by changing the microbiome, which is implicated in CRC outcomes.

OBJECTIVES

We conducted a pilot cross-sectional study to explore associations between ACS guidelines and the gut microbiome.

METHODS

Stool samples and questionnaires were collected from 28 CRC survivors at the University of California, San Francisco from 2019 to 2020. ACS scores were calculated based on validated questionnaires. Gut microbial community structure from 16S amplicons and gene/pathway abundances from metagenomics were tested for associations with the ACS score and its components using ANOVA and general linear models.

RESULTS

The overall ACS score was not significantly associated with variations in the fecal microbiota. However, fruit and vegetable intake and alcohol intake accounted for 19% (P = 0.005) and 13% (P = 0.01) of variation in the microbiota, respectively. Fruit/vegetable consumption was associated with increased microbial diversity, increased Firmicutes, decreased Bacteroidota, and changes to multiple genes and metabolic pathways, including enriched pathways for amino acid and short-chain fatty acid biosynthesis and plant-associated sugar degradation. In contrast, alcohol consumption was positively associated with overall microbial diversity, negatively associated with Bacteroidota abundance, and associated with changes to multiple genes and metabolic pathways. The other components of the ACS score were not statistically significantly associated with the fecal microbiota in our sample.

CONCLUSIONS

These results guide future studies examining the impact of changes in the intake of fruits, vegetables, and alcoholic drinks on the gut microbiome of CRC survivors.

Human induced pluripotent stem cell-derived liver-on-a-chip for studying drug metabolism: the challenge of the cytochrome P450 family

The liver is the primary organ responsible for the detoxification and metabolism of drugs. To date, a lack of preclinical models that accurately emulate drug metabolism by the human liver presents a significant challenge in the drug development pipeline, particularly for predicting drug efficacy and toxicity. In recent years, emerging microfluidic-based organ-on-a-chip (OoC) technologies, combined with human induced pluripotent stem cell (hiPSC) technology, present a promising avenue for the complete recapitulation of human organ biology in a patient-specific manner. However, hiPSC-derived organoids and liver-on-a-chip models have so far failed to sufficiently express cytochrome P450 monooxygenase (CYP450) enzymes, the key enzymes involved in first-pass metabolism, which limits the effectiveness and translatability of these models in drug metabolism studies. This review explores the potential of innovative organoid and OoC technologies for studying drug metabolism and discusses their existing drawbacks, such as low expression of CYP450 genes. Finally, we postulate potential approaches for enhancing CYP450 expression in the hope of paving the way toward developing novel, fully representative liver drug-metabolism models.

Intracellular hydrogelation of macrophage conjugated probiotics for hitchhiking delivery and combined treatment of colitis

Immune cell membrane coated nanomedicine was developed to neutralize cytokines via receptor-ligand interaction, which showed potential for the treatment of inflammatory bowel disease (IBD). However, cell membrane isolation and re-assembly process involved protein loss and spatial disorder, which reduced the sequestration efficiency towards cytokines. In addition, oral administration of probiotics was accepted for IBD treatment via gut microbiota modulation, but most probiotics showed weak adhesion to intestine mucosa and were quickly expelled from gastrointestinal tract. Herein, an intracellular hydrogelation technology was proposed to construct gelated peritoneal macrophage (GPM) with intact membrane structure, resulting from the avoidance of membrane isolation and re-assembly process. GPM efficiently neutralized multiple cytokines in vitro and in vivo to ameliorate inflammatory Caco-2 ​cells and colitis rats by regulating oxidative stress, inflammation level and intestinal barrier repair. Moreover, the probiotics (Nissle1917, EcN) were easily attached on GPM surface through specific recognition, to construct GPM-EcN conjugate for GPM hitchhiking delivery to colitis tissue. Conjugation process of GPM and EcN showed no damage on bacterial physiological function. Due to the chemical attachment on inflammatory cells, GPM carried the attached EcN hand-in-hand to accumulate in the colitis tissue of IBD rat, and enhanced intestine retention time of EcN in comparison to free EcN, which improved bacterial diversity, and shifted the microbiota community and acid metabolites to an anti-inflammatory phenotype. This study transferred the hydrogel synthesis from in vitro to intracellular cytoplasm, and came to a new insight of conjugating strategy of GPM and probiotics for hitchhiking delivery and combined anti-IBD treatment.

A Review of Gut Microbiota-Derived Metabolites in Tumor Progression and Cancer Therapy

Gut microbiota-derived metabolites are key hubs connecting the gut microbiome and cancer progression, primarily by remodeling the tumor microenvironment and regulating key signaling pathways in cancer cells and multiple immune cells. The use of microbial metabolites in radiotherapy and chemotherapy mitigates the severe side effects from treatment and improves the efficacy of treatment. Immunotherapy combined with microbial metabolites effectively activates the immune system to kill tumors and overcomes drug resistance. Consequently, various novel strategies have been developed to modulate microbial metabolites. Manipulation of genes involved in microbial metabolism using synthetic biology approaches directly affects levels of microbial metabolites, while fecal microbial transplantation and phage strategies affect levels of microbial metabolites by altering the composition of the microbiome. However, some microbial metabolites harbor paradoxical functions depending on the context (e.g., type of cancer). Furthermore, the metabolic effects of microorganisms on certain anticancer drugs such as irinotecan and gemcitabine, render the drugs ineffective or exacerbate their adverse effects. Therefore, a personalized and comprehensive consideration of the patient's condition is required when employing microbial metabolites to treat cancer. The purpose of this review is to summarize the correlation between gut microbiota-derived metabolites and cancer, and to provide fresh ideas for future scientific research.

Decipher enzymes from human microbiota for drug discovery and development

The human microbiota plays an important role in human health and contributes to the metabolism of therapeutic drugs affecting their potency. However, the current knowledge on human gut bacterial metabolism is limited and lacks an understanding of the underlying mechanisms of observed drug biotransformations. Despite the complexity of the gut microbial community, genomic and metagenomic sequencing provides insights into the diversity of chemical reactions that can be carried out by the microbiota and poses new challenges to functionally annotate thousands of bacterial enzymes. Here, we outline methods to systematically address the structural and functional space of the human microbiome, highlighting a combination of in silico and in vitro approaches. Systematic knowledge about microbial enzymes could eventually be applied for personalized therapy, the development of prodrugs and modulators of unwanted bacterial activity, and the further discovery of new antibiotics.

Gut microbes promote chemoradiotherapy resistance via metabolic cross-feeding

Gut microorganisms can modulate response to cancer therapies. In this issue of Cancer Cell, Teng et al. trace the gut bacteria and metabolites in rectal cancer patients over the course of neoadjuvant chemoradiotherapy and identify Bacteroides vulgatus as a driver bacterium of therapeutic resistance by supplying tumors with nucleotides.

Pharmacomicrobiomics in Anticancer Therapies: Why the Gut Microbiota Should Be Pointed Out

Anticancer treatments have shown a variable therapeutic outcome that may be partly attributable to the activity of the gut microbiota on the pathology and/or therapies. In recent years, microbiota-drug interactions have been extensively investigated, but most of the underlying molecular mechanisms still remain unclear. In this review, we discuss the relationship between the gut microbiota and some of the most commonly used drugs in oncological diseases. Different strategies for manipulating the gut microbiota layout (i.e., prebiotics, probiotics, antibiotics, and fecal microbiota transplantation) are then explored in order to optimize clinical outcomes in cancer patients. Anticancer technologies that exploit tumor-associated bacteria to target tumors and biotransform drugs are also briefly discussed. In the field of pharmacomicrobiomics, multi-omics strategies coupled with machine and deep learning are urgently needed to bring to light the interaction among gut microbiota, drugs, and host for the development of truly personalized precision therapies.