Expansion of Colorectal Cancer Biomarkers Based on Gut Bacteria and Viruses

Diversity in gut microbiota among colorectal cancer patients: findings from a case-control study conducted at a Tunisian University Hospital

PURPOSE

Globally, colorectal cancer (CRC) is among the most prevalent cancers. One distinctive feature of colorectal cancer is its close relationship to the gut microbiota, which is a crucial component of the tumor microenvironment. Over the last ten years, research has demonstrated that colorectal cancer is accompanied with dysbiosis of gut bacteria, fungi, viruses, and Archaea, and that these alterations may be causal.

OBJECTIVES

This study aimed to evaluate the disruption of the microorganism composition in the intestine, especially bacteria and to determine their relationship with colorectal cancer.

METHODS

An evaluation system for determining colorectal cancer (CRC) risk and prognosis can be established more easily with the help of accurate gut microbiota profiling. Stool samples from 14 CRC patients and 13 controls were collected and the flora relative abundance was measured using targeted quantitative PCR (qPCR) assays to evaluate diagnostic potential of selected biomarkers: Streptococcus gallolyticus and Enterococcus faecalis. Culture and MALDI-TOF mass spectrometry were coupled to identify the gut microbiota in both colorectal cancer and control groups.

RESULTS

Compared with controls, the gut microbiota of CRC patients showed an increase in the abundance of Enterococcus, Fusobacterium and Streptococcus. At the species level, the CRC enriched bacterium including Escherichia coli, Enterococcus faecalis, Fusobacterium nucleatum, Streptococcus gallolyticus, Flavoni fractorplautii and Eggerthella lenta acted as promising biomarkers for early detection of CRC.

CONCLUSION

This study highlights the potential of gut microbiota biomarkers as a promising non-invasive tool for the accurate detection and distinction of individuals with CRC.

Characterizing the gut phageome and phage-borne antimicrobial resistance genes in pigs

BACKGROUND

Mammalian intestine harbors a mass of phages that play important roles in maintaining gut microbial ecosystem and host health. Pig has become a common model for biomedical research and provides a large amount of meat for human consumption. However, the knowledge of gut phages in pigs is still limited.

RESULTS

Here, we investigated the gut phageome in 112 pigs from seven pig breeds using PhaBOX strategy based on the metagenomic data. A total of 174,897 non-redundant gut phage genomes were assembled from 112 metagenomes. A total of 33,487 gut phage genomes were classified and these phages mainly belonged to phage families such as Ackermannviridae, Straboviridae, Peduoviridae, Zierdtviridae, Drexlerviridae, and Herelleviridae. The gut phages in seven pig breeds exhibited distinct communities and the gut phage communities changed with the age of pig. These gut phages were predicted to infect a broad range of 212 genera of prokaryotes, such as Candidatus Hamiltonella, Mycoplasma, Colwellia, and Lactobacillus. The data indicated that broad KEGG and CAZy functions were also enriched in gut phages of pigs. The gut phages also carried the antimicrobial resistance genes (ARGs) and the most abundant antimicrobial resistance genotype was diaminopyrimidine resistance.

CONCLUSIONS

Our research delineates a landscape for gut phages in seven pig breeds and reveals that gut phages serve as a key reservoir of ARGs in pigs. Video Abstract.

The multispecies microbial cluster of Fusobacterium, Parvimonas, Bacteroides and Faecalibacterium as a precision biomarker for colorectal cancer diagnosis

The incidence of colorectal cancer (CRC) has increased worldwide, and early diagnosis is crucial to reduce mortality rates. Therefore, new noninvasive biomarkers for CRC are required. Recent studies have revealed an imbalance in the oral and gut microbiomes of patients with CRC, as well as impaired gut vascular barrier function. In the present study, the microbiomes of saliva, crevicular fluid, feces, and non-neoplastic and tumor intestinal tissue samples of 93 CRC patients and 30 healthy individuals without digestive disorders (non-CRC) were analyzed by 16S rRNA metabarcoding procedures. The data revealed that Parvimonas, Fusobacterium, and Bacteroides fragilis were significantly over-represented in stool samples of CRC patients, whereas Faecalibacterium and Blautia were significantly over-abundant in the non-CRC group. Moreover, the tumor samples were enriched in well-known periodontal anaerobes, including Fusobacterium, Parvimonas, Peptostreptococcus, Porphyromonas, and Prevotella. Co-occurrence patterns of these oral microorganisms were observed in the subgingival pocket and in the tumor tissues of CRC patients, where they also correlated with other gut microbes, such as Hungatella. This study provides new evidence that oral pathobionts, normally located in subgingival pockets, can migrate to the colon and probably aggregate with aerobic bacteria, forming synergistic consortia. Furthermore, we suggest that the group composed of Fusobacterium, Parvimonas, Bacteroides, and Faecalibacterium could be used to design an excellent noninvasive fecal test for the early diagnosis of CRC. The combination of these four genera would significantly improve the reliability of a discriminatory test with respect to others that use a single species as a unique CRC biomarker.

Multiomics Analysis Revealed Colorectal Cancer Pathogenesis

Gut microbiota-derived microbial compounds may link to the pathogenesis of colorectal cancer (CRC). However, the role of the host-microbiome in the incidence and progression of CRC remains elusive. We performed 16S rRNA sequencing, metabolomics, and proteomic studies on samples from 85 CRC patients who underwent colonoscopy examination and found two distinct changed patterns of microbiome in CRC patients. The relative abundances of Catabacter and Mogibacterium continuously increased from intramucosal carcinoma to advanced stages, whereas Clostridium, Anaerostipes, Vibrio, Flavonifractor, Holdemanella, and Hungatella were significantly altered only in intermediate lesions. Fecal metabolomics analysis exhibited consistent increases in bile acids, indoles, and urobilin as well as a decrease in heme. Serum metabolomics uncovered the highest levels of bilin, glycerides, and nucleosides together with the lowest levels of bile acids and amino acids in the stage of intermediate lesions. Three fecal and one serum dipeptides were elevated in the intermediate lesions. Proteomics analysis of colorectal tissues showed that oxidation and autophagy through the PI3K/Akt-mTOR signaling pathway contribute to the development of CRC. Diagnostic analysis showed multiomics features have good predictive capability, with AUC greater than 0.85. Our overall findings revealed new candidate biomarkers for CRC, with potentially significant diagnostic and prognostic capabilities.

Impact of Periodontitis on the Leakage of Oral Bacteria to the Gut

Colorectal cancer (CRC) and periodontitis have recently been related due to the higher incidence of CRC in periodontal patients and the involvement of periodontal pathogens in carcinogenesis, suggesting that leakage from the oral cavity to the gut occurs. However, the magnitude of this pass-through in healthy individuals is controversial, and the effect that periodontitis could play in it is understudied. To evaluate the rate of bacterial leakage from the oral cavity to the gut, we analyzed the microbial composition of saliva, subgingival plaque, and fecal samples in healthy individuals without gastrointestinal disorders, including 20 periodontitis patients and 20 oral healthy controls, using PacBio full-length 16S rRNA gene sequencing. As expected, we observed a higher abundance of periodontal pathogens in the subgingival plaque and saliva of periodontal patients. In contrast, no significant differences were found between the fecal samples of both groups, implying that gut samples from periodontal patients were not enriched in periodontal pathogens. Fusobacterium nucleatum, a biomarker of CRC, was not found in the fecal samples of any participant. Our study does show a small leakage of some oral bacteria (mainly streptococci) to the gut, regardless of periodontal health status. Future studies should test whether other host factors and/or the preexistence of a gut disorder must be present in addition to periodontitis to promote the colonization of the gut by oral pathogens. The absence of periodontal pathogens in feces supports the idea that these bacteria could be used as biomarkers of intestinal disorders, including CRC.

VirGrapher: a graph-based viral identifier for long sequences from metagenomes

Viruses are the most abundant biological entities on earth and are important components of microbial communities. A metagenome contains all microorganisms from an environmental sample. Correctly identifying viruses from these mixed sequences is critical in viral analyses. It is common to identify long viral sequences, which has already been passed thought pipelines of assembly and binning. Existing deep learning-based methods divide these long sequences into short subsequences and identify them separately. This makes the relationships between them be omitted, leading to poor performance on identifying long viral sequences. In this paper, VirGrapher is proposed to improve the identification performance of long viral sequences by constructing relationships among short subsequences from long ones. VirGrapher see a long sequence as a graph and uses a Graph Convolutional Network (GCN) model to learn multilayer connections between nodes from sequences after a GCN-based node embedding model. VirGrapher achieves a better AUC value and accuracy on validation set, which is better than three benchmark methods.

Diet and gut microbial associations in irritable bowel syndrome according to disease subtype

The role of diet and the gut microbiome in the etiopathogenesis of irritable bowel syndrome (IBS) is not fully understood. Therefore, we investigated the interplay between dietary risk factors and gut microbiota in IBS subtypes using a food frequency questionnaire and stool metagenome data from 969 participants aged 18-65 years in the ZOE PREDICT 1 study, an intervention study designed to predict postprandial metabolic responses. We identified individuals with IBS subtype according to the Rome III criteria based on predominant bowel habits during symptom onset: diarrhea (i.e. looser), constipation (i.e. harder), and mixed. Participants with IBS-D (n = 59) consumed more healthy plant-based foods (e.g. whole grains, leafy vegetables) and fiber, while those with IBS-C (n = 49) tended to consume more unhealthy plant-based foods (e.g. refined grains, fruit juice) than participants without IBS (n = 797). Microbial diversity was nominally lower in patients with IBS-D than in participants without IBS or with IBS-C. Using multivariable-adjusted linear regression, we identified specific microbiota variations in IBS subtypes, including slight increases in pro-inflammatory taxa in IBS-C (e.g. Escherichia coli) and loss of strict anaerobes in IBS-D (e.g. Faecalibacterium prausnitzii). Our analysis also revealed intriguing evidence of interactions between diet and Faecalibacterium prausnitzii. The positive associations between fiber and iron intake and IBS-diarrhea were stronger among individuals with a higher relative abundance of Faecalibacterium prausnitzii, potentially driven by carbohydrate metabolic pathways, including the superpathway of β-D-glucuronide and D-glucuronate degradation. In conclusion, our findings suggest subtype-specific variations in dietary habits, gut microbial composition and function, and diet-microbiota interactions in IBS, providing insights into potential microbiome-informed dietary interventions.

Machine learning: a powerful tool for identifying key microbial agents associated with specific cancer types

Machine learning (ML) includes a broad class of computer programs that improve with experience and shows unique strengths in performing tasks such as clustering, classification and regression. Over the past decade, microbial communities have been implicated in influencing the onset, progression, metastasis, and therapeutic response of multiple cancers. Host-microbe interaction may be a physiological pathway contributing to cancer development. With the accumulation of a large number of high-throughput data, ML has been successfully applied to the study of human cancer microbiomics in an attempt to reveal the complex mechanism behind cancer. In this review, we begin with a brief overview of the data sources included in cancer microbiomics studies. Then, the characteristics of the ML algorithm are briefly introduced. Secondly, the application progress of ML in cancer microbiomics is also reviewed. Finally, we highlight the challenges and future prospects facing ML in cancer microbiomics. On this basis, we conclude that the development of cancer microbiomics can not be achieved without ML, and that ML can be used to develop tumor-targeting microbial therapies, ultimately contributing to personalized and precision medicine.

Young-onset Rectal Cancer: Unique Tumoral Microbiome and Correlation With Response to Neoadjuvant Therapy

OBJECTIVE

External exposures, the host, and the microbiome interact in oncology. We aimed to investigate tumoral microbiomes in young-onset rectal cancers (YORCs) for profiles potentially correlative with disease etiology and biology.

BACKGROUND

YORC is rapidly increasing, with 1 in 4 new rectal cancer cases occurring under the age of 50 years. Its etiology is unknown.

METHODS

YORC (<50 y old) or later-onset rectal cancer (LORC, ≥50 y old) patients underwent pretreatment biopsied of tumor and tumor-adjacent normal (TAN) tissue. After whole genome sequencing, metagenomic analysis quantified microbial communities comparing tumors versus TANs and YORCs versus LORCs, controlling for multiple testing. Response to neoadjuvant therapy (NT) was categorized as major pathological response (MPR, ≤10% residual viable tumor) versus non-MPR.

RESULTS

Our 107 tumors, 75 TANs from 37 (35%) YORCs, and 70 (65%) LORCs recapitulated bacterial species were previously associated with colorectal cancers (all P <0.0001). YORC and LORC tumoral microbiome signatures were distinct. After NT, 13 patients (12.4%) achieved complete pathologic response, whereas MPR occurred in 47 patients (44%). Among YORCs, MPR was associated with Fusobacterium nucleaum , Bacteroides dorei, and Ruminococcus bromii (all P <0.001), but MPR in LORC was associated with R. bromii ( P <0.001). Network analysis of non-MPR tumors demonstrated a preponderance of oral bacteria not observed in MPR tumors.

CONCLUSIONS

Microbial signatures were distinct between YORC and LORC. Failure to achieve an MPR was associated with oral bacteria in tumors. These findings urge further studies to decipher correlative versus mechanistic associations but suggest a potential for microbial modulation to augment current treatments.

Gut microbiota interactions with antitumor immunity in colorectal cancer: From understanding to application

Colorectal cancer (CRC) is one of highly prevalent cancer. Immunotherapy with immune checkpoint inhibitors (ICIs) has dramatically changed the landscape of treatment for many advanced cancers, but CRC still exhibits suboptimal response to immunotherapy. The gut microbiota can affect both anti-tumor and pro-tumor immune responses, and further modulate the efficacy of cancer immunotherapy, particularly in the context of therapy with ICIs. Therefore, a deeper understanding of how the gut microbiota modulates immune responses is crucial to improve the outcomes of CRC patients receiving immunotherapy and to overcome resistance in nonresponders. The present review aims to describe the relationship between the gut microbiota, CRC, and antitumor immune responses, with a particular focus on key studies and recent findings on the effect of the gut microbiota on the antitumor immune activity. We also discuss the potential mechanisms by which the gut microbiota influences host antitumor immune responses as well as the prospective role of intestinal flora in CRC treatment. Furthermore, the therapeutic potential and limitations of different modulation strategies for the gut microbiota are also discussed. These insights may facilitate to better comprehend the interplay between the gut microbiota and the antitumor immune responses of CRC patients and provide new research pathways to enhance immunotherapy efficacy and expand the patient population that could be benefited by immunotherapy.

Weighted Gene Co-Expression Network Analysis Identifies a Functional Guild and Metabolite Cluster Mediating the Relationship between Mucosal Inflammation and Adherence to the Mediterranean Diet in Ulcerative Colitis

Diet influences the pathogenesis and clinical course of inflammatory bowel disease (IBD). The Mediterranean diet (MD) is linked to reductions in inflammatory biomarkers and alterations in microbial taxa and metabolites associated with health. We aimed to identify features of the gut microbiome that mediate the relationship between the MD and fecal calprotectin (FCP) in ulcerative colitis (UC). Weighted gene co-expression network analysis (WGCNA) was used to identify modules of co-abundant microbial taxa and metabolites correlated with the MD and FCP. The features considered were gut microbial taxa, serum metabolites, dietary components, short-chain fatty acid and bile acid profiles in participants that experienced an increase (n = 13) or decrease in FCP (n = 16) over eight weeks. WGCNA revealed ten modules containing sixteen key features that acted as key mediators between the MD and FCP. Three taxa (Faecalibacterium prausnitzii, Dorea longicatena, Roseburia inulinivorans) and a cluster of four metabolites (benzyl alcohol, 3-hydroxyphenylacetate, 3-4-hydroxyphenylacetate and phenylacetate) demonstrated a strong mediating effect (ACME: -1.23, p = 0.004). This study identified a novel association between diet, inflammation and the gut microbiome, providing new insights into the underlying mechanisms of how a MD may influence IBD. See clinicaltrials.gov (NCT04474561).

Causal relationships between gut microbiota and programmed cell death protein 1/programmed cell death-ligand 1: A bidirectional Mendelian randomization study

Background

Multiple clinical studies have indicated that the gut microbiota influences the effects of immune checkpoint blockade (ICB) therapy comprising PD-1/PD-L1 inhibitors, but the causal relationship is unclear. Because of numerous confounders, many microbes related to PD-1/PD-L1 have not been identified. This study aimed to determine the causal relationship between the microbiota and PD-1/PD-L1 and identify possible biomarkers for ICB therapy.

Method

We used bidirectional two-sample Mendelian randomization with two different thresholds to explore the potential causal relationship between the microbiota and PD-1/PD-L1 and species-level microbiota GWAS to verify the result.

Result

In the primary forward analysis, genus_Holdemanella showed a negative correlation with PD-1 [βIVW = -0.25; 95% CI (-0.43 to -0.07); PFDR = 0.028] and genus_Prevotella9 showed a positive correlation with PD-1 [βIVW = 0.2; 95% CI (0.1 to 0.4); PFDR = 0.027]; order_Rhodospirillales [βIVW = 0.2; 95% CI (0.1 to 0.4); PFDR = 0.044], family_Rhodospirillaceae [βIVW = 0.2; 95% CI (0 to 0.4); PFDR = 0.032], genus_Ruminococcaceae_UCG005 [βIVW = 0.29; 95% CI (0.08 to 0.5); PFDR = 0.028], genus_Ruminococcus_gnavus_group [βIVW = 0.22; 95% CI (0.05 to 0.4); PFDR = 0.029], and genus_Coprococcus_2 [βIVW = 0.4; 95% CI (0.1 to 0.6); PFDR = 0.018] were positively correlated with PD-L1; and phylum_Firmicutes [βIVW = -0.3; 95% CI (-0.4 to -0.1); PFDR = 0.031], family_ClostridialesvadinBB60group [βIVW = -0.31; 95% CI (-0.5 to -0.11), PFDR = 0.008], family_Ruminococcaceae [βIVW = -0.33; 95% CI (-0.58 to -0.07); PFDR = 0.049], and genus_Ruminococcaceae_UCG014 [βIVW = -0.35; 95% CI (-0.57 to -0.13); PFDR = 0.006] were negatively correlated with PD-L1. The one significant species in further analysis was species_Parabacteroides_unclassified [βIVW = 0.2; 95% CI (0-0.4); PFDR = 0.029]. Heterogeneity (P &gt; 0.05) and pleiotropy (P &gt; 0.05) analyses confirmed the robustness of the MR results.

Tissue vs. Fecal-Derived Bacterial Dysbiosis in Precancerous Colorectal Lesions: A Systematic Review

Alterations in gut microbiota play a pivotal role in the adenoma-carcinoma sequence. However, there is still a notable lack of the correct implementation of tissue and fecal sampling in the setting of human gut microbiota examination. This study aimed to review the literature and to consolidate the current evidence on the use of mucosa and a stool-based matrix investigating human gut microbiota changes in precancerous colorectal lesions. A systematic review of papers from 2012 until November 2022 published on the PubMed and Web of Science databases was conducted. The majority of the included studies have significantly associated gut microbial dysbiosis with premalignant polyps in the colorectum. Although methodological differences hampered the precise fecal and tissue-derived dysbiosis comparison, the analysis revealed several common characteristics in stool-based and fecal-derived gut microbiota structures in patients with colorectal polyps: simple or advanced adenomas, serrated lesions, and carcinomas in situ. The mucosal samples considered were more relevant for the evaluation of microbiota's pathophysiological involvement in CR carcinogenesis, while non-invasive stool sampling could be beneficial for early CRC detection strategies in the future. Further studies are required to identify and validate mucosa-associated and luminal colorectal microbial patterns and their role in CRC carcinogenesis, as well as in the clinical setting of human microbiota studies.

The Gut Microbiome and Its Implication in the Mucosal Digestive Disorders

The gastrointestinal (GI) tract is one of the most studied compartments of the human body as it hosts the largest microbial community including trillions of germs. The relationship between the human and its associated flora is complex, as the microbiome plays an important role in nutrition, metabolism and immune function. With a dynamic composition, influenced by many intrinsic and extrinsic factors, there is an equilibrium maintained in the composition of GI microbiota, translated as "eubiosis". Any disruption of the microbiota leads to the development of different local and systemic diseases. This article reviews the human GI microbiome's composition and function in healthy individuals as well as its involvement in the pathogenesis of different digestive disorders. It also highlights the possibility to consider flora manipulation a therapeutic option when treating GI diseases.