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Review
Colorectal cancer
 Gut microbiome in colorectal cancer: recent advances and clinical implications
Jun Yong Han1orcid, Min Jung Kim1,2,3orcid, Ji Won Park1,2,3orcid, Seung-Yong Jeong1,2,3orcid
Annals of Coloproctology 2026;42(1):72-85.
DOI: https://doi.org/10.3393/ac.2026.00010.0001
Published online: February 25, 2026

1Department of Surgery, Seoul National University College of Medicine, Seoul, Korea

2Colorectal Cancer Center, Seoul National University Cancer Hospital, Seoul, Korea

3Seoul National University Cancer Research Institute, Seoul, Korea

Correspondence to: Min Jung Kim, MD, PhD Department of Surgery, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul 03080, Korea Email: minjungkim@snuh.org
• Received: January 1, 2026   • Revised: January 17, 2026   • Accepted: January 17, 2026

© 2026 The Korean Society of Coloproctology

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • The gut microbiome is not just a bystander of colorectal carcinogenesis but is an active driver of colorectal cancer (CRC). CRC-associated microbiome contributes in the tumorigenesis through chronic inflammation, formation of toxic metabolite and genotoxins, oncogenic signal activation, immune evasion, and barrier disruption—all reinforcing a tumor microenvironment. In contrast, beneficial microbiome supports the barrier-immune-metabolic axis by maintaining mucosal integrity and balanced immune tone. Despite extensive studies of microbiome-based CRC biomarkers, microbiome-based CRC biomarkers have not been yet ready for routine clinical use due to variation across populations and lack of standardization of key steps such as sampling, analysis, cutoffs, and interpretation. Microbiome-based therapies aim to change the overall intestinal ecosystem rather than simply adding or removing single strains. At present, dietary modulation and prebiotics are considered supportive measures, while probiotics or synbiotics are in preclinical stage. Fecal microbiota transplantation (FMT) still faces important challenges in effectiveness, standardization and safety. By its role in reshaping the tumor–host immune environment, FMT is viewed as a potential option for cancer therapy after further development through well-controlled clinical trials with careful safety monitoring.
  • Keywords: Gastrointestinal microbiome; Colorectal neoplasms; Carcinogenesis; Biomarkers
The etiology of colorectal cancer (CRC), the second most common cause of cancer-related morbidity worldwide, is complex and multifactorial [1]. Some established factors such as inherited susceptibility, lifestyle and dietary patterns, explain a substantial proportion of CRC risk [2, 3]. However, they do not fully explain the variability in CRC incidence and tumor behavior. This limitation has prompted growing interest in additional host–environment interactions that may contribute to CRC. In recent years, gut microbiome has been in the spotlight as a potential factor of colorectal carcinogenesis [4, 5]. The gut microbiome is a community of intestinal microorganisms [6] which interacts with dietary and environmental factors and regulates host metabolism and immune responses determining susceptibility to diseases [7]. Eubiosis, a balanced gut microbiome composition, supports intestinal barrier integrity, maintains immune and metabolic homeostasis, and confers colonization resistance against pathogenic microorganisms. Dysbiosis, alterations in the composition, can disrupt homeostasis and have been increasingly associated with CRC [8].
Dysbiosis is driven by a combination of diet, medications, host factors and environmental exposures [9]. In dysbiosis, pathogens associated with CRC begin to emerge and expand. Fusobacterium nucleatum (Fn), polyketide synthase positive (pks+) Escherichia coli, enterotoxigenic Bacteroides fragilis (ETBF), Streptococcus gallolyticus subsp gallolyticus (Sgg), and Peptostreptococcus anaerobius (Pa) are among the best-characterized pathogens [10]. There are several pathways these pathogens contribute to CRC (Fig. 1) [11]. First, they drive chronic inflammation by activating innate immune pathways and producing pro-inflammatory cytokines, creating a tumor microenvironment [12]. Second, some generate toxic metabolites, including specific secondary bile acids and other small molecules, altering metabolism and inducing oxidative stress [13]. Third, genotoxins produced by certain strains can directly damage host DNA, causing double-strand breaks (DSBs), and accelerate the accumulation of driver alterations. Fourth, bacterial adhesins and toxins can activate oncogenic signaling pathways such as Wnt/β-catenin, nuclear factor–κB (NF-κB), and signal transducer and activator of transcription 3 (STAT3), leading to increased cell division and resistance to cell death [14]. Fifth, the microbiome can modulate antitumor immunity by recruiting immunosuppressive cells or inhibiting T-cell function, thus enabling immune evasion [14]. Finally, disruption of the mucus layer and epithelial junctions compromises barrier integrity, increasing exposure to antigens and metabolites, further reinforcing these carcinogenic processes.
These biological insights have motivated 2 major translational clinical research directions: microbiome-based biomarkers and microbiome-based therapies. From a diagnostic perspective, microbiome signatures can be assessed noninvasively and may reflect CRC-associated host–microbe alterations, thus have potential as adjunct biomarkers for risk stratification, early detection and screening. From a therapeutic perspective, the microbiome is regarded as a modifier of tumorigenesis, suggesting that manipulating microbial ecosystems may influence treatment tolerance and responsiveness. Taken together, the gut microbiome is both a measurable marker of CRC-associated biology and a potentially modifiable factor, highlighting the need to clarify underlying mechanisms and to define practical routes for clinical translation.
In this review, recent advances in gut microbiome and CRC research were reviewed, with an emphasis on the mechanisms of carcinogenesis and the clinical implications of the microbiome. CRC-associated pathogenic bacteria and representative host–microbe interaction pathways relevant to tumor initiation and progression are first described (Fig. 2, Table 1) [15–39]. Protective bacterial functions that stabilize mucosal homeostasis are then discussed, with a focus on microbiota-derived metabolites that shape the barrier-immune-metabolic axis. Finally, recent research trends of microbiome-based biomarker and therapeutic implications are reviewed in the context of the current levels of clinical evidence.
Fusobacterium nucleatum
Fn is a gram-negative anaerobe that commonly resides in the oral cavity [40]. Many studies have observed Fn to be more concentrated in the CRC tissue compared to the surrounding normal mucosa, raising concerns about its association with CRC [15]. Fn adheres to and invades colonic epithelial cells via specific bacterial adhesins called FadA. FadA binds to epithelial cadherin (E-cadherin), a cell adhesion molecule primarily expressed in epithelial cells, and disrupts the normal cadherin–β-catenin complex [15]. The disrupted cadherin–β-catenin complex prevents β-catenin degradation and promotes its nuclear accumulation. Accumulated β-catenin activates Wnt/β-catenin signaling pathway, enhancing proliferative gene expression and contributing to early tumorigenesis. Fn also expresses lipopolysaccharides (LPS) which bind to Toll-like receptor 4 (TLR4) of epithelial tissues [16]. TLR4 signaling via myeloid differentiation primary response 88 (MYD88) activates NF-κB and induces pro-inflammatory cytokines; together with FadA-driven β-catenin activation, Fn colonization promotes tumor-associated transcriptional programs.
Fn also promotes immune evasion: its outer membrane protein Fap2 binds to T-cell immunoreceptor with immunoglobulin and ITIM (immunoreceptor tyrosine-based inhibitory motif) domains (TIGIT) [17]. TIGIT is an immune checkpoint receptor expressed on the surface of T cells or NK cells, reducing cytotoxic responses against tumor cells. Fap2 binding activates TIGIT and contributes to immune evasion, making a tumor-producing environment [41].
In addition, Fn plays a role in disease progression. Fn can facilitate dissemination by compromising barrier integrity. FadA acts on vascular endothelial cadherin, loosening the junctions between vascular cells and accelerating the infiltration of other pathogens and signaling molecules via the blood stream [42]. Fn promotes therapy resistance and persistence; Fn has been linked to chemoresistance via autophagy, in which TLR4/MYD88 signaling and microRNA-mediated regulatory networks converge on autophagy pathway activation, reducing chemotherapy-induced tumor cell killing [43]. Fn-associated chemoresistance has also been reported to be associated to antiapoptosis that reduce 5-fluorouracil (5-FU) response [44]. Overall, Fn is not an organism that merely accumulates in CRC, but is an active promoter of tumor development and progression by acting on tumor cells and creating a tumorigenic environment.
pks+ E. coli
E. coli is a well-known gram-negative bacillus bacterium usually found in the gastrointestinal tract. pks+ E coli is a strain belonging to phylogroup B2 E. coli with pks, 54-kilobase sized pathogenicity island [45]. The pks island endcodes the enzyme producing a genotoxin called colibactin [46]. Colibactin exposure leaves characteristic mutational signatures, most notably single base substitution signature SBS88 and indel signature ID18 [18, 19]. These colibactin-associated mutations are enriched at specific APC motifs, including a recurrent APC splice-site hotspot (c.835-8A>G), and intratumoral pks+ E. coli has been linked to this APC alteration, particularly in early-onset CRCs. Consistently, colibactin-positive CRC cases tend to present at a younger age across multiple cohorts, supporting a potential role of early-life or prolonged exposure in accelerating tumorigenesis [20]. Colibactin induces DNA alkylation and interstrand crosslinks, leading to replication stress and DSBs, thereby promoting genomic instability and mutagenesis [21]. DSBs trigger stress responses and pro-inflammatory signaling [47], while repeated damage increases error-prone repair, accelerating mutation accumulation and intratumoral heterogeneity [22]—together fostering a microenvironment that supports tumor initiation and progression. In addition, colibactin damages the gut epithelial barrier, increasing the permeability of intestinal mucosa, and contributing to carcinogenesis by causing leakage of bacterial toxins and antigens [23]. Colibactin also promotes immunosuppressive microenvironment by regulating the host's immune and causing cell cycle arrest and promoting cell aging [48]. Taken together, pks+ E. coli can act as a driver of carcinogenesis that directly imprints tumor genomes while concurrently remodeling epithelial barrier integrity, inflammatory signaling, and immune tone in ways that accelerate colorectal tumor initiation and progression.
Enterotoxigenic B. fragilis
B. fragilis is one of the most abundant gram-negative anaerobe in the human gut [49]. B. fragilis is divided into ETBF, which makes B. fragilis toxin (BFT), and nontoxigenic B. fragilis (NTBF), which does not [50]. BFT, a zinc dependent 20 kDA metalloprotease is an important factor for tumorigenesis of ETBF [24, 51]. BFT cleaves E-cadherin and facilitates β-catenin nuclear translocation [25]. Accumulated β-catenin upregulates inflammatory and tumor-promoting signaling pathways such as NF-κB, Wnt and interleukin 17 (IL-17)/STAT [24, 52]. Inflammatory responses driven by IL-17, IL-6, and STAT3 activation, lead to epithelial proliferation and dysplasia in epithelial cells [26]. It also induces the production of cyclooxygenase 2 (COX-2), prostaglandin E2, reactive oxygen species (ROS), and the secretion of inflammatory cytokines [27]. The oncogenic pathway and inflammation-inducing reactions induced by BFT contributes to the development of colon cancer.
P. anaerobius
Pa is a gram-positive anaerobe that coexists in the oral cavity and gut. They are observed to be selectively increased in growth in stools and tumor/mucosal tissues of CRC patients. Pa is involved in epithelial cell metabolic reprogramming, inflammatory signal amplification and immunosuppression. Pa elevates ROS levels by signaling through TLR2 and TLR4 in colonic epithelial and cancer cells. ROS activates the sterol regulatory element-binding protein 2 (SREBP2) signaling pathway, increasing cholesterol biosynthesis promoting cancer cell proliferation and colonic dysplasia [28]. Pa directly amplifies inflammatory signals within the tumor microenvironment [29]. A surface protein of Pa, called putative cell wall binding repeat 2 (PCWBR2), interacts with integrin α2/β1 on colon cells to activate the NF-κB cascade. This interaction reinforces pro-inflammatory immune responses. Pa is also known to attenuate antitumor immunity by activating immunosuppressive myeloid-derived suppressor cell (MDSC) in a tumor microenvironment [30]. These signaling pathways inhibit antitumor activity of CD8+ and CD4+ T cells and decrease anti–programmed death receptor 1 (anti–PD-1) immunotherapy response.
S. gallolyticus subsp gallolyticus
Sgg is associated with the initiation and progression of CRC. The carcinogenic mechanism of Sgg can be described with several specific molecular pathways. First, Sgg carries multiple pili that support the adaptation and colonization to colon tissue. The pil1 pilus binds to collagens, especially types I and IV, facilitating adherence and persistence in neoplastic colonic sites, while the pil3 pilus promotes colonic colonization by binding to colonic mucins and fibrinogen [31]. Second, Sgg directly activates Wnt/β-catenin signaling pathway, promoting abnormal proliferation of tumor cells [32]. β-catenin binds to TCF/LEF transcription factors, abnormally increasing the expression of major cell cycle regulatory genes such as c-Myc and cyclin D1. Third, Sgg supports tumor growth by creating a chronic inflammatory microenvironment and regulating the immune response [33]. The attachment of Sgg upregulates the expression of COX-2 and increases the synthesis of inflammatory prostaglandins. At the same time, it maintains a local chronic inflammatory state by stimulating the secretion of pro-inflammatory cytokines such as IL-6, and IL-8. By these mechanisms, Sgg has been recognized as a key pathogen of accelerating tumor malignancy and progression.
This section explores the protective role of the intestinal microbial ecosystem. In a normal intestinal environment, butyrate-producing bacteria such as Faecalibacterium prausnitzii, Roseburia, Eubacterium, and lactate-producing bacteria such as Bifidobacterium and Lactobacillus protect the mucosal barrier and maintain immune homeostasis [53]. In fact, F. prausnitzii is a representative example of beneficial bacteria in the CRC context, as its protective effect has been reported to alleviate inflammation and tumor-related indicators in the experimental model [54, 55]. In addition, Bifidobacteria, including Bifidobacterium longum, have been observed to have antitumor effects through immune response control and normalization of intestinal microbial composition [56]. Akkermansia muciniphila, associated with the mucus layer and immune response, have various reports on the relationship with the immunotherapy response depending on the experimental conditions and the survival/administration method of the bacteria, so a context-based interpretation is needed [57, 58].
The key to beneficial intestinal microorganisms is not only in the bacteria themselves, but also in the microbiological metabolites produced by the bacteria that change the host biology. Typically, short-chain fatty acids (SCFAs; acetate/propionate/butyrate) are produced by dietary fiber fermentation and are involved in the provision of energy sources of colon epithelial cells, the regulation of inflammation, and the maintenance of barrier functions [59, 60]. In particular, butyrate has been described in the antitumor role with growth inhibition, differentiation, and apoptosis induction in tumor cells through the epigenetic regulation. Histone deacetylase inhibition and mechanisms that adjust dendritic cell/T-cell response to escape from over-inflammatory condition have been reported even at the immune cell level [61]. In addition, tryptophan-derived indole metabolites are organized as an axis that regulates the intestinal mucosal barrier and immune tone through the aryl hydrocarbon receptor axis [62], and it is suggested that tryptophan-indole metabolic changes can be observed early in CRC. This concept of beneficial bacteria and metabolites has recently been extended to the frame of clinical applicability, while safety and standardization is still being discussed.
Finally, beneficial gut microbiota in CRC should be conceptualized as an ecosystem level function that integrates epithelial barrier maintenance, immune regulation, and metabolic homeostasis rather than as individual taxa. By preserving mucus and tight-junction integrity and shaping epithelial metabolism, it limits antigen translocation, oxidative stress, and chronic low-grade inflammation while maintaining baseline mucosal defense. Overall, this system-level stabilization reduces the conditions that foster tumor-promoting microenvironments.
Microbiome-based biomarker in CRC is a potential microbial predictive model that aims to capture CRC-related changes in microbial composition for early detection, risk evaluation, prognosis, or treatment-response prediction [63]. Early CRC microbiome biomarker studies were mainly cross-sectional and discovery-oriented, detecting differences between CRC and control groups, and suggesting CRC-associated pathogens as biomarkers. The recent research shifted from single bacteria to stool metagenomic, multimarker panels for noninvasive screening. Metagenomics is a method that reads the DNA of the entire microbial community in a sample, rather than testing for one specific bacterium [64]. The following studies highlight key trends in developing and validating these metagenomic stool biomarkers (Table 2) [34, 65–69].
Wu et al. [65] combined 1,056 publicly available stool metagenome samples and looked for gut bacteria patterns linked to colorectal adenomas. Even though the studies came from different places and their overall microbiome profiles varied a lot, the adenoma-related signals showed up consistently across cohorts. Su et al. [66] trained a multiclass machine learning model using fecal metagenomes from 2,320 individuals, which achieved high diagnostic performance for CRC and showed solid performance when evaluated on independent datasets. Gao et al. [67] showed that strain-level difference in gut bacteria, called single nucleotide variants (SNVs) from fecal metagenomes can detect early colorectal lesions better than using only how much of each species or gene is present. Their SNV-based models maintained accuracy in cross-cohort testing, which implies that strain-level signals stay more consistent even when bacterial abundance varies across cohorts. Tito et al. [68] demonstrated that many known stool biomarkers can be confounded by stool and host factors such as intestinal inflammation, stool features influenced by bowel transit and body composition, leading to misleading marker lists when only relative abundance is considered. After adjusting for confounding variables, some pathogens known to be associated with CRC no longer looked clearly linked. This shows that accurate quantification and careful control of confounders are necessary to find biomarkers that stay reliable across different disease stages. More recently, Piccinno et al. [69] combined 3,741 stool metagenome samples from 18 different cohorts and looked for microbial patterns that were consistently seen across multiple studies and across different stages of CRC. The study showed that using a large pooled analysis can help pick biomarkers that are more reliable even when populations and study methods vary. They also went a step further by examining strain-level differences, including different subtype clades of Fn, and found signals related to how advanced the tumor is and where in the colon the tumor is located. In other words, the stool markers not only were useful for diagnosis but also provided information linked to prognosis and location. Similarly, Périchon et al. [34] quantified multiple CRC-associated bacteria in stool and showed that detection rates vary by disease stage rather than moving in parallel for all markers. Notably, ETBF was frequently detectable already at the adenoma stage while other markers increased toward advanced CRC.
Compared with current screening such as fecal immunochemical test (FIT) and colonoscopy, microbiome assays offer the potential advantages of richer biological information and multimarker pattern recognition from a single stool sample, but they currently face disadvantages in cost, complexity, and performance transportability across cohorts. Therefore, microbiome signatures should be framed as research-use or investigational tools at present and the next steps are to standardize stool collection and processing and to test the same models prospectively in real screening workflows. Several large clinical studies are already underway to evaluate fecal metagenomics or microbiome-based screening approaches in screening-like populations, rather than small case–control cohorts [70–72]. Collectively, these efforts should clarify the real-world added value of microbiome markers and define how they can be integrated into population screening as a complementary and scalable test.
The recent trend of gut microbiome-based treatment is expanding in the direction of restructuring the intestinal environment and controlling the response and toxicity of chemotherapy by targeting disease-related functions and ecosystems, not just the simple increase and decrease control of specific strains [5]. In this section, the principles of various therapeutic implications related to gut microbiome and the steps in the research progress are described (Table 3) [73–95].
Dietary modulation and prebiotics
Dietary modulation and prebiotics are a treatment strategy to strengthen the growth and metabolic function of beneficial bacteria through fiber and plant-based foods, and to induce the production of SCFAs, stabilization of intestinal mucosal barriers, and reduction of inflammatory tone. Evidence supporting this strategy has been mainly accumulated in epidemiological studies [85]. In prospective cohorts and meta-analysis, associations with higher dietary fiber intake have been repeatedly reported to lower the risk of CRC [86]. International recommendations have also suggested that increased dietary fiber intake is consistently linked to reduced risk of CRC. However, randomized trials verifying the effectiveness as a therapeutic intervention showed different results. Adenoma recurrence was not reduced in a large-scale multicenter randomized trial with a low-fat, high-fiber diet, and no effect of preventing adenoma recurrence was confirmed in another randomized trial using wheat bran fiber supplementation [73, 74]. This discrepancy suggests that even though diet can positively shift microbiota and metabolic environment, it is difficult to translate into therapeutic effects due to short-term interventions, compliance, underlying microbiota heterogeneity, confounding factors and susceptibility issues of clinical endpoints. Also in a recent review, high-fiber diets have strong epidemiological evidence associated with risk reduction, while randomized trials aimed at preventing recurrence are generally neutral or negative [87]. Therefore, at the current stage, dietary control and prebiotics are closer to the recommended position as adjuvant strategies for lifestyle-level prevention and standard treatment rather than being defined as monotherapy in CRC, and in the future, research is being conducted in the direction of re-evaluating therapeutic effectiveness through response prediction according to underlying microbiota characteristics and standardized intervention design.
Probiotics, synbiotics, and postbiotics
Probiotics refer to living bacteria that have health-related benefits when consumed in sufficient amounts, and in the CRC context, it is treated to resolve dysbiosis by introducing beneficial microbes in the intestine. Synbiotics is a combination of living beneficial bacteria and the substrates that they selectively use. Postbiotics is a standardized form of nonliving microorganisms and their components, and it is extended to a microbial metabolites-based approach in actual clinical applications. Most studies for probiotics, synbiotics, and postbiotics with CRC are still at the preclinical stage. In probiotics study with CRC mouse model, oral supplementation with 2 Bifidobacterium breve strains reduced tumor growth, but only 1 strain further enhanced the antitumor efficacy of oxaliplatin and PD-1 blockade [75]. Another postbiotics study performed by our group showed that cell-free bacterial products from beneficial Bifidobacterium species could suppress growth in CRC organoid models [76]. A recent synbiotics study tested a probiotics with its supportive substrate in a CRC mouse model. It reduced tumor incidence and mucosal injury, while also lowering inflammatory signals, improving barrier markers [77]. However, evidence from CRC patient trials remains limited, and routine use in real-world settings is premature.
Fecal microbiota transplantation
Fecal microbiota transplantation (FMT) is defined as a method of reorganizing the intestinal ecosystem by administering the feces of healthy donors to the recipients [88]. The study has been extended to a strategy of correcting dysbiosis and rearranging microbiological metabolites production and immune signals, reducing inflammation, suppressing CRC-related pathogens, and modulating immune responses through the engraftment of the donor microbiota [78]. To date, the most developed clinical evidence for FMT in oncology comes from immunotherapy settings in other tumor types, particularly melanoma, where microbiome modulation has been explored to improve immune checkpoint inhibitor responses [89]. Phase 1 clinical study of melanoma patients who had not responded to anti–PD-1 therapy results in recovering anti–PD-1 response in some patients when donor-based FMT was combined with PD-1 therapy. Also, it has been suggested that a similar concept of FMT combination clinical trial was performed in solid cancer refractory groups, which may be accompanied by immune response and microbiota change [90]. In CRC, evidence is limited, yet a phase 2 study that evaluated FMT, immunotherapy, and targeted therapy in combination at microsatellite stable metastatic CRC reported improvement signals for oncological indicators such as progression free survival, overall survival, and objective response rate, but since they were designed without a control group, it was difficult to determine the effectiveness compared to control [79, 80]. Therefore, FMT in CRC should be framed as an investigational/experimental, clinical trial–based intervention rather than an established treatment, until well-controlled prospective studies show clearly defined endpoints. In the aspect of safety, invasive infection and mortality due to the spread of multidrug-resistant bacteria have been reported in immunocompromised patients, and regulatory agencies have announced warnings and recommended additional screening [91, 92]. Safety, donor screening, and long-term ecology concerns remain major barriers.
Engineered/synthetic probiotics
Engineered probiotics are genetically modified living bacteria designed to perform specific functions within the body as a therapeutic agent [93]. Synthetic probiotics have the same concept, but are more precisely designed to operate only in a specific environment by inserting genetic pathways using synthetic biology. The principle of the strategy is to make immune modulating substances or anticancer proteins on the spot by attaching at the target location, such as a tumor. As CRC-specific preclinical support, engineered, tumor-colonizing E. coli Nissle 1917 (EcN) has been shown to selectively colonize colorectal neoplastic lesions in CRC predisposition and orthotopic CRC mouse models, allowing the bacteria to produce therapeutic molecules directly at the lesion site and leading to an experimental reduction in adenoma burden [81]. In contrast, human evidence is currently limited and largely not CRC-specific. For example, SYNB1891, a modified E coli Nissle engineered to generate STING (stimulator of interferon genes)-activating signals in advanced solid tumors, was evaluated in a phase 1 trial using intratumoral injection, alone or with atezolizumab (humanized immunoglobulin G1 monoclonal antibody targeting PD-L1). Treatment was reported to be generally safe and well tolerated, with evidence of STING pathway activation such as increased interferon-related genes and higher levels of immune signaling molecules [82]. However human clinical trials are in very early stages, and CRC-specific efficacy data remain limited. Clinical application barriers such as safety, inhibition of spread in the body, and standardization remain key challenges.
Antibiotics
Theoretically, antibiotics can eliminate specific bacteria, but as a result, it can cause dysbiosis and reduce beneficial bacteria and their metabolic functions together, making it difficult to use as a microbiota treatment strategy in CRC. Epidemiologic studies and meta-analyses have repeatedly reported that antibiotic exposure is associated with a higher risk of CRC, and a nationwide Swedish population-based study suggested that antibiotic use is associated particularly with an increased risk of proximal colon cancer [83]. A systematic review and meta-analysis in 2020 also summarized a positive association between antibiotic use and CRC risk and noted that the association may vary by antibiotic class and anatomic subsite [94]. A systematic review and meta-analysis in 2025 concluded that antibiotic exposure is associated with increased risk of benign and malignant colorectal tumors, making it hard to support antibiotics for long-term prevention or treatment purposes in CRC [84]. In addition, clinical evidence has been accumulating that antibiotic exposure may be associated with worse outcomes to immune checkpoint inhibitors, so unnecessary antibiotics should be avoided during anticancer therapy [95]. Accordingly, antibiotics should be used only when clinically indicated, such as for treatment of infection or perioperative indications, and they cannot be recommended as a therapeutic strategy for CRC treatment or recurrence prevention.
This review provides a comprehensive and up-to-date knowledge on the relationship between the gut microbiome and CRC. There have been accumulating evidence supporting the gut microbiome to be an active participant in colorectal carcinogenesis by influencing tumor initiation and progression, immune modulation, and therapeutic response.
Despite the known association of the previously described to colorectal tumorigenesis, the precise molecular and cellular pathways remain unknown. Further mechanistic studies at the molecular, cellular, and systemic levels are required to clarify causal relationships. In addition, there is a need to move beyond a pathogen-focused perspective to a systemic perspective to understand the broad microbial ecosystem and its interactions with the host, to maximize the beneficial effects of the gut microbiome on human health.
Microbiome-based diagnostic biomarkers and therapeutic strategies are rapidly evolving, yet several critical challenges remain. Large-scale prospective studies, well-designed randomized controlled trials, standardized methodologies for sampling and analysis, and quantification thresholds are still needed before routine clinical use. Despite these limitations, the gut microbiome remains a promising field with the potential to open new frontiers in the diagnosis and treatment of CRC.

Conflict of interest

No potential conflict of interest relevant to this article was reported.

Funding

None.

Author contributions

Conceptualization: all authors; Formal analysis: JYH, MJK; Investigation: JYH; Methodology: JYH, MJK; Supervision: MJK, JWP, SYJ; Visualization: JYH, MJK; Writing–original draft: JYH, MJK; Writing–review & editing: all authors. All authors read and approved the final manuscript.

Fig. 1.
Mechanistic pathways linking gut microbial dysbiosis to colorectal carcinogenesis. Fn, Fusobacterium nucleatum; TLR4, Toll-like-receptor 4; NF-κB, nuclear factor–κB; IL-6, interleukin 6; TNF-α, tumor necrosis factor α; ETBF, enterotoxigenic Bacteroides fragilis; Th17, T helper 17 cell; IL-17, interleukin 17; pks+, polyketide synthase positive; CDT, cytolethal distending toxin; BFT, Bacteroides fragilis toxin; E-cadherin, epithelial cadherin; TIGIT, T-cell immunoreceptor with immunoglobulin and ITIM (immunoreceptor tyrosine-based inhibitory motif) domains; NK, natural killer; Pa, Peptostreptococcus anaerobius; MDSC, myeloid-derived suppressor cell; TAM, tumor-associated macrophage; VE-cadherin, vascular endothelial cadherin.
ac-2026-00010-0001f1.jpg
Fig. 2.
Oncogenic mechanisms of major colorectal cancer-linked gut microbes. BFT, Bacteroides fragilis toxin; COX-2, cyclooxygenase 2; DSB, double-strand break; E-cadherin, epithelial cadherin; IL-6, interleukin 6; IL-8, interleukin 8; LPS, lipopolysaccharides; MDSC, myeloid-derived suppressor cell; MYD88, myeloid differentiation primary response 88; NF-κB, nuclear factor–κB; PCWBR2, putative cell wall binding repeat 2; PGE2, prostaglandin E2; pks+, polyketide synthase positive; ROS, reactive oxygen species; SREBP2, sterol regulatory element-binding protein 2; STAT3, signal transducer and activator of transcription 3; TIGIT, T-cell immunoreceptor with immunoglobulin and ITIM (immunoreceptor tyrosine-based inhibitory motif) domains; TLR2, Toll-like receptor 2; TLR4, Toll-like receptor 4; VE-cadherin, vascular endothelial cadherin.
ac-2026-00010-0001f2.jpg
Table 1.
CRC-associated pathogenic bacteria: evidence and unresolved questions
Pathogenic bacteria Evidence Reference
Fn
 Mechanistic data FadA binds E-cadherin → β-catenin/Wnt activation [15]
LPS–TLR4/MYD88 signaling → NF-κB activation [16]
Fap2 binds TIGIT [17]
Induces chemotherapy resistance
 Observational data Enriched in CRC tissue/stool and linked to clinicopathologic features [19]
Higher Fn burden is associated with worse outcomes in pooled analyses [35]
 Interventional data Metronidazole-mediated depletion of Fn lowers succinate level, restores the sensitivity to anti–PD-1 therapy, and suppresses tumor growth in CRC models [36]
pks+ Escherichia coli
 Mechanistic data pks island encodes colibactin → induces DSB [21]
Colibactin leaves a characteristic mutational signature [18, 20, 22]
Promotes genomic instability and epithelial barrier dysfunction [23]
 Observational data pks+ E. coli detected in human CRC tissue [19]
 Interventional data Inhibition of colibactin peptidase blocks colibactin genotoxicity and reduces tumorigenesis in colonized mouse CRC models [37]
ETBF
 Mechanistic data BFT cleaves E-cadherin and activates β-catenin/Wnt and inflammatory cascades [24, 25]
Induces Th17/IL-17–dominant mucosal inflammation that promotes tumorigenesis [26]
Associated with epigenetic remodeling of colonic epithelium in experimental models [27]
 Observational data ETBF gene  is prevalent in colonic mucosa of CRC patients and is associated with colorectal neoplasia [19]
ETBF signals reproducibly detected in population datasets → stage-dependent patterns reported [34]
 Interventional data Clearing ETBF with cefoxitin in colonized mice reduces IL-17–dependent colon tumorigenesis [38]
Pa
 Mechanistic data Activated SREBP2 increases cell proliferation via cholesterol biosynthesis [28]
Binds to integrin α2/β1 via PCWBR2 → triggers inflammatory signaling [29]
 Observational data Bacteremia with Pa is linked to CRC diagnosis in retrospective cohorts [39]
 Interventional data In mice, Pa supplementation promotes tumor growth; depletion/antibiotic approaches can restore anti–PD-1 efficacy in resistant models [30]
Sgg
 Mechanistic data Induces inflammatory and pro-proliferative signaling in colon tissue [33]
 Observational data Detected in CRC-associated microbiome profiles [31]
 Interventional data In mice, Sgg colonization increases tumor burden and accelerates tumor progression [32]

CRC, colorectal cancer; Fn, Fusobacterium nucleatum; E-cadherin, epithelial cadherin; LPS, lipopolysaccharides; TLR4, Toll-like receptor 4; MYD88, myeloid differentiation primary response 88; NF-κB, nuclear factor–κB; TIGIT, T-cell immunoreceptor with immunoglobulin and ITIM (immunoreceptor tyrosine-based inhibitory motif) domains; PD-1, programmed death receptor 1; pks, polyketide synthase; DSB, double-strand break; ETBF, enterotoxigenic Bacteroides fragilis; BFT, Bacteroides fragilis toxin; Th17, T helper 17 cell; IL-17, interleukin 17; Pa, Peptostreptococcus anaerobius; SREBP2, sterol regulatory element-binding protein 2; PCWBR2, putative cell wall binding repeat 2; Sgg, Streptococcus gallolyticus subsp gallolyticus.

Table 2.
Gut microbiome-related biomarkers in the colorectal adenoma and CRC
Study Cohort Approach Results Implication
Wu et al. [65] (2021) 1,056 Public fecal samples across multiple studies Integrated cross-study analysis with confounder adjustment Adenoma-stage signals can be reproducible across populations, supporting stool microbiome panels as an early detection
Adenoma vs. control: AUC=0.80
Adenoma vs. CRC: AUC=0.89
External validation: AUC of 0.78 and 0.84 in two independent cohorts
Su et al. [66] (2022) 2,320 Metagenomic dataset with 9 phenotypes including CRC and adenoma Multiclass machine learning on fecal metagenomes AUROC, 0.90–0.99 Propose the noninvasive model for disease screening/risk assessment and potentially for treatment-response monitoring
Sensitivity, 0.81–0.95
Specificity, 0.76–0.98
Metagenomic analysis from public datasets: AUROC, 0.69–0.91
Gao et al. [67] (2023) Cross-cohort WMS, 750 samples Comparison of multimodal features; emphasis on strain-level SNVs SNV model (adenoma vs. control): Provide a rationale of microbial SNVs for the early detection of CRC
AUC=0.89
Sensitivity=0.79
Specificity=0.85
MCC=0.74
Tito et al. [68] (2024) 589 Patients across CRC stages; compared with 15 published studies Quantitative microbiome profiling with rigorous confounder control The strongest microbiome covariates were transit time, fecal calprotectin, and BMI Stool biomarkers may reflect inflammation /transit/body composition rather than CRC itself
Total 4,439 participants The diagnosis group was not associated with microbiota variation (univariate dbRDA R²=0.2%, adjusted P=0.22) Absolute/quantitative profiling plus explicit covariate control is essential
Fn lost its apparent CRC-stage association after deconfounding (P>0.05)
Piccinno et al. [69] (2025) 3,741 Stool metagenomes from 18 cohorts Large pooled meta-analysis with strain-level analyses CRC prediction: AUC=0.85 Large, pooled training improves cross-cohort performance
Tumor location signal: left-sided vs. right-sided CRC discrimination AUC=0.66 Stool metagenomes carry location- and stage-linked signals
Périchon et al. [34] (2022) Stool PCR cohort: Targeted PCR and qPCR for 5 CRC-associated markers ETBF detection: Marker positivity is stage-dependent, multimarker, stage-aware panels
Control (n=25) Control, 24.0% ETBF’s higher detection at the adenoma stage may be useful for early-risk enrichment
Adenoma (n=23) Adenoma, 56.5%
CRC (n=81) CRC, 30.9%
 Stage I/II, 34.6%
 Stage IV, 22.2%

CRC, colorectal cancer; AUC, area under the curve; AUROC, area under the receiver operating characteristic curve; WMS, whole metagenome sequencing; SNV, single nucleotide variant; MCC, Matthews correlation coefficient; BMI, body mass index; dbRDA, distance-based redundancy analysis; Fn, Fusobacterium nucleatum; PCR, polymerase chain reaction; qPCR, quantitative polymerase chain reaction; ETBF, enterotoxigenic Bacteroides fragilis.

Table 3.
Gut microbiome–targeted interventions in CRC
Strategy Mechanism Current evidence and limitation Reference
Dietary modulation and prebiotics Promotes SCFA-producing beneficial bacteria Epidemiological evidence for reduced CRC risk with high-fiber diets [86]
→ anti-inflammatory signaling, epithelial barrier protection, immune homeostasis Randomized trials targeting adenoma/CRC recurrence largely negative or neutral
Currently lifestyle-level recommendation rather than a therapeutic intervention
Probiotics, synbiotics, and postbiotics Introduces beneficial microbes or microbial metabolites Consistent results at CRC mouse or organoid model [75–77]
→ reduces inflammation, improves gut barrier, suppresses CRC-related pathogens, modulates immune responses Evidence from CRC patient lacking
FMT Replaces dysbiotic microbiota with donor microbiota Clinical evidence mainly from melanoma in improving immune checkpoint inhibitor response [78–80]
→ reprograms immune/metabolic tumor microenvironment; enhances immunotherapy responsiveness CRC data limited, mainly small pilots/uncontrolled combination trials
Safety, donor screening, and long-term ecology concerns remain major barriers
Engineered/synthetic probiotics Genetically modified bacteria selectively colonize tumors and release anticancer molecules or immunomodulators Reduces adenoma burden in CRC mouse model [81, 82]
Human evidence is currently limited and not CRC-specific
Antibiotics Theoretical elimination of CRC-promoting pathogens or dysbiosis drivers Not recommended as a CRC-preventive/therapeutic strategy [83, 84]

CRC, colorectal cancer; SCFA, short-chain fatty acid; FMT, fecal microbiota transplantation.

  • 1. Siegel RL, Kratzer TB, Giaquinto AN, Sung H, Jemal A. Cancer statistics, 2025. CA Cancer J Clin 2025;75:10–45. ArticlePubMedPMC
  • 2. Murphy N, Moreno V, Hughes DJ, Vodicka L, Vodicka P, Aglago EK, et al. Lifestyle and dietary environmental factors in colorectal cancer susceptibility. Mol Aspects Med 2019;69:2–9. ArticlePubMed
  • 3. Zheng X, Hur J, Nguyen LH, Liu J, Song M, Wu K, et al. Comprehensive assessment of diet quality and risk of precursors of early-onset colorectal cancer. J Natl Cancer Inst 2021;113:543–52. ArticlePubMedPMCPDF
  • 4. Fong W, Li Q, Yu J. Gut microbiota modulation: a novel strategy for prevention and treatment of colorectal cancer. Oncogene 2020;39:4925–43. ArticlePubMedPMCPDF
  • 5. García Mansilla MJ, Rodríguez Sojo MJ, Roxana Lista A, Ayala Mosqueda CV, García García J, Gálvez Peralta J, et al. Modulating strategies of the intestinal microbiota in colorectal cancer. Nutrients 2025;17:3565.ArticlePubMedPMC
  • 6. Pickard JM, Zeng MY, Caruso R, Núñez G. Gut microbiota: role in pathogen colonization, immune responses, and inflammatory disease. Immunol Rev 2017;279:70–89. ArticlePubMedPMCPDF
  • 7. Chen Y, Zhou J, Wang L. Role and mechanism of gut microbiota in human disease. Front Cell Infect Microbiol 2021;11:625913.ArticlePubMedPMC
  • 8. DeGruttola AK, Low D, Mizoguchi A, Mizoguchi E. Current understanding of dysbiosis in disease in human and animal models. Inflamm Bowel Dis 2016;22:1137–50. ArticlePubMedPMC
  • 9. Hrncir T. Gut microbiota dysbiosis: triggers, consequences, diagnostic and therapeutic options. Microorganisms 2022;10:578.ArticlePubMedPMC
  • 10. Dahmus JD, Kotler DL, Kastenberg DM, Kistler CA. The gut microbiome and colorectal cancer: a review of bacterial pathogenesis. J Gastrointest Oncol 2018;9:769–77. ArticlePubMedPMC
  • 11. Karam F, El Deghel Y, Iratni R, Dakroub AH, Eid AH. The gut microbiome and colorectal cancer: an integrative review of the underlying mechanisms. Cell Biochem Biophys 2025;83:2637–50. ArticlePubMedPMCPDF
  • 12. Al Bander Z, Nitert MD, Mousa A, Naderpoor N. The gut microbiota and inflammation: an overview. Int J Environ Res Public Health 2020;17:7618.ArticlePubMedPMC
  • 13. Kim M, Friesen L, Park J, Kim HM, Kim CH. Microbial metabolites, short-chain fatty acids, restrain tissue bacterial load, chronic inflammation, and associated cancer in the colon of mice. Eur J Immunol 2018;48:1235–47. ArticlePubMedPMCPDF
  • 14. Fan X, Jin Y, Chen G, Ma X, Zhang L. Gut microbiota dysbiosis drives the development of colorectal cancer. Digestion 2021;102:508–15. ArticlePubMedPDF
  • 15. Rubinstein MR, Wang X, Liu W, Hao Y, Cai G, Han YW. Fusobacterium nucleatum promotes colorectal carcinogenesis by modulating E-cadherin/β-catenin signaling via its FadA adhesin. Cell Host Microbe 2013;14:195–206. ArticlePubMedPMC
  • 16. Yang Y, Weng W, Peng J, Hong L, Yang L, Toiyama Y, et al. Fusobacterium nucleatum increases proliferation of colorectal cancer cells and tumor development in mice by activating Toll-like receptor 4 signaling to nuclear factor-κB, and up-regulating expression of microRNA-21. Gastroenterology 2017;152:851–66. ArticlePubMedPMC
  • 17. Gur C, Ibrahim Y, Isaacson B, Yamin R, Abed J, Gamliel M, et al. Binding of the Fap2 protein of Fusobacterium nucleatum to human inhibitory receptor TIGIT protects tumors from immune cell attack. Immunity 2015;42:344–55. ArticlePubMedPMC
  • 18. Chen B, Ramazzotti D, Heide T, Spiteri I, Fernandez-Mateos J, James C, et al. Contribution of pks+ E. coli mutations to colorectal carcinogenesis. Nat Commun 2023;14:7827.ArticlePubMedPMCPDF
  • 19. Joo JE, Chu YL, Georgeson P, Walker R, Mahmood K, Clendenning M, et al. Intratumoral presence of the genotoxic gut bacteria pks+ E. coli, Enterotoxigenic Bacteroides fragilis, and Fusobacterium nucleatum and their association with clinicopathological and molecular features of colorectal cancer. Br J Cancer 2024;130:728–40. ArticlePubMedPMCPDF
  • 20. Rosendahl Huber A, Pleguezuelos-Manzano C, Puschhof J, Ubels J, Boot C, Saftien A, et al. Improved detection of colibactin-induced mutations by genotoxic E. coli in organoids and colorectal cancer. Cancer Cell 2024;42:487–96. ArticlePubMed
  • 21. Wilson MR, Jiang Y, Villalta PW, Stornetta A, Boudreau PD, Carrá A, et al. The human gut bacterial genotoxin colibactin alkylates DNA. Science 2019;363:eaar7785. ArticlePubMedPMC
  • 22. Pleguezuelos-Manzano C, Puschhof J, Rosendahl Huber A, van Hoeck A, Wood HM, Nomburg J, et al. Mutational signature in colorectal cancer caused by genotoxic pks+ E. coli. Nature 2020;580:269–73. ArticlePubMedPMC
  • 23. Harnack C, Berger H, Liu L, Mollenkopf HJ, Strowig T, Sigal M. Short-term mucosal disruption enables colibactin-producing E. coli to cause long-term perturbation of colonic homeostasis. Gut Microbes 2023;15:2233689.ArticlePubMedPMC
  • 24. Cheng WT, Kantilal HK, Davamani F. The mechanism of Bacteroides fragilis toxin contributes to colon cancer formation. Malays J Med Sci 2020;27:9–21. ArticlePubMedPMC
  • 25. Wu S, Rhee KJ, Zhang M, Franco A, Sears CL. Bacteroides fragilis toxin stimulates intestinal epithelial cell shedding and gamma-secretase-dependent E-cadherin cleavage. J Cell Sci 2007;120(Pt 11):1944–52.Article
  • 26. Wu S, Rhee KJ, Albesiano E, Rabizadeh S, Wu X, Yen HR, et al. A human colonic commensal promotes colon tumorigenesis via activation of T helper type 17 T cell responses. Nat Med 2009;15:1016–22. ArticlePubMedPMCPDF
  • 27. Kim JM, Lee JY, Yoon YM, Oh YK, Kang JS, Kim YJ, et al. Bacteroides fragilis enterotoxin induces cyclooxygenase-2 and fluid secretion in intestinal epithelial cells through NF-kappaB activation. Eur J Immunol 2006;36:2446–56. ArticlePubMed
  • 28. Tsoi H, Chu ES, Zhang X, Sheng J, Nakatsu G, Ng SC, et al. Peptostreptococcus anaerobius induces intracellular cholesterol biosynthesis in colon cells to induce proliferation and causes dysplasia in mice. Gastroenterology 2017;152:1419–33. e5. ArticlePubMed
  • 29. Long X, Wong CC, Tong L, Chu ES, Ho Szeto C, Go MY, et al. Peptostreptococcus anaerobius promotes colorectal carcinogenesis and modulates tumour immunity. Nat Microbiol 2019;4:2319–30. ArticlePubMedPDF
  • 30. Liu Y, Wong CC, Ding Y, Gao M, Wen J, Lau HC, et al. Peptostreptococcus anaerobius mediates anti-PD1 therapy resistance and exacerbates colorectal cancer via myeloid-derived suppressor cells in mice. Nat Microbiol 2024;9:1467–82. ArticlePubMedPMCPDF
  • 31. Pasquereau-Kotula E, Martins M, Aymeric L, Dramsi S. Significance of Streptococcus gallolyticus subsp. gallolyticus association with colorectal cancer. Front Microbiol 2018;9:614.ArticlePubMedPMC
  • 32. Kumar R, Herold JL, Schady D, Davis J, Kopetz S, Martinez-Moczygemba M, et al. Streptococcus gallolyticus subsp. gallolyticus promotes colorectal tumor development. PLoS Pathog 2017;13:e1006440. ArticlePubMedPMC
  • 33. Biarc J, Nguyen IS, Pini A, Gossé F, Richert S, Thiersé D, et al. Carcinogenic properties of proteins with pro-inflammatory activity from Streptococcus infantarius (formerly S.bovis). Carcinogenesis 2004;25:1477–84. ArticlePubMed
  • 34. Périchon B, Lichtl-Häfele J, Bergsten E, Delage V, Trieu-Cuot P, Sansonetti P, et al. Detection of Streptococcus gallolyticus and four other CRC-associated bacteria in patient stools reveals a potential "driver" role for enterotoxigenic Bacteroides fragilis. Front Cell Infect Microbiol 2022;12:794391.ArticlePubMedPMC
  • 35. Kim Y, Cho NY, Kang GH. Prognostic and clinicopathological significance of Fusobacterium nucleatum in colorectal cancer: a systemic review and meta-analysis. J Pathol Transl Med 2022;56:144–51. ArticlePubMedPMCPDF
  • 36. Jiang SS, Xie YL, Xiao XY, Kang ZR, Lin XL, Zhang L, et al. Fusobacterium nucleatum-derived succinic acid induces tumor resistance to immunotherapy in colorectal cancer. Cell Host Microbe 2023;31:781–97. e9. ArticlePubMed
  • 37. Cougnoux A, Delmas J, Gibold L, Faïs T, Romagnoli C, Robin F, et al. Small-molecule inhibitors prevent the genotoxic and protumoural effects induced by colibactin-producing bacteria. Gut 2016;65:278–85. ArticlePubMed
  • 38. DeStefano Shields CE, Van Meerbeke SW, Housseau F, Wang H, Huso DL, Casero RA, et al. Reduction of murine colon tumorigenesis driven by enterotoxigenic Bacteroides fragilis using cefoxitin treatment. J Infect Dis 2016;214:122–9. ArticlePubMedPMC
  • 39. Kwong TN, Wang X, Nakatsu G, Chow TC, Tipoe T, Dai RZ, et al. Association between bacteremia from specific microbes and subsequent diagnosis of colorectal cancer. Gastroenterology 2018;155:383–90. ArticlePubMed
  • 40. Jiang SS, Chen YX, Fang JY. Fusobacterium nucleatum: ecology, pathogenesis and clinical implications. Nat Rev Microbiol 2026;24:197–214. ArticlePubMed
  • 41. Abed J, Emgård JE, Zamir G, Faroja M, Almogy G, Grenov A, et al. Fap2 mediates Fusobacterium nucleatum colorectal adenocarcinoma enrichment by binding to tumor-expressed Gal-GalNAc. Cell Host Microbe 2016;20:215–25. ArticlePubMedPMC
  • 42. Fardini Y, Wang X, Témoin S, Nithianantham S, Lee D, Shoham M, et al. Fusobacterium nucleatum adhesin FadA binds vascular endothelial cadherin and alters endothelial integrity. Mol Microbiol 2011;82:1468–80. ArticlePubMedPMC
  • 43. Yu T, Guo F, Yu Y, Sun T, Ma D, Han J, et al. Fusobacterium nucleatum promotes chemoresistance to colorectal cancer by modulating autophagy. Cell 2017;170:548–63. ArticlePubMedPMC
  • 44. Zhang S, Yang Y, Weng W, Guo B, Cai G, Ma Y, et al. Fusobacterium nucleatum promotes chemoresistance to 5-fluorouracil by upregulation of BIRC3 expression in colorectal cancer. J Exp Clin Cancer Res 2019;38:14.ArticlePubMedPMCPDF
  • 45. Johnson JR, Johnston B, Kuskowski MA, Nougayrede JP, Oswald E. Molecular epidemiology and phylogenetic distribution of the Escherichia coli pks genomic island. J Clin Microbiol 2008;46:3906–11. ArticlePubMedPMCPDF
  • 46. Dougherty MW, Jobin C. Shining a light on colibactin biology. Toxins (Basel) 2021;13:346.ArticlePubMedPMC
  • 47. Cuevas-Ramos G, Petit CR, Marcq I, Boury M, Oswald E, Nougayrède JP. Escherichia coli induces DNA damage in vivo and triggers genomic instability in mammalian cells. Proc Natl Acad Sci U S A 2010;107:11537–42. ArticlePubMedPMC
  • 48. de Oliveira Alves N, Dalmasso G, Nikitina D, Vaysse A, Ruez R, Ledoux L, et al. The colibactin-producing Escherichia coli alters the tumor microenvironment to immunosuppressive lipid overload facilitating colorectal cancer progression and chemoresistance. Gut Microbes 2024;16:2320291.ArticlePubMedPMC
  • 49. Patrick S. A tale of two habitats: Bacteroides fragilis, a lethal pathogen and resident in the human gastrointestinal microbiome. Microbiology (Reading) 2022;168(4). ArticlePubMed
  • 50. Spigaglia P. The ambivalent nature of Bacteroides fragilis and the interaction with Clostridioides difficile: benefits and disadvantages for the human host. Toxins (Basel) 2025;17:513.ArticlePubMedPMC
  • 51. Allen J, Hao S, Sears CL, Timp W. Epigenetic changes induced by Bacteroides fragilis toxin. Infect Immun 2019;87:e00447-18. ArticlePubMedPMCPDF
  • 52. Lee CG, Hwang S, Gwon SY, Park C, Jo M, Hong JE, et al. Bacteroides fragilis toxin induces intestinal epithelial cell secretion of interleukin-8 by the E-cadherin/β-catenin/NF-κB dependent pathway. Biomedicines 2022;10:827.ArticlePubMedPMC
  • 53. Louis P, Hold GL, Flint HJ. The gut microbiota, bacterial metabolites and colorectal cancer. Nat Rev Microbiol 2014;12:661–72. ArticlePubMedPDF
  • 54. Miquel S, Martín R, Rossi O, Bermúdez-Humarán LG, Chatel JM, Sokol H, et al. Faecalibacterium prausnitzii and human intestinal health. Curr Opin Microbiol 2013;16:255–61. ArticlePubMed
  • 55. Sokol H, Pigneur B, Watterlot L, Lakhdari O, Bermúdez-Humarán LG, Gratadoux JJ, et al. Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc Natl Acad Sci U S A 2008;105:16731–6. ArticlePubMedPMC
  • 56. Sivan A, Corrales L, Hubert N, Williams JB, Aquino-Michaels K, Earley ZM, et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science 2015;350:1084–9. ArticlePubMedPMC
  • 57. Routy B, Le Chatelier E, Derosa L, Duong CPM, Alou MT, Daillère R, et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 2018;359:91–7. ArticlePubMed
  • 58. Gubernatorova EO, Gorshkova EA, Bondareva MA, Podosokorskaya OA, Sheynova AD, Yakovleva AS, et al. Akkermansia muciniphila: friend or foe in colorectal cancer? Front Immunol 2023;14:1303795.ArticlePubMedPMC
  • 59. den Besten G, Bleeker A, Gerding A, van Eunen K, Havinga R, van Dijk TH, et al. Short-chain fatty acids protect against high-fat diet-induced obesity via a PPARγ-dependent switch from lipogenesis to fat oxidation. Diabetes 2015;64:2398–408. ArticlePubMedPDF
  • 60. Koh A, De Vadder F, Kovatcheva-Datchary P, Bäckhed F. From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell 2016;165:1332–45. ArticlePubMed
  • 61. Furusawa Y, Obata Y, Fukuda S, Endo TA, Nakato G, Takahashi D, et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature 2013;504:446–50. ArticlePubMed
  • 62. Zelante T, Iannitti RG, Cunha C, De Luca A, Giovannini G, Pieraccini G, et al. Tryptophan catabolites from microbiota engage aryl hydrocarbon receptor and balance mucosal reactivity via interleukin-22. Immunity 2013;39:372–85. ArticlePubMed
  • 63. Sepich-Poore GD, Zitvogel L, Straussman R, Hasty J, Wargo JA, Knight R. The microbiome and human cancer. Science 2021;371:eabc4552. ArticlePubMedPMC
  • 64. Thomas T, Gilbert J, Meyer F. Metagenomics: a guide from sampling to data analysis. Microb Inform Exp 2012;2:3.ArticlePubMedPMCPDF
  • 65. Wu Y, Jiao N, Zhu R, Zhang Y, Wu D, Wang AJ, et al. Identification of microbial markers across populations in early detection of colorectal cancer. Nat Commun 2021;12:3063.ArticlePubMedPMCPDF
  • 66. Su Q, Liu Q, Lau RI, Zhang J, Xu Z, Yeoh YK, et al. Faecal microbiome-based machine learning for multi-class disease diagnosis. Nat Commun 2022;13:6818.ArticlePubMedPMCPDF
  • 67. Gao W, Gao X, Zhu L, Gao S, Sun R, Feng Z, et al. Multimodal metagenomic analysis reveals microbial single nucleotide variants as superior biomarkers for early detection of colorectal cancer. Gut Microbes 2023;15:2245562.ArticlePubMedPMC
  • 68. Tito RY, Verbandt S, Aguirre Vazquez M, Lahti L, Verspecht C, Lloréns-Rico V, et al. Microbiome confounders and quantitative profiling challenge predicted microbial targets in colorectal cancer development. Nat Med 2024;30:1339–48. ArticlePubMedPMCPDF
  • 69. Piccinno G, Thompson KN, Manghi P, Ghazi AR, Thomas AM, Blanco-Míguez A, et al. Pooled analysis of 3,741 stool metagenomes from 18 cohorts for cross-stage and strain-level reproducible microbial biomarkers of colorectal cancer. Nat Med 2025;31:2416–29. ArticlePubMedPMCPDF
  • 70. Gianluca I. Microbiome testing for the screening of colorectal cancer (NI-GUILTI) [updated 2025 May 28]. ClinicalTrials.gov identifier: NCT06588166. In: ClinicalTrials.gov [Internet]. US National Library of Medicine; [cited 2025 Dec 30]. Available from: https://clinicaltrials.gov/study/NCT06588166
  • 71. Gulbenkian Institute for Molecular Medicine. Improving colorectal cancer early screening in Portugal: identification of gut microbiome biomarkers in stool (GUTBIOME-PT) (GUTBIOME-PT) [updated 2024 Dec 18]. ClinicalTrials.gov identifier: NCT06741293. In: ClinicalTrials.gov [Internet]. US National Library of Medicine; [cited 2025 Dec 30]. Available from: https://clinicaltrials.gov/study/NCT06741293
  • 72. Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement. The French gut-colo [updated 2025 Sep 16]. ClinicalTrials.gov identifier: NCT06174233. In: ClinicalTrials.gov [Internet]. US National Library of Medicine; [cited 2025 Dec 30]. Available from: https://clinicaltrials.gov/study/NCT06174233
  • 73. Schatzkin A, Lanza E, Corle D, Lance P, Iber F, Caan B, et al. Lack of effect of a low-fat, high-fiber diet on the recurrence of colorectal adenomas. N Engl J Med 2000;342:1149–55. ArticlePubMed
  • 74. Alberts DS, Martínez ME, Roe DJ, Guillén-Rodríguez JM, Marshall JR, van Leeuwen JB, et al. Lack of effect of a high-fiber cereal supplement on the recurrence of colorectal adenomas. N Engl J Med 2000;342:1156–62. ArticlePubMed
  • 75. Yoon Y, Kim G, Jeon BN, Fang S, Park H. Bifidobacterium strain-specific enhances the efficacy of cancer therapeutics in tumor-bearing mice. Cancers (Basel) 2021;13:957.ArticlePubMedPMC
  • 76. Kim MJ, Song MH, Ji YS, Park JW, Shin YK, Kim SC, et al. Cell free supernatants of Bifidobacterium adolescentis and Bifidobacterium longum suppress the tumor growth in colorectal cancer organoid model. Sci Rep 2025;15:935.ArticlePubMedPMCPDF
  • 77. Oh NS, Lee JY, Kim YT, Kim SH, Lee JH. Cancer-protective effect of a synbiotic combination between Lactobacillus gasseri 505 and a Cudrania tricuspidata leaf extract on colitis-associated colorectal cancer. Gut Microbes 2020;12:1785803.Article
  • 78. Allegretti JR, Mullish BH, Kelly C, Fischer M. The evolution of the use of faecal microbiota transplantation and emerging therapeutic indications. Lancet 2019;394:420–31. Article
  • 79. Zhao W, Lei J, Ke S, Chen Y, Xiao J, Tang Z, et al. Fecal microbiota transplantation plus tislelizumab and fruquintinib in refractory microsatellite stable metastatic colorectal cancer: an open-label, single-arm, phase II trial (RENMIN-215). EClinicalMedicine 2023;66:102315.ArticlePubMedPMC
  • 80. Zhao W, Chen Y, Xiao J, Tang Z, Wang L, Ren Y, et al. Updated outcomes and exploratory analysis of RENMIN-215: tislelizumab plus fruquintinib and fecal microbiota transplantation in refractory microsatellite stable metastatic colorectal cancer. Am J Cancer Res 2024;14:5351–64. ArticlePubMedPMC
  • 81. Gurbatri CR, Radford GA, Vrbanac L, Im J, Thomas EM, Coker C, et al. Engineering tumor-colonizing E. coli Nissle 1917 for detection and treatment of colorectal neoplasia. Nat Commun 2024;15:646.ArticlePubMedPMCPDF
  • 82. Luke JJ, Piha-Paul SA, Medina T, Verschraegen CF, Varterasian M, Brennan AM, et al. Phase I study of SYNB1891, an engineered E. coli Nissle strain expressing STING agonist, with and without atezolizumab in advanced malignancies. Clin Cancer Res 2023;29:2435–44. ArticlePubMedPMCPDF
  • 83. Lu SSM, Mohammed Z, Häggström C, Myte R, Lindquist E, Gylfe Å, et al. Antibiotics use and subsequent risk of colorectal cancer: a Swedish nationwide population-based study. J Natl Cancer Inst 2022;114:38–46. ArticlePubMedPMCPDF
  • 84. Liu YC, Tang XY, Lang JX, Qiu Y, Chen Y, Li XY, et al. Effects of antibiotic exposure on risks of colorectal tumors: a systematic review and meta-analysis. J Transl Med 2025;23:682.ArticlePubMedPMCPDF
  • 85. Bingham SA, Day NE, Luben R, Ferrari P, Slimani N, Norat T, et al. Dietary fibre in food and protection against colorectal cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC): an observational study. Lancet 2003;361:1496–501. ArticlePubMed
  • 86. Aune D, Chan DS, Lau R, Vieira R, Greenwood DC, Kampman E, et al. Dietary fibre, whole grains, and risk of colorectal cancer: systematic review and dose-response meta-analysis of prospective studies. BMJ 2011;343:d6617.ArticlePubMedPMC
  • 87. Song M, Garrett WS, Chan AT. Nutrients, foods, and colorectal cancer prevention. Gastroenterology 2015;148:1244–60. e16. ArticlePubMedPMC
  • 88. Smits LP, Bouter KE, de Vos WM, Borody TJ, Nieuwdorp M. Therapeutic potential of fecal microbiota transplantation. Gastroenterology 2013;145:946–53. ArticlePubMed
  • 89. Routy B, Lenehan JG, Miller WH, Jamal R, Messaoudene M, Daisley BA, et al. Fecal microbiota transplantation plus anti-PD-1 immunotherapy in advanced melanoma: a phase I trial. Nat Med 2023;29:2121–32. ArticlePubMedPDF
  • 90. Kim Y, Kim G, Kim S, Cho B, Kim SY, Do EJ, et al. Fecal microbiota transplantation improves anti-PD-1 inhibitor efficacy in unresectable or metastatic solid cancers refractory to anti-PD-1 inhibitor. Cell Host Microbe 2024;32:1380–93. e9. ArticlePubMed
  • 91. Gulati AS, Nicholson MR, Khoruts A, Kahn SA. Fecal microbiota transplantation across the lifespan: balancing efficacy, safety, and innovation. Am J Gastroenterol 2023;118:435–9. ArticlePubMedPMC
  • 92. Kelly CR, Kahn S, Kashyap P, Laine L, Rubin D, Atreja A, et al. Update on fecal microbiota transplantation 2015: indications, methodologies, mechanisms, and outlook. Gastroenterology 2015;149:223–37. ArticlePubMedPMC
  • 93. Murali SK, Mansell TJ. Next generation probiotics: engineering live biotherapeutics. Biotechnol Adv 2024;72:108336.ArticlePubMed
  • 94. Simin J, Fornes R, Liu Q, Olsen RS, Callens S, Engstrand L, et al. Antibiotic use and risk of colorectal cancer: a systematic review and dose-response meta-analysis. Br J Cancer 2020;123:1825–32. ArticlePubMedPMCPDF
  • 95. Tsikala-Vafea M, Belani N, Vieira K, Khan H, Farmakiotis D. Use of antibiotics is associated with worse clinical outcomes in patients with cancer treated with immune checkpoint inhibitors: a systematic review and meta-analysis. Int J Infect Dis 2021;106:142–54. ArticlePubMed

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    Gut microbiome in colorectal cancer: recent advances and clinical implications
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    Fig. 1. Mechanistic pathways linking gut microbial dysbiosis to colorectal carcinogenesis. Fn, Fusobacterium nucleatum; TLR4, Toll-like-receptor 4; NF-κB, nuclear factor–κB; IL-6, interleukin 6; TNF-α, tumor necrosis factor α; ETBF, enterotoxigenic Bacteroides fragilis; Th17, T helper 17 cell; IL-17, interleukin 17; pks+, polyketide synthase positive; CDT, cytolethal distending toxin; BFT, Bacteroides fragilis toxin; E-cadherin, epithelial cadherin; TIGIT, T-cell immunoreceptor with immunoglobulin and ITIM (immunoreceptor tyrosine-based inhibitory motif) domains; NK, natural killer; Pa, Peptostreptococcus anaerobius; MDSC, myeloid-derived suppressor cell; TAM, tumor-associated macrophage; VE-cadherin, vascular endothelial cadherin.
    Fig. 2. Oncogenic mechanisms of major colorectal cancer-linked gut microbes. BFT, Bacteroides fragilis toxin; COX-2, cyclooxygenase 2; DSB, double-strand break; E-cadherin, epithelial cadherin; IL-6, interleukin 6; IL-8, interleukin 8; LPS, lipopolysaccharides; MDSC, myeloid-derived suppressor cell; MYD88, myeloid differentiation primary response 88; NF-κB, nuclear factor–κB; PCWBR2, putative cell wall binding repeat 2; PGE2, prostaglandin E2; pks+, polyketide synthase positive; ROS, reactive oxygen species; SREBP2, sterol regulatory element-binding protein 2; STAT3, signal transducer and activator of transcription 3; TIGIT, T-cell immunoreceptor with immunoglobulin and ITIM (immunoreceptor tyrosine-based inhibitory motif) domains; TLR2, Toll-like receptor 2; TLR4, Toll-like receptor 4; VE-cadherin, vascular endothelial cadherin.

    Fig. 1.

    Fig. 2.

    Gut microbiome in colorectal cancer: recent advances and clinical implications
    Pathogenic bacteria Evidence Reference
    Fn
     Mechanistic data FadA binds E-cadherin → β-catenin/Wnt activation [15]
    LPS–TLR4/MYD88 signaling → NF-κB activation [16]
    Fap2 binds TIGIT [17]
    Induces chemotherapy resistance
     Observational data Enriched in CRC tissue/stool and linked to clinicopathologic features [19]
    Higher Fn burden is associated with worse outcomes in pooled analyses [35]
     Interventional data Metronidazole-mediated depletion of Fn lowers succinate level, restores the sensitivity to anti–PD-1 therapy, and suppresses tumor growth in CRC models [36]
    pks+ Escherichia coli
     Mechanistic data pks island encodes colibactin → induces DSB [21]
    Colibactin leaves a characteristic mutational signature [18, 20, 22]
    Promotes genomic instability and epithelial barrier dysfunction [23]
     Observational data pks+ E. coli detected in human CRC tissue [19]
     Interventional data Inhibition of colibactin peptidase blocks colibactin genotoxicity and reduces tumorigenesis in colonized mouse CRC models [37]
    ETBF
     Mechanistic data BFT cleaves E-cadherin and activates β-catenin/Wnt and inflammatory cascades [24, 25]
    Induces Th17/IL-17–dominant mucosal inflammation that promotes tumorigenesis [26]
    Associated with epigenetic remodeling of colonic epithelium in experimental models [27]
     Observational data ETBF gene  is prevalent in colonic mucosa of CRC patients and is associated with colorectal neoplasia [19]
    ETBF signals reproducibly detected in population datasets → stage-dependent patterns reported [34]
     Interventional data Clearing ETBF with cefoxitin in colonized mice reduces IL-17–dependent colon tumorigenesis [38]
    Pa
     Mechanistic data Activated SREBP2 increases cell proliferation via cholesterol biosynthesis [28]
    Binds to integrin α2/β1 via PCWBR2 → triggers inflammatory signaling [29]
     Observational data Bacteremia with Pa is linked to CRC diagnosis in retrospective cohorts [39]
     Interventional data In mice, Pa supplementation promotes tumor growth; depletion/antibiotic approaches can restore anti–PD-1 efficacy in resistant models [30]
    Sgg
     Mechanistic data Induces inflammatory and pro-proliferative signaling in colon tissue [33]
     Observational data Detected in CRC-associated microbiome profiles [31]
     Interventional data In mice, Sgg colonization increases tumor burden and accelerates tumor progression [32]
    Study Cohort Approach Results Implication
    Wu et al. [65] (2021) 1,056 Public fecal samples across multiple studies Integrated cross-study analysis with confounder adjustment Adenoma-stage signals can be reproducible across populations, supporting stool microbiome panels as an early detection
    Adenoma vs. control: AUC=0.80
    Adenoma vs. CRC: AUC=0.89
    External validation: AUC of 0.78 and 0.84 in two independent cohorts
    Su et al. [66] (2022) 2,320 Metagenomic dataset with 9 phenotypes including CRC and adenoma Multiclass machine learning on fecal metagenomes AUROC, 0.90–0.99 Propose the noninvasive model for disease screening/risk assessment and potentially for treatment-response monitoring
    Sensitivity, 0.81–0.95
    Specificity, 0.76–0.98
    Metagenomic analysis from public datasets: AUROC, 0.69–0.91
    Gao et al. [67] (2023) Cross-cohort WMS, 750 samples Comparison of multimodal features; emphasis on strain-level SNVs SNV model (adenoma vs. control): Provide a rationale of microbial SNVs for the early detection of CRC
    AUC=0.89
    Sensitivity=0.79
    Specificity=0.85
    MCC=0.74
    Tito et al. [68] (2024) 589 Patients across CRC stages; compared with 15 published studies Quantitative microbiome profiling with rigorous confounder control The strongest microbiome covariates were transit time, fecal calprotectin, and BMI Stool biomarkers may reflect inflammation /transit/body composition rather than CRC itself
    Total 4,439 participants The diagnosis group was not associated with microbiota variation (univariate dbRDA R²=0.2%, adjusted P=0.22) Absolute/quantitative profiling plus explicit covariate control is essential
    Fn lost its apparent CRC-stage association after deconfounding (P>0.05)
    Piccinno et al. [69] (2025) 3,741 Stool metagenomes from 18 cohorts Large pooled meta-analysis with strain-level analyses CRC prediction: AUC=0.85 Large, pooled training improves cross-cohort performance
    Tumor location signal: left-sided vs. right-sided CRC discrimination AUC=0.66 Stool metagenomes carry location- and stage-linked signals
    Périchon et al. [34] (2022) Stool PCR cohort: Targeted PCR and qPCR for 5 CRC-associated markers ETBF detection: Marker positivity is stage-dependent, multimarker, stage-aware panels
    Control (n=25) Control, 24.0% ETBF’s higher detection at the adenoma stage may be useful for early-risk enrichment
    Adenoma (n=23) Adenoma, 56.5%
    CRC (n=81) CRC, 30.9%
     Stage I/II, 34.6%
     Stage IV, 22.2%
    Strategy Mechanism Current evidence and limitation Reference
    Dietary modulation and prebiotics Promotes SCFA-producing beneficial bacteria Epidemiological evidence for reduced CRC risk with high-fiber diets [86]
    → anti-inflammatory signaling, epithelial barrier protection, immune homeostasis Randomized trials targeting adenoma/CRC recurrence largely negative or neutral
    Currently lifestyle-level recommendation rather than a therapeutic intervention
    Probiotics, synbiotics, and postbiotics Introduces beneficial microbes or microbial metabolites Consistent results at CRC mouse or organoid model [75–77]
    → reduces inflammation, improves gut barrier, suppresses CRC-related pathogens, modulates immune responses Evidence from CRC patient lacking
    FMT Replaces dysbiotic microbiota with donor microbiota Clinical evidence mainly from melanoma in improving immune checkpoint inhibitor response [78–80]
    → reprograms immune/metabolic tumor microenvironment; enhances immunotherapy responsiveness CRC data limited, mainly small pilots/uncontrolled combination trials
    Safety, donor screening, and long-term ecology concerns remain major barriers
    Engineered/synthetic probiotics Genetically modified bacteria selectively colonize tumors and release anticancer molecules or immunomodulators Reduces adenoma burden in CRC mouse model [81, 82]
    Human evidence is currently limited and not CRC-specific
    Antibiotics Theoretical elimination of CRC-promoting pathogens or dysbiosis drivers Not recommended as a CRC-preventive/therapeutic strategy [83, 84]
    Table 1. CRC-associated pathogenic bacteria: evidence and unresolved questions

    CRC, colorectal cancer; Fn, Fusobacterium nucleatum; E-cadherin, epithelial cadherin; LPS, lipopolysaccharides; TLR4, Toll-like receptor 4; MYD88, myeloid differentiation primary response 88; NF-κB, nuclear factor–κB; TIGIT, T-cell immunoreceptor with immunoglobulin and ITIM (immunoreceptor tyrosine-based inhibitory motif) domains; PD-1, programmed death receptor 1; pks, polyketide synthase; DSB, double-strand break; ETBF, enterotoxigenic Bacteroides fragilis; BFT, Bacteroides fragilis toxin; Th17, T helper 17 cell; IL-17, interleukin 17; Pa, Peptostreptococcus anaerobius; SREBP2, sterol regulatory element-binding protein 2; PCWBR2, putative cell wall binding repeat 2; Sgg, Streptococcus gallolyticus subsp gallolyticus.

    Table 2. Gut microbiome-related biomarkers in the colorectal adenoma and CRC

    CRC, colorectal cancer; AUC, area under the curve; AUROC, area under the receiver operating characteristic curve; WMS, whole metagenome sequencing; SNV, single nucleotide variant; MCC, Matthews correlation coefficient; BMI, body mass index; dbRDA, distance-based redundancy analysis; Fn, Fusobacterium nucleatum; PCR, polymerase chain reaction; qPCR, quantitative polymerase chain reaction; ETBF, enterotoxigenic Bacteroides fragilis.

    Table 3. Gut microbiome–targeted interventions in CRC

    CRC, colorectal cancer; SCFA, short-chain fatty acid; FMT, fecal microbiota transplantation.

    Table 1.

    Table 2.

    Table 3.

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