The heterogeneity of CRC is largely reflected in the differences in intratumoral microbial communities across distinct anatomical sites. Studies indicate that proximal (right-sided) colon cancer possesses a distinct microbial lineage compared to distal (left-sided) colon cancer and rectal cancer. Right-sided colon cancer typically exhibits higher microbial diversity. It is also more prone to enriching bacterial taxa associated with biofilm formation (18, 19). For example, research has found that the abundance of Fusobacterium is significantly higher in right-sided tumors than in left-sided ones. This abundance is closely related to microsatellite instability (MSI) status (18, 20). Conversely, left-sided colon cancer and rectal cancer show different dominant bacterial groups, which are often associated with lung metastasis (21). Meanwhile, the patterns of difference between normal mucosa and cancerous tissue vary by anatomical site. In patients with left-sided colon cancer, the taxonomic difference between cancerous and non-cancerous tissues is substantial. However, this difference is relatively smaller in patients with right-sided colon cancer (19). Furthermore, microbiomes in the cecum and terminal ileum exhibit specific associations related to tumor location (22). This heterogeneity in microbial distribution based on anatomical sites suggests that tumors in different locations may possess unique microecological pathogenic mechanisms. This provides a theoretical basis for site-specific precision therapy.

Intratumoral microbes are not confined to primary tumors; they also migrate to distant organs accompanying the metastasis of tumor cells. Studies on colorectal cancer liver metastasis (CRLM) have found significant similarity in microbial community structures between primary and liver metastatic lesions. This suggests that bacteria may “hitchhike” with tumor cells during metastasis (8, 23). For instance, F. nucleatum has been detected in both primary CRC and its liver metastases. Its presence in metastatic lesions is highly consistent with that in the primary tumor. Even in germ-free mouse models, tail vein injection of this bacterium leads to its specific colonization at tumor sites (23). However, the microenvironment of the metastatic site also selectively reshapes the colonizing flora. Some studies note that while the microbial diversity of metastases is influenced by the primary tumor type, the biopsy site (e.g., liver, lung, or lymph nodes) can sometimes influence microbial composition more than the primary tumor source does (24). Additionally, patients with liver metastases can be classified into different subtypes based on intratumoral microbial community characteristics (25). These subtypes are closely associated with metabolic features and prognosis. This reveals the critical role of microecological evolution in metastatic progression.

In the complex microecological network of CRC, several core pathogenic bacterial groups have been repeatedly confirmed to exert significant pro-tumorigenic effects. F. nucleatum is the most extensively studied “star bacterium.” F. nucleatum not only colonizes tissues itself but often co-exists with other pathogens, such as Campylobacter species, to form a pro-tumorigenic microecological network (35). ETBF represents another key pathogen. Its secreted toxins have been confirmed to induce an invasive phenotype in tumor cells. Furthermore, it drives tumor transformation toward the mesenchymal subtype (consensus molecular subtype 4, CMS4), which is associated with a poorer prognosis (36). Additionally, E. coli carrying the pks genomic island (pks+ E. coli) produces the genotoxin colibactin. This toxin causes host DNA double-strand breaks and induces genomic instability, thereby directly promoting tumorigenesis (37). These dominant microbial groups do not exist in isolation. They often exhibit patterns of co-exclusion or co-occurrence within tumor tissues. For instance, some studies have observed a negative correlation between F. nucleatum and probiotics such as Bifidobacterium (38). This imbalance in community structure acts as a significant driving force for CRC progression.

Although bacteria are the current focus of research, the roles of the non-bacterial microbiome (fungi, viruses, and archaea) within CRC tumors are gradually emerging. Fungi, in particular, play a role in the TME that cannot be ignored. For example, studies have identified an enrichment of Malassezia in hepatocellular carcinoma. This fungus promotes tumor progression by downregulating bile acid synthesis and modulating the TME. This mechanism may hold potential reference value for CRC liver metastasis (39). In CRC, specific fungal signatures have also been associated with molecular subtypes and prognosis (3). Furthermore, bacteriophages, as bacterial viruses, may indirectly influence tumor progression by regulating bacterial community structure. Alternatively, they may integrate directly into bacterial genomes to propagate virulence factors, as seen with specific prophage regions discovered in CRC-associated bacteria (26). Although archaea are present in lower abundance, they have been confirmed in CRC tissues. Their association with specific host protein expression suggests they may play underappreciated roles in host-microbe interactions (3).

Intratumoral microbes profoundly influence tumor cell metabolic reprogramming and gene expression by secreting metabolites and modulating host epigenetic modifications. Staphylococcus sciuri converts L-lysine to Nα-acetyl-L-lysine via its GCN5-related N-acetyltransferase. This subsequently activates oxidative stress-related JNK and JAK/STAT signaling pathways through the host Loxl2/H2O2 axis, promoting intestinal stem cell division and tumor growth (40). Alterations in fatty acid metabolism serve as a critical bridge connecting microbes and the TME. Research indicates that perturbations in the intratumoral microbiota can lead to abnormalities in fatty acid metabolic pathways. This, in turn, regulates stromal cell populations (such as fibroblasts), influencing patient prognosis and drug sensitivity (41). Additionally, the enrichment of bacteria related to bile acid metabolism (such as Bilophila) in CRC mucosa, along with its correlation with bile secretion gene expression, suggests a potential role for secondary bile acids in the carcinogenic process (27).

F. nucleatum also participates in the remodeling of amino acid metabolism. For instance, it promotes tumor cell proliferation by producing putrescine (42). It also metabolizes tryptophan to produce indole derivatives (such as 3-indolepropionic acid). These derivatives activate the aryl hydrocarbon receptor (AhR) signaling pathway, thereby promoting tumor stemness, epithelial-mesenchymal transition (EMT), and chemotherapy resistance (43–45). Conversely, colibactin-producing E. coli (pks+E. coli) can remodel lipid metabolism. This leads to a reduction in immunogenic lipids and the formation of a glycerophospholipid microenvironment within the tumor. This state of lipid overload not only hinders CD8+ T cell infiltration but also provides necessary energy for tumor cell survival, resulting in chemotherapy resistance (46). These metabolites serve not only as energy sources or synthetic raw materials but also as signaling molecules that regulate host cell transcriptional programs.

Regarding epigenetic regulation, gut and intratumoral microbes have been found to cause widespread changes in DNA methylation patterns in CRC tissues by influencing methyl donor metabolism. This is particularly evident in the abnormal methylation of promoter regions in tumor-related genes (47, 48). Although short-chain fatty acids (especially butyrate) are generally considered beneficial metabolites, their effects can be detrimental in specific spatial microenvironments within the tumor. Their inhibition of histone deacetylases (HDACs) may lead to epigenetic remodeling and exhaustion of CD8+ T cells, thereby producing an immunosuppressive effect (49). This “microbe-epigenetic” axis provides a new perspective for understanding how environmental factors induce changes in gene expression.

Intratumoral microbes are key drivers in reshaping the TME. F. nucleatum has been confirmed to interact with cancer-associated fibroblasts (CAFs). It induces CAFs to secrete pro-inflammatory cytokines (such as CXCL1 and IL-6), thereby promoting tumor cell invasion and metastasis (50). At the cellular immunity level, the presence of intratumoral microbes is closely related to the functional state of T cells. For instance, a high load of ETBF is associated with a decrease in FOXP3+ regulatory T cells (Tregs) and an increase in CD68+ macrophages (9). While seemingly contradictory, this likely reflects a complex immune escape mechanism. Peptostreptococcus anaerobius activates the integrin α2/β1- nuclear factor kappa B (NF-κB) signaling pathway in tumor cells to induce CXCL1 secretion. This recruits polymorphonuclear myeloid-derived suppressor cells (MDSCs). Simultaneously, the lytC_22 protein secreted by this bacterium acts directly on the Slamf4 receptor on MDSCs. This promotes their immunosuppressive activity, thereby weakening the anti-tumor response of T cells (51). On the other hand, specific microbial metabolites (such as the sphingolipid S1P) can upregulate PD-L1 (programmed death-ligand 1) expression in tumor cells. This leads to restricted expansion of effector T cells and an increase in exhausted T cells (52). Furthermore, ectopic colonization by oral pathogens (such as Fusobacterium) has been found to directly reduce CD8+ T cell infiltration by activating the TLR2/NF-κB pathway, thus weakening anti-tumor immune surveillance (53).

The host’s genetic background, particularly mutations in key driver genes, plays a selective role in shaping the colonization of intratumoral microbes. KRAS is a common mutated gene in CRC. Its mutation status is closely related to the composition of gut and intratumoral microbes. Studies have found that KRAS mutations inhibit the secretion of interferon-beta (IFN-β) by regulating specific microRNAs (such as miR3655) and their downstream targets (such as the SURF6/IRF7 axis). This reduces the host’s ability to clear ETBF, leading to increased ETBF colonization within the tumor (54). Conversely, the enrichment of ETBF further promotes tumor progression, creating a vicious cycle. Another study confirmed that the microbial community structure in tumor biopsies with KRAS mutations differs significantly from that in wild-type tumors. This heterogeneity is correlated with tumor progression (55). Additionally, single nucleotide polymorphisms (SNPs) in the host gene KCNJ11 have been associated with Fusobacterium abundance. Carriers of specific alleles exhibit downregulated KCNJ11 expression. This increases levels of Gal-GalNAc on the tumor cell surface, thereby promoting the adhesion and colonization of F. nucleatum via the Fap2 protein (56). These findings reveal a complex bidirectional interaction mechanism between host genetics and the intratumoral microecology.

The molecular heterogeneity of CRC is closely coupled with the structure of its intratumoral microbial community. Studies indicate a significant covariation relationship between the widely used consensus molecular subtypes (CMS) classification system and specific microbial signatures. For instance, the CMS1 subtype (immune-activated) is typically associated with high microsatellite instability (MSI-H) and a high tumor mutation burden. In this subtype, dysregulated ferroptosis triggered by abundant immune cells is often observed, which may be linked to the colonization of specific microbes (57). The most significant association appears in the CMS4 subtype (mesenchymal, worst prognosis). Research has found that ETBF is significantly enriched in tumors of this subtype. Furthermore, experiments demonstrate that ETBF can induce tumor cells to exhibit CMS4-like gene expression profiles, thereby promoting epithelial-mesenchymal transition (EMT) and tumor growth (36). Additionally, distinct immune subtypes are also related to microbial communities. For example, in the IFN-γ-dominated C2 immune subtype, pathogenic genera such as Selenomonas and Butyricimonas are significantly enriched. This may explain the “immune paradox” observed in patients with this subtype, who exhibit poor survival rates despite high immune infiltration (58).

In specific clinical subgroups, the intratumoral microbiome also exhibits unique fingerprint characteristics. For example, in patients with colorectal cancer liver metastasis (CRLM), the intratumoral microbiome can be classified into three subtypes (IMCS1-3). These correspond to features related to glucose, protein, and lipid metabolism, respectively. Among them, the lipid metabolism-related subtype (IMCS3) is characterized by immune depletion and high invasiveness, carrying the worst prognosis (25). Furthermore, in appendiceal cancer, a unique pathological entity, the relationship between intratumoral F. nucleatum density and prognosis is contrary to that in CRC. High density is associated with better survival, suggesting organ-specific microbial mechanisms (59). Proteomic studies have also identified four novel CRC subtypes (C1-C4). These subtypes possess unique clinical prognoses and microbial features, revealing dynamic reorganization of host-microbe interactions at the protein level during the adenoma-to-carcinoma sequence (3).

With the rising incidence of early-onset colorectal cancer (EOCRC, onset age < 50 years), its unique etiological characteristics have attracted widespread attention. Differences in intratumoral microecology represent a crucial dimension. Compared with late-onset colorectal cancer (AOCRC), the tumor microbiota in EOCRC patients exhibits significantly different α-diversity and β-diversity (38). In EOCRC tumors, the relative abundances of Akkermansia and Bacteroides are higher. In contrast, Fusobacterium and Bacillus are more common in AOCRC (38). Although some studies suggest that differences in microbial composition between the two groups lack statistical consistency, the interaction patterns between microbes and the immune system in EOCRC show stronger and more extensive positive correlations. This suggests that immune microenvironment dysregulation is more prominent in EOCRC (47). Additionally, EOCRC patients typically exhibit accelerated epigenetic aging (DNA methylation age). This may also be related to specific microbial exposures and associated chronic inflammation (47). Another study focusing on young patients found that Fusobacterium acts as a key microbe in EOCRC. By co-localizing with cancer-associated fibroblasts (CAFs) and activating inflammatory pathways, it promotes tumorigenesis (53).

Recent studies indicate an association between the intratumoral microbiome of CRC and host characteristics (such as gender and ethnicity), although current evidence remains incomplete. Regarding gender disparities, a large-cohort (n=859) droplet digital PCR (ddPCR) study revealed a significantly higher proportion of F. nucleatum-positive tumor tissues in female patients (60). However, because females are more prone to proximal colon cancer and F. nucleatum colonization exhibits an anatomical preference of increasing from the rectum to the cecum, tumor location serves as a strong covariate confounding this conclusion (61). As tumor location and molecular features may exert confounding effects on these results, further validation is required. Additionally, some small-sample studies suggest that the α-diversity in the female CRC group is higher than in males, with an observed enrichment of Faecalibacterium, Megamonas, and Klebsiella at the genus level in females; conversely, Prevotella and Akkermansia are more prominent in male CRC patients, and the phylum Fusobacteria is also higher in males (62). However, the cross-cohort reproducibility of these genus-level differences is poor, and these conclusions need to be confirmed in larger sample sizes.

Regarding ethnic disparities, a multinational study demonstrated significant differences in the composition of the CRC microbiome across different populations. For instance, African American CRC tissues are significantly enriched with Leptotrichia, European Americans are enriched with Flexspiria and Streptococcus, the Egyptian population is dominated by Herbaspirillum and Staphylococcus, while the Kenyan population exhibits an enrichment of Akkermansia muciniphila (63). Furthermore, a study on metastatic CRC combining RNA-seq suggested a higher abundance of actively transcribing bacteria, such as Helicobacter cinaedi, in the tumors of Black patients (64). These differences may be related to genetic backgrounds, dietary habits, and environmental factors. However, the sample sizes of existing studies are generally small, and the presence of batch effects and methodological discrepancies results in low reproducibility and reliability of the findings. Therefore, although current studies provide some clues, conclusions regarding gender and ethnic disparities still need to be validated in larger-scale prospective studies.

Given the specific alterations of the microbiome in CRC, multimodal diagnostic strategies based on microbes are becoming a research hotspot. Fecal microbial detection holds the greatest potential for clinical translation due to its non-invasive nature. Multiple studies indicate that the abundance changes of key species, such as F. nucleatum, Bacteroides fragilis, and Parvimonas micra, can be combined with machine learning algorithms (e.g., random forest models). This approach allows for the construction of diagnostic models for CRC and adenoma with high sensitivity and specificity. Their performance often surpasses that of traditional fecal occult blood tests (FOBT) or carcinoembryonic antigen (CEA) detection (65–68). In particular, detection technologies for F. nucleatum are continuously innovating. Examples include droplet digital PCR (ddPCR) and CRISPR-Cas12a-based biosensors. These advancements have significantly improved detection limits for low-abundance samples, making the identification of early lesions possible (69, 70). Beyond fecal samples, the oral (saliva/plaque) microbiome also demonstrates unique diagnostic value. Due to the existence of the “oral-gut” axis, elevated levels of oral pathogens like F. nucleatum and P. micra in saliva have been confirmed to correlate with CRC risk. Furthermore, salivary microbial markers exhibit good diagnostic efficacy in distinguishing CRC patients from healthy individuals. They may even serve as effective supplements or alternatives to fecal testing (71, 72). This “distal” sampling approach offers new insights for non-invasive screening.

The intratumoral microbiome possesses not only diagnostic value but also serves as a crucial biomarker for CRC prognostic assessment. Extensive research consistently shows that high abundance of F. nucleatum is significantly associated with poor prognosis in CRC patients. This includes shorter overall survival (OS), shorter disease-free survival (DFS), and a higher risk of recurrence (73–75). This correlation is evident across different tumor stages. Particularly in stage III patients, intratumoral microbial characteristics are considered independent predictors of postoperative recurrence. Their predictive efficacy even outperforms traditional clinicopathological indicators (76). In metastatic CRC, the microbiome plays an equally critical role. Studies confirm that the persistent presence of F. nucleatum in metastatic lesions is significantly and positively correlated with lymph node and distant metastases. Additionally, the enrichment of ETBF corresponds directly to worse survival outcomes (53, 77). Moreover, specific microbial community subtypes (such as those characterized by glucose, protein, or lipid metabolism) have been identified as being associated with different prognoses in colorectal cancer liver metastasis (CRLM). This provides a new basis for risk stratification in CRLM (25). Beyond F. nucleatum, other microbes, such as specific species within Bacteroides fragilis, Parvimonas micra, and the Alistipes genus, have also been found to be associated with poor prognosis (78, 79).

The characteristics of the intratumoral microbiota have emerged as important biomarkers for predicting responses to various colorectal cancer treatments. In the field of chemotherapy, direct microbial interference with drug metabolism is a significant cause of drug resistance. Studies have found that F. nucleatum is sensitive to the first-line chemotherapeutic agent 5-fluorouracil (5-FU). However, co-existing Escherichia coli possesses innate resistance to 5-FU. Furthermore, E. coli can detoxify 5-FU through metabolic modification, thereby protecting both F. nucleatum and tumor cells from drug-induced cytotoxicity (80). This synergistic protective mechanism between microbes explains the chemotherapy resistance observed in some patients. Additionally, models based on telomere scoring (TELscore) combined with microbiome features indicate that the high-score group (enriched with pathogens such as Selenomonas) exhibits reduced sensitivity to standard chemotherapy regimens (e.g., fluorouracil and oxaliplatin). Conversely, this group is more sensitive to MAPK pathway inhibitors. This suggests that microbial characteristics can guide the selection of chemotherapy regimens (81).

In the context of immune checkpoint inhibitor (ICI) therapy, the role of the intratumoral microbiome is particularly critical. Although Helicobacter pylori infection is primarily associated with gastric cancer, its positive status has been linked to the efficacy of immunotherapy in patients with dMMR/MSI-H (deficient mismatch repair/microsatellite instability-high) colorectal cancer. H. pylori infection remodels the structure of gut and intratumoral microbiota, such as the mutual exclusion observed between Clostridium and Streptococcus species. It enhances survival benefits from immunotherapy by augmenting amino acid metabolism and the abundance of specific bacterial groups (82). However, microbes can also act as barriers to immunotherapy. As previously mentioned, the microbial metabolite sphingosine-1-phosphate (S1P) can upregulate PD-L1. Interestingly, in the context of combination therapy with capecitabine, this might actually enhance the efficacy of anti-PD-1 antibodies by increasing the available targets. This complexity underscores the predictive value of microbial markers in specific combination therapies (52). Multiple studies have constructed microbiome-based scoring systems (such as the CMS score). These systems can effectively stratify patients, predict resistance to immunotherapy (indicated by high TIDE scores), and guide strategies such as combination with HDAC inhibitors to overcome drug resistance (49, 83).

For locally advanced rectal cancer (LARC), neoadjuvant chemoradiotherapy (nCRT) is the standard treatment, yet response rates vary significantly. Combined analysis of the intratumoral microbiome and immune gene expression profiles reveals that enrichment of genera such as Fusobacterium, Coriobacteriaceae, and Sneathia is closely associated with an incomplete response (Non-CR) to nCRT. In contrast, genera like Lactobacillus and Streptococcus are associated with a complete response (CR) (84). Further metagenomic analysis has identified key bacterial groups associated with radiation resistance, such as Streptococcus equinus, along with their metabolic functions (e.g., nitrate assimilation and histidine degradation). High-accuracy efficacy prediction models have subsequently been established (28). Interactions between microbes and cancer-associated fibroblasts (CAFs) have also been proven to mediate nCRT efficacy. Risk scores based on differential microbial signatures can independently predict treatment response (85). During chemoradiotherapy for anal squamous cell carcinoma, the enrichment of specific intratumoral genera (such as Clostridia) is closely associated with increased treatment toxicity (86). Additionally, tumor hypoxia induces specific microbial transcriptional responses, such as adaptive changes in F. nucleatum. This “hypoxia-microbe” interaction further reduces radiosensitivity and presages a poor prognosis (87).

The introduction of nanotechnology and engineered delivery systems offers a breakthrough solution for precisely targeting the intratumoral microbiome. Strategies for clearing key intratumoral pathogens are becoming increasingly precise. Using biomimetic technology, researchers developed neutrophil membrane-coated PLGA nanoparticles co-loaded with metronidazole and oxaliplatin (NM@PLGA-MTI-OXA). These nanoparticles inherit the neutrophil’s tropism for inflammatory sites (tumors). They are efficiently taken up by tumor cells to precisely eliminate intracellular F. nucleatum. This reverses F. nucleatum-induced epithelial-mesenchymal transition (EMT) and immunosuppression, significantly inhibiting liver metastasis (23). Another strategy utilizes protein-supported copper single-atom nanozymes (BSA-Cu SAN). These nanozymes can passively target tumor sites. By catalyzing the production of reactive oxygen species (ROS), they specifically eliminate F. nucleatum, disrupting the “pathogen-tumor symbiote.” Simultaneously, they relieve bacteria-mediated autophagy activation, restoring tumor cell sensitivity to ROS (88). Additionally, a lincomycin-loaded iron-based nanozyme was designed to specifically target and eliminate intratumoral Peptostreptococcus anaerobius. It leverages peroxidase-like activity to induce ferroptosis in tumor cells. This triggers immunogenic cell death (ICD), thereby activating anti-tumor immunity (89).

Constructing smart responsive delivery systems can achieve synergistic enhancement of drugs and immunomodulators. An inulin-based oral hydrogel system (Oxa@HMI) was designed for colon-targeted delivery. This system utilizes inulinase produced by specific colonic flora to degrade the hydrogel backbone, releasing hollow manganese oxide nanocarriers loaded with oxaliplatin. This process generates short-chain fatty acids in situ to regulate the microecology. Furthermore, the released chemotherapeutic drugs and manganese ions induce immunogenic cell death and activate the cGAS-STING pathway. This achieves a synergistic effect combining chemotherapy, immunotherapy, and microecological regulation (90). Similarly, lectin-functionalized biopolymer microspheres loaded with capecitabine, combined with prebiotics (such as Gum Odina), can specifically release drugs in the colon. This regulates the flora, prolongs the drug half-life, and enhances anti-tumor immunity (91, 92).

Further research has explored nano-vaccine strategies based on bacterial membranes. A biomimetic nano-vaccine was constructed by integrating F. nucleatum bacterial membranes with adjuvants (such as CpG oligonucleotides). This vaccine is efficiently taken up by dendritic cells, inducing a strong specific immune response. It selectively clears intratumoral F. nucleatum without affecting normal intestinal flora, thereby significantly improving chemotherapy efficacy and reducing metastasis (93). This “bacteria-treating-bacteria” nanomedicine strategy solves the problem of antibiotic overuse. It also offers a new approach to overcoming bacteria-mediated drug resistance.

Probiotics and their engineered derivatives demonstrate significant therapeutic potential. Clostridium butyricum has been identified as a probiotic that enhances the efficacy of anti-PD-1 therapy. Its surface protein, secD, binds to the GRP78 receptor on the surface of CRC cells. This inhibits the PI3K-AKT-NF-κB pathway and reduces the secretion of the immunosuppressive cytokine IL-6. Consequently, it relieves inhibition of CD8+ T cells and weakens the function of tumor-associated macrophages (TAMs) (94). Additionally, a specific mixture of Clostridiales strains (CC4) has been confirmed to promote intratumoral infiltration and activation of CD8+ T cells. It exerts independent or synergistic anti-tumor effects with anti-PD-1 therapy in CRC models (95). To overcome the difficulty of colonizing oral probiotics, researchers developed exopolysaccharides (EPS) derived from Lactobacillus plantarum. This postbiotic regulates the gut microbiota and enriches short-chain fatty acid-producing genera. It also enhances chemotherapy efficacy by modulating amino acid metabolism (96).

Phage therapy is regaining attention as a highly specific antimicrobial method. Bacteriophages can directly lyse tumor-associated pathogens, including multidrug-resistant bacteria and F. nucleatum. They can also be engineered to serve as vectors for delivering drugs or immunomodulators. For example, specific phages targeting F. nucleatum can precisely clear the intratumoral pathogen load. This blocks bacteria-mediated chemotherapy resistance and immunosuppression. This “programmable” biological weapon, combined with AI-assisted screening and CRISPR technology, holds promise for achieving precise “surgical” modification of the tumor microecology (97).

Compared to fecal samples, tumor tissue possesses a very low microbial biomass. This makes the “signal” easily masked by background “noise” from the environment. The so-called “Kitome” contamination—microbial DNA originating from extraction kits, PCR reagents, or the laboratory environment—represents one of the major technical challenges in this field (6, 13). Such contamination can lead to false-positive results. Consequently, distinguishing true tumor colonizers from environmental contaminants becomes extremely difficult. The lack of standardized pollution control protocols limits data comparability between different studies. This remains a key bottleneck hindering the translation of this field to clinical practice (98). To overcome this limitation, establishing strict experimental controls and replication systems is crucial. Nieciecki et al. demonstrated a workflow involving independent laboratory replication and the inclusion of multiple controls (such as blank and normal tissue controls). This approach effectively identified reproducible core microbial taxa, thereby eliminating false signals caused by environmental contamination (13).

The unique anatomical structure of CRC makes it difficult to avoid contamination by luminal fecal flora when obtaining tumor tissues. Intestinal folds and villi can easily trap non-tumor-specific transient bacteria. This creates interference when defining the true “intratumoral” microbiome. Studies indicate that different sampling sites and tissue washing standards result in significant differences in the detected microbial composition (99). To address this issue, scholars have developed novel cell separation techniques, such as enzymatic digestion. These methods aim to remove non-specifically adherent bacteria, thereby more accurately enriching and detecting microbes closely associated with tumor cells. Results show that in enzymatically treated samples, the abundance of Proteobacteria increases significantly, while Firmicutes and Bacteroidetes decrease relative to untreated controls. This suggests that conventional bulk tissue sequencing may overestimate the contribution of feces-associated flora (99). Furthermore, tumors in different anatomical sites (such as the left versus right colon) possess distinct microbial baselines. This inherent heterogeneity necessitates detailed stratified analysis in study design (100).

Although the presence of intratumoral microbes has been confirmed, their origins remain controversial. Current hypotheses include direct invasion following mucosal barrier damage, migration from adjacent tissues, hematogenous dissemination, and co-metastasis with tumor cells (6). In particular, how oral anaerobes such as F. nucleatum enrich in colorectal tumors requires more supporting evidence. A more central challenge lies in defining the causal relationship between microbes and tumors. Does a specific microbe drive tumorigenesis, or does the altered TME attract specific microbial colonization? We currently lack ideal models that fully simulate the complexity of the human TME. Additionally, interactions within microbial communities are complex. Consequently, current research often remains at the level of correlation analysis, making it difficult to establish definitive causal chains.

To bridge this gap and establish true causality, future methodologies must transition from observational studies to functional validations. Methodologically, researchers are increasingly relying on the inoculation of germ-free mice with defined synthetic microbial communities (SynComs) to track the temporal dynamics of tumorigenesis in a controlled environment. Furthermore, the application of Mendelian randomization to human genomic and metagenomic datasets offers a robust computational approach to infer causal directions, minimizing confounding biases. In terms of future directions, integrating high-resolution spatial transcriptomics with microbial single-cell RNA sequencing (scRNA-seq) will be vital. This will allow researchers to trace direct molecular crosstalk between specific microbes and host cells in situ. Additionally, the development of advanced organ-on-a-chip technologies that perfectly mimic the mucosal barrier and immune infiltration will provide the necessary physiological context to untangle these complex causal networks.