YuRong Yuan
Wei Zhang2*
Deqiang Wang- 1Jiangsu University, Affiliated Hospital of Jiangsu University, Zhenjiang, China
- 2Department of Gastroenterology, Affiliated Hospital of Jiangsu University & Institute of Digestive Diseases, Jiangsu University, Zhenjiang, China
- 3Department of Oncology, Digestive Disease Institute & Cancer Institute of Jiangsu University, Affiliated Hospital of Jiangsu University, Zhenjiang, China
With advances in microbial sequencing technology, the role of microorganisms in cancer development and treatment has been increasingly explored. The gut microbiota, as a key shaper of both innate and adaptive immunity, is believed to migrate from the gut and colonize the pancreas, thereby influencing the tumor microenvironment(TME) of pancreatic cancer. Pancreatic cancer exhibits treatment resistance due to its immunosuppressive TME and high interstitial density. Multiple sequencing analyses of pancreatic tumor tissues have revealed that alterations in the tumor-associated microbiota are associated with prognosis and treatment response, suggesting that the microbiota may serve as a complementary modality in immunotherapy. This paper describes potential pathways by which the gut microbiota can migrate to the pancreas and analyzes changes in tumor microbiota composition. It also identifies microbiota types associated with prognosis, and summarizes treatment strategies leveraging the gut-pancreas axis to enhance the personalization and precision of care. It critically examines the limitations of existing research, and aims to leverage microbiome ecology to overcome the immune -suppressive barrier in pancreatic cancer and improve patient outcomes.
1 Introduction
Pancreatic cancer is a highly aggressive cancer with a significant burden, expected to become the second leading cause of cancer-related deaths in the United States by 2030 (1). Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic solid tumor, accounting for over 95% of all pancreatic cancer (1). Nonspecific clinical symptoms, early micro-metastasis, and a highly fibrotic, immunosuppressive TME make treatment of PDAC challenging (1, 2). These factors together lead to a five-year survival rate of only 13%, making it one of the deadliest cancers (3).
Facing this significant challenge, current treatment approaches focus on surgical removal supported by systemic chemotherapy. For patients with good performance status, the FOLFIRINOX regimen (oxaliplatin, irinotecan, fluorouracil, and calcium folinate) or albumin-bound paclitaxel with gemcitabine is now a standard first-line treatment option (1). Although these approaches significantly improve patient survival, their overall effectiveness remains limited and frequently associated with drug resistance and high rates of recurrence (4–6). Despite the rise of precision medicine, where targeted therapies for specific genetic mutations (e.g., BRCA, KRAS) and immune checkpoint inhibitors (ICIs) offer hope for a small group of patients, response rates to these new treatments remain very low for most of PDAC patients (7–10). Consequently, developing innovative adjuvant strategies to address treatment resistance and enhance patient outcomes has become a critical challenge in current clinical practice.
Recent evidence suggests that gut microbiota and its translocation to the PDAC TME influence its progression and treatment response, indicating a new potential avenue for therapy. The main mechanism of gut microbiota translocation is due to disruption of the intestinal barrier and dysbiosis. In PDAC or its precancerous stages, various risk factors, such as smoking, alcohol abuse, and chemotherapy can damage the intestinal mucosal, mechanical barrier, reduce tight junction protein levels, and worsen mucosal injury through an increase in harmful bacteria (11–13). This process enables bacteria and their metabolites, which are normally symbiotic in the gut, to breach the intestinal mucosa and access the portal venous circulation and lymphatic system. Once translocated to the pancreas, these microbiome components can trigger both local and systemic immune responses, leading to alterations in the TME (14, 15).
In this article, we first explore the potential origins of pancreatic microbiome from the gut. We then review and analyze the types of microorganisms linked to prognosis in PDAC, examining possible mechanisms by which microbes affect immunotherapy. Finally, we look ahead to the potential of innovative microbiome-based therapeutic strategies for improving PDAC immunotherapy.
2 Microbial translocation from the intestine to the pancreas: sources and compositional changes
2.1 Intestinal origin of microorganisms in the pancreas
Under normal physiological conditions, several mechanisms work together to maintain a low biomass environment in the pancreas. These include the antimicrobial effects of pancreatic enzymes, the mechanical barrier provided by the sphincter of Oddi, the integrity of the intestinal mucosal barrier, and the immune filtration role of the liver (16). Microbial translocation relies on the disruption of these barriers (Figure 1).
Figure 1. Possible pathways for pancreatic microbial translocation include the Duodenopancreatic retrograde flow pathway, where intestinal bacteria enter the pancreas via retrograde migration through the pancreatic duct; the Bloodstream pathway, where bacteria enter the bloodstream following intestinal barrier disruption and migrate to the pancreas; and the lymphatic pathway, where bacteria drain to the pancreas via MLNs or migrate after phagocytes capture intestinal bacteria. Additionally, it also includes the potential oral-intestinal-pancreatic transfer axis caused by smoking and periodontal disease. Created in BioRender. Yuan, Y. (2026) https://BioRender.com/gxjwbbf.
Evidence clearly shows a distinct, active microbial community in pancreatic cancer, with much higher abundance than in normal pancreatic tissue. Its microbial profile suggests it mainly comes from the gut. Ghaddar found gastrointestinal pathogens like Campylobacter spp, Fusobacterium nucleatum, Leptotrichia spp, and Clostridioides difficile enriched in pancreatic tumors through single-cell analysis of PDAC groups (17). Pushalkar demonstrated gut microbiota translocation to the pancreas by detecting orally given fluorescent Enterococcus faecalis and GFP-labeled Escherichia coli in pancreatic tissues of wild type(WT) mice. They also found a bacterial peak at just 0.5 hours after ingestion, indicating a swift retrograde flow of gut bacteria through the pancreatic duct into the pancreas (18). Aykut’s research similarly observed this rapid translocation in both WT mice and pancreatic cancer mouse models, which used oral force-feeding, with GFP-labeled Saccharomyces cerevisiae (19). Mouse models demonstrate the potential for retrograde microbial migration through the pancreatic duct via the duodenal papilla, supported by physiological and pathological evidence. While Nejman showed through human pan-cancer microbiome analysis that the Proteobacteria-dominated microbiome of pancreatic cancer mirrors that of the duodenum, direct evidence from human samples has yet to be established (20).
Similarly, with oral gavage, Ma tracked the live-cell tracer calcein-AM and detected the periodontal pathogen Porphyromonas gingivalis in the pancreas and feces of mice, supporting a potential oral-intestinal-pancreatic translocation route (21, 22).
Increased permeability of intestinal barrier, resulting in intestinal permeability, is often the initial step for microbial translocation to various organs and the activation of inflammatory cascades (23–25). Pancreatitis and risk factors linked to pancreatic cancer, such as obesity and smoking, are often associated with increased intestinal permeability and gut microbiota dysbiosis (26). Early studies with mouse models of induced pancreatitis, along with blood endotoxin detection and electron microscopy of mucosal ultrastructural changes, indicated that intestinal bacteria enter the bloodstream by compromising tight junctions in the intestinal mucosa (27). Study in feline models of acute pancreatitis also indicate that Escherichia coli can spread to the pancreas through the bloodstream and colon wall, as well as reflux into the pancreatic duct (28).
The gut microbiome and its metabolites play a key role in shaping immunity. Phagocytes usually capture these components to present antigenic information to T cells, which helps regulate future immune responses. A study using single-strain germ-free mice representing dominant gut bacterial phyla, including Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria, and Fusobacteria, found that the vast majority (88%) of gut microbes could migrate to and survive in proximal lymph nodes, while nearly half (47%) could survive in systemic lymphoid organs such as distal subcutaneous lymph nodes tissue (29). An earlier study showed that in Myeloid differentiation primary response 88 (Myd88)-deficient mice or under dysbiosis conditions, non-invasive Salmonella is transported to the mesenteric lymph nodes (MLNs) by CX3CR1hi mononuclear phagocytes through a CCR7-dependent process, leading to T cell responses and IgA production (30). Surprisingly, exogenous immunotherapy—ICIs—has been shown to cause intestinal bacterial translocation to secondary lymphoid organs, displaying a dynamic translocation pattern characterized by an initial dominance of Enterococcus faecalis followed by a later dominance of Lactobacillus johnsonii (31). The selection, capture, and transport of bacteria from the intestine to the MLN may enable intestinal microbiota to reach the pancreas via the lymphatic drainage pathway. Recent studies have also used real-time in vivo tracing technology to detect a significant increase in bacterial signals within phagocytes in the liver and Peyer’s patches of lymph nodes in obese mouse models, showing gut microbiota translocation via the circulatory system and liver tissue (32).
Experimental evidence indicates multiple potential pathways for gut-to-pancreas microbial translocation, with core mechanisms and corresponding animal models summarized below (Table 1). These pathways provide a structural basis for gut microbiota-mediated regulation of the pancreatic TME and immunotherapeutic response.
Table 1. Primary pathways of microbial translocation (ductal, vascular, lymphatic, phagocytosis-mediated) and associated animal models.
2.2 Changes in the microbial composition of tumors
The number and diversity of genes in the human microbiome significantly surpass those in the human genome (33), and dysbiosis of the microbiome has been linked to various malignant tumors (34, 35). Ley et al. propose that the microbial diversity in the human gut results from co-evolution between microbial communities and their hosts, and that the human environment applies selective pressure on microbial colonization (36). Merali’s team systematically described and summarized PDAC biomarkers from various microbial enrichment chamber in the human body, discovering that each microbial enrichment chamber has its own unique profile (37). This suggests that, based on intestinal microbial dysbiosis, during translocation and colonization, microbial communities change further due to environmental pressures and the microorganisms’ inherent tendencies and preferences. This emphasizes the importance of assessing the microbial composition within pancreatic tumors to better understand the development of pancreatic cancer and how it responds to treatment.
As early as 2017, Geller et al. performed a quantitative analysis of bacterial 16S rRNA in surgical resection samples of PDAC and normal pancreatic control samples, discovering that the bacterial DNA in pancreatic cancer samples was significantly higher than that in normal controls (76% vs. 15%, P < 0.005). Subsequent Fluorescence in situ hybridization and immunohistochemistry studies also verified the presence of tumor-associated bacteria in human PDAC samples. To identify the types of tumor-associated bacteria, deep sequencing of bacterial 16S rDNA amplified by PCR was conducted on 65 samples, showing that the most common bacteria in pancreatic cancer tissue belonged to the Enterobacteriaceae and Pseudomonadaceae families within the Gammaproteobacteria class (38). Subsequently, Pushalkar et al. discovered that pancreatic cancer shows enrichment of 13 bacterial phyla, mainly Proteobacteria (45%), Bacteroidetes (31%), and Firmicutes (22%) (18). These three phyla have been consistently enriched across multiple studies on tumor-associated microbiota in pancreatic cancer, with Proteobacteria exhibiting the highest consistency (39–46). Thus, Proteobacteria are the fundamental phylum in the microbiota of pancreatic cancer tumors. Moreover, it exhibits a dynamic profile of sustained enrichment throughout the entire spectrum from chronic pancreatitis to advanced pancreatic cancer (46). Following the gradual discovery of the role of bacterial communities, the potential of fungi in pancreatic cancer has also begun to emerge. Malassezia are also significantly enriched in PDAC tumor tissues and promote tumor progression (19). Subsequently, pan-cancer fungal analysis further confirmed that the fungal burden in pancreatic cancer tissues was not only significantly increased and tumor-specific, but also primarily colonized within cancer cells. This provides crucial evidence for the direct involvement of fungi in tumor cell behavior (47, 48). These studies collectively outline a preliminary map of the PDAC tumor-associated microbiome: dominated by the Proteobacteria phylum and characterized by a significant enrichment of fungal communities, including Malassezia.
Having established enrichment of gut-derived microbiota within tumors, the research focus naturally shifts to its association with clinical prognosis naturally. Riquelme et al. discovered that tumor-associated microbiome features (Pseudoxanthomonas-Streptomyces-Saccharopolyspora-Bacillus clausii) can strongly predict long-term survival (LTS) rates (49). Studying the differences in microbiome composition between short-term survival (STS) patients and LTS patients is seen as a more effective way to predict prognosis and how patients will respond to treatment (39, 40, 46, 49–54). (Table 2 reports microbial features linked to survival in pancreatic cancer). However, the same bacterial genus can have opposite prognostic values in the same study or across different studies. For the Proteobacteria phylum, which showed the highest enrichment consistency in the study, different genera within this phylum demonstrated opposite prognostic values. Pseudomonas, a relatively common genus in tumor tissues, was associated with longer survival in the study by Gao (51). In vitro experiments showed that Pseudomonas fluorescens inhibits pancreatic cancer cell proliferation and induces apoptosis, demonstrating notable antitumor activity (51). In contrast, the report by Guo indicates that Pseudomonas was more prevalent in aggressive basal-like tumors and linked to worse prognosis, potentially playing a role in inflammation and contributing to pancreatic carcinogenesis (55). This apparent paradox profoundly reveals the complexity of tumor microbiome research, whose prognostic value is neither straightforward nor fixed. This divergence likely arises from several key factors: First, tumor molecular diversity is crucial. Guo’s study focused on the basal-like subtype, a specific high-risk group whose unique immunosuppressive and inflammatory TME may influence microbial function, shifting them from harmless commensals or bystanders into accomplices of oncogenic agents (55). In contrast, Gao’s study did not stratify by subtype, and its results may reflect the overall effect across mixed tumor subtypes (51). Second, strain-level specificity must not be overlooked. The genus Pseudomonas comprises diverse species with markedly different pathogenic and probiotic potential. A simplistic genus-level analysis risks hiding critical distinctions. Additionally, differences in research methods and TME contexts, such as the functional insights provided by metagenomics versus the community structure shown by 16S rRNA sequencing, alongside variations in patient genetics, geographic factors, and tumor immune states, collectively influence the final phenotypic outcome of the microbiome. Akkermansia muciniphila shows a similar bidirectional effect. In a study by May, Akkermansia muciniphila was a characteristic of the STS cohort in patients receiving gemcitabine chemotherapy (52), which contrasts with its previous studies reporting it as a probiotic that improves intestinal barrier function and has anti-inflammatory properties (56). This suggests it may play a pro-carcinogenic role under certain conditions. This paradox could arise from the TME reshaping microbial functions. For example, Akkermansia muciniphila’s ability to degrade mucin benefits the gut but may also disrupt tissue barriers or activate carcinogenic pathways in the pancreas. Additionally, strain specificity, host factors, and the overall composition of the microbial community can all influence its ultimate effect. Therefore, as with Pseudomonas species, the prognostic value of Akkermansia muciniphila is not straightforward, underscoring the importance of understanding microbial functions in specific contexts. Future studies should move beyond simple “microbiome-prognosis” correlations and focus on elucidating microbial functions at the strain level. This involves integrating metagenomics with culture-based microbiome research in the context of specific tumor subtypes and the spatial dynamics of the TME.
Table 2. Microbial characteristics associated with survival in pancreatic cancer.
Notably, sampling and sequencing strategies directly influence the accuracy and resolution of taxonomic detection. Standard sampling methods include surgical resection, endoscopic ultrasound-guided fine needle aspiration (EUS-FNA), and bile collection. Surgical resection offers intact tumor tissue, although surgical manipulation may change microbial distribution (57). EUS-FNA is minimally invasive but yields limited sample volume (58). Bile samples reflect the biliary tract microbiota, yet their direct relevance to pancreatic tumors requires further validation (59). Formalin-fixed paraffin-embedded (FFPE) samples are the mainstay of retrospective clinical studies, but DNA degradation during embedding and storage impairs the sensitivity of microbial detection, especially in low-microbial abundance environments (52). Fresh frozen samples (e.g., surgical resections, EUS-FNA) maximize DNA preservation and thus represent a superior alternative to FFPE specimens (46, 52).
Low biomass in pancreatic tumor tissues is a well-documented challenge. The poor reproducibility of tumor-specific microbiome studies underscores the urgency of optimizing DNA/RNA extraction protocols and standardizing the analysis of sequencing data (60, 61). 16S rRNA sequencing remains the main method, reliably identifying taxa at the genus level but lacking enough resolution at the species level. This limitation significantly contributes to the conflicting prognostic associations of genus-level microbiota across studies (50, 55). Metagenomic sequencing has enhanced detection resolution, but cross-validation with tumor tissue samples from various sources remains crucial to ensure the specificity and accuracy of taxonomic assignments (62).
3 Potential mechanisms by which the microbiome influences immunotherapy
Having established the presence of gut- and tumor-associated microbiomes and their clinical significance, current research focuses on how these microbiomes influence the tumor immune microenvironment (TME). Through their metabolites, cellular components, or direct immune interactions, the microbiota significantly shapes the immune landscape of pancreatic cancer. It also impacts its response to treatment across various levels, including innate immunity, adaptive immunity, and physicochemical barriers.
3.1 Regulation of innate immune cells
The innate immune system acts as the body’s first line of defense against tumors. Thomas et al. observed increased infiltration of CD45+ immune cells in PDAC xenograft mice following microbial depletion (63). This finding in a preclinical PDAC model, consistent with evidence from other tumor preclinical models, suggests that the microbiota may shape the TME by regulating the recruitment and function of innate immune cells (64, 65).
The microbiome associated with pancreatic cancer differentially activates Toll-like receptors (TLRs), particularly TLR2, TLR4, and TLR5, via its components, such as lipopolysaccharide(LPS) and flagellin (18). In the PDAC model, this activation induces tumor-associated macrophages (TAMs) to polarize toward an immunosuppressive M2-like state via the TLR-TRAF6 signaling pathway (18). Specifically, this is characterized by decreased expression of co-stimulatory molecules such as MHC II and CD86, along with increased production of the anti-inflammatory cytokine IL-10 (18). In another in vivo and in vitro experiment using a pancreatic cancer model, sustained activation of the TLR4/NF-κB signaling pathway under LPS stimulation was similarly observed, leading to an increased proportion of M2-like macrophages within the TME (66). Concurrently, analysis of the PDAC database shows that prolonged LPS exposure increases Programmed Death-Ligand 1 (PD-L1) expression in tumor cells, thereby reducing the efficacy of ICIs (66). Macrophages treated with PDAC gut microbiota extracts exhibited reduced expression of CD44 and PD-1 in both CD4+ and CD8+ T cells (18). Similarly, Malassezia enriched in pancreatic cancer tumors exhibits cell wall sugar structures that are recognized by mannose-binding lectin (MBL), thereby activating the MBL–C3 complement cascade (19). This mechanism was directly validated in PDAC mouse model, large amounts of activated C3a bind to the C3aR receptor on the surface of pancreatic cancer cells, thereby directly promoting tumor proliferation (19). Beyond the complement cascade, in vitro study shows that β-glucan structures from PDAC tumor-enriched fungi (Alternaria and Malassezia) are recognized by Dectin-1 receptors on PDAC cancer cell surfaces, thereby activating downstream Src–Syk–CARD9–NFκB signaling, promoting IL-33 secretion (67). Subsequently, vivo studies in a PDAC mouse model confirmed the ability of specific fungi to promote IL-33 secretion by PDAC cells, as well as the critical role of IL-33 secretion in recruiting and activating Th2 cells, ILC2 cells, and Treg cells within the TME (67). Notably, under inflammatory and other tumor models, mechanisms involving biochemical factors such as reactive oxygen species (ROS) and oxidative stress have also been found to promote the extracellular secretion of IL-33 (68, 69). Moreover, in the context of pancreatic cancer, IL-33 simultaneously exhibits other tumor-promoting mechanisms distinct from those induced by fungi (70, 71). Another study under the PDAC model demonstrated that IL-33-stimulated ILC2 cells derived from myeloid cells possess antitumor immune potential by recruiting CD103+ DCs and activating CD8+ T cells (72). It also suggests that dual antitumor effects can be achieved by blocking PD-1 expression on ILC2 cells and supplementing IL-33 (72). The differing outcomes of the IL-33-ILC2 axis under distinct immune TME suggest that the impact of microbial-mediated innate immune cell activation pathways requires investigation and discussion across various tumor types, locations, and tumor immune potentials. Similar to their tumor-suppressing effects in most cancers (73, 74), the probiotic combination of Lactobacillus casei and Lactobacillus reuteri promotes M1 polarization of macrophages by inhibiting the TLR4-MyD88 signaling pathway in pancreatic cancer cells, thereby enhancing antitumor immune responses (75). Additionally, analysis using pancreatic cancer mouse models and metabolomics showed that this probiotic combination can decrease intestinal Alloprevotella abundance and increase azelate (75).
Concurrently, the microbiome promotes the accumulation of myeloid-derived suppressor cells (MDSCs) within the PDAC TME (18). After antibiotics eradicated the microbiome, MDSCs infiltration dropped significantly, showing that the microbiome plays a crucial role in maintaining the immunosuppressive myeloid cell population in pancreatic cancer (18). Research indicates that Fusobacterium nucleatum, driven by Fap2 to colonize pancreatic cancer cells and normal pancreatic epithelial cells, specifically induces the release of chemokines CXCL1, IL-8, GM-CSF, and MIP-3α (76). These factors promote the proliferation and migration of pancreatic cancer cells and the malignant transformation of normal cells through both autocrine and paracrine mechanisms (76). Similarly, through the CXCL1–CXCR2 axis, it promotes pancreatic cancer cell migration and invasion via autocrine signaling and attracts MDSCs infiltration via paracrine signaling to suppress CD8+ T cells, thereby creating an immunosuppressive TME (77).
Neutrophils are the most rapidly responding innate immune cells (78). Porphyromonas gingivalis enriched in pancreatic tumors significantly recruits tumor-associated neutrophils by upregulating chemokines (22). This process, accompanied by elevated neutrophil elastase, creates a pro-inflammatory and immunosuppressive TME that promotes tumor growth while suppressing the function of CD8+ T cells (22). In contrast, microbiome analysis based on a cohort of Chinese PDAC patients revealed that a lower Eubacterium/Bacteroides ratio in tumors and peri-tumor tissues predicted better prognosis in PDAC patients (40). Subsequently, in a PDAC mouse model, oral administration of the probiotic Bacillus coagulans demonstrated significant PDAC tumor suppression accompanied by substantial infiltration of inflammatory neutrophils in the TME (40). However, the detailed molecular pathways by which Bacillus coagulans modulates neutrophil function require further investigation. Notably, Bacillus coagulans has also been reported to exert immunomodulatory effects in other tumor models, though its cellular targets and mechanisms may vary across tumor types (79, 80).
In the PDAC TME, natural killer (NK) cells show impaired local infiltration and phenotypic imbalance. Their infiltration rate is very low (making up only 3.5% of tumor-infiltrating lymphocytes), and their phenotype is more immature (81, 82). Tumor cells can also evade NK cell surveillance by upregulating ligands that cause downregulation of NK cell activity receptors (82). Worse still, under the PDAC immunosuppressive TME, NK cells produced large amounts of the immunosuppressive cytokine IL-10, showing a shift toward a regulatory phenotype (81). Yu et al. found that microbe-associated soluble components under PDAC conditions exert multiple inhibitory effects on NK cells, including reduced cytotoxicity, migration, IFNγ secretion, and perforin expression, thereby contributing to the regulatory remodeling of NK cells (83). Unlike tumor-associated microbial effects, a recent study shows that in PDAC mouse models, the probiotic Lactobacillus reuteri improves antitumor activity by increasing NK cell infiltration and function (84). This antitumor effect has been shown to depend on NK cell-mediated innate immunity, although its specific mechanism requires further investigation.
The mentioned tumor-associated microbes have shown potential to promote the development of an immunosuppressive TME in studies exploring mechanisms that regulate innate immunity. Conversely, antibiotic clearance and probiotic supplementation demonstrate significant antitumor potential, indicating that manipulating the microbiome under tumor conditions could be promising for boosting immunity and working together with other immunotherapies.
3.2 Regulation of adaptive immune cells
Adaptive immunity, especially CD8+ cytotoxic T cells, plays a key role in antitumor immunity and the effectiveness of ICIs. An imbalance in adaptive immunity within the PDAC TME mainly appears as serious issues with antigen presentation, functional exhaustion, and low numbers of effector T cells, and increased infiltration and activation of immunosuppressive cells. Overall, these factors contribute to the failure of antitumor immune responses.
Because of its low mutation burden, PDAC exhibits a paucity of high-quality neoantigens. However, one study demonstrates that introducing a single potent neoantigen can reverse the immune “cold” state and activate T-cell-mediated clearance of tumor responses (85). This suggests that neoantigens play a crucial role in initiating immunotherapy. Later, in identifying unique neoantigens specific to long-term pancreatic cancer survivors, tumor-infiltrating T cells from LTS patients were found to cross-react with both cancer neoantigens and similar non-cancer microbial antigens (86). I In a pancreatic cancer mouse model, mice that received fecal microbiota transplantation from LST patients showed a significant increase in the number of CD8+ T cells and activated T cells (CD8+/IFNg+ T cells) (49). Further research indicates that specific microorganisms inhabiting the gut or tumors can produce peptide segments that structurally resemble pancreatic cancer tumor neoantigens. These microbial peptides can be internalized by antigen-presenting cells (APCs) and cross-presented to CD8+ T cells through MHC class I molecules, thereby triggering cytotoxic responses against the tumor cells (87). The study also suggests that a highly diverse microbiome correlates with better responses to immunotherapy and higher survival rates, opening new possibilities for improving immunotherapy through microbial means modulation (87).
Recently, a new gut bacterium, YB328, isolated from the feces of responders to immunotherapy, was found to promote tumor-infiltrating PD-1+ CD8+ T cells with a more diverse T cell receptor repertoire (88). This suggests that these cells can recognize a broader range of tumor antigens, thereby preventing rapid loss of individual T cell clones and improving the effectiveness of PD-1 blockade therapy. Although this mechanism has not been directly validated in pancreatic cancer, it provides novel insights for future studies on training effector T cells. This should be based on identifying unique microbiomes in immune responders to enhance immunotherapy. A recent study using a pancreatic cancer mouse model revealed that microbial distribution in pancreatic tumor tissues exhibits T cell-associated spatial patterns heterogeneity (89). Tumors enriched in CD8+ T cells showed genus-level enrichment of Arthrobacter and Bacillus, as well as species-level enrichment of Methylobacteriaceae. Conversely, tumors lacking CD8+ T cells showed an increase in Salirhabdus at the genus level and a specific enrichment of certain species of Oxalobacteraceae (89). This finding provides particular directions for microbial research in studies aimed at enhancing the efficacy of immunotherapy through microbiota-mediated modulation.
3.3 Metabolites indirectly regulate immunity: classification and implications for immunotherapy
Microbial metabolites, acting as small-molecule messengers, can diffuse from the gut to the systemic circulation, where they modulate antitumor immunity and constitute a crucial component of the TME.
3.3.1 Short-chain fatty acids
In short-chain fatty acids (SCFAs), butyrate and its associated microbiota were found to be significantly decreased in fecal and tumor tissue samples from pancreatic cancer patients (50). Meanwhile, the bacterial genera enriched in tumors of LTS patients possess substantial capacity to produce SCFAs, including butyrate, valeric acid, and isovaleric acid (90). Preclinical studies suggest that supplementation with specific SCFAs may exhibit antitumor effects. However, clinical data in patients with PDAC remain lacking. Mouse models of melanoma and pancreatic cancer showed that certain SCFAs can significantly boost the antitumor capacity of CD8+ T cells through a combined metabolic-epigenetic programming mechanism (91). Specifically, the HDAC class I inhibitory activity of valerate and butyrate increases the expression of TNF-α and IFN-γ effector molecules in cytotoxic T lymphocytes (CTLs) (91). The HDAC class I inhibitory effect was mediated by pentanoate- and butyrate-producing M. massiliensis and M. elsdenii, as well as by the butyrate-producing F. prausnitzii and A. hadrus (91). Butyrate activates the mTOR signaling pathway, prompting T cells to adopt a glycolytic metabolic mode. This supplies the essential energy and raw materials necessary for rapid T cell proliferation, cytokine production, and sustained survival within the body (91). Additionally, in PDAC mouse models, butyrate can remodel the TME by reducing collagen deposition, decreasing myofibroblast infiltration, lowering proangiogenic factor production, and inhibiting M2-type TAMs polarization (92). This reverses the immunosuppressive TME and enhances the delivery of chemotherapy drugs. ROR1-specific CAR T cells from humans and mice treated with valerate and butyrate exhibit significant antitumor activity, further underscoring the clinical potential of pretreated CTLs and a supplemental SCFA-producing microbiota for synergistic adoptive cell therapy (91). However, the optimal timing, dosage, and route of administration for SCFAs remain unclear, and their effects mediated by the gut microbiota may vary among individuals, creating significant challenges for precision interventions.
3.3.2 Polyamines and L-arginine
Unlike the decline in relevant SCFAs, the levels of microbially derived polyamines in the cystic fluid of patients with PDAC were significantly elevated (93). This promotes tumor cell growth and stimulates M2 macrophage polarization, thereby enhancing immune evasion (93). In genetically engineered PDAC mouse models (KPC), the synchronized increase in Lactobacillus reuteri and polyamine concentrations indicates a potential role for Lactobacillus reuteri in polyamine production (94). Existing approaches to blocking polyamines primarily focus on enzyme- and transporter-inhibitor pathways, whereas microbial-related pathways remain underdeveloped. Interestingly, arginine, a key precursor in polyamine biosynthesis, has recently been found to be depleted in the pancreatic cancer TME (95). Pancreatic cancer cells can acquire polyamines via the ornithine transaminase pathway (95). Canale’s team increased tumor-specific levels of L-arginine, a crucial precursor in polyamine biosynthesis, using engineered probiotics (96). In a mouse model of colon cancer, this approach increased the number of tumor-infiltrating T cells while reducing the proportion of Treg cells, thereby boosting the antitumor response to ICIs (96). Therefore, targeting the microbe-polyamine axis or regulating the metabolism of the polyamine precursor arginine with engineered probiotics offers a new translational strategy to overcome immune suppression in pancreatic cancer.
3.3.3 Bile acids
Furthermore, bile acids (BAs) are believed to be associated with many risk factors for pancreatic cancer. They can serve as important signaling molecules that regulate disease development and progression (97). Unlike Joshi’s finding that both deoxycholic acid (DCA) and chenodeoxycholic acid promote malignant progression in pancreatic cancer cells by activating the FXR receptor and upregulating the oncogene MUC4 through the Src/FAK/c-Jun signaling pathway axis (98). In vitro, high concentrations of BAs mixtures were found to inhibit cancer cell migration and promote apoptosis by inducing ROS production and suppressing the epithelial-mesenchymal transition (EMT) process (99). Primary BAs are metabolized by intestinal microbiota in the duodenum into secondary BAs (100). Different intestinal microbiota produce secondary BAs with distinct modifications, leading to their diversity (101). Other types of BAs induce, in a dose-dependent manner, the cancer-associated genes MUC4 and COX-2, thereby promoting tumor growth (102, 103). DCA, as a key stimulatory bile acid in PDAC, is recognized for its dual properties: it exhibits antitumor characteristics by inhibiting epithelial-mesenchymal transition, reducing tumor stem cells, and inducing oxidative/nitrosative stress. At the same time, it promotes tumor growth by inducing a hypermetabolic state that generates chemoresistance (104). In contrast, Kim et al. reported that another secondary bile acid, ursodeoxycholic acid, effectively inhibits EMT and cancer stem cell formation by decreasing ROS levels and by increasing superoxide dismutase 2 (105). This duality strongly indicates that the gut microbiota, through its metabolic activity in regulating bile acid profiles, may serve as a key environmental factor affecting the biological behavior of pancreatic cancer. However, the role of deoxycholic acid varies considerably across different cancer contexts, showing high environmental influence dependence (106). The mechanism of action of specific secondary BAs in the body environment requires further investigation.
3.3.4 Tryptophan metabolite
In addition to the classic metabolites mentioned earlier, studies have shown that Lactobacillus metabolizes dietary tryptophan into indole, which activates the aryl hydrocarbon receptor (AhR) in macrophages, promoting an immunosuppressive phenotype and reducing inflammatory T-cell infiltration (107). Tintelnot found that, in a humanized gnotobiotic mouse model of PDAC, combining the microbial-derived tryptophan metabolite indole-3-acetic acid with chemotherapy reduced tumor growth via a mechanism independent of AhR (108). Although 3−IAA shows strong preclinical synergy with FOLFIRINOX/GnP, clinical translation remains to be defined.
3.3.5 Trimethylamine N-oxide
Trimethylamine N-oxide (TMAO) is a metabolite mainly produced by gut microbiota. In an in situ PDAC mouse model, TMAO is believed to directly enhance the immune-stimulatory phenotype of TAMs, strengthen the antitumor immune response of effector T cells, reduce tumor burden, and increase their responsiveness to ICIs (109). However, TMAO is also associated with an increased risk of cardiovascular events, and its safety in cancer treatment requires further validation (110).
3.4 Driving the development of treatment resistance
Multiple small-scale clinical trials have shown that monotherapy or combination immunotherapy for pancreatic cancer has not produced satisfactory results (10, 111, 112). However, combining immunotherapy with radiotherapy and chemotherapy is thought to improve efficacy (113). Along with the aforementioned role of microorganisms in shaping the immune TME, a 2017 study revealed that Gammaproteobacteria within tumors can metabolize the chemotherapy drug gemcitabine to an inactive form by producing the bacterial enzyme cytidine deaminase (CDDL), and antibiotics targeting these bacteria can help prevent this resistance (38). Photodynamic antimicrobial therapy targeting Gammaproteobacteria effectively inhibited gemcitabine metabolism and improved chemotherapy effectiveness (114). Meanwhile, oral administration of multiple probiotics can enhance the effectiveness of gemcitabine chemotherapy and improve tolerance to chemotherapy (115–117).
A study on the longitudinal changes in the gut microbiome of melanoma patients after immunotherapy indicated that Eisenbergiella sp., Bacteroides wexlerae, Clostridium spiroforme, and Erysipelotrichaceae are linked to resistance to ICIs. Similar research should be done in patients with pancreatic cancer undergoing immunotherapy or combination therapy to identify the microbial communities associated with resistance, aiding targeted elimination and reducing the adverse effects of resistance (116).
4 Microbial control methods
The microbiome influences host antitumor immunity through the mechanisms mentioned earlier and potentially other pathways, thereby affecting the clinical response and outcomes of patients undergoing cancer immunotherapy. It might also be possible to predict the effectiveness of immunotherapy. Specific interventions that modify the microbiome could lead to the development of new therapeutic strategies as valuable adjuncts to current antitumor treatments and immunotherapies (Figure 2).
Figure 2. Core Intervention Methods for Microbial Regulation. Diet: fasting 24h, ketogenic diets, high-fiber diets, black raspberry, engineered resistant-starch diet. Fecal Microbiota Transplantation: TME from healthy or LTS patients to recipients to restore gut microbial balance. Antibiotics and Phages: Targeted elimination of tumor-promoting or drug-resistant microbial populations, genetically engineered bacteriophages to block the PD-1/PD-L1 Axis. Probiotics and Engineered Microorganisms: Supplementing probiotics or their metabolites directly modulates the TME. Engineered microorganisms (such as Escherichia coli Nissle 1917, Salmonella VNP20009, Clostridium butyricum, and its spores) are engineered to target specific substrates or deliver drugs. Created in BioRender. Yuan, Y. (2026) https://BioRender.com/395il9b.
4.1 Diet
Dietary intake, as an important environmental factor, is believed to influence tumor metabolism and thereby enhance treatment effectiveness (118). Gemcitabine-treated pancreatic cancer xenograft mouse models that underwent 24-hour fasting before treatment exhibited significantly slower tumor growth. Both in vivo and in vitro assays confirmed that fasting enhances gemcitabine uptake and counteracts chemoresistance caused by mTOR activation (119). Similarly, the ketogenic diet (extremely low in carbohydrates, low in protein, high in fat) shows significant potential to limit tumor growth in KPC mouse models when combined with standard PDAC treatments, chemotherapeutics (120). A related randomized clinical trial investigating ketogenic diets combined with standard chemotherapy in metastatic pancreatic cancer patients is currently underway (NCT04631445). A retrospective review, based primarily on multiple mouse models and supplemented by limited rat models and human studies, concludes that high-fat diets typically decrease Bacteroidetes and increase Firmicutes and Proteobacteria. These changes promote inflammation and increased permeability, thereby allowing bacteria and their metabolites to translocate and potentially exacerbate microbial dysbiosis in pancreatic cancer (121). High-fiber diets may enhance treatment effectiveness by promoting the growth of beneficial microbiota, such as Bifidobacterium and Lactobacillus, which produce helpful metabolites such as butyrate (122). Similarly, feeding pancreatic cancer xenograft mice an engineered diet replacing corn starch with resistant starch for 18 days significantly slowed tumor growth. This antiproliferative effect may be linked to reduced pro-inflammatory gut microbes and an increase in butyrate-producing Lachnospiraceae (123). A 5% black raspberry diet fed for six weeks modulated immune activity in both xenograft and genetically engineered PDAC mouse models by increasing CD8+T cell and NK cell infiltration while reducing MDSCs—an effect similarly linked to diet-induced butyrate production (124).
4.2 Fecal microbiota transplantation
Due to the difficulty in identifying specific species within the gut microbiota and the potential impact of supplementing with a single bacterial strain on the gut microbiota diversity (125). FMT is considered the simplest method for directly changing gut microbiota composition. It is believed to have the potential to restore immune balance, reduce immune-related adverse events, and improve immunotherapy effectiveness (126). Some clinical studies have shown that combining FMT and immunotherapy has demonstrated significant efficacy in melanoma, colorectal cancer, and other gastrointestinal solid tumors (127–129). In preclinical pancreatic cancer studies, the donor source of FMT, LTS versus STS, directly determines its regulatory effects on the TME. Foundational work by the Riquelme group provides direct evidence supporting this idea. They transplanted gut microbiota from pancreatic cancer LTS and STS donors into syngeneic pancreatic cancer mouse models, respectively. Results showed that mice receiving LTS-derived FMT exhibited favorable changes in intratumoral microbiome composition, along with increased CD8+ T-cell activity (49). Meanwhile, the accumulation of MDSCs and Tregs was suppressed, leading to a significant slowdown in tumor progression. In contrast, STS-derived microbiota failed to induce such beneficial immune reprogramming. Instead, they likely exacerbated immunosuppression by increasing TME fibrosis and promoting M2-type TAMs polarization, thereby impairing the efficacy of ICIs (49). This critical difference underscores the need for rigorous donor selection and functional characterization in FMT-based interventions. Currently, Phase I clinical trials are investigating the effect of FMT in pancreatic cancer are underway to assess the safety and effectiveness, as well as the safety of combining it with chemotherapy. (NCT 06393400 and NCT 04975217).
4.3 Antibiotics and phages
The impact of antibiotics on immunotherapy is twofold. On the one hand, antibiotics help eliminate drug-resistant microorganisms associated with chemotherapy and immunotherapy, thereby improving treatment effectiveness. For precise regulation, clarifying their distinct mechanisms and exploring more targeted alternative strategies is critical.
4.3.1 Antibiotics in reversing microbiome-mediated drug resistance
Geller et al.’s groundbreaking work showed that intratumoral Gammaproteobacteria metabolize the chemotherapeutic drug gemcitabine into its inactive form through bacterial cytidine deaminase expression, leading to treatment failure (38). Eradicating these bacteria with the targeted antibiotic ciprofloxacin reverses this resistance and restores gemcitabine efficacy (38). Furthermore, metagenomic data analysis of pancreatic cancer patient samples suggests that antibiotic resistance genes carried by gut-derived bacteria, such as Klebsiella pneumoniae, Klebsiella oxytoca, and Acinetobacter mucosus, may reduce tumor cell chemosensitivity to drugs such as gemcitabine through mechanisms including increased efflux pump activity and drug-target modification (130). Findings from these preclinical models confirm that bacteria not only directly degrade drugs but also contribute to chemoresistance by enhancing the intrinsic tolerance of tumor cells or TME. Subsequent studies developed photodynamic antimicrobial therapy targeting such drug-resistant bacteria, which effectively inhibits bacterial gemcitabine metabolism and enhances chemotherapeutic efficacy (114). Collectively, these mechanisms highlight the value of antibiotics to overcome both direct and indirect bacterial-mediated chemoresistance.
4.3.2 Antibiotics and ICIs response: a double-edged sword
Beyond chemoresistance, the impact of antibiotics extends to the emerging realm of immunotherapy for PDAC. While the clinical success of ICIs in PDAC has been limited, combinatorial strategies with chemotherapy are actively being explored to overcome the immunosuppressive TME (131, 132). In this context, the impact of antibiotics used for infection management in cancer patients on the efficacy of ICIs has also become a critical clinical consideration. Multiple observational studies have reported that administering broad-spectrum antibiotics before or after ICIs impairs the effectiveness of immunotherapy and reduces patient survival (133–135). The underlying mechanism involves the indiscriminate disruption of gut microbiota diversity and homeostasis by these antibiotics. This process depletes beneficial commensal bacteria, such as Akkermansia muciniphila, Alistipes spp., Ruminococcus spp., Eubacterium spp., and Lactobacillus johnsonii, which are critical for initiating and maintaining robust antitumor T cell responses (133, 134). Such dysbiosis shifts the TME toward an immunosuppressive state, for example, by reducing tumor-infiltrating CD8+ T cells and increasing regulatory T cells, thereby abrogating ICIs activity.
To address this issue, narrow-spectrum antibiotics and microbiota-protective strategies have become important research focuses. These methods involve screening for specific pathogenic or drug-resistant strains through metagenomic sequencing and developing targeted antibiotic combinations to maintain beneficial microbiota. Alternatively, co-administering antibiotics with probiotics, prebiotics, or FMT can help protect or quickly restore the gut ecosystem necessary for optimal immunotherapy efficacy.
4.3.3 Phages
Phages, as a complementary therapy for antibiotic resistance, exhibit both specificity and immune-modulatory abilities (136), and have been reported to be effective in treating pancreatitis caused by multidrug-resistant Acinetobacter baumannii (137). Phage display technology identified plectin-1 as a novel PDAC biomarker in 2008, offering new molecular and imaging tools for pancreatic cancer diagnosis (138). In melanoma, genetically engineered filamentous phages are considered cost-effective and highly effective tumor-targeted immunotherapy agents that inhibit tumor cell immune evasion by blocking the PD-1/PD-L1 axis (139). The bidirectional effects of antibiotics on antitumor therapy highlight the importance of accurately targeting microorganisms associated with cancer. Phages offer an economically feasible targeting approach, demonstrating the potential for precise modulation of the microbiome within pancreatic tumors.
4.4 Probiotics and engineered bacteria
Probiotics may act as a natural adjunct approach for pancreatic cancer immunotherapy by regulating gut microbiota balance, improving intestinal barrier function, and modulating immune cell activity. Building on this foundation, genetic engineering techniques further enhance microbial targeting and functional specificity, turning engineered bacteria into innovative tools to precisely breach the TME barrier and potentially synergize with immunotherapy.
4.4.1 Probiotics: natural microbiota regulation and immune synergy
Probiotics are defined as live microorganisms that confer health benefits on the host when administered in adequate amounts (140). Common probiotics include Bifidobacterium, Lactobacillus, Acinetobacter mucosus, and Ruminococcus. Specific probiotic strains have been shown in preclinical studies to modulate immune cell function in the TME. For example, Bifidobacterium and Ruminococcus were associated with enhanced dendritic cell activity and increased CD8+ T cell infiltration into tumors, which may contribute to improved efficacy of anti-PD-L1/PD-1 therapy in those models (141, 142). In a pancreatic cancer mouse model, dietary supplementation with Lactobacillus reuteri was associated with increased NK cell infiltration into the TME and correlated with enhanced antitumor activity (84). Similarly, pancreatic cancer models fed with the probiotic strain AJ2 was associated with restored NK cell cytotoxicity and IFN-γ secretion (143). Beyond modulating immune cell function, a probiotic mixture dominated by Bifidobacterium and Lactobacillus species was reported to delay pancreatic epithelial-mesenchymal transition and reduce chemotherapy-related toxicity in a xenograft model (117).
Probiotics can produce systemically active antitumor molecules through intestinal fermentation. For instance, Aspergillus oryzae and its metabolite heptelidic acid activate the p38 MAPK pathway, whereas ferrichrome from Lactobacillus casei induces endoplasmic reticulum stress; both pathways have been shown to induce apoptosis in pancreatic cancer cells (144, 145). Furthermore, ferrichrome has been shown to activate TLR4 signaling in mouse models, leading to M1 polarization of TAMs, increased CD8+ T cell infiltration, and improved response to anti-PD-L1 therapy (146).
In addition to providing probiotics, prebiotics, and nondigestible food ingredients that serve as nourishment for beneficial bacteria in your gut, they also serve as beneficial substrates that support probiotic colonization. These may indirectly affect treatment results and aid in repairing damaged intestinal barriers (147). In the context of PDAC, preclinical evidence suggests that dietary fibers can increase the abundance of SCFA-producing bacteria, which may indirectly modulate antitumor immunity (122). However, direct evidence linking specific prebiotic supplementation to improved immunotherapy outcomes in PDAC patients is currently lacking. Synbiotics, which combine probiotics and prebiotics, have been shown in a randomized controlled trial to enhance anti-tumor immune cell infiltration and lead to fewer surgical complications compared to the use of probiotics alone (148). This highlights a potential combinatorial approach, though larger confirmatory studies are needed.
Despite promising preclinical data, several challenges must be addressed for clinical translation. The optimal probiotic strain, dosage, timing, and duration for PDAC remain undefined and likely vary among individuals due to baseline microbiome differences. Safety concerns, though generally low for traditional probiotics, include the risk of bacteremia in immunocompromised patients (149). Furthermore, the regulatory pathway for probiotics as cancer therapeutics is complex, as they are often classified as dietary supplements rather than drugs, which limits the requirement for rigorous clinical trial validation of specific health claims (150).
4.4.2 Engineering bacteria: precision targeting and functional enhancement
Genetic engineering can improve microorganisms with abilities such as targeted delivery, tissue penetration, and combination drug release. These modified microbes are designed to overcome key barriers in the TME, including stromal fibrosis, immune suppression, and poor drug infiltration, and with the aim of synergizing with immunotherapy.
Engineered facultative anaerobic bacteria can target hypoxic tumor regions and degrade dense stroma locally. A key example is Escherichia coli Nissle 1917 (ECN), which can be loaded with collagenase or hyaluronidase to disrupt the matrix barrier, thereby enhancing the penetration and accumulation of chemotherapeutics and ICIs, such as anti-PD-L1 antibodies (151, 152). Similarly, Clostridium butyricum has been modified to deliver the TGF-β inhibitor Vaxotib, thereby suppressing extracellular matrix production (153). This promotes drug and immune cell infiltration while competitively inhibiting pro-tumor γ-proteobacteria, thus modulating the tumor microbiome (153). While these strategies effectively remodeled the TME in mouse models, their safety regarding non-targeted tissue damage and systemic immune responses in humans remains to be evaluated.
In addition to targeting the TME, engineered bacteria in the following preclinical models can also serve as carriers for chemotherapeutic drugs and immunomodulators, allowing precise and sustained drug delivery to tumors. For example, ECN loaded with anti-PD-L1 antibodies, autophagy inhibitors, and chemotherapeutics reduces immunosuppression and increases intratumoral drug levels (151, 152). Similarly, Salmonella VNP20009 engineered to deliver aptamer drugs has been shown to foster an immune-activated TME, suggesting potential for enhancing both chemotherapy and immunotherapy (154). Additionally, a harsh-condition-tolerant spore of Clostridium butyricum has been developed for the delivery of gemcitabine; after oral administration, it targets pancreatic tumors specifically via the gut-pancreatic axis (115).
5 Methodological limitations and future directions
5.1 Low biomass and pollution control
Pancreatic tissue is a low-microbial-biomass environment, making it susceptible to exogenous microbial DNA contamination from reagents, laboratory settings, and sampling procedures, which may produce false-positive signals (155). Improper handling and storage can degrade microbial DNA, reducing signal intensity and increasing the risk of false negatives (155). Batch effects arising from different platforms and data collection methods also require consideration (156). Although negative controls and bioinformatic filtering can partially address contamination and batch effects, future studies should implement more rigorous experimental controls and standardized decontamination protocols. Recent consensus reports outline strategies to reduce contamination and cross-contamination, and establish minimum reporting standards for contamination-related information and decontamination steps (157).
5.2 Correlation and causation
Most human studies show links between microbial features and clinical outcomes. However, baseline gut microbiota can differ based on patient location, diet, and smoking/alcohol habits, leading to variations in tumor-related microbial profile shifts (50, 158). Treatments also change microbial composition; for example, in tumor−bearing rats with experimental cancers, irinotecan increased Clostridium cluster XI and Enterobacteriaceae in tumor-bearing rats (159, 160). Establishing large-scale, multicenter databases with detailed clinical metadata is therefore essential for validating biomarkers and supporting clinical translation. Furthermore, tumors exhibit spatial heterogeneity, potentially harboring distinct microbial communities in different regions, such as immune-cell-deficient versus immune-cell-enriched areas (89). Bulk sequencing masks this micro-geographic distribution. Future mapping of microbial–host interactions will benefit from combining single-cell and spatial transcriptomics with microbial detection (17).
Current causal inference primarily relies on animal models, such as xenograft, germ-free, and humanized FMT models. Xenograft models, which involve implanting human tumor tissue into immunodeficient mice, are useful for evaluating drug responses but cannot fully reproduce the entire immune–microbiome system interactions (161, 162). Germ-free models represent a non-physiological extreme and prevent the study of inter-microbial ecology, such as competition or cooperation. Although mono-colonization studies can demonstrate causality, they do not capture the complexity of human microbial communities ecosystems (29). Humanized FMT models depend on donor, recipient, and procedural variables and therefore require standardized protocols to ensure reproducibility. Patient−derived organoids, which retain key TME features, provide a complementary platform (163). Integrating organoids with animal models may provide a more comprehensive research strategy (164).
5.3 Clinical translation challenges
Although FMT is approved for recurrent Clostridioides difficile infection (165), its long-term efficacy and safety in non−infectious diseases require further validation. FMT outcomes can vary based on donor and recipient microbiome characteristics, as well as differing clinical regulations, drug policies, and medical practices globally (166). Establishing international consensus on donor screening and production protocols is therefore necessary to improve safety and generalizability (167).
Engineered microbial therapies, such as modified bacteria and phages, provide high versatility and represent a promising approach in microbiome-based precision medicine (168). While investigating different disease models, they must address biosafety and ethical concerns, such as preventing unintended genetic recombination or the spread of antibiotic resistance (169). The variety of these artificial therapies complicates regulatory standardization, highlighting the need for validated preclinical models and mutually agreed-upon regulatory frameworks (170).
6 Summary and outlook
This review discusses the role of the gut and tumor microbiome in pancreatic cancer metastasis and treatment response. Evidence indicates that the microbiome actively influences the immunosuppressive TME through cellular components, metabolites, and immune interactions, thereby impacting disease progression and therapy. This provides a strong rationale for targeting the microbiome to enhance immunotherapy. However, translating these findings into clinical practice still faces significant challenges.
Microorganisms often participate in migration and colonization collectively. In addition to their interactions with immune cells, the patterns of their internal interactions also deserve attention. Studies have shown that the microbial interaction patterns in pancreatic cancer patients are less complex than those in healthy individuals, with reduced tightness (171). Such changes in interaction patterns may also influence the development of the pancreatic cancer TME. Future research should focus on the overall structure of microbial communities, the stability of their interaction networks, and their collective metabolic functions. A functional ecological niche may be more significant than the presence of specific taxa. Integrating metagenomics, metabolomics, and single-cell sequencing will help decipher this complex ecosystem.
Current analyses linking tumor-associated microbes to prognosis yield conflicting results, underscoring significant inter-patient microbiome diversity as a key obstacle to personalized therapy. This variation arises from host genetics, diet, medication history, tumor molecular subtype, and anatomical location. Future clinical trials should therefore consider these factors and develop microbiota-based patient stratification to identify those most likely to benefit from specific treatments. All microbiome-targeting strategies must be validated for effectiveness and safety through carefully designed randomized controlled trials, with close monitoring of potential effects on immunotherapy-related adverse events.
In summary, microbiome research is transforming our understanding of PDAC. Through interdisciplinary collaboration and technological innovation, targeting the microbiome is expected to become a key part of multimodal PDAC therapy, offering a new strategy to improve outcomes for this immunologically cold tumor.
Author contributions
YY: Writing – original draft. WZ: Conceptualization, Supervision, Writing – review & editing. DW: Supervision, Conceptualization, Writing – review & editing.
Funding
The author(s) declared that financial support was not received for this work and/or its publication.
Acknowledgments
Figures were created in https://BioRender.com.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Abbreviations
TME, Tumor microenvironment; PDAC, Pancreatic ductal adenocarcinoma; ICIs, Immune checkpoint inhibitors; WT, Wild type; PD-1, Programmed cell death protein 1; Myd88, Myeloid differentiation primary response 88; MLNs, Mesenteric lymph nodes; MBL, Mannose-binding lectin; STS, Short-term survival; LTS, Long-term survival; EUS-FNA, Endoscopic ultrasound-guided fine needle aspiration; TLRs, Toll-like receptors; LPS, Lipopolysaccharide; MDSCs, Myeloid-derived suppressor cells; Tregs, Regulatory T cells; NK, Natural killer; FMT, Fecal microbiota transplantation; SCFAs, Short-chain fatty acids; HDAC, Histone deacetylase; CTLs, Cytotoxic T lymphocytes; AhR, Aryl hydrocarbon receptor; BAs, Bile acids; DCA, Deoxycholic acid; ROS, Reactive oxygen species; EMT, Epithelial-mesenchymal transition; TMAO, Trimethylamine N-oxide; TAMs, Tumor-associated macrophages; PD-L1, Programmed death ligand 1; ECN, Escherichia coli strain Nissle 1917; FFPE, Formalin-fixed paraffin-embedded.
References
1. Stoop TF, Javed AA, Oba A, Koerkamp BG, Seufferlein T, Wilmink JW, et al. Pancreatic cancer. Lancet. (2025) 405:1182–202. doi: 10.1016/s0140-6736(25)00261-2
2. Falcomatà C, Bärthel S, Schneider G, Rad R, Schmidt-Supprian M, and Saur D. Context-specific determinants of the immunosuppressive tumor microenvironment in pancreatic cancer. Cancer Discov. (2023) 13:278–97. doi: 10.1158/2159-8290.CD-22-0876
3. Siegel RL, Kratzer TB, Giaquinto AN, Sung H, and Jemal A. Cancer statistics, 2025. CA Cancer J Clin. (2025) 75:10–45. doi: 10.3322/caac.21871
4. Amrutkar M and Gladhaug I. Pancreatic cancer chemoresistance to gemcitabine. Cancers. (2017) 9:157. doi: 10.3390/cancers9110157
5. Conroy T, Hammel P, Hebbar M, Ben Abdelghani M, Wei AC, Raoul JL, et al. FOLFIRINOX or gemcitabine as adjuvant therapy for pancreatic cancer. N Engl J Med. (2018) 379:2395–406. doi: 10.1056/NEJMoa1809775
6. Leonhardt CS, Gustorff C, Klaiber U, Le Blanc S, Stamm TA, Verbeke CS, et al. Prognostic factors for early recurrence after resection of pancreatic cancer: A systematic review and meta-analysis. Gastroenterology. (2024) 167:977–92. doi: 10.1053/j.gastro.2024.05.028
7. O’Reilly EM, Lee JW, Zalupski M, Capanu M, Park J, Golan T, et al. Randomized, multicenter, phase II trial of gemcitabine and cisplatin with or without veliparib in patients with pancreas adenocarcinoma and a germline BRCA/PALB2 mutation. J Clin Oncol. (2020) 38:1378–88. doi: 10.1200/JCO.19.02931
8. Strickler JH, Satake H, George TJ, Yaeger R, Hollebecque A, Garrido-Laguna I, et al. Sotorasib in KRAS p.G12C–mutated advanced pancreatic cancer. N Engl J Med. (2023) 388:33–43. doi: 10.1056/NEJMoa2208470
9. Marabelle A, Le DT, Ascierto PA, Di Giacomo AM, De Jesus-Acosta A, Delord JP, et al. Efficacy of pembrolizumab in patients with noncolorectal high microsatellite instability/mismatch repair–deficient cancer: results from the phase II KEYNOTE-158 study. J Clin Oncol. (2020) 38:1–10. doi: 10.1200/JCO.19.02105
10. O’Reilly EM, Oh DY, Dhani N, Renouf DJ, Lee MA, Sun W, et al. Durvalumab with or without tremelimumab for patients with metastatic pancreatic ductal adenocarcinoma: A phase 2 randomized clinical trial. JAMA Oncol. (2019) 5:1431. doi: 10.1001/jamaoncol.2019.1588
11. Anderson CJ, Boeckaerts L, Chin P, Cardas JB, Xie W, Gonçalves A, et al. Metabolite-based inter-kingdom communication controls intestinal tissue recovery following chemotherapeutic injury. Cell Host Microbe. (2024) 32:1469–1487.e9. doi: 10.1016/j.chom.2024.07.026
12. Fan J, Zhou Y, Meng R, Tang J, Zhu J, Aldrich MC, et al. Cross-talks between gut microbiota and tobacco smoking: a two-sample Mendelian randomization study. BMC Med. (2023) 21:163. doi: 10.1186/s12916-023-02863-1
13. Ames NJ, Barb JJ, Schuebel K, Mudra S, Meeks BK, Tuason RTS, et al. Longitudinal gut microbiome changes in alcohol use disorder are influenced by abstinence and drinking quantity. Gut Microbes. (2020) 11:1608–31. doi: 10.1080/19490976.2020.1758010
14. Sepich-Poore GD, Zitvogel L, Straussman R, Hasty J, Wargo JA, and Knight R. The microbiome and human cancer. Science. (2021) 371:eabc4552. doi: 10.1126/science.abc4552
15. Sethi V, Vitiello GA, Saxena D, Miller G, and Dudeja V. The role of the microbiome in immunologic development and its implication for pancreatic cancer immunotherapy. Gastroenterology. (2019) 156:2097–2115.e2. doi: 10.1053/j.gastro.2018.12.045
16. Ahuja M, Schwartz DM, Tandon M, Son A, Zeng M, Swaim W, et al. Orai1-mediated antimicrobial secretion from pancreatic acini shapes the gut microbiome and regulates gut innate immunity. Cell Metab. (2017) 25:635–46. doi: 10.1016/j.cmet.2017.02.007
17. Ghaddar B, Biswas A, Harris C, Omary MB, Carpizo DR, Blaser MJ, et al. Tumor microbiome links cellular programs and immunity in pancreatic cancer. Cancer Cell. (2022) 40:1240–1253.e5. doi: 10.1016/j.ccell.2022.09.009
18. Pushalkar S, Hundeyin M, Daley D, Zambirinis CP, Kurz E, Mishra A, et al. The pancreatic cancer microbiome promotes oncogenesis by induction of innate and adaptive immune suppression. Cancer Discov. (2018) 8:403–16. doi: 10.1158/2159-8290.CD-17-1134
19. Aykut B, Pushalkar S, Chen R, Li Q, Abengozar R, Kim JI, et al. The fungal mycobiome promotes pancreatic oncogenesis via activation of MBL. Nature. (2019) 574:264–7. doi: 10.1038/s41586-019-1608-2
20. Nejman D, Livyatan I, Fuks G, Gavert N, Zwang Y, Geller LT, et al. The human tumor microbiome is composed of tumor type–specific intracellular bacteria. Science. (2020) 368:973–80. doi: 10.1126/science.aay9189
21. Michaud DS, Liu Y, Meyer M, Giovannucci E, and Joshipura K. Periodontal disease, tooth loss, and cancer risk in male health professionals: a prospective cohort study. Lancet Oncol. (2008) 9:550–8. doi: 10.1016/S1470-2045(08)70106-2
22. Tan Q, Ma X, Yang B, Liu Y, Xie Y, Wang X, et al. Periodontitis pathogen Porphyromonas gingivalis promotes pancreatic tumorigenesis via neutrophil elastase from tumor-associated neutrophils. Gut Microbes. (2022) 14:2073785. doi: 10.1080/19490976.2022.2073785
23. Neurath MF, Artis D, and Becker C. The intestinal barrier: a pivotal role in health, inflammation, and cancer. Lancet Gastroenterol Hepatol. (2025) 10:573–92. doi: 10.1016/S2468-1253(24)00390-X
24. Aburto MR and Cryan JF. Gastrointestinal and brain barriers: unlocking gates of communication across the microbiota–gut–brain axis. Nat Rev Gastroenterol Hepatol. (2024) 21:222–47. doi: 10.1038/s41575-023-00890-0
25. Brenchley JM and Douek DC. Microbial translocation across the GI tract. Annu Rev Immunol. (2012) 30:149–73. doi: 10.1146/annurev-immunol-020711-075001
26. Rumyantsev KA, Polyakova VV, Sorokina IV, Feoktistova PS, Khatkov IE, Bodunova NA, et al. The gut microbiota impacts gastrointestinal cancers through obesity, diabetes, and chronic inflammation. Life. (2024) 14:1219. doi: 10.3390/life14101219
27. Liu ZH, Peng JS, Li CJ, Yang ZL, Xiang J, Song H, et al. A simple taurocholate-induced model of severe acutepancreatitis in rats. World J Gastroenterol. (2009) 15:5732. doi: 10.3748/wjg.15.5732
28. Widdison AL, Karanjia ND, and Reber HA. Routes of spread of pathogens into the pancreas in a feline model of acute pancreatitis. Gut. (1994) 35:1306–10. doi: 10.1136/gut.35.9.1306
29. Geva-Zatorsky N, Sefik E, Kua L, Pasman L, Tan TG, Ortiz-Lopez A, et al. Mining the human gut microbiota for immunomodulatory organisms. Cell. (2017) 168:928–943.e11. doi: 10.1016/j.cell.2017.01.022
30. Diehl GE, Longman RS, Zhang JX, Breart B, Galan C, Cuesta A, et al. Microbiota restricts trafficking of bacteria to mesenteric lymph nodes by CX3CR1hi cells. Nature. (2013) 494:116–20. doi: 10.1038/nature11809
31. Choi Y, Lichterman JN, Coughlin LA, Poulides N, Li W, Del Valle P, et al. Immune checkpoint blockade induces gut microbiota translocation that augments extraintestinal antitumor immunity. Sci Immunol. (2023) 8:eabo2003. doi: 10.1126/sciimmunol.abo2003
32. Fan X, Zhou Y, Bai W, Li X, Lin L, Lin H, et al. Intravital imaging of translocated bacteria via fluorogenic labeling of gut microbiota in situ. Proc Natl Acad Sci. (2025) 122:e2415845122. doi: 10.1073/pnas.2415845122
33. MetaHIT Consortium, Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature. (2010) 464:59–65. doi: 10.1038/nature08821
34. Plottel CS and Blaser MJ. Microbiome and Malignancy. Cell Host Microbe. (2011) 10:324–35. doi: 10.1016/j.chom.2011.10.003
36. Ley RE, Peterson DA, and Gordon JI. Ecological and evolutionary forces shaping microbial diversity in the human intestine. Cell. (2006) 124:837–48. doi: 10.1016/j.cell.2006.02.017
37. Merali N, Chouari T, Sweeney C, Halle-Smith J, Jessel MD, Wang B, et al. The microbial composition of pancreatic ductal adenocarcinoma: a systematic review of 16S rRNA gene sequencing. Int J Surg. (2024) 110:6771–99. doi: 10.1097/JS9.0000000000001762
38. Geller LT, Barzily-Rokni M, Danino T, Jonas OH, Shental N, Nejman D, et al. Potential role of intratumor bacteria in mediating tumor resistance to the chemotherapeutic drug gemcitabine. Science. (2017) 357:1156–60. doi: 10.1126/science.aah5043
39. Abe S, Masuda A, Matsumoto T, Inoue J, Toyama H, Sakai A, et al. Impact of intratumoral microbiome on tumor immunity and prognosis in human pancreatic ductal adenocarcinoma. J Gastroenterol. (2024) 59:250–62. doi: 10.1007/s00535-023-02069-5
40. Zhang Z, Wang T, Xu M, Zhang Z, Wang H, Xue J, et al. Deciphering the pancreatic cancer microbiome in Mainland China: Impact of Exiguobacterium/Bacillus ratio on tumor progression and prognostic significance. Pharmacol Res. (2024) 204:107197. doi: 10.1016/j.phrs.2024.107197
41. Chung M, Zhao N, Meier R, Koestler DC, Wu G, Del Castillo E, et al. Comparisons of oral, intestinal, and pancreatic bacterial microbiomes in patients with pancreatic cancer and other gastrointestinal diseases. J Oral Microbiol. (2021) 13:1887680. doi: 10.1080/20002297.2021.1887680
42. Langheinrich M, Wirtz S, Kneis B, Gittler MM, Tyc O, Schierwagen R, et al. Microbiome patterns in matched bile, duodenal, pancreatic tumor tissue, drainage, and stool samples: association with preoperative stenting and postoperative pancreatic fistula development. J Clin Med. (2020) 9:2785. doi: 10.3390/jcm9092785
43. Uguz A, Muftuoglu C, Mert U, Gumus T, Ece D, Asadi M, et al. Unveiling microbiota profiles in saliva and pancreatic tissues of patients with pancreatic cancer. Microorganisms. (2025) 13:119. doi: 10.3390/microorganisms13010119
44. Gleeson FC, Jeraldo P, Levy MJ, Murphy SJ, Mendes-Soares H, Karagouga G, et al. Composition, diversity and potential utility of intervention-naïve pancreatic cancer intratumoral microbiome signature profiling via endoscopic ultrasound. Gut. (2022) 71:441–3. doi: 10.1136/gutjnl-2021-324031
45. Nakano S, Kawamoto Y, Komatsu Y, Saito R, Ito K, Yamamura T, et al. Analysis of the pancreatic cancer microbiome using endoscopic ultrasound–guided fine-needle aspiration–derived samples. Pancreas. (2022) 51:351–7. doi: 10.1097/MPA.0000000000002028
46. Zhu Y, Liang X, Zhi M, Li L, Zhang G, Chen C, et al. Succession of the multi-site microbiome along pancreatic ductal adenocarcinoma tumorigenesis. Front Immunol. (2024) 15:1487242. doi: 10.3389/fimmu.2024.1487242
47. Dohlman AB, Klug J, Mesko M, Gao IH, Lipkin SM, Shen X, et al. A pan-cancer mycobiome analysis reveals fungal involvement in gastrointestinal and lung tumors. Cell. (2022) 185:3807–3822.e12. doi: 10.1016/j.cell.2022.09.015
48. Narunsky-Haziza L, Sepich-Poore GD, Livyatan I, Asraf O, Martino C, Nejman D, et al. Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions. Cell. (2022) 185:3789–3806.e17. doi: 10.1016/j.cell.2022.09.005
49. Riquelme E, Zhang Y, Zhang L, Montiel M, Zoltan M, Dong W, et al. Tumor microbiome diversity and composition influence pancreatic cancer outcomes. Cell. (2019) 178:795–806.e12. doi: 10.1016/j.cell.2019.07.008
50. Huang Y, Zhu N, Zheng X, Liu Y, Lu H, Yin X, et al. Intratumor microbiome analysis identifies positive association between megasphaera and survival of chinese patients with pancreatic ductal adenocarcinomas. Front Immunol. (2022) 13:785422. doi: 10.3389/fimmu.2022.785422
51. Gao YC, Zhou DD, Lu YB, Yang L, Gong XJ, Chen MY, et al. Antitumor potentials of onco-microbial in Chinese patients with pancreatic cancer. Heliyon. (2024) 10:e40890. doi: 10.1016/j.heliyon.2024.e40890
52. May MS, Park H, Moallem DH, Seeram D, Dajiang S, Hibshoosh H, et al. Low bacterial biomass in human pancreatic cancer and adjacent normal tissue. Int J Mol Sci. (2024) 26:140. doi: 10.3390/ijms26010140
53. Van Eijck CWF, Ju J, Van ‘T Land FR, Verheij M, Li Y, Stubbs A, et al. The tumor immune microenvironment in resected treatment-naive pancreatic cancer patients with long-term survival. Pancreatology. (2024) 24:1057–65. doi: 10.1016/j.pan.2024.08.014
54. Fang Y, Liu X, Ren J, Wang X, Zhou F, Huang S, et al. Integrated analysis of microbiome and metabolome reveals signatures in PDAC tumorigenesis and prognosis. Microbiol Spectr. (2024) 12:e00962–24. doi: 10.1128/spectrum.00962-24
55. Guo W, Zhang Y, Guo S, Mei Z, Liao H, Dong H, et al. Tumor microbiome contributes to an aggressive phenotype in the basal-like subtype of pancreatic cancer. Commun Biol. (2021) 4:1019. doi: 10.1038/s42003-021-02557-5
56. Ioannou A, Berkhout MD, Geerlings SY, and Belzer C. Akkermansia muciniphila: biology, microbial ecology, host interactions and therapeutic potential. Nat Rev Microbiol. (2025) 23:162–77. doi: 10.1038/s41579-024-01106-1
57. Kikuchi T, Mimura K, Ashizawa M, Okayama H, Endo E, Saito K, et al. Characterization of tumor-infiltrating immune cells in relation to microbiota in colorectal cancers. Cancer Immunol Immunother. (2020) 69:23–32. doi: 10.1007/s00262-019-02433-6
58. Chu CS, Yang CY, Yeh CC, Lin RT, Chen CC, Bai LY, et al. Endoscopic ultrasound-guided fine-needle biopsy as a tool for studying the intra-tumoral microbiome in pancreatic ductal adenocarcinoma: a pilot study. Sci Rep. (2022) 12:107. doi: 10.1038/s41598-021-04095-w
59. Jiang H, Tian Y, Xu L, Chen X, Huang Y, Wu J, et al. Alterations of the bile microbiome is associated with progression-free survival in pancreatic ductal adenocarcinoma patients. BMC Microbiol. (2024) 24:235. doi: 10.1186/s12866-024-03371-9
60. Fletcher AA, Kelly MS, Eckhoff AM, and Allen PJ. Revisiting the intrinsic mycobiome in pancreatic cancer. Nature. (2023) 620:E1–6. doi: 10.1038/s41586-023-06292-1
61. Xu F, Saxena D, Pushalkar S, and Miller G. Reply to: Revisiting the intrinsic mycobiome in pancreatic cancer. Nature. (2023) 620:E7–9. doi: 10.1038/s41586-023-06293-0
62. Liu S, Rodriguez JS, Munteanu V, Ronkowski C, Sharma NK, Alser M, et al. Analysis of metagenomic data. Nat Rev Methods Primer. (2025) 5:5. doi: 10.1038/s43586-024-00376-6
63. Thomas RM, Gharaibeh RZ, Gauthier J, Beveridge M, Pope JL, Guijarro MV, et al. Intestinal microbiota enhances pancreatic carcinogenesis in preclinical models. Carcinogenesis. (2018) 39:1068–78. doi: 10.1093/carcin/bgy073
64. Sun J, Chen F, and Wu G. Potential effects of gut microbiota on host cancers: focus on immunity, DNA damage, cellular pathways, and anticancer therapy. ISME J. (2023) 17:1535–51. doi: 10.1038/s41396-023-01483-0
65. Corrales L, Matson V, Flood B, Spranger S, and Gajewski TF. Innate immune signaling and regulation in cancer immunotherapy. Cell Res. (2017) 27:96–108. doi: 10.1038/cr.2016.149
66. Han ZY, Fu ZJ, Wang YZ, Zhang C, Chen QW, An JX, et al. Probiotics functionalized with a gallium-polyphenol network modulate the intratumor microbiota and promote anti-tumor immune responses in pancreatic cancer. Nat Commun. (2024) 15:7096. doi: 10.1038/s41467-024-51534-z
67. Alam A, Levanduski E, Denz P, Villavicencio HS, Bhatta M, Alhorebi L, et al. Fungal mycobiome drives IL-33 secretion and type 2 immunity in pancreatic cancer. Cancer Cell. (2022) 40:153–167.e11. doi: 10.1016/j.ccell.2022.01.003
68. Uchida M, Anderson EL, Squillace DL, Patil N, Maniak PJ, Iijima K, et al. Oxidative stress serves as a key checkpoint for IL-33 release by airway epithelium. Allergy. (2017) 72:1521–31. doi: 10.1111/all.13158
69. Taniguchi S, Elhance A, Van Duzer A, Kumar S, Leitenberger JJ, and Oshimori N. Tumor-initiating cells establish an IL-33–TGF-β niche signaling loop to promote cancer progression. Science. (2020) 369:eaay1813. doi: 10.1126/science.aay1813
70. Park JH, Ameri AH, Dempsey KE, Conrad DN, Kem M, Mino-Kenudson M, et al. Nuclear IL-33/SMAD signaling axis promotes cancer development in chronic inflammation. EMBO J. (2021) 40:e106151. doi: 10.15252/embj.2020106151
71. Alonso-Curbelo D, Ho YJ, Burdziak C, Maag JLV, Morris JP, Chandwani R, et al. A gene–environment-induced epigenetic program initiates tumorigenesis. Nature. (2021) 590:642–8. doi: 10.1038/s41586-020-03147-x
72. Moral JA, Leung J, Rojas LA, Ruan J, Zhao J, Sethna Z, et al. ILC2s amplify PD-1 blockade by activating tissue-specific cancer immunity. Nature. (2020) 579:130–5. doi: 10.1038/s41586-020-2015-4
73. Jacouton E, Chain F, Sokol H, Langella P, and Bermúdez-Humarán LG. Probiotic strain lactobacillus casei BL23 prevents colitis-associated colorectal cancer. Front Immunol. (2017) 8:1553. doi: 10.3389/fimmu.2017.01553
74. Hu C, Xu B, Wang X, Wan W, Lu J, Kong D, et al. Gut microbiota–derived short-chain fatty acids regulate group 3 innate lymphoid cells in HCC. Hepatology. (2023) 77:48–64. doi: 10.1002/hep.32449
75. Zhu Z, Yi B, Tang Z, Chen X, Li M, Xu T, et al. Lactobacillus casei combined with Lactobacillus reuteri alleviate pancreatic cancer by inhibiting TLR4 to promote macrophage M1 polarization and regulate gut microbial homeostasis. BMC Cancer. (2023) 23:1044. doi: 10.1186/s12885-023-11557-z
76. Udayasuryan B, Ahmad RN, Nguyen TTD, Umaña A, Monét Roberts L, Sobol P, et al. Fusobacterium nucleatum induces proliferation and migration in pancreatic cancer cells through host autocrine and paracrine signaling. Sci Signal. (2022) 15:eabn4948. doi: 10.1126/scisignal.abn4948
77. Hayashi M, Ikenaga N, Nakata K, Luo H, Zhong P, Date S, et al. Intratumor Fusobacterium nucleatum promotes the progression of pancreatic cancer via the CXCL1-CXCR2 axis. Cancer Sci. (2023) 114:3666–78. doi: 10.1111/cas.15901
78. Ley K, Hoffman HM, Kubes P, Cassatella MA, Zychlinsky A, Hedrick CC, et al. Neutrophils: New insights and open questions. Sci Immunol. (2018) 3:eaat4579. doi: 10.1126/sciimmunol.aat4579
79. Zeng X, Liu H, Huang Z, Dong P, and Chen X. Anticancer effect of arbutin on diethylnitrosamine-induced liver carcinoma in rats via the GRP and GADD pathway. J Environ Pathol Toxicol Oncol. (2022) 41:15–26. doi: 10.1615/JEnvironPatholToxicolOncol.2021039772
80. Safari H, Zabihi E, Pouramir M, Morakabati P, Abedian Z, Karkhah A, et al. Decrease of intracellular ROS by arbutin is associated with apoptosis induction and downregulation of IL-1β and TNF-α in LNCaP; prostate cancer. J Food Biochem. (2020) 44:e13360. doi: 10.1111/jfbc.13360
81. Marcon F, Zuo J, Pearce H, Nicol S, Margielewska-Davies S, Farhat M, et al. NK cells in pancreatic cancer demonstrate impaired cytotoxicity and a regulatory IL-10 phenotype. OncoImmunology. (2020) 9:1845424. doi: 10.1080/2162402X.2020.1845424
82. Lim SA, Kim J, Jeon S, Shin MH, Kwon J, Kim TJ, et al. Defective localization with impaired tumor cytotoxicity contributes to the immune escape of NK cells in pancreatic cancer patients. Front Immunol. (2019) 10:496. doi: 10.3389/fimmu.2019.00496
83. Yu Q, Newsome RC, Beveridge M, Hernandez MC, Gharaibeh RZ, Jobin C, et al. Intestinal microbiota modulates pancreatic carcinogenesis through intratumoral natural killer cells. Gut Microbes. (2022) 14:2112881. doi: 10.1080/19490976.2022.2112881
84. Liang Y, Du M, Li X, Gao J, Li Q, Li H, et al. Upregulation of Lactobacillus spp. in gut microbiota as a novel mechanism for environmental eustress-induced anti-pancreatic cancer effects. Gut Microbes. (2025) 17:2470372. doi: 10.1080/19490976.2025.2470372
85. Evans RA, Diamond MS, Rech AJ, Chao T, Richardson MW, Lin JH, et al. Lack of immunoediting in murine pancreatic cancer reversed with neoantigen. JCI Insight. (2016) 1:e88328. doi: 10.1172/jci.insight.88328
86. Australian Pancreatic Cancer Genome Initiative, Balachandran VP, Łuksza M, Zhao JN, Makarov V, Moral JA, et al. Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer. Nature. (2017) 551:512–6. doi: 10.1038/nature24462
87. Boesch M, Baty F, Rothschild SI, Tamm M, Joerger M, Früh M, et al. Tumour neoantigen mimicry by microbial species in cancer immunotherapy. Br J Cancer. (2021) 125:313–23. doi: 10.1038/s41416-021-01365-2
88. Lin NYT, Fukuoka S, Koyama S, Motooka D, Tourlousse DM, Shigeno Y, et al. Microbiota-driven antitumour immunity mediated by dendritic cell migration. Nature. (2025) 644:1058–68. doi: 10.1038/s41586-025-09249-8
89. Li Y, Chang RB, Stone ML, Delman D, Markowitz K, Xue Y, et al. Multimodal immune phenotyping reveals microbial-T cell interactions that shape pancreatic cancer. Cell Rep Med. (2024) 5:101397. doi: 10.1016/j.xcrm.2024.101397
90. Yang X, Zhang Z, Shen X, Xu J, Weng Y, Wang W, et al. Clostridium butyricum and its metabolite butyrate promote ferroptosis susceptibility in pancreatic ductal adenocarcinoma. Cell Oncol. (2023) 46:1645–58. doi: 10.1007/s13402-023-00831-8
91. Luu M, Riester Z, Baldrich A, Reichardt N, Yuille S, Busetti A, et al. Microbial short-chain fatty acids modulate CD8+ T cell responses and improve adoptive immunotherapy for cancer. Nat Commun. (2021) 12:4077. doi: 10.1038/s41467-021-24331-1
92. Panebianco C, Villani A, Pisati F, Orsenigo F, Ulaszewska M, Latiano TP, et al. Butyrate, a postbiotic of intestinal bacteria, affects pancreatic cancer and gemcitabine response in in vitro and in vivo models. BioMed Pharmacother. (2022) 151:113163. doi: 10.1016/j.biopha.2022.113163
93. León-Letelier RA, Chen Y, Dou R, Irajizad E, Yip-Schneider MT, Wu R, et al. Integrated metabolomics and spatial transcriptomics of cystic pancreatic cancer precursors reveals dysregulated polyamine metabolism as a biomarker of progression. Clin Cancer Res. (2025) 31:2454–65. doi: 10.1158/1078-0432.CCR-24-2931
94. Mendez R, Kesh K, Arora N, Di Martino L, McAllister F, Merchant N, et al. Microbial dysbiosis and polyamine metabolism as predictive markers for early detection of pancreatic cancer. Carcinogenesis. (2020) 41:561–70. doi: 10.1093/carcin/bgz116
95. Lee MS, Dennis C, Naqvi I, Dailey L, Lorzadeh A, Ye G, et al. Ornithine aminotransferase supports polyamine synthesis in pancreatic cancer. Nature. (2023) 616:339–47. doi: 10.1038/s41586-023-05891-2
96. Canale FP, Basso C, Antonini G, Perotti M, Li N, Sokolovska A, et al. Metabolic modulation of tumours with engineered bacteria for immunotherapy. Nature. (2021) 598:662–6. doi: 10.1038/s41586-021-04003-2
97. Feng HY and Chen YC. Role of bile acids in carcinogenesis of pancreatic cancer: An old topic with new perspective. World J Gastroenterol. (2016) 22:7463. doi: 10.3748/wjg.v22.i33.7463
98. Joshi S, Cruz E, Rachagani S, Guha S, Brand RE, Ponnusamy MP, et al. Bile acids-mediated overexpression of MUC4 via FAK-dependent c-Jun activation in pancreatic cancer. Mol Oncol. (2016) 10:1063–77. doi: 10.1016/j.molonc.2016.04.007
99. Zhu S, Yang K, Yang S, Zhang L, Xiong M, Zhang J, et al. A high bile acid environment promotes apoptosis and inhibits migration in pancreatic cancer. Bioengineered. (2022) 13:6719–28. doi: 10.1080/21655979.2022.2045823
100. Collins SL, Stine JG, Bisanz JE, Okafor CD, and Patterson AD. Bile acids and the gut microbiota: metabolic interactions and impacts on disease. Nat Rev Microbiol. (2023) 21:236–47. doi: 10.1038/s41579-022-00805-x
101. Winston JA and Theriot CM. Diversification of host bile acids by members of the gut microbiota. Gut Microbes. (2020) 11:158–71. doi: 10.1080/19490976.2019.1674124
102. Gál E, Veréb Z, Kemény L, Rakk D, Szekeres A, Becskeházi E, et al. Bile accelerates carcinogenic processes in pancreatic ductal adenocarcinoma cells through the overexpression of MUC4. Sci Rep. (2020) 10:22088. doi: 10.1038/s41598-020-79181-6
103. Tucker ON. Bile acids induce cyclooxygenase-2 expression in human pancreatic cancer cell lines. Carcinogenesis. (2003) 25:419–23. doi: 10.1093/carcin/bgh010
104. Schwarcz S, Kovács P, Kovács T, Ujlaki G, Nyerges P, Uray K, et al. The pro- and antineoplastic effects of deoxycholic acid in pancreatic adenocarcinoma cell models. Mol Biol Rep. (2023) 50:5273–82. doi: 10.1007/s11033-023-08453-x
105. Kim Y, Jeong S, Kim EK, Kim E, and Cho J. Ursodeoxycholic acid suppresses epithelial-mesenchymal transition and cancer stem cell formation by reducing the levels of peroxiredoxin II and reactive oxygen species in pancreatic cancer cells. Oncol Rep. (2017) 38:3632–3638. doi: 10.3892/or.2017.6045
106. Režen T, Rozman D, Kovács T, Kovács P, Sipos A, Bai P, et al. The role of bile acids in carcinogenesis. Cell Mol Life Sci. (2022) 79:243. doi: 10.1007/s00018-022-04278-2
107. Hezaveh K, Shinde RS, Klötgen A, Halaby MJ, Lamorte S, Ciudad MT, et al. Tryptophan-derived microbial metabolites activate the aryl hydrocarbon receptor in tumor-associated macrophages to suppress anti-tumor immunity. Immunity. (2022) 55:324–340.e8. doi: 10.1016/j.immuni.2022.01.006
108. Tintelnot J, Xu Y, Lesker TR, Schönlein M, Konczalla L, Giannou AD, et al. Microbiota-derived 3-IAA influences chemotherapy efficacy in pancreatic cancer. Nature. (2023) 615:168–74. doi: 10.1038/s41586-023-05728-y
109. Mirji G, Worth A, Bhat SA, El Sayed M, Kannan T, Goldman AR, et al. The microbiome-derived metabolite TMAO drives immune activation and boosts responses to immune checkpoint blockade in pancreatic cancer. Sci Immunol. (2022) 7:eabn0704. doi: 10.1126/sciimmunol.abn0704
110. Cho CE and Caudill MA. Trimethylamine- N -oxide: friend, foe, or simply caught in the cross-fire? Trends Endocrinol Metab. (2017) 28:121–30. doi: 10.1016/j.tem.2016.10.005
111. Brahmer JR, Tykodi SS, Chow LQM, Hwu WJ, Topalian SL, Hwu P, et al. Safety and activity of anti–PD-L1 antibody in patients with advanced cancer. N Engl J Med. (2012) 366:2455–65. doi: 10.1056/NEJMoa1200694
112. Patnaik A, Kang SP, Rasco D, Papadopoulos KP, Elassaiss-Schaap J, Beeram M, et al. Phase I study of pembrolizumab (MK-3475; anti–PD-1 monoclonal antibody) in patients with advanced solid tumors. Clin Cancer Res. (2015) 21:4286–93. doi: 10.1158/1078-0432.CCR-14-2607
113. Du J, Lu C, Mao L, Zhu Y, Kong W, Shen S, et al. PD-1 blockade plus chemoradiotherapy as preoperative therapy for patients with BRPC/LAPC: A biomolecular exploratory, phase II trial. Cell Rep Med. (2023) 4:100972. doi: 10.1016/j.xcrm.2023.100972
114. Liu R, Yang H, Qu S, Yang P, Zhi X, Xu Y, et al. Photodynamic eradication of intratumoral microbiota with bacteria-targeted micelles overcomes gemcitabine resistance of pancreatic cancer. Aggregate. (2024) 5:e423. doi: 10.1002/agt2.423
115. Han ZY, Chen QW, Fu ZJ, Cheng SX, and Zhang XZ. Probiotic spore-based oral drug delivery system for enhancing pancreatic cancer chemotherapy by gut–pancreas-axis-guided delivery. Nano Lett. (2022) 22:8608–17. doi: 10.1021/acs.nanolett.2c03131
116. Chen SM, Chieng WW, Huang SW, Hsu LJ, and Jan MS. The synergistic tumor growth-inhibitory effect of probiotic Lactobacillus on transgenic mouse model of pancreatic cancer treated with gemcitabine. Sci Rep. (2020) 10:20319. doi: 10.1038/s41598-020-77322-5
117. Panebianco C, Pisati F, Ulaszewska M, Andolfo A, Villani A, Federici F, et al. Tuning gut microbiota through a probiotic blend in gemcitabine-treated pancreatic cancer xenografted mice. Clin Transl Med. (2021) 11:e580. doi: 10.1002/ctm2.580
118. Xiao YL, Gong Y, Qi YJ, Shao ZM, and Jiang YZ. Effects of dietary intervention on human diseases: molecular mechanisms and therapeutic potential. Signal Transduct Target Ther. (2024) 9:59. doi: 10.1038/s41392-024-01771-x
119. D’Aronzo M, Vinciguerra M, Mazza T, Panebianco C, Saracino C, Pereira SP, et al. Fasting cycles potentiate the efficacy of gemcitabine treatment in in vitro and in vivo pancreatic cancer models. Oncotarget. (2015) 6:18545–57. doi: 10.18632/oncotarget.4186
120. Yang L, TeSlaa T, Ng S, Nofal M, Wang L, Lan T, et al. Ketogenic diet and chemotherapy combine to disrupt pancreatic cancer metabolism and growth. Med. (2022) 3:119–136.e8. doi: 10.1016/j.medj.2021.12.008
121. Malesza IJ, Malesza M, Walkowiak J, Mussin N, Walkowiak D, Aringazina R, et al. High-fat, western-style diet, systemic inflammation, and gut microbiota: A narrative review. Cells. (2021) 10:3164. doi: 10.3390/cells10113164
122. Kok CR, Rose D, and Hutkins R. Predicting personalized responses to dietary fiber interventions: opportunities for modulation of the gut microbiome to improve health. Annu Rev Food Sci Technol. (2023) 14:157–82. doi: 10.1146/annurev-food-060721-015516
123. Panebianco C, Adamberg K, Adamberg S, Saracino C, Jaagura M, Kolk K, et al. Engineered resistant-starch (ERS) diet shapes colon microbiota profile in parallel with the retardation of tumor growth in in vitro and in vivo pancreatic cancer models. Nutrients. (2017) 9:331. doi: 10.3390/nu9040331
124. Pan P, Zhu Z, Oshima K, Aldakkak M, Tsai S, Huang Y, et al. Black raspberries suppress pancreatic cancer through modulation of NKp46+, CD8+, and CD11b+ immune cells. Food Front. (2020) 1:70–82. doi: 10.1002/fft2.1
125. Ting NLN, Lau HCH, and Yu J. Cancer pharmacomicrobiomics: targeting microbiota to optimise cancer therapy outcomes. Gut. (2022) 71:1412–25. doi: 10.1136/gutjnl-2021-326264
126. Chen D, Wu J, Jin D, Wang B, and Cao H. Fecal microbiota transplantation in cancer management: Current status and perspectives. Int J Cancer. (2019) 145:2021–31. doi: 10.1002/ijc.32003
127. Baruch EN, Youngster I, Ben-Betzalel G, Ortenberg R, Lahat A, Katz L, et al. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science. (2021) 371:602–9. doi: 10.1126/science.abb5920
128. 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. doi: 10.1016/j.eclinm.2023.102315
129. 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) 32:1380–1393.e9. doi: 10.1016/j.chom.2024.06.010
130. Zhao L, Peng S, Ge M, Xing B, Zhao X, Yang T, et al. Gut-to-tumor translocation of multidrug-resistant Klebsiella pneumoniae shapes the microbiome and chemoresistance in pancreatic cancer. Front Cell Infect Microbiol. (2025) 15:1694479. doi: 10.3389/fcimb.2025.1694479
131. Cheng K, Li X, Lv W, Zhao G, Zhou R, Chang C, et al. Spatial interactions of immune cells as potential predictors to efficacy of toripalimab plus chemotherapy in locally advanced or metastatic pancreatic ductal adenocarcinoma: a phase Ib/II trial. Signal Transduct Target Ther. (2024) 9:321. doi: 10.1038/s41392-024-02031-8
132. Jia R, Si HY, Fan MJ, Zhang N, Deng GC, Liu FF, et al. First-line treatment with chemotherapy, surufatinib (an angio-immuno kinase inhibitor), and camrelizumab (an anti-PD-1 antibody) for locally advanced or metastatic pancreatic ductal adenocarcinoma: a phase Ib/II randomized study. Signal Transduct Target Ther. (2025) 10:339. doi: 10.1038/s41392-025-02441-2
133. Ahmed J, Kumar A, Parikh K, Anwar A, Knoll BM, Puccio C, et al. Use of broad-spectrum antibiotics impacts outcome in patients treated with immune checkpoint inhibitors. OncoImmunology. (2018) 7:e1507670. doi: 10.1080/2162402X.2018.1507670
134. 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. doi: 10.1126/science.aan3706
135. Kim H, Lee JE, Hong SH, Lee M, Kang JH, and Kim IH. The effect of antibiotics on the clinical outcomes of patients with solid cancers undergoing immune checkpoint inhibitor treatment: a retrospective study. BMC Cancer. (2019) 19:1100. doi: 10.1186/s12885-019-6267-z
136. Popescu M, Van Belleghem JD, Khosravi A, and Bollyky PL. Bacteriophages and the immune system. Annu Rev Virol. (2021) 8:415–35. doi: 10.1146/annurev-virology-091919-074551
137. Schooley RT, Biswas B, Gill JJ, Hernandez-Morales A, Lancaster J, Lessor L, et al. Development and use of personalized bacteriophage-based therapeutic cocktails to treat a patient with a disseminated resistant acinetobacter baumannii infection. Antimicrob Agents Chemother. (2017) 61:e00954–17. doi: 10.1128/AAC.00954-17
138. Kelly KA, Bardeesy N, Anbazhagan R, Gurumurthy S, Berger J, Alencar H, et al. Targeted nanoparticles for imaging incipient pancreatic ductal adenocarcinoma. PloS Med. (2008) 5:e85. doi: 10.1371/journal.pmed.0050085
139. Yue H, Li Y, Yang T, Wang Y, Bao Q, Xu Y, et al. Filamentous phages as tumour-targeting immunotherapeutic bionanofibres. Nat Nanotechnol. (2025) 20:167–76. doi: 10.1038/s41565-024-01800-4
140. Hill C, Guarner F, Reid G, Gibson GR, Merenstein DJ, Pot B, et al. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic. Nat Rev Gastroenterol Hepatol. (2014) 11:506–14. doi: 10.1038/nrgastro.2014.66
141. 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. doi: 10.1126/science.aac4255
142. Gopalakrishnan V, Spencer CN, Nezi L, Reuben A, Andrews MC, Karpinets TV, et al. Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients. Science. (2018) 359:97–103. doi: 10.1126/science.aan4236
143. Kaur K, Kozlowska AK, Topchyan P, Ko MW, Ohanian N, Chiang J, et al. Probiotic-treated super-charged NK cells efficiently clear poorly differentiated pancreatic tumors in hu-BLT mice. Cancers. (2019) 12:63. doi: 10.3390/cancers12010063
144. Konishi H, Isozaki S, Kashima S, Moriichi K, Ichikawa S, Yamamoto K, et al. Probiotic Aspergillus oryzae produces anti-tumor mediator and exerts anti-tumor effects in pancreatic cancer through the p38 MAPK signaling pathway. Sci Rep. (2021) 11:11070. doi: 10.1038/s41598-021-90707-4
145. Kita A, Fujiya M, Konishi H, Tanaka H, Kashima S, Iwama T, et al. Probiotic−derived ferrichrome inhibits the growth of refractory pancreatic cancer cells. Int J Oncol. (2020) 57:721–32. doi: 10.3892/ijo.2020.5096
146. Chaib M, Hafeez BB, Mandil H, Daria D, Pingili AK, Kumari S, et al. Reprogramming of pancreatic adenocarcinoma immunosurveillance by a microbial probiotic siderophore. Commun Biol. (2022) 5:1181. doi: 10.1038/s42003-022-04102-4
147. Jing Y and Yan D. Modulation of gut microbiota and immune response by soy peptides mitigates irinotecan induced intestinal toxicity. Front Physiol. (2025) 16:1538733. doi: 10.3389/fphys.2025.1538733
148. Maher S, Elmeligy HA, Aboushousha T, Helal NS, Ossama Y, Rady M, et al. Synergistic immunomodulatory effect of synbiotics pre- and postoperative resection of pancreatic ductal adenocarcinoma: a randomized controlled study. Cancer Immunol Immunother. (2024) 73:109. doi: 10.1007/s00262-024-03686-6
149. Yelin I, Flett KB, Merakou C, Mehrotra P, Stam J, Snesrud E, et al. Genomic and epidemiological evidence of bacterial transmission from probiotic capsule to blood in ICU patients. Nat Med. (2019) 25:1728–32. doi: 10.1038/s41591-019-0626-9
150. Merenstein D, Pot B, Leyer G, Ouwehand AC, Preidis GA, Elkins CA, et al. Emerging issues in probiotic safety: 2023 perspectives. Gut Microbes. (2023) 15:2185034. doi: 10.1080/19490976.2023.2185034
151. Li Z, Mo F, Guo K, Ren S, Wang Y, Chen Y, et al. Nanodrug-bacteria conjugates-mediated oncogenic collagen depletion enhances immune checkpoint blockade therapy against pancreatic cancer. Med. (2024) 5:348–367.e7. doi: 10.1016/j.medj.2024.02.012
152. Zhang H, Wang Y, Zhu L, Qi Z, Cao K, Chang J, et al. A “bulldozer” driven by anoxic bacteria for pancreatic cancer chemo-immunotherapy. J Controlled Release. (2023) 360:660–71. doi: 10.1016/j.jconrel.2023.07.014
153. Yao W, Song W, Deng X, Lin Y, Meng R, Wang J, et al. Harnessing the engineered probiotic-nanosystem to remodulate tumor extracellular matrix and regulate tumor-colonizing bacteria for improving pancreatic cancer chemo-immunotherapy. Small. (2025) 21:2406837. doi: 10.1002/smll.202406837
154. Xiao Y, Pan T, Da W, Liu Y, Chen S, Chen D, et al. Aptamer-drug conjugates-loaded bacteria for pancreatic cancer synergistic therapy. Signal Transduct Target Ther. (2024) 9:272. doi: 10.1038/s41392-024-01973-3
155. Li Y, Ma A, Johnson E, Eng C, De S, Jiang S, et al. The new microbiome on the block: challenges and opportunities of using human tumor sequencing data to study microbes. Nat Methods. (2025) 22:1788–99. doi: 10.1038/s41592-025-02807-y
156. Gihawi A, Ge Y, Lu J, Puiu D, Xu A, Cooper CS, et al. Major data analysis errors invalidate cancer microbiome findings. mBio. (2023) 14:e01607–23. doi: 10.1128/mbio.01607-23
157. Fierer N, Leung PM, Lappan R, Eisenhofer R, Ricci F, Holland SI, et al. Guidelines for preventing and reporting contamination in low-biomass microbiome studies. Nat Microbiol. (2025) 10:1570–80. doi: 10.1038/s41564-025-02035-2
158. Ren Z, Jiang J, Xie H, Li A, Lu H, Xu S, et al. Gut microbial profile analysis by MiSeq sequencing of pancreatic carcinoma patients in China. Oncotarget. (2017) 8:95176–91. doi: 10.18632/oncotarget.18820
159. Lin XB, Dieleman LA, Ketabi A, Bibova I, Sawyer MB, Xue H, et al. Irinotecan (CPT-11) chemotherapy alters intestinal microbiota in tumour bearing rats. PloS One. (2012) 7:e39764. doi: 10.1371/journal.pone.0039764
160. Montassier E, Gastinne T, Vangay P, Al-Ghalith GA, Bruley Des Varannes S, Massart S, et al. Chemotherapy-driven dysbiosis in the intestinal microbiome. Aliment Pharmacol Ther. (2015) 42:515–28. doi: 10.1111/apt.13302
161. Garrido-Laguna I, Uson M, Rajeshkumar NV, Tan AC, De Oliveira E, Karikari C, et al. Tumor engraftment in nude mice and enrichment in stroma- related gene pathways predict poor survival and resistance to gemcitabine in patients with pancreatic cancer. Clin Cancer Res. (2011) 17:5793–800. doi: 10.1158/1078-0432.CCR-11-0341
162. Pantazopoulou V, Kubota CS, Ogawa S, Gulay KCM, Lin X, Song H, et al. Experimental models of pancreas cancer: what has been the impact for precision medicine? J Clin Invest. (2025) 135:e191945. doi: 10.1172/JCI191945
163. Ely ZA, Kulstad ZJ, Gunaydin G, Addepalli S, Verzani EK, Casarrubios M, et al. Pancreatic cancer–restricted cryptic antigens are targets for T cell recognition. Science. (2025) 388:eadk3487. doi: 10.1126/science.adk3487
164. Gayibov E, Sychra T, Spálenková A, Souček P, and Oliverius M. The use of patient-derived xenografts and patient-derived organoids in the search for new therapeutic regimens for pancreatic carcinoma. A review. BioMed Pharmacother. (2025) 182:117750. doi: 10.1016/j.biopha.2024.117750
165. Van Prehn J, Reigadas E, Vogelzang EH, Bouza E, Hristea A, Guery B, et al. European Society of Clinical Microbiology and Infectious Diseases: 2021 update on the treatment guidance document for Clostridioides difficile infection in adults. Clin Microbiol Infect. (2021) 27:S1–21. doi: 10.1016/j.cmi.2021.09.038
166. Porcari S, Ng SC, Zitvogel L, Sokol H, Weersma RK, Elinav E, et al. The microbiome for clinicians. Cell. (2025) 188:2836–44. doi: 10.1016/j.cell.2025.04.016
167. Cammarota G, Ianiro G, Kelly CR, Mullish BH, Allegretti JR, Kassam Z, et al. International consensus conference on stool banking for faecal microbiota transplantation in clinical practice. Gut. (2019) 68:2111–21. doi: 10.1136/gutjnl-2019-319548
168. Porcari S, Fusco W, Spivak I, Fiorani M, Gasbarrini A, Elinav E, et al. Fine-tuning the gut ecosystem: the current landscape and outlook of artificial microbiome therapeutics. Lancet Gastroenterol Hepatol. (2024) 9:460–75. doi: 10.1016/S2468-1253(23)00357-6
169. Luo Z, Qi Z, Luo J, and Chen T. Potential applications of engineered bacteria in disease diagnosis and treatment. Microbiome Res Rep. (2024) 4:10. doi: 10.20517/mrr.2024.57
170. Chemla Y, Sweeney CJ, Wozniak CA, and Voigt CA. Design and regulation of engineered bacteria for environmental release. Nat Microbiol. (2025) 10:281–300. doi: 10.1038/s41564-024-01918-0
Keywords: gut microbiota, gut-pancreatic axis, immunotherapy, pancreatic ductal adenocarcinoma, tumor microenvironment
Citation: Yuan YR, Zhang W and Wang D (2026) Targeting the gut-pancreatic axis: microbial modulation of immunotherapy in pancreatic cancer. Front. Immunol. 17:1682390. doi: 10.3389/fimmu.2026.1682390
Received: 08 August 2025; Accepted: 19 January 2026; Revised: 13 January 2026;
Published: 02 February 2026.
Edited by:
Bharathi Muruganantham, Karpagam Academy of Higher Education, IndiaReviewed by:
Ayca Sayi Yazgan, Istanbul Technical University, TürkiyeTheodoros Sidiropoulos, National and Kapodistrian University of Athens, Greece
Copyright © 2026 Yuan, Zhang and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Wei Zhang, enc4ODM5MjAwQDE2My5jb20=; Deqiang Wang, ZGVxaWFuZ193YW5nQGFsaXl1bi5jb20=