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Review

Optimizing Cancer Treatment Through Gut Microbiome Modulation

1
College of Medicine, Ewha Womans University, 25 Magokdong-ro 2-gil, Gangseo-gu, Seoul 03760, Republic of Korea
2
College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea
3
Department of Hospital Pathology, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 10, 63-ro, Yeongdeungpo-gu, Seoul 07345, Republic of Korea
*
Author to whom correspondence should be addressed.
Cancers 2025, 17(7), 1252; https://doi.org/10.3390/cancers17071252
Submission received: 2 March 2025 / Revised: 30 March 2025 / Accepted: 5 April 2025 / Published: 7 April 2025
(This article belongs to the Special Issue Human Microbiome, Diet and Cancerogenesis)

Simple Summary

This review summarizes the impact of the gut microbiome on cancer treatment outcomes across three therapeutic approaches: immune checkpoint inhibitors, cytotoxic chemotherapy, and microbial interventions, including probiotics and fecal microbiota transplantation. We focus on five major cancer types—gastrointestinal cancer, lung cancer, liver cancer, breast cancer, and metastatic melanoma—to illustrate cancer type-specific microbiome associations. Particular emphasis is placed on microbial taxa and functional pathways that consistently influence treatment efficacy or toxicity across specific cancer types. By organizing preclinical and clinical evidence by therapy type and cancer type, this review offers a structured summary of current microbiome–cancer therapy interactions for researchers and clinicians.

Abstract

The gut microbiome plays a pivotal role in modulating cancer therapies, including immunotherapy and chemotherapy. Emerging evidence demonstrates its influence on treatment efficacy, immune response, and resistance mechanisms. Specific microbial taxa enhance immune checkpoint inhibitor efficacy, while dysbiosis can contribute to adverse outcomes. Chemotherapy effectiveness is also influenced by microbiome composition, with engineered probiotics and prebiotics offering promising strategies to enhance drug delivery and reduce toxicity. Moreover, microbial metabolites, such as short-chain fatty acids, and engineered microbial systems have shown potential to improve therapeutic responses. These findings underscore the importance of personalized microbiome-based approaches in optimizing cancer treatments.

1. Introduction

The microbiome has emerged as a critical determinant in cancer therapeutics, influencing responsiveness to both immunotherapy and chemotherapy. Intestinal microbial communities modulate immune responses and drug metabolism, directly impacting treatment efficacy and toxicity. While specific bacterial taxa enhance immune checkpoint inhibitor (ICI) activity, microbial dysbiosis can induce treatment resistance and adverse effects.
In chemotherapy, microbial enzymes activate or deactivate antineoplastic agents, altering therapeutic outcomes. Microbially derived metabolites, particularly short-chain fatty acids (SCFAs) and tryptophan-derived compounds, further regulate immune responses that affect treatment efficacy. Additionally, the microbiome plays a crucial role in drug metabolism, contributing to chemotherapy resistance and modulating drug toxicity.
Current research highlights microbiome modulation strategies in oncology, including fecal microbiota transplantation (FMT), probiotics, prebiotics, and postbiotics. These approaches, implemented alongside conventional treatments, show promise for enhancing therapeutic responses while reducing adverse effects.
As illustrated in Figure 1, the microbiome influences cancer therapy through three primary mechanisms: immune modulation, drug metabolism, and microbial metabolite production. It contributes to immune regulation by promoting T-cell activation, modulating ICI responses, and reducing immunosuppressive cells. Additionally, microbial communities influence chemotherapy efficacy by modulating drug activation, resistance mechanisms, and toxicity. Furthermore, microbial metabolites such as SCFAs and tryptophan-derived compounds play a key role in shaping the tumor microenvironment and immune response.
This manuscript analyzes the mechanisms underlying microbiome influence on cancer treatments across gastrointestinal, pulmonary, hepatocellular, breast, and metastatic melanoma malignancies. We evaluate current microbiome-based adjunctive therapies and their clinical applications, exploring the future development of microbiome-targeted interventions in oncological practice.

2. Enhancing Immunotherapy Through Microbiome Modulation

The gut microbiome exerts a critical influence on metabolic and immunological pathways that is essential for maintaining host equilibrium [1]. Beyond supporting immune homeostasis, it substantially impacts both localized and systemic antitumor immune responses [2]. This relationship is particularly pronounced in gastrointestinal (GI) cancers, where microbial dysbiosis—characterized by an imbalance in microbial populations—has been implicated in reduced therapeutic efficacy and adverse clinical outcomes [3].
Recent advances have highlighted distinct mechanisms by which the gut microbiota modulates immunotherapy. These include immune checkpoint regulation, tumor microenvironment remodeling, and the attenuation of therapy-associated adverse effects, as illustrated in Figure 2 [4,5,6]. Notably, several ongoing clinical trials are evaluating microbiome-based interventions to enhance immunotherapy efficacy, as summarized in Table 1. Specific microbial taxa, such as Akkermansia muciniphila and Faecalibacterium prausnitzii, have been identified as key contributors to enhancing the efficacy of immune checkpoint inhibitors (ICIs) [7,8,9]. Moreover, microbiota-derived metabolites, including short-chain fatty acids (SCFAs), play central roles in reducing inflammation, fostering T-cell infiltration, and reprogramming tumor-associated metabolic pathways [10]. Conversely, disruptions to the microbiome, often marked by the depletion of beneficial bacteria or overrepresentation of proinflammatory species, have been linked to suboptimal immunotherapy outcomes and increased susceptibility to immune-related adverse events (irAEs) [11].
Advances in microbiome research have opened new avenues for optimizing immunotherapy by both enhancing its therapeutic efficacy and mitigating associated toxicities. Figure 2 provides an overview of these mechanisms, underscoring the role of the microbiome in fine-tuning immune checkpoint pathways, reconfiguring the tumor microenvironment, and strengthening gut barrier function through the production of SCFAs. The following sections will delve deeper into these aspects, focusing on specific cancer contexts, including gastrointestinal, lung, liver, and breast cancers, as well as metastatic melanoma.

2.1. Gastrointestinal Cancer

Microorganisms inhabit various anatomical sites, with over 90% residing in the gastrointestinal (GI) tract [12]. The gut microbiota undergoes significant alterations in colorectal cancer (CRC), including reduced alpha diversity and disruption of microbial community structure [13]. Similar patterns of dysbiosis have been reported across GI malignancies. These shifts have been linked to variations in response to the immune checkpoint inhibitor (ICI), particularly anti–PD-1/PD-L1 agents [14].
Short-chain fatty acids (SCFAs), particularly butyrate, contribute to antitumor immunity by enhancing T cell cytotoxicity [15]. Enhanced anti-PD-1 efficacy has been observed in murine CRC models colonized with butyrate-producing taxa such as Roseburia intestinalis. This effect appears to be driven by increased intratumoral CD8+ T cell infiltration, resulting in reduced tumor burden [16]. Notably, in the MSS CT26 model, butyrate directly binds to TLR5 (KD = 264 μM), triggering NF-κB activation in cytotoxic T cells.
While these findings underscore the immunostimulatory potential of SCFAs, recent studies have revealed that their effects are not universally beneficial. In certain microbial and host contexts, SCFAs may instead promote tumor progression. For example, in CRC models colonized by Fusobacterium nucleatum, butyrate activates FFAR2, leading to Th17 cell expansion and IL-17-driven inflammation—an axis associated with tumor-promoting immune remodeling [17]. Similarly, in APCMin/+MSH2−/− mice, butyrate enhances β-catenin signaling and drives epithelial transformation, highlighting that microbial metabolites may exert tumorigenic effects in genetically susceptible hosts [17]. This functional divergence is further reflected in population-level associations. In a case–control study, elevated plasma levels of acetic and propionic acid were positively associated with CRC occurrence (adjusted OR = 1.02 and 1.29; q = 0.007 and 0.03, respectively), whereas valeric and i-valeric acids showed inverse trends [18].
In addition to SCFAs, other microbial metabolites also contribute to immunomodulation. Inosine produced by B. pseudolongum enhances Th1 activation via the A2A receptor in murine CRC models, with its effect contingent on T cell costimulation, ultimately improving ICI efficacy [19].
Microbial structural components such as lipopolysaccharide (LPS) also exhibit strain-specific immune effects. LPS from Fusobacterium periodonticum (6 ng/mL) increased IL-1 β , IL-6, and IFN- γ production in PBMCs, while LPS from Bacteroides fragilis and Porphyromonas asaccharolytica (600 ng/mL) suppressed cytokine levels (Cohen’s d > 0.8; p < 0.05) [20]. These divergent effects reflect differences in the immune contexture of CRC subtypes: CMS1 tumors are enriched with immunostimulatory bacteria, whereas CMS4 tumors are associated with immunosuppressive taxa.
Beyond CRC, similar microbiome-mediated modulation of ICI efficacy has been observed in other GI malignancies. In pancreatic cancer models, trimethylamine N-oxide (TMAO) improved anti-PD-1 response through enhanced immune activation [21]. In gastric cancer, a metagenomic study of patients with HER2-negative advanced disease receiving immunotherapy or combination treatment found that responders exhibited significantly higher relative abundance of Lactobacillus, particularly L. salivarius and L. mucosae, alongside increased microbial diversity. The abundance of these taxa correlated positively with PFS in both discovery and validation cohorts [22].
Taken together, microbial diversity, compositional features, and immunomodulatory metabolites collectively shape host responsiveness to ICI activity across gastrointestinal cancers.

2.2. Lung Cancer

In lung cancer, both gut and lung microbiota are increasingly recognized as modulators of immunotherapy outcomes [4,23]. The lung microbiota, in particular, is a key determinant of local immune responses, with dysbiosis being implicated in tumor progression and diminished therapeutic efficacy [23].
In advanced NSCLC patients receiving anti-PD-1 therapy ( n = 37 ), higher gut microbiota diversity has been associated with improved progression-free survival and favorable immunotherapy outcomes (median PFS: 209 vs. 52 days, p = 0.005) [24]. Responders were characterized by an enrichment of bacterial taxa such as Alistipes putredinis, Bifidobacterium longum, and Prevotella copri, which were present at baseline and further enriched during therapy [24].
Microbial imbalance may impair ICI responsiveness in lung cancer, mirroring observations in GI malignancies [11]. In contrast to GI tumors, where microbial modulation of the tumor immune microenvironment occurs locally via mucosal immune signaling [25], lung tumors are influenced primarily through systemic immune effects mediated by the gut–lung axis [23]. Ongoing clinical trials are exploring whether microbiome-modulating strategies, such as probiotic supplementation, can enhance ICI responsiveness in lung cancer patients (Table 1).
Several gut-derived taxa have been associated with favorable immunotherapy outcomes in NSCLC. These include members of the Clostridia class, Bifidobacterium longum, Lactobacillus, and Phascolarctobacterium, which have been linked to improved survival metrics such as progression-free survival and time to treatment failure [26,27,28]. However, it remains unclear whether these taxa preexisted or were enriched during therapy.
In line with these findings, SCFA-producing bacteria such as Agathobaculum butyriciproducens have also been linked to improved responses in KRAS-mutant NSCLC, possibly through enhanced inflammatory signaling [29].
Lung microbiota composition, including the enrichment of oral commensals such as Veillonella, Prevotella, and Streptococcus, has been associated with chronic inflammation and immune evasion [23,30]. These taxa, several of which are known oral commensals, may impair cytotoxic cell function and activate protumor signaling pathways [31]. Tobacco exposure, a major environmental modifier of the lung microbiota, promotes dysbiosis characterized by the expansion of taxa such as Odoribacter, Alistipes, and Ruminococcus, as well as the depletion of SCFA-producing species like Akkermansia [32]. Evidence from COPD cohorts—though derived from non-malignant populations—suggests that similar microbial shifts, including increased Streptococcus and Haemophilus, may recapitulate immune-modulatory patterns relevant to lung cancer [33].
Altogether, findings from both gut- and lung-focused studies point to a multifaceted role of the microbiota in shaping immunotherapeutic outcomes in lung cancer. Through systemic signaling pathways originating in the gut and local immune modulation within the lung, microbial communities help shape the tumor microenvironment and are increasingly recognized as promising targets for therapeutic modulation.

2.3. Liver Cancer

The interactions between microbial composition, bile acid metabolism, and the immune microenvironment are critical in hepatocellular carcinoma (HCC) pathogenesis, particularly in non-alcoholic fatty liver disease (NAFLD) [34]. The liver, connected to the gut via portal circulation, is influenced by alterations in the gut microbiota that impact immune responses and disease progression. These microbial changes modulate ICI efficacy, potentially improving treatment outcomes.
NAFLD-associated HCC is distinguished from its viral counterpart by its distinct metabolic and immunological characteristics. Chronic inflammation driven by obesity and diabetes fosters an immunosuppressive environment, which may undermine the efficacy of ICI therapy [35]. Moreover, NAFLD-associated HCC exhibits unique immune evasion mechanisms that differ from viral HCC, necessitating tailored therapeutic approaches. Although ICI therapy has demonstrated therapeutic potential, NAFLD-associated immunosuppression remains a significant barrier, necessitating further investigation into its underlying mechanisms.
Dysbiosis, frequently observed in NAFLD, increases intestinal permeability, allowing microbial products such as LPSs to translocate into the portal circulation. This promotes chronic hepatic inflammation and fibrosis, which are key contributors to HCC progression [35,36]. Additionally, alterations in bile acid metabolism influence immune homeostasis, further contributing to an immunosuppressive tumor microenvironment.
Recent therapeutic strategies aim to restore microbial balance and modulate bile acid metabolism. FXR agonists, engineered probiotics, and dietary modifications are under investigation for their potential to enhance ICI response [36]. Several clinical trials are evaluating microbiome-based interventions in HCC. For example, NCT06551272 is investigating the use of Faecalibacterium prausnitzii-derived EXL01 in combination with atezolizumab and bevacizumab (Table 1). Similarly, NCT05620004 is examining whether Bifidobacterium bifidum can enhance the effects of carrilizumab and apatinib mesylate in advanced HCC patients (Table 1).
Despite these promising developments, substantial challenges persist. The heterogeneity of NAFLD-associated HCC, coupled with the complex interplay between gut microbiota and bile acid metabolism, requires comprehensive and longitudinal studies to identify actionable targets. Tailored therapeutic strategies that address metabolic comorbidities and microbiota diversity are critical for advancing clinical outcomes in this patient population.

2.4. Breast Cancer

Breast cancer is generally classified as an immune-cold tumor characterized by low immune cell infiltration and an immunosuppressive microenvironment, which limits responsiveness to ICIs [37]. Unlike immunogenic tumors that attract effector T cells, breast cancer exhibits poor immune infiltration driven by active immunosuppressive mechanisms in the TME [37]. These mechanisms include TGF- β signaling, tumor-associated macrophages (TAMs), regulatory T cells (Tregs), and myeloid-derived suppressor cells (MDSCs), which collectively inhibit antitumor immune responses and reduce the efficacy of ICIs.
The gut microbiota profoundly affects systemic immune responses and tumor progression. Enzymatic activity, such as β -glucuronidase (GUS), facilitates the breakdown of estrogen metabolites, increasing their systemic availability [38]. Elevated estrogen levels are associated with tumor proliferation and the establishment of an immunosuppressive TME through the activation of Tregs and MDSCs, further diminishing the effectiveness of ICIs [38].
Targeting GUS activity demonstrates promise as a therapeutic approach. Inhibitors such as UNC10201652 have been shown to reduce estrogen reactivation, thereby counteracting immunosuppressive mechanisms within the tumor milieu and augmenting ICI responses [38]. Although primarily studied in hormone receptor-positive breast cancer, the prospective role of these strategies in other subtypes remains under investigation.
The breast tissue microbiota is another factor that facilitates tumor progression and immune modulation. Distinct microbial communities have been identified in both healthy and cancerous breast tissue, with tumor samples frequently enriched in bacterial genera such as Ralstonia, Methylobacterium, and Sphingomonas, which are associated with metabolic alterations that support tumor survival [39]. While their specific contribution to immune modulation has yet to be fully elucidated, these bacteria may influence immune cell recruitment and function within the TME.
The composition of the gut microbiota is a critical determinant of ICI efficacy in breast cancer. Reduced microbial diversity, including lower levels of Lachnospiraceae and Bifidobacteriaceae, is associated with resistance to trastuzumab in HER2-positive patients [40]. Conversely, beneficial bacteria such as Akkermansia muciniphila augment ICI responses by restoring CD8+ T cell cytotoxicity and promoting immune surveillance, particularly in tumors with low PD-L1 expression [7]. Additionally, metabolites such as SCFAs, produced by Faecalibacterium and Bacteroides, optimize immune function and enhance treatment efficacy [41].
Dietary modifications underscore the potential of microbiota-targeted interventions in breast cancer. In preclinical models of TNBC, quercetin supplementation has been shown to increase the abundance of Akkermansia muciniphila, correlating with improved responses to anti-PD-1 therapy and cyclophosphamide. These effects have been attributed to heightened NK cell activity and a reduction in Tregs [8].
Although the precise function of bacterial genera such as Ralstonia and Methylobacterium has yet to be fully elucidated, their enrichment in tumor tissues suggests that they could serve as potential biomarkers for disease progression or therapeutic targets for modulating the TME. Further investigation is required to determine their precise impact on immune dynamics and whether their presence correlates with treatment outcomes in breast cancer patients.

2.5. Metastatic Melanoma

Metastatic melanoma is an aggressive malignancy associated with high mortality rates and historically limited therapeutic options. The introduction of immunotherapy, particularly ICIs, has led to substantial improvements in survival outcomes for patients with advanced disease [42].
The gut microbiome is instrumental in modulating the efficacy of ICIs in metastatic melanoma. Specific bacterial taxa, such as Bacteroides fragilis, have been shown to enhance the therapeutic effects of ipilimumab, a CTLA-4 inhibitor, by influencing host immune responses [43]. Likewise, the oral administration of Bifidobacterium species in murine melanoma models has been demonstrated to improve tumor control in conjunction with anti-PD-L1 therapy [44].
Gut microbiota composition influences ICI responses: the enrichment of Faecalibacterium and Firmicutes is associated with prolonged PFS and OS—in contrast to Bacteroides profiles [45].
Increased microbial diversity and the presence of SCFA-producing bacteria, such as Faecalibacterium prausnitzii, Ruminococcaceae, and Akkermansia muciniphila, have been associated with favorable immunotherapy outcomes across melanoma cohorts [9,46]. These taxa enhance antitumor immunity through SCFA-mediated T cell activation and barrier integrity. However, the role of SCFAs is context-dependent. Certain species, such as Bacteroides fragilis, have been implicated in immune-related adverse events (irAEs) via IL-1 β -mediated inflammation, while others may exhibit tumor-promoting effects under specific host or microbial conditions [47]. This functional duality underscores the need to evaluate microbial metabolites within the broader ecological and immunological context of each patient.
Microbiota-based models incorporating bacterial and eukaryotic taxa have demonstrated strong performance in predicting ICI responsiveness, with an AUROC of 0.8019 in metastatic melanoma [9]. Yet, meta-analyses suggest that interindividual microbiome variability limits the reliability of universal biomarkers, as reflected by a lower AUROC of 0.625 [48].
Intratumor microbiome diversity in TCGA melanoma samples has also been correlated with ICI responsiveness, with taxa such as Eudoraea enhancing CD8+ T cell infiltration [49]. Intratumor microbial features may reflect local immune context and hold promise as predictive biomarkers.
Longitudinal analyses have revealed distinct microbiome shifts during ICI therapy, with responders showing the enrichment of beneficial taxa such as Faecalibacterium prausnitzii, Akkermansia muciniphila, Agathobaculum butyriciproducens, and Lactobacillus gasseri. Notably, taxa such as A. butyriciproducens persisted following therapy, while S. intestinalis and B. clarus, enriched in non-responders declined to baseline levels [50].
Among the microbial candidates, A. muciniphila and F. prausnitzii stand out for their consistent association with clinical response and mechanistic validation [51]. Computational models incorporating these taxa achieved high predictive accuracy [9]. Ongoing trials are evaluating A. muciniphila (Oncobax-AK) and F. prausnitzii (EXL01) as adjunctive therapies alongside ICIs (Table 1; NCT05865730 and NCT06448572). Together with gut-derived signals, intratumor microbial signatures expand the spectrum of clinically translatable biomarkers for melanoma immunotherapy.
In conclusion, both gut and intratumor microbiota constitute clinically actionable biomarkers and modulators of ICI efficacy in metastatic melanoma. SCFA-producing taxa enhance antitumor immunity, whereas proinflammatory microbes may exacerbate toxicity. Future efforts should refine microbiota-based predictors and validate their clinical utility in guiding ICI selection and individualizing immunotherapy.

3. Enhancing Chemotherapy Through Microbiome Modulation

Chemotherapy remains a cornerstone of cancer treatment, yet its efficacy is often compromised by systemic toxicity, therapeutic resistance, and significant variability in patient responses. Recent studies demonstrate that gut microbiota significantly contribute to these outcomes by regulating drug metabolism, inflammatory pathways, and tumor microenvironment dynamics [52,53]. Accordingly, a number of clinical trials have been initiated to evaluate microbiome-modulating strategies alongside chemotherapy across various cancer types (Table 2).
As shown in Figure 3, the microbiome’s influence on chemotherapy can be categorized into three key domains: drug metabolism, inflammation and toxicity, and chemotherapy resistance. For instance, microbial enzymes can degrade chemotherapeutic agents or reactivate toxic metabolites, altering their pharmacological efficacy [54,55]. Similarly, dysbiosis exacerbates systemic inflammation through LPS-driven pathways, heightening treatment-associated toxicity. Moreover, microbial interactions within the tumor microenvironment contribute to resistance mechanisms by promoting autophagy, inhibiting apoptosis, or impeding drug penetration [56].
This framework assesses how the microbiome modulates chemotherapy response through distinct biological mechanisms. The following sections will investigate these relationships across different cancer types, with a particular focus on microbiota-driven influences on treatment efficacy and their implications for optimizing therapeutic strategies.

3.1. Gastrointestinal Cancer

Chemotherapy remains a cornerstone in the management of GI malignancies; however, its therapeutic efficacy is frequently limited by resistance and toxicity [57].
Accumulating evidence demonstrates that gut microbes can interfere with treatment efficacy through the enzymatic biotransformation of drugs and modulation of host immunity [55,58]. For example, microbial cytidine deaminase converts gemcitabine into its inactive metabolite, 2’,2’-difluorodeoxyuridine. In murine models of CRC colonized with Gammaproteobacteria, gemcitabine monotherapy failed to suppress tumor growth, whereas cotreatment with ciprofloxacin led to a nearly 60% reduction in tumor volume [58]. Similarly, microbial β -glucuronidase reverses the hepatic glucuronidation of irinotecan, reactivating SN-38 and promoting severe gastrointestinal toxicity, including diarrhea [55].
Beyond enzymatic activity, microbial composition shapes the tumor microenvironment (TME). In CRC patients, high intratumoral Fusobacterium nucleatum was significantly associated with disease recurrence and inferior recurrence-free survival (AUC = 0.875) [59]. In vivo, F. nucleatum attenuated the tumor-suppressive effects of 5-fluorouracil (5-FU)—an effect that was reversed by BCL2 knockdown [59]. This bacterium contributes to chemoresistance through multiple mechanisms, including the inhibition of chemotherapy-induced pyroptosis via Hippo-YAP-mediated BCL2 upregulation and the enhancement of autophagy through TLR4 signaling and miRNA modulation [59,60].
These findings exemplify the role of “complicit microbes”—a group of pathobionts that promote tumor progression through chronic inflammation, immune evasion, and metabolic reprogramming [61]. Notably, colibactin-producing E. coli (CoPEC) reshapes the TME by inducing lipid droplet accumulation, thereby limiting CD8+ T cell infiltration and IFN- γ production [62].
While chemotherapy exerts substantial perturbations on the gut microbial ecosystem, certain beneficial taxa appear to re-emerge in patients exhibiting favorable therapeutic responses. In a prospective study of stage IV CRC patients receiving XELOX chemotherapy, the relative abundance of Bifidobacterium longum significantly increased post-treatment (p < 0.05) [63]. Notably, this increase was more pronounced in individuals with stable disease compared to those with progressive disease (p = 0.023), suggesting a potential role for microbial reconstitution in sustaining treatment benefit.
Chemotherapy-driven microbiota shifts may either exacerbate toxicity or support therapeutic benefit, depending on the direction of microbial reassembly. Understanding these dynamics may inform microbiota-targeted strategies to improve therapeutic efficacy and mitigate toxicity.

3.2. Lung Cancer

NSCLC is frequently diagnosed at advanced or metastatic stages, often precluding surgical interventions. For these patients, platinum-based doublet chemotherapy, typically combining cisplatin with gemcitabine or paclitaxel, remains the standard therapeutic approach [64].
The gut–lung axis, a two-way communication network connecting the GI and respiratory systems, regulates systemic immune responses and localized inflammation [65]. Microbial dysbiosis is linked to weakened immune responses and reduced chemotherapy efficacy [65]. Furthermore, antibiotic-induced microbiota depletion has been associated with OS and PFS in NSCLC patients undergoing chemotherapy [66].
SCFAs, as mentioned earlier, influence chemotherapy responses by modulating the immune system and inflammation. In a murine NSCLC model, concurrent antibiotic use negated the tumor-reducing effects of cisplatin. Conversely, oral supplementation with Lactobacillus acidophilus enhanced cisplatin’s efficacy, resulting in greater tumor reduction and improved survival outcomes [67]. This effect was linked to changes in genes regulating angiogenesis (VEGFA), apoptosis (BAX), and cell cycle progression (CDKN1B) [67].
While baseline microbiome composition correlates with chemotherapy response, certain bacterial species may actively enhance treatment efficacy through direct metabolic and immune modulation. A metagenomic study has identified distinct bacterial taxa linked to chemotherapy response in NSCLC patients, providing further insight into host–microbiome interactions [68]. In a cohort of advanced-stage cases, microbial profiling revealed substantial differences between individuals with favorable treatment outcomes and those with limited therapeutic benefits. Responders exhibited a greater prevalence of Streptococcus mutans and Enterococcus casseliflavus, whereas individuals with diminished efficacy exhibited higher levels of Leuconostoc lactis and Eubacterium siraeum [68]. Further metabolic assessments indicated that responders exhibited increased L-glutamate degradation, while non-responders relied more heavily on carbohydrate fermentation [68].
Chemotherapy itself induces substantial shifts in gut microbial composition over the course of treatment. Longitudinal monitoring of gut microbiota before and after chemotherapy revealed marked compositional alterations, including an increased prevalence of Firmicutes, Euryarchaeota, and Synergistetes, alongside a reduction in Bacteroides, Proteobacteria, and Actinobacteria [69]. Notably, chemotherapy-induced gastrointestinal toxicity was linked to an increased abundance of Prevotella, Megamonas, Streptococcus, and Faecalibacterium, whereas patients with higher levels of Veillonella, Ruminococcus, and Akkermansia exhibited lower toxicity rates. These observations underscore the intricate relationship between pre-existing microbiome composition and chemotherapy-induced alterations, influencing both therapeutic response and treatment-related complications [69].
Advancing microbiome-based therapeutic strategies requires a deeper understanding of the microbiota-driven metabolic pathways that influence drug bioavailability and immune modulation. Defining specific microbial taxa that predict chemotherapy response and incorporating microbiome-based biomarkers into clinical workflows may enhance precision oncology approaches.

3.3. Liver Cancer

Hepatocellular carcinoma presents significant challenges for chemotherapy due to its intrinsic drug resistance and the critical role of hepatic metabolism in drug clearance. Unlike lung cancer, where systemic chemotherapy remains a primary strategy, HCC treatment often integrates locoregional therapies such as transarterial chemoembolization (TACE) and hepatic artery infusion chemotherapy (HAIC) to improve drug delivery and efficacy. However, chemotherapy resistance remains a major limitation, necessitating novel approaches to enhance treatment outcomes [70].
The gut microbiota significantly influences HCC chemotherapy by modulating bile acid metabolism, drug detoxification, and systemic inflammation. Dysbiosis alters the gut–liver axis, disrupting bile acid homeostasis and leading to an immunosuppressive tumor microenvironment. This disruption has been attributed to the reduction in bile salt hydrolase (BSH)-producing taxa, including Bifidobacteriales and Clostridiales, which impairs the conversion of primary to conjugated secondary bile acids, such as glycodeoxycholic acid (GDCA). Importantly, GDCA exerts antiproliferative and proapoptotic effects on HCC cells, indicating that its depletion contributes to a tumor-promoting microenvironment and may reduce chemosensitivity [71]. Such dysregulation of the bile acid pool may ultimately impair the metabolism and efficacy of chemotherapeutic agents, particularly fluoropyrimidines and anthracyclines, which rely on hepatic enzymatic activation [72].
Natural products (NPs), including flavonoids and triterpenoids, have been studied for their role in enhancing chemotherapy responses in HCC. Flavonoids suppress tumor proliferation by inhibiting the Wnt/ β -catenin signaling pathway, whereas triterpenoids, such as ginsenosides, attenuate NF- κ B-mediated inflammation, which is a key driver of chemotherapy resistance [73]. Recent studies suggest that certain triterpenoids, such as those derived from Ganoderma lucidum, may influence gut microbiota composition, contributing to the suppression of liver cancer progression [73]. While the direct impact of flavonoids and triterpenoids on gut microbiota remains under investigation, their ability to regulate inflammatory pathways and bile acid metabolism may indirectly support a more favorable gut–liver axis for chemotherapy efficacy.
Building on these insights, microbiota-targeted interventions represent a promising avenue for overcoming chemotherapy resistance in HCC. Such strategies include dietary modulation, microbial metabolite supplementation, and engineered bacterial therapies that aim to restore microbial functions, including BSH activity [73]. Notably, the targeted restoration of GDCA levels has demonstrated therapeutic efficacy in preclinical models, where oral GDCA administration suppressed tumor growth and promoted apoptosis in HCC-bearing mice [71].

3.4. Breast Cancer

Chemotherapy is a cornerstone treatment for breast cancer, particularly for triple-negative and high-risk hormone receptor-positive subtypes. Neoadjuvant chemotherapy, administered prior to surgery to shrink tumors, offers valuable insights into treatment sensitivity. However, its efficacy varies among molecular subtypes, with higher pathological complete response rates observed in triple-negative and HER2-positive cancers compared to hormone receptor-positive tumors [74].
In patients with triple-negative breast cancer, those achieving a pathological complete response after neoadjuvant chemotherapy showed significantly higher gut microbial α diversity [75]. Further analysis identified specific bacterial taxa, notably Bacteroides eggerthii, which were more abundant in treatment responders [75].
Certain gut bacterial enzymes, particularly β -glucuronidases, influence tamoxifen metabolism by reactivating its inactive metabolites, thereby enhancing its bioavailability and therapeutic efficacy. Consequently, excessive inhibition of β -glucuronidases could reduce metabolite reactivation, compromising tamoxifen’s clinical effectiveness [76,77]. Additionally, bacterial enzymatic activity can directly degrade chemotherapeutic agents, reducing their antineoplastic effects. For example, Gammaproteobacteria-derived cytidine deaminase inactivates gemcitabine, compromising its efficacy. This effect has been reversed in preclinical models using ciprofloxacin to inhibit bacterial cytidine deaminase, restoring gemcitabine’s anticancer activity [78].
Changes in microbial community composition not only influence chemotherapy response but also play a critical role in resistance development and toxicity profiles. For example, increased abundance of Veillonella correlates with resistance to aromatase inhibitors, potentially through the modulation of estrogen-deconjugating enzymatic activities that alters estrogen metabolism pathways [79]. Future studies should aim to identify precise microbial biomarkers that are predictive of therapy responses and elucidate their mechanistic roles in drug metabolism and resistance.
The gut microbiome also significantly contributes to chemotherapy-induced toxicity, primarily through the microbial modulation of drug metabolism. For instance, irinotecan’s active metabolite, SN-38, is reactivated by bacterial β -glucuronidases, resulting in severe GI toxicities such as mucosal damage and diarrhea. Preclinical studies demonstrated that inhibiting these microbial enzymes effectively reduces SN-38 reactivation and mitigates irinotecan-induced toxicity [6,78].
In conclusion, the gut microbiome substantially impacts chemotherapy efficacy, resistance, and toxicity in breast cancer. A comprehensive understanding of microbiome–drug interactions and their underlying mechanisms could facilitate the development of targeted microbiome-based strategies, ultimately enhancing treatment outcomes and advancing personalized oncology.

3.5. Metastatic Melanoma

Advanced metastatic melanoma presents formidable therapeutic challenges, particularly when resistance to ICIs or targeted therapies manifests. Although chemotherapeutic approaches occupy a subordinate position relative to immunotherapeutic interventions, they maintain clinical relevance in select circumstances. Accumulating evidence indicates that the gut microbiota exerts significant influence on chemotherapeutic efficacy and associated toxicity through the modulation of immune function and transformation of the tumor microenvironment [80].
Specific chemotherapeutic compounds, notably cyclophosphamide (CTX), induce substantial alterations in gut microbiota composition characterized by diminished populations of beneficial bacterial taxa, including Faecalibacterium prausnitzii and Roseburia [52]. These microbial disruptions compromise intestinal barrier function, thereby facilitating bacterial translocation and consequent immunological activation [52]. This process operates through MyD88-dependent signaling mechanisms, resulting in enhanced Th1 and Th17 immunological responses that potentially influence therapeutic outcomes [52]. Furthermore, CTX administration modifies dendritic cell functionality by augmenting antigen acquisition and T-lymphocyte priming via the TLR/MyD88/MAPK signaling axis, further potentiating Th1 and Th17 cellular differentiation [81].
The microbial compositional shifts associated with chemotherapeutic intervention extend beyond localized effects to impact the broader tumor microenvironment [80]. Diminished SCFA concentrations contribute to immunological dysregulation, potentially influencing therapeutic response, resistance mechanisms, and treatment-related toxicity [80]. Additionally, alterations in microbial community structure demonstrate associations with epithelial-to-mesenchymal transition (EMT) and angiogenic processes, which are both recognized as significant factors in tumor progression dynamics [80].
While CTX-induced gut microbiota alterations have been extensively characterized, the interactions between alternative chemotherapeutic agents employed in melanoma management, particularly dacarbazine, and the intestinal microbiome remain inadequately investigated [80]. Contemporary research suggests that microbiota composition may significantly influence chemotherapy-induced immunological responses, though additional investigation is warranted to elucidate the precise mechanisms by which these microbial alterations impact therapeutic efficacy.
Investigative efforts continue to examine potential microbiome modulation strategies to enhance chemotherapeutic responses in melanoma treatment contexts [80]. Comprehensive understanding of these intricate host–microbiome interactions may reveal novel therapeutic opportunities through the integration of microbiota-targeted interventions with established treatment protocols, potentially improving clinical outcomes in this challenging malignancy.

4. Microbiome-Driven Supportive Interventions in Cancer Treatment

Dysbiosis, referring to the imbalance of microbial communities, is frequently observed in cancer patients and has been implicated in both tumor progression and therapeutic response [13,23]. However, whether dysbiosis acts as a cause or consequence of cancer remains debated. Some studies suggest that it contributes to oncogenesis by promoting inflammation, genomic instability, and immune evasion [82,83], whereas others view it as a secondary effect driven by tumor-induced metabolic changes, immune modulation, or therapy-associated perturbations [84].
Given the association between dysbiosis and treatment outcomes, various microbiome-based strategies have been explored to restore microbial homeostasis, including fecal microbiota transplantation (FMT), antibiotics, and microbiota-directed biotherapeutics. Among the latter, prebiotics, probiotics, and postbiotics differ in both their biological mechanisms and timing of administration. Prebiotics are generally administered before or during cancer therapy to promote the growth of beneficial microbes and preserve microbial diversity. Probiotics, consisting of live microorganisms, are typically used concurrently with chemotherapy or immunotherapy to reduce gastrointestinal toxicity, reinforce the intestinal barrier, and modulate systemic immune responses. In contrast, postbiotics—non-viable microbial products or metabolites—are introduced during or after treatment, offering anti-inflammatory and immunomodulatory effects while minimizing the safety concerns associated with live microbial administration in immunocompromised patients [85].
The following sections examine the current landscape of these interventions and their potential to enhance therapeutic efficacy in oncology.

4.1. FMT

Fecal microbiota transplantation (FMT), a microbiome-based intervention, introduces beneficial microbial communities from healthy donors [86] to restore gut homeostasis and modulate host responses during cancer treatment [87,88].
Ongoing clinical trials continue to explore the potential of FMT in modulating immunotherapy response across different cancer types. As shown in Table 3, FMT is being investigated in multiple malignancies. Trials employ various administration routes, such as oral capsules and colonoscopic infusion. A key focus has been on transferring microbiota from ICI responders to non-responders to overcome therapeutic resistance through microbial modulation. For instance, FMT from immunotherapy responders may enhance efficacy in previously resistant metastatic melanoma patients [89], which is supported by preclinical findings confirming restored responsiveness to PD-1 blockade and immune infiltration modulation [5].
Additionally, FMT has been investigated as a strategy to mitigate chemotherapy-induced dysbiosis. Such microbial interventions have been shown to persist for several months post-transplantation, supporting microbiome restoration and improved chemotherapy tolerance [90,91]. In one study, donor-derived microbial strains were detected in recipients up to three months after FMT, with strain-level coexistence confirmed by single-nucleotide variant tracking [91].
Most current FMT trials in oncology remain in early-phase development, in part because clinical implementation is constrained by safety concerns and inconsistencies arising from donor-to-donor microbial variability, which together underscore the urgent need for standardization.
Although generally well-tolerated, FMT carries risks, particularly infections linked to upper gastrointestinal administration, posing greater concerns for immunocompromised oncology patients [92,93]. Thus, the route selection and patient condition must be carefully considered in clinical practice. In particular, donor-to-donor variation in microbiota composition remains a major barrier to reproducible clinical outcomes. The therapeutic success of FMT is highly dependent on donor-specific microbial composition, particularly strain-level differences that govern engraftment dynamics and long-term microbiome stability in the recipient [94]. Recent strategies to address this include synthetic microbial consortia and microbial fingerprinting. While synthetic microbial consortia reduce variability by introducing a standardized set of defined strains, microbial fingerprinting focuses on optimizing donor selection through the identification of favorable microbial signatures [95]. Future efforts should prioritize translating these strategies into clinically applicable protocols—backed by long-term safety monitoring, regulatory approval pathways, and robust efficacy data across diverse patient populations.

4.2. Prebiotics

Prebiotics are defined as “substrates selectively utilized by host microorganisms to confer health benefits” [96]. Rather than introducing external microbial strains, these compounds promote beneficial resident bacteria that support mucosal immunity and epithelial integrity [96,97].
Gut microbiota modulation by prebiotics has been explored as a complementary approach to existing cancer treatments. In one study, inulin-based hydrogels loaded with oxaliplatin and MnO2 nanoparticles (Oxa@HMI) improved metabolite profiles, restored microbial balance, and enhanced antitumor immune responses in preclinical models [10]. Specifically, inulin alone was found to expand the abundance of Akkermansia muciniphila, which is a species linked to epithelial barrier reinforcement and decreased systemic inflammation [97]. In addition, plant-derived compounds with prebiotic activity have been shown to increase SCFA-producing genera such as Blautia, which are inversely correlated with inflammation and metabolic dysregulation [98]. Nutritional interventions, such as black raspberry supplementation, have shown potential to reshape microbial composition and mitigate tumorigenic factors [99].
Prebiotics have been incorporated into chemotherapeutic formulations to enhance drug bioavailability and microbiota-mediated efficacy. For example, a xylan-based capecitabine complex (SCXN) enhanced drug bioavailability and simultaneously supported the proliferation of bacterial taxa such as Akkermansia and Faecalibaculum, which are associated with improved treatment efficacy in murine models [100].
While these preclinical results are encouraging, the clinical translation of prebiotics remains challenging. Interindividual variability in microbiome composition significantly alters responses to prebiotic interventions, limiting reproducibility and standardization across populations [101,102]. In addition, the need for high therapeutic doses and the susceptibility of outcomes to external confounders such as diet and medication use further complicate trial design and scalability [102].
These limitations highlight the need for personalized prebiotic strategies tailored to host microbial and dietary profiles. Therapeutic outcomes may be improved through selective enrichment of taxa such as Akkermansia or SCFA-producing genera guided by predictive microbial biomarkers and integrated into precision-based treatment frameworks [103].

4.3. Probiotics

Probiotics constitute “live strains of microorganisms that, when administered in adequate amounts, confer health benefits to the host” [96]. Within oncological contexts, these microbial interventions facilitate the restoration of microbial homeostasis, suppress complicit microbes which directly contribute to tumorigenesis [61], and generate critical bioactive compounds, notably SCFAs, which play instrumental roles in inflammatory modulation and intestinal barrier maintenance [10].
Probiotics such as Bifidobacterium species have been proposed to reduce carcinogenic metabolite toxicity and enhance antitumor immune responses [44,64]. Preclinical investigations reveal that oral Bifidobacterium supplementation may potentially enhance anti-PD-L1 efficacy through immune priming and increased tumor-infiltrating T cell responses [44]. Clinical evidence from meta-analyses among NSCLC patients receiving ICIs indicates that probiotic supplementation was associated with improved overall survival (HR = 0.50, 95% CI: 0.30–0.85) and progression-free survival (HR = 0.51, 95% CI: 0.42–0.61) [104].
Furthermore, genetically engineered probiotic organisms present innovative strategies for TME modulation. For instance, oral administration of IL-2-expressing attenuated Salmonella strains led to increased NK and NK-T cell activity in a phase I trial [105]. Unlike prebiotics, which rely on host-dependent microbial fermentation and exhibit considerable interindividual variability [101,102], engineered probiotics can be designed to deliver therapeutic payloads directly within the tumor microenvironment, including cytokines such as IL-2 [105], thereby enabling more targeted and controllable immunomodulation.
Despite increasing clinical trials and growing evidence supporting the potential of probiotic-based interventions, several barriers hinder their clinical translation. First, safety concerns persist, as rare but serious cases of bacteremia and sepsis have been reported following the administration of probiotics such as Lactobacillus rhamnosus GG and Saccharomyces boulardii [106,107]. Second, the potential for horizontal transfer of antibiotic resistance genes (ARGs) between probiotic strains and pathogenic bacteria raises significant biosafety issues [106]. Third, variability in strain viability and host colonization efficiency poses challenges to consistent therapeutic delivery [108]. Finally, regulatory frameworks for live biotherapeutic products remain underdeveloped, with strain-specific characterization and manufacturing controls adding further complexity to clinical implementation [102].
To bridge these translational gaps, future efforts should prioritize the development of standardized evaluation frameworks that balance therapeutic efficacy with biosafety. Strain-specific selection based on immunological function, resistance profiles, and colonization capacity must be guided by rigorous preclinical and clinical validation. Ultimately, the safe and effective integration of probiotics into oncology care will depend on harmonized regulatory pathways and precision-based deployment strategies tailored to individual patient and microbial characteristics.

4.4. Postbiotics

Postbiotics, metabolic byproducts of microbial activity have gained attention for their immunomodulatory properties and potential application as adjuncts in cancer therapy. Unlike probiotics, which require bacterial colonization, postbiotics exert their effects through bioactive compounds such as SCFAs, tryptophan-derived metabolites, exopolysaccharides (EPSs), and microbial cell wall fragments [109,110]. Such characteristics render postbiotics promising candidates for modulating the tumor microenvironment and enhancing immunotherapy efficacy.
SCFAs, including butyrate, propionate, and acetate, are known to regulate immune responses and influence ICI therapy outcomes [14]. These metabolites impact both Treg and CD8+ T cells, contributing to enhanced antitumor activity through histone deacetylase (HDAC) inhibition [111,112,113]. Notably, butyrate increases IL-12R expression in CD8+ T cells by upregulating inhibitor of DNA Binding 2 (ID2), further strengthening antitumor immunity [103]. However, the rapid clearance of SCFAs from circulation remains a challenge, leading to the development of nanoparticle-based delivery strategies to improve their bioavailability [114,115].
SCFAs do not exert uniform effects across different ICI therapies. Higher fecal propionate levels have been associated with better responses to anti-PD-1 therapy, whereas increased systemic butyrate concentrations have been linked to reduced efficacy of anti-CTLA-4 therapy [116,117]. Additionally, butyrate may promote immunosuppressive effects, such as expanding Tregs and increasing IL-10 production, under certain host-dependent contexts [118]. These divergent outcomes emphasize that SCFA-mediated immune modulation is influenced by factors such as treatment timing, metabolite concentration, and the local immune microenvironment [117,118].
Beyond SCFAs, tryptophan-derived metabolites also play a key role in immune regulation. Indole-3-aldehyde, produced by Lactobacillus reuteri, has been shown to enhance ICI efficacy by stimulating IFN-γ production in CD8+ T cells [15].
Exopolysaccharides (EPSs) and other microbial-derived components further contribute to immune modulation. EPSs from Bacillus coagulans have been found to reshape the tumor-associated microbiome, improving gut homeostasis and reducing colorectal cancer progression [119]. Additionally, metabolites from Lactobacillus strains influence oncogenic pathways by modulating cell proliferation, apoptosis, and inflammation [120].
Despite their therapeutic potential, the variability of individual gut microbiota composition remains a challenge for postbiotics, similar to other microbial interventions such as probiotics and FMT [121]. However, recent evidence suggests that postbiotics might also exert colonization-independent effects—a distinct advantage over live microbial interventions such as probiotics and FMT. For instance, metabolites derived from Bifidobacterium breve and Lactobacillus rhamnosus induced apoptosis in colorectal cancer cells by modulating the expression of apoptosis-related genes (increased Bax and caspase-3 and decreased Bcl-2) and suppressed metastasis-associated genes (RSPO2, NGF, and MMP7) [122]. Acting via defined molecular routes, postbiotics may complement cancer therapy while providing a targeted adjunctive option that is less dependent on host microbiota composition.

4.5. Antibiotics

Antimicrobial agents remain indispensable for infection management in oncology patients, most notably those receiving chemotherapeutic or immunotherapeutic interventions, wherein immunocompromised states substantially elevate susceptibility to bacterial pathogens [123,124]. Nevertheless, the administration of broad-spectrum antimicrobials inevitably disrupts intestinal microbial ecosystems, potentially compromising the therapeutic efficacy of immune-mediated cancer treatments.
Observational clinical investigations suggest that recent antimicrobial exposure correlates with diminished responsiveness to ICI therapy and reduced survival duration, although considerable heterogeneity exists across research findings [125,126,127]. Experimental studies utilizing murine models demonstrated that antimicrobial administration depletes beneficial bacterial populations, particularly Bifidobacterium species, subsequently altering critical immunological signaling cascades that include T-lymphocyte activation, major histocompatibility complex class I expression, and SCFA production, ultimately attenuating ICI therapeutic efficacy [52,128].
Paradoxically, antimicrobial agents concurrently serve as strategic therapeutic modalities within oncological contexts when applied with precision. The eradication of Helicobacter pylori infection substantially mitigates gastric carcinoma risk [129], while selective antibiotic-based therapeutic approaches targeting tumor-associated bacterial communities have demonstrated the capacity to generate novel antigenic determinants and augment antitumor immunity [130].
Antimicrobial influence on ICI therapeutic outcomes has been extensively documented in pulmonary malignancies. Specific antibiotics—including ampicillin, colistin, and streptomycin—demonstrably attenuate PD-1 inhibitor efficacy, both as monotherapeutic agents and in combination with CTLA-4 blockade [5]. Comprehensive clinical analysis encompassing NSCLC, RCC, and urothelial carcinoma revealed that patients exposed to antimicrobial agents either preceding or during PD-1/PD-L1 targeted therapy experienced significantly abbreviated progression-free and overall survival intervals, suggesting that microbiome perturbation potentially contributes to ICI resistance mechanisms [5].
Achieving equilibrium between infectious disease control and the preservation of microbial diversity constitutes a fundamental challenge in contemporary cancer management. While extensive antimicrobial regimens potentially undermine ICI effectiveness, selective and judicious antimicrobial utilization—guided by optimal timing parameters and culture-directed selection protocols—may mitigate detrimental consequences while maintaining protective functions against infectious complications. Considering the intricate interactions between antimicrobial therapy, microbiome composition, and cancer treatment outcomes, individualized approaches to antimicrobial stewardship remain essential in optimizing patient care.

5. Conclusions

The microbiome has emerged as a critical component in the advancement of cancer therapeutics, particularly in immunotherapy and chemotherapy. Recent studies underscore the profound influence of the gut microbiota on treatment efficacy, immune modulation, and toxicity management. Specific microbial taxa and metabolites have been shown to enhance the effectiveness of ICIs and chemotherapeutic agents, while dysbiosis has been implicated in resistance mechanisms and adverse outcomes.
While many microbial taxa have been shown to promote therapeutic efficacy, others may compromise treatment responses or contribute to tumor persistence. This dual nature of the microbiome highlights the importance of considering both beneficial and harmful microbial components in the development of microbiome-based therapies.
Innovative approaches, such as engineered probiotics, prebiotics, and microbiome-modulating therapies, offer promising strategies to optimize treatment responses. Moreover, personalized microbiome profiling has opened new avenues for predicting therapeutic outcomes and tailoring interventions to individual patient needs. These findings highlight the potential of integrating microbiome-based strategies into precision oncology.
Despite significant progress, challenges remain, including the complexity of host–microbiome interactions, variability in microbiota composition, and the need for standardized methodologies. Future research should focus on elucidating the mechanisms underlying microbiome-mediated effects, developing robust biomarkers for patient stratification, and exploring the synergistic potential of combining microbiome-targeted therapies with existing cancer treatments.
By leveraging the microbiome’s role in cancer therapy, the medical community can unlock new opportunities to enhance therapeutic efficacy, minimize toxicity, and improve patient outcomes in the fight against cancer.

Author Contributions

Conceptualization, K.K. and T.-J.K.; methodology, K.K.; investigation, K.K.; writing—original draft preparation, K.K.; writing—review and editing, M.L., Y.S., Y.L. and T.-J.K.; visualization, K.K.; supervision, T.-J.K. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) [grant No. 2022R1A2C1092956].

Data Availability Statement

The data that are discussed in this article are presented in cited studies.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

AbbreviationDefinition
ICIImmune Checkpoint Inhibitor
PDProgrammed Death (e.g., PD-1, PD-L1)
CTLACytotoxic T-Lymphocyte Antigen
NKNatural Killer Cell
NSCLCNon-Small-Cell Lung Cancer
HCCHepatocellular Carcinoma
CRCColorectal Cancer
RCCRenal Cell Carcinoma
GIGastrointestinal
FMTFecal Microbiota Transplantation
SCFAShort-Chain Fatty Acid
LPSLipopolysaccharide
GUSGut Microbial / β -glucuronidases
PFSProgression-Free Survival
OSOverall Survival
RCTRandomized Controlled Trial
TMETumor Microenvironment
NAFLDNon-Alcoholic Fatty Liver Disease
ILInterleukin

References

  1. Hooper, L.V.; Littman, D.R.; Macpherson, A.J. Interactions between the microbiota and the immune system. Science 2012, 336, 1268–1273. [Google Scholar] [PubMed]
  2. Velikova, T.; Krastev, B.; Lozenov, S.; Gencheva, R.; Peshevska-Sekulovska, M.; Nikolaev, G.; Peruhova, M. Antibiotic-related changes in microbiome: The hidden villain behind colorectal carcinoma immunotherapy failure. Int. J. Mol. Sci. 2021, 22, 1754. [Google Scholar] [CrossRef]
  3. De Castilhos, J.; Tillmanns, K.; Blessing, J.; Laraño, A.; Borisov, V.; Stein-Thoeringer, C.K. Microbiome and pancreatic cancer: Time to think about chemotherapy. Gut Microbes 2024, 16, 2374596. [Google Scholar]
  4. Zhao, Y.; Liu, Y.; Li, S.; Peng, Z.; Liu, X.; Chen, J.; Zheng, X. Role of lung and gut microbiota on lung cancer pathogenesis. J. Cancer Res. Clin. Oncol. 2021, 147, 2177–2186. [Google Scholar] [PubMed]
  5. Routy, B.; Le Chatelier, E.; Derosa, L.; Duong, C.P.; Alou, M.T.; Daillère, R.; Fluckiger, A.; Messaoudene, M.; Rauber, C.; Roberti, M.P.; et al. Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors. Science 2018, 359, 91–97. [Google Scholar]
  6. Ervin, S.M.; Li, H.; Lim, L.; Roberts, L.R.; Liang, X.; Mani, S.; Redinbo, M.R. Gut microbial β-glucuronidases reactivate estrogens as components of the estrobolome that reactivate estrogens. J. Biol. Chem. 2019, 294, 18586–18599. [Google Scholar] [CrossRef]
  7. Zhu, Z.; Huang, J.; Zhang, Y.; Hou, W.; Chen, F.; Mo, Y.Y.; Zhang, Z. Landscape of tumoral ecosystem for enhanced anti-PD-1 immunotherapy by gut Akkermansia muciniphila. Cell Rep. 2024, 43, 114306. [Google Scholar]
  8. Manni, A.; Sun, Y.W.; Schell, T.D.; Lutsiv, T.; Thompson, H.; Chen, K.M.; Aliaga, C.; Zhu, J.; El-Bayoumy, K. Complementarity between Microbiome and Immunity May Account for the Potentiating Effect of Quercetin on the Antitumor Action of Cyclophosphamide in a Triple-Negative Breast Cancer Model. Pharmaceuticals 2023, 16, 1422. [Google Scholar] [CrossRef]
  9. Lin, Y.; Xie, M.; Lau, H.C.H.; Zeng, R.; Zhang, R.; Wang, L.; Li, Q.; Wang, Y.; Chen, D.; Jiang, L.; et al. Effects of gut microbiota on immune checkpoint inhibitors in multi-cancer and as microbial biomarkers for predicting therapeutic response. Med 2024, 6, 100530. [Google Scholar]
  10. Li, L.; He, S.; Liao, B.; Wang, M.; Lin, H.; Hu, B.; Lan, X.; Shu, Z.; Zhang, C.; Yu, M.; et al. Orally Administrated Hydrogel Harnessing Intratumoral Microbiome and Microbiota-Related Immune Responses for Potentiated Colorectal Cancer Treatment. Research 2024, 7, 0364. [Google Scholar]
  11. Dai, J.H.; Tan, X.R.; Qiao, H.; Liu, N. Emerging clinical relevance of microbiome in cancer: Promising biomarkers and therapeutic targets. Protein Cell 2024, 15, 239–260. [Google Scholar] [PubMed]
  12. Lazar, V.; Ditu, L.M.; Pircalabioru, G.G.; Gheorghe, I.; Curutiu, C.; Holban, A.M.; Picu, A.; Petcu, L.; Chifiriuc, M.C. Aspects of gut microbiota and immune system interactions in infectious diseases, immunopathology, and cancer. Front. Immunol. 2018, 9, 1830. [Google Scholar]
  13. Sobhani, I.; Tap, J.; Roudot-Thoraval, F.; Roperch, J.P.; Letulle, S.; Langella, P.; Corthier, G.; Van Nhieu, J.T.; Furet, J.P. Microbial dysbiosis in colorectal cancer (CRC) patients. PLoS ONE 2011, 6, e16393. [Google Scholar]
  14. Peng, Z.; Cheng, S.; Kou, Y.; Wang, Z.; Jin, R.; Hu, H.; Zhang, X.; Gong, J.F.; Li, J.; Lu, M.; et al. The gut microbiome is associated with clinical response to anti–PD-1/PD-L1 immunotherapy in gastrointestinal cancer. Cancer Immunol. Res. 2020, 8, 1251–1261. [Google Scholar]
  15. Bender, M.J.; McPherson, A.C.; Phelps, C.M.; Pandey, S.P.; Laughlin, C.R.; Shapira, J.H.; Sanchez, L.M.; Rana, M.; Richie, T.G.; Mims, T.S.; et al. Dietary tryptophan metabolite released by intratumoral Lactobacillus reuteri facilitates immune checkpoint inhibitor treatment. Cell 2023, 186, 1846–1862. [Google Scholar]
  16. Kang, X.; Liu, C.; Ding, Y.; Ni, Y.; Ji, F.; Lau, H.C.H.; Jiang, L.; Sung, J.J.; Wong, S.H.; Yu, J. Roseburia intestinalis generated butyrate boosts anti-PD-1 efficacy in colorectal cancer by activating cytotoxic CD8+ T cells. Gut 2023, 72, 2112–2122. [Google Scholar]
  17. Yang, Q.; Wang, B.; Zheng, Q.; Li, H.; Meng, X.; Zhou, F.; Zhang, L. A review of gut microbiota-derived metabolites in tumor progression and cancer therapy. Adv. Sci. 2023, 10, 2207366. [Google Scholar] [CrossRef]
  18. Genua, F.; Mirković, B.; Mullee, A.; Levy, M.; Gallagher, W.M.; Vodicka, P.; Hughes, D.J. Association of circulating short chain fatty acid levels with colorectal adenomas and colorectal cancer. Clin. Nutr. ESPEN 2021, 46, 297–304. [Google Scholar]
  19. Mager, L.F.; Burkhard, R.; Pett, N.; Cooke, N.C.; Brown, K.; Ramay, H.; Paik, S.; Stagg, J.; Groves, R.A.; Gallo, M.; et al. Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy. Science 2020, 369, 1481–1489. [Google Scholar]
  20. Sulit, A.; Daigneault, M.; Allen-Vercoe, E.; Silander, O.; Hock, B.; McKenzie, J.; Pearson, J.; Frizelle, F.; Schmeier, S.; Purcell, R. Bacterial lipopolysaccharide modulates immune response in the colorectal tumor microenvironment. Npj Biofilms Microbiomes 2023, 9, 59. [Google Scholar]
  21. Mirji, G.; Worth, A.; Bhat, S.A.; El Sayed, M.; Kannan, T.; Goldman, A.R.; Tang, H.Y.; Liu, Q.; Auslander, N.; Dang, C.V.; 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. [Google Scholar] [CrossRef] [PubMed]
  22. Han, Z.; Cheng, S.; Dai, D.; Kou, Y.; Zhang, X.; Li, F.; Yin, X.; Ji, J.; Zhang, Z.; Wang, X.; et al. The gut microbiome affects response of treatments in HER2-negative advanced gastric cancer. Clin. Transl. Med. 2023, 13, e1312. [Google Scholar] [CrossRef] [PubMed]
  23. Ramírez-Labrada, A.G.; Isla, D.; Artal, A.; Arias, M.; Rezusta, A.; Pardo, J.; Gálvez, E.M. The influence of lung microbiota on lung carcinogenesis, immunity, and immunotherapy. Trends Cancer 2020, 6, 86–97. [Google Scholar] [CrossRef]
  24. Jin, Y.; Dong, H.; Xia, L.; Yang, Y.; Zhu, Y.; Shen, Y.; Zheng, H.; Yao, C.; Wang, Y.; Lu, S. The diversity of gut microbiome is associated with favorable responses to anti–programmed death 1 immunotherapy in Chinese patients with NSCLC. J. Thorac. Oncol. 2019, 14, 1378–1389. [Google Scholar] [CrossRef]
  25. Newsome, R.C.; Yang, Y.; Jobin, C. The microbiome, gastrointestinal cancer, and immunotherapy. J. Gastroenterol. Hepatol. 2022, 37, 263–272. [Google Scholar] [CrossRef]
  26. Grenda, A.; Iwan, E.; Krawczyk, P.; Frąk, M.; Chmielewska, I.; Bomba, A.; Giza, A.; Rolska-Kopińska, A.; Szczyrek, M.; Kieszko, R.; et al. Attempting to identify bacterial allies in immunotherapy of NSCLC patients. Cancers 2022, 14, 6250. [Google Scholar] [CrossRef]
  27. Katayama, Y.; Yamada, T.; Shimamoto, T.; Iwasaku, M.; Kaneko, Y.; Uchino, J.; Takayama, K. The role of the gut microbiome on the efficacy of immune checkpoint inhibitors in Japanese responder patients with advanced non-small cell lung cancer. Transl. Lung Cancer Res. 2019, 8, 847. [Google Scholar] [CrossRef]
  28. Zhang, F.; Ferrero, M.; Dong, N.; D’Auria, G.; Reyes-Prieto, M.; Herreros-Pomares, A.; Calabuig-Farinas, S.; Durendez, E.; Aparisi, F.; Blasco, A.; et al. Analysis of the gut microbiota: An emerging source of biomarkers for immune checkpoint blockade therapy in non-small cell lung cancer. Cancers 2021, 13, 2514. [Google Scholar] [CrossRef]
  29. Hiddinga, B.I.; Bolte, L.A.; van der Leest, P.; Hijmering-Kappelle, L.B.; van der Wekken, A.J.; Schuuring, E.; Gacesa, R.; Hospers, G.A.; Weersma, R.K.; Björk, J.R.; et al. Response to immune checkpoint inhibition is associated with the gut microbiome in advanced KRAS-mutated non-small cell lung cancer. medRxiv 2023, 2023-10. [Google Scholar]
  30. Lee, S.H.; Sung, J.Y.; Yong, D.; Chun, J.; Kim, S.Y.; Song, J.H.; Chung, K.S.; Kim, E.Y.; Jung, J.Y.; Kang, Y.A.; et al. Characterization of microbiome in bronchoalveolar lavage fluid of patients with lung cancer comparing with benign mass like lesions. Lung Cancer 2016, 102, 89–95. [Google Scholar] [CrossRef]
  31. Lan, Z.; Liu, W.J.; Cui, H.; Zou, K.L.; Chen, H.; Zhao, Y.Y.; Yu, G.T. The role of oral microbiota in cancer. Front. Microbiol. 2023, 14, 1253025. [Google Scholar]
  32. Finnicum, C.T.; Rahal, Z.; Hassane, M.; Treekitkarnmongkol, W.; Sinjab, A.; Morris, R.; Liu, Y.; Tang, E.L.; Viet, S.; Petersen, J.L.; et al. Pathogenesis of tobacco-associated lung adenocarcinoma is closely coupled with changes in the gut and lung microbiomes. Int. J. Mol. Sci. 2022, 23, 10930. [Google Scholar] [CrossRef] [PubMed]
  33. Yang, L.; Li, N.; Yi, X.; Wang, Z. The translational potential of the lung microbiome as a biomarker and a therapeutic target for chronic obstructive pulmonary disease. Interdiscip. Med. 2023, 1, e20230023. [Google Scholar]
  34. Ohtani, N.; Kamiya, T.; Kawada, N. Recent updates on the role of the gut-liver axis in the pathogenesis of NAFLD/NASH, HCC, and beyond. Hepatol. Commun. 2023, 7, e0241. [Google Scholar]
  35. Foerster, F.; Gairing, S.J.; Müller, L.; Galle, P.R. NAFLD-driven HCC: Safety and efficacy of current and emerging treatment options. J. Hepatol. 2022, 76, 446–457. [Google Scholar]
  36. Song, Y.; Lau, H.C.; Zhang, X.; Yu, J. Bile acids, gut microbiota, and therapeutic insights in hepatocellular carcinoma. Cancer Biol. & Med. 2023, 21, 144. [Google Scholar]
  37. Khosravi, G.R.; Mostafavi, S.; Bastan, S.; Ebrahimi, N.; Gharibvand, R.S.; Eskandari, N. Immunologic tumor microenvironment modulators for turning cold tumors hot. Cancer Commun. 2024, 44, 521–553. [Google Scholar] [CrossRef]
  38. Fernández-Murga, M.L.; Gil-Ortiz, F.; Serrano-García, L.; Llombart-Cussac, A. A New Paradigm in the Relationship between Gut Microbiota and Breast Cancer: β-glucuronidase Enzyme Identified as Potential Therapeutic Target. Pathogens 2023, 12, 1086. [Google Scholar] [CrossRef]
  39. Schettini, F.; Gattazzo, F.; Nucera, S.; Garcia, E.R.; López-Aladid, R.; Morelli, L.; Fontana, A.; Vigneri, P.; Casals-Pascual, C.; Iebba, V.; et al. Navigating the complex relationship between human gut microbiota and breast cancer: Physiopathological, prognostic and therapeutic implications. Cancer Treat. Rev. 2024, 130, 102816. [Google Scholar]
  40. Di Modica, M.; Gargari, G.; Regondi, V.; Bonizzi, A.; Arioli, S.; Belmonte, B.; De Cecco, L.; Fasano, E.; Bianchi, F.; Bertolotti, A.; et al. Gut microbiota condition the therapeutic efficacy of trastuzumab in HER2-positive breast cancer. Cancer Res. 2021, 81, 2195–2206. [Google Scholar]
  41. Herrera, P.S.; van den Brink, M. The Intestinal Microbiota and Therapeutic Responses to Immunotherapy. Annu. Rev. Cancer Biol. 2024, 8, 435–452. [Google Scholar]
  42. Knight, A.; Karapetyan, L.; Kirkwood, J.M. Immunotherapy in melanoma: Recent advances and future directions. Cancers 2023, 15, 1106. [Google Scholar] [PubMed]
  43. Vétizou, M.; Pitt, J.M.; Daillère, R.; Lepage, P.; Waldschmitt, N.; Flament, C.; Rusakiewicz, S.; Routy, B.; Roberti, M.P.; Duong, C.P.; et al. Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science 2015, 350, 1079–1084. [Google Scholar]
  44. Sivan, A.; Corrales, L.; Hubert, N.; Williams, J.B.; Aquino-Michaels, K.; Earley, Z.M.; Benyamin, F.W.; Man Lei, Y.; Jabri, B.; Alegre, M.L.; et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti–PD-L1 efficacy. Science 2015, 350, 1084–1089. [Google Scholar]
  45. Chaput, N.; Lepage, P.; Coutzac, C.; Soularue, E.; Le Roux, K.; Monot, C.; Boselli, L.; Routier, E.; Cassard, L.; Collins, M.; et al. Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab. Ann. Oncol. 2017, 28, 1368–1379. [Google Scholar]
  46. Gopalakrishnan, V.; Spencer, C.N.; Nezi, L.; Reuben, A.; Andrews, M.C.; Karpinets, T.V.; Prieto, P.; Vicente, D.; Hoffman, K.; Wei, S.C.; et al. Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients. Science 2018, 359, 97–103. [Google Scholar]
  47. Miao, Y.D.; Quan, W.X.; Tang, X.L.; Shi, W.W.; Li, Q.; Li, R.J.; Wang, J.T.; Gan, J.; Dong, X.; Hao, L.; et al. Uncovering the flip side of immune checkpoint inhibitors: A comprehensive review of immune-related adverse events and predictive biomarkers. Int. J. Biol. Sci. 2024, 20, 621. [Google Scholar]
  48. Limeta, A.; Ji, B.; Levin, M.; Gatto, F.; Nielsen, J. Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma. JCI Insight 2020, 5, e140940. [Google Scholar]
  49. Zhang, Z.; Gao, Q.; Ren, X.; Luo, M.; Liu, Y.; Liu, P.; Liu, Y.; Ye, Y.; Chen, X.; Liu, H.; et al. Characterization of intratumor microbiome in cancer immunotherapy. Innovation 2023, 4, 100482. [Google Scholar]
  50. Björk, J.R.; Bolte, L.A.; Maltez Thomas, A.; Lee, K.A.; Rossi, N.; Wind, T.T.; Smit, L.M.; Armanini, F.; Asnicar, F.; Blanco-Miguez, A.; et al. Longitudinal gut microbiome changes in immune checkpoint blockade-treated advanced melanoma. Nat. Med. 2024, 30, 785–796. [Google Scholar]
  51. Zhang, M.; Liu, J.; Xia, Q. Role of gut microbiome in cancer immunotherapy: From predictive biomarker to therapeutic target. Exp. Hematol. Oncol. 2023, 12, 84. [Google Scholar] [CrossRef] [PubMed]
  52. Viaud, S.; Saccheri, F.; Mignot, G.; Yamazaki, T.; Daillère, R.; Hannani, D.; Enot, D.P.; Pfirschke, C.; Engblom, C.; Pittet, M.J.; et al. The intestinal microbiota modulates the anticancer immune effects of cyclophosphamide. Science 2013, 342, 971–976. [Google Scholar] [PubMed]
  53. Alexander, J.L.; Wilson, I.D.; Teare, J.; Marchesi, J.R.; Nicholson, J.K.; Kinross, J.M. Gut microbiota modulation of chemotherapy efficacy and toxicity. Nat. Rev. Gastroenterol. Hepatol. 2017, 14, 356–365. [Google Scholar] [PubMed]
  54. Iida, N.; Dzutsev, A.; Stewart, C.A.; Smith, L.; Bouladoux, N.; Weingarten, R.A.; Molina, D.A.; Salcedo, R.; Back, T.; Cramer, S.; et al. Commensal bacteria control cancer response to therapy by modulating the tumor microenvironment. Science 2013, 342, 967–970. [Google Scholar]
  55. Pellock, S.J.; Redinbo, M.R. Glucuronides in the gut: Sugar-driven symbioses between microbe and host. J. Biol. Chem. 2017, 292, 8569–8576. [Google Scholar]
  56. Ma, J.; Huang, L.; Hu, D.; Zeng, S.; Han, Y.; Shen, H. The role of the tumor microbe microenvironment in the tumor immune microenvironment: Bystander, activator, or inhibitor? J. Exp. Clin. Cancer Res. 2021, 40, 1–17. [Google Scholar] [CrossRef]
  57. Yarahmadi, A.; Afkhami, H. The role of microbiomes in gastrointestinal cancers: New insights. Front. Oncol. 2024, 13, 1344328. [Google Scholar]
  58. Geller, L.T.; Barzily-Rokni, M.; Danino, T.; Jonas, O.H.; Shental, N.; Nejman, D.; Gavert, N.; Zwang, Y.; Cooper, Z.A.; Shee, K.; et al. Potential role of intratumor bacteria in mediating tumor resistance to the chemotherapeutic drug gemcitabine. Science 2017, 357, 1156–1160. [Google Scholar]
  59. Wang, N.; Zhang, L.; Leng, X.X.; Xie, Y.L.; Kang, Z.R.; Zhao, L.C.; Song, L.H.; Zhou, C.B.; Fang, J.Y. Fusobacterium nucleatum induces chemoresistance in colorectal cancer by inhibiting pyroptosis via the Hippo pathway. Gut Microbes 2024, 16, 2333790. [Google Scholar]
  60. Yu, T.; Guo, F.; Yu, Y.; Sun, T.; Ma, D.; Han, J.; Qian, Y.; Kryczek, I.; Sun, D.; Nagarsheth, N.; et al. Fusobacterium nucleatum promotes chemoresistance to colorectal cancer by modulating autophagy. Cell 2017, 170, 548–563. [Google Scholar]
  61. Li, M.Y.; Gu, A.; Li, J.; Tang, N.; Matin, M.; Yang, Y.; Zengin, G.; Atanasov, A.G. Exploring food and medicine homology: Potential implications for cancer treatment innovations. Acta Mater. Medica 2025, 4, 200–206. [Google Scholar]
  62. De Oliveira Alves, N.; Dalmasso, G.; Nikitina, D.; Vaysse, A.; Ruez, R.; Ledoux, L.; Pedron, T.; Bergsten, E.; Boulard, O.; Autier, L.; et al. The colibactin-producing Escherichia coli alters the tumor microenvironment to immunosuppressive lipid overload facilitating colorectal cancer progression and chemoresistance. Gut Microbes 2024, 16, 2320291. [Google Scholar] [PubMed]
  63. Li, J.; Chu, R.; Wang, C.; Li, Y.; Wu, B.; Wan, J. Microbiome characteristics and Bifidobacterium longum in colorectal cancer patients pre-and post-chemotherapy. Transl. Cancer Res. 2020, 9, 2178. [Google Scholar] [PubMed]
  64. Xia, Q.; Chen, G.; Ren, Y.; Zheng, T.; Shen, C.; Li, M.; Chen, X.; Zhai, H.; Li, Z.; Xu, J.; et al. Investigating efficacy of “microbiota modulation of the gut-lung Axis” combined with chemotherapy in patients with advanced NSCLC: Study protocol for a multicenter, prospective, double blind, placebo controlled, randomized trial. BMC Cancer 2021, 21, 721. [Google Scholar]
  65. Alswat, A.S. The Influence of the Gut Microbiota on Host Health: A Focus on the Gut–Lung Axis and Therapeutic Approaches. Life 2024, 14, 1279. [Google Scholar] [CrossRef]
  66. Elkrief, A.; Méndez-Salazar, E.O.; Maillou, J.; Vanderbilt, C.M.; Gogia, P.; Desilets, A.; Messaoudene, M.; Kelly, D.; Ladanyi, M.; Hellmann, M.D.; et al. Antibiotics are associated with worse outcomes in lung cancer patients treated with chemotherapy and immunotherapy. NPJ Precis. Oncol. 2024, 8, 143. [Google Scholar]
  67. Gui, Q.; Lu, H.; Zhang, C.; Xu, Z.; Yang, Y. Well-balanced commensal microbiota contributes to anti-cancer response in a lung cancer mouse model. Genet. Mol. Res. 2015, 14, 5642–5651. [Google Scholar] [CrossRef]
  68. Zhao, Z.; Fei, K.; Bai, H.; Wang, Z.; Duan, J.; Wang, J. Metagenome association study of the gut microbiome revealed biomarkers linked to chemotherapy outcomes in locally advanced and advanced lung cancer. Thorac. Cancer 2021, 12, 66–78. [Google Scholar]
  69. Zhang, M.; Zhou, H.; Xu, S.; Liu, D.; Cheng, Y.; Gao, B.; Li, X.; Chen, J. The gut microbiome can be used to predict the gastrointestinal response and efficacy of lung cancer patients undergoing chemotherapy. Ann. Palliat. Med. 2020, 9, 4211227–4214227. [Google Scholar]
  70. Hou, Z.; Liu, J.; Jin, Z.; Qiu, G.; Xie, Q.; Mi, S.; Huang, J. Use of chemotherapy to treat hepatocellular carcinoma. Biosci. Trends 2022, 16, 31–45. [Google Scholar] [CrossRef]
  71. Shen, R.; Ke, L.; Li, Q.; Dang, X.; Shen, S.; Shen, J.; Li, S.; Liang, L.; Peng, B.; Kuang, M.; et al. Abnormal bile acid-microbiota crosstalk promotes the development of hepatocellular carcinoma. Hepatol. Int. 2022, 16, 396–411. [Google Scholar] [PubMed]
  72. Ohtani, N.; Hara, E. Gut-liver axis-mediated mechanism of liver cancer: A special focus on the role of gut microbiota. Cancer Sci. 2021, 112, 4433–4443. [Google Scholar] [PubMed]
  73. Guo, J.; Yan, W.; Duan, H.; Wang, D.; Zhou, Y.; Feng, D.; Zheng, Y.; Zhou, S.; Liu, G.; Qin, X. Therapeutic Effects of Natural Products on Liver Cancer and Their Potential Mechanisms. Nutrients 2024, 16, 1642. [Google Scholar] [CrossRef]
  74. Asaoka, M.; Gandhi, S.; Ishikawa, T.; Takabe, K. Neoadjuvant chemotherapy for breast cancer: Past, present, and future. Breast Cancer: Basic Clin. Res. 2020, 14, 1178223420980377. [Google Scholar]
  75. Vernaci, G.; Savarino, E.V.; Patuzzi, I.; Facchin, S.; Zingone, F.; Massa, D.; Faggioni, G.; Giarratano, T.; Miglietta, F.; Griguolo, G.; et al. Characterization of gut microbiome composition in patients with triple-negative breast cancer treated with neoadjuvant chemotherapy. Oncologist 2023, 28, e703–e711. [Google Scholar]
  76. Chen, K.L.A.; Liu, X.; Zhao, Y.C.; Hieronymi, K.; Rossi, G.; Auvil, L.S.; Welge, M.; Bushell, C.; Smith, R.L.; Carlson, K.E.; et al. Long-term administration of conjugated estrogen and bazedoxifene decreased murine fecal β-glucuronidase activity without impacting overall microbiome community. Sci. Rep. 2018, 8, 8166. [Google Scholar] [CrossRef]
  77. Chen, K.L.; Madak-Erdogan, Z. Estrogen and microbiota crosstalk: Should we pay attention? Trends Endocrinol. Metab. 2016, 27, 752–755. [Google Scholar]
  78. Álvarez-Mercado, A.I.; del Valle Cano, A.; Fernández, M.F.; Fontana, L. Gut microbiota and breast cancer: The dual role of microbes. Cancers 2023, 15, 443. [Google Scholar] [CrossRef]
  79. Lasagna, A.; De Amici, M.; Rossi, C.; Zuccaro, V.; Corbella, M.; Petazzoni, G.; Comandatore, F.; Sacchi, L.; Testa, G.; Ferraris, E.; et al. The bio-diversity and the role of gut microbiota in postmenopausal women with luminal breast cancer treated with aromatase inhibitors: An observational cohort study. Pathogens 2022, 11, 1421. [Google Scholar] [CrossRef]
  80. Sevcikova, A.; Mladosievicova, B.; Mego, M.; Ciernikova, S. Exploring the Role of the Gut and Intratumoral Microbiomes in Tumor Progression and Metastasis. Int. J. Mol. Sci. 2023, 24, 17199. [Google Scholar] [CrossRef]
  81. Bao, L.; Hao, C.; Wang, J.; Wang, D.; Zhao, Y.; Li, Y.; Yao, W. High-dose cyclophosphamide administration orchestrates phenotypic and functional alterations of immature dendritic cells and regulates Th cell polarization. Front. Pharmacol. 2020, 11, 775. [Google Scholar]
  82. Fan, X.; Jin, Y.; Chen, G.; Ma, X.; Zhang, L. Gut microbiota dysbiosis drives the development of colorectal cancer. Digestion 2021, 102, 508–515. [Google Scholar] [CrossRef] [PubMed]
  83. Ranjbar, M.; Salehi, R.; Haghjooy Javanmard, S.; Rafiee, L.; Faraji, H.; Jafarpor, S.; Ferns, G.A.; Ghayour-Mobarhan, M.; Manian, M.; Nedaeinia, R. The dysbiosis signature of Fusobacterium nucleatum in colorectal cancer-cause or consequences? A systematic review. Cancer Cell Int. 2021, 21, 1–24. [Google Scholar]
  84. Jia, W.; Rajani, C.; Xu, H.; Zheng, X. Gut microbiota alterations are distinct for primary colorectal cancer and hepatocellular carcinoma. Protein Cell 2021, 12, 374–393. [Google Scholar]
  85. Ciernikova, S.; Sevcikova, A.; Drgona, L.; Mego, M. Modulating the gut microbiota by probiotics, prebiotics, postbiotics, and fecal microbiota transplantation: An emerging trend in cancer patient care. Biochim. Et Biophys. Acta (BBA)-Rev. Cancer 2023, 1878, 188990. [Google Scholar]
  86. Kaźmierczak-Siedlecka, K.; Daca, A.; Fic, M.; van de Wetering, T.; Folwarski, M.; Makarewicz, W. Therapeutic methods of gut microbiota modification in colorectal cancer management–fecal microbiota transplantation, prebiotics, probiotics, and synbiotics. Gut Microbes 2020, 11, 1518–1530. [Google Scholar]
  87. Matsuo, K.; Haku, A.; Bi, B.; Takahashi, H.; Kamada, N.; Yaguchi, T.; Saijo, S.; Yoneyama, M.; Goto, Y. Fecal microbiota transplantation prevents Candida albicans from colonizing the gastrointestinal tract. Microbiol. Immunol. 2019, 63, 155–163. [Google Scholar] [CrossRef]
  88. Chen, D.; Wu, J.; Jin, D.; Wang, B.; Cao, H. Fecal microbiota transplantation in cancer management: Current status and perspectives. Int. J. Cancer 2019, 145, 2021–2031. [Google Scholar]
  89. Baruch, E.N.; Youngster, I.; Ben-Betzalel, G.; Ortenberg, R.; Lahat, A.; Katz, L.; Adler, K.; Dick-Necula, D.; Raskin, S.; Bloch, N.; et al. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science 2021, 371, 602–609. [Google Scholar]
  90. Li, H.L.; Lu, L.; Wang, X.S.; Qin, L.Y.; Wang, P.; Qiu, S.P.; Wu, H.; Huang, F.; Zhang, B.B.; Shi, H.L.; et al. Alteration of gut microbiota and inflammatory cytokine/chemokine profiles in 5-fluorouracil induced intestinal mucositis. Front. Cell. Infect. Microbiol. 2017, 7, 455. [Google Scholar]
  91. Xu, H.; Cao, C.; Ren, Y.; Weng, S.; Liu, L.; Guo, C.; Wang, L.; Han, X.; Ren, J.; Liu, Z. Antitumor effects of fecal microbiota transplantation: Implications for microbiome modulation in cancer treatment. Front. Immunol. 2022, 13, 949490. [Google Scholar] [CrossRef] [PubMed]
  92. Marcella, C.; Cui, B.; Kelly, C.R.; Ianiro, G.; Cammarota, G.; Zhang, F. Systematic review: The global incidence of faecal microbiota transplantation-related adverse events from 2000 to 2020. Aliment. Pharmacol. Ther. 2021, 53, 33–42. [Google Scholar] [CrossRef] [PubMed]
  93. Rapoport, E.A.; Baig, M.; Puli, S.R. Adverse events in fecal microbiota transplantation: A systematic review and meta-analysis. Ann. Gastroenterol. 2022, 35, 150. [Google Scholar]
  94. Schmidt, T.S.; Li, S.S.; Maistrenko, O.M.; Akanni, W.; Coelho, L.P.; Dolai, S.; Fullam, A.; Glazek, A.M.; Hercog, R.; Herrema, H.; et al. Drivers and determinants of strain dynamics following fecal microbiota transplantation. Nat. Med. 2022, 28, 1902–1912. [Google Scholar] [CrossRef]
  95. Servetas, S.L.; Daschner, P.J.; Guyard, C.; Thomas, V.; Affagard, H.; Sergaki, C.; Sokol, H.; Wargo, J.A.; Wu, G.D.; Sabot, P. Evolution of FMT–From early clinical to standardized treatments. Biologicals 2022, 76, 31–35. [Google Scholar] [CrossRef]
  96. Gibson, G.R.; Hutkins, R.; Sanders, M.E.; Prescott, S.L.; Reimer, R.A.; Salminen, S.J.; Scott, K.; Stanton, C.; Swanson, K.S.; Cani, P.D.; et al. Expert consensus document: The International Scientific Association for Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of prebiotics. Nat. Rev. Gastroenterol. Hepatol. 2017, 14, 491–502. [Google Scholar] [CrossRef]
  97. Han, K.; Nam, J.; Xu, J.; Sun, X.; Huang, X.; Animasahun, O.; Achreja, A.; Jeon, J.H.; Pursley, B.; Kamada, N.; et al. Generation of systemic antitumour immunity via the in situ modulation of the gut microbiome by an orally administered inulin gel. Nat. Biomed. Eng. 2021, 5, 1377–1388. [Google Scholar] [CrossRef]
  98. Liu, Y.M.; Liu, C.; Deng, Y.S.; Chen, Y.; Qiu, Q.W.; Shang, X.X.; Wang, C.R.; Han, L.J.; Huang, L.; Yang, Z.M.; et al. Beneficial effects of dietary herbs on high-fat diet-induced obesity linking with modulation of gut microbiota. Food Med. Homol. 2025, 2, 9420034. [Google Scholar] [CrossRef]
  99. Chen, L.; Teng, H.; Jia, Z.; Battino, M.; Miron, A.; Yu, Z.; Cao, H.; Xiao, J. Intracellular signaling pathways of inflammation modulated by dietary flavonoids: The most recent evidence. Crit. Rev. Food Sci. Nutr. 2018, 58, 2908–2924. [Google Scholar] [CrossRef]
  100. Lang, T.; Zhu, R.; Zhu, X.; Yan, W.; Li, Y.; Zhai, Y.; Wu, T.; Huang, X.; Yin, Q.; Li, Y. Combining gut microbiota modulation and chemotherapy by capecitabine-loaded prebiotic nanoparticle improves colorectal cancer therapy. Nat. Commun. 2023, 14, 4746. [Google Scholar] [CrossRef]
  101. Holmes, Z.C.; Villa, M.M.; Durand, H.K.; Jiang, S.; Dallow, E.P.; Petrone, B.L.; Silverman, J.D.; Lin, P.H.; David, L.A. Microbiota responses to different prebiotics are conserved within individuals and associated with habitual fiber intake. Microbiome 2022, 10, 114. [Google Scholar]
  102. McCoubrey, L.E.; Elbadawi, M.; Basit, A.W. Current clinical translation of microbiome medicines. Trends Pharmacol. Sci. 2022, 43, 281–292. [Google Scholar] [PubMed]
  103. He, Y.; Fu, L.; Li, Y.; Wang, W.; Gong, M.; Zhang, J.; Dong, X.; Huang, J.; Wang, Q.; Mackay, C.R.; et al. Gut microbial metabolites facilitate anticancer therapy efficacy by modulating cytotoxic CD8+ T cell immunity. Cell Metab. 2021, 33, 988–1000. [Google Scholar] [PubMed]
  104. Wan, L.; Wu, C.; Wu, Q.; Luo, S.; Liu, J.; Xie, X. Impact of probiotics use on clinical outcomes of immune checkpoint inhibitors therapy in cancer patients. Cancer Med. 2023, 12, 1841–1849. [Google Scholar]
  105. Gniadek, T.J.; Augustin, L.; Schottel, J.; Leonard, A.; Saltzman, D.; Greeno, E.; Batist, G. A phase I, dose escalation, single dose trial of oral attenuated Salmonella typhimurium containing human IL-2 in patients with metastatic gastrointestinal cancers. J. Immunother. 2020, 43, 217–221. [Google Scholar]
  106. Yang, S.; Qiao, J.; Zhang, M.; Kwok, L.Y.; Matijašić, B.B.; Zhang, H.; Zhang, W. Prevention and treatment of antibiotics-associated adverse effects through the use of probiotics: A review. J. Adv. Res. 2024. [Google Scholar]
  107. Anadón, A.; Ares, I.; Martínez-Larrañaga, M.R.; Martínez, M.A. Probiotics: Safety and toxicity considerations. In Nutraceuticals; Elsevier: Amsterdam, The Netherlands, 2021; pp. 1081–1105. [Google Scholar]
  108. Han, S.; Lu, Y.; Xie, J.; Fei, Y.; Zheng, G.; Wang, Z.; Liu, J.; Lv, L.; Ling, Z.; Berglund, B.; et al. Probiotic gastrointestinal transit and colonization after oral administration: A long journey. Front. Cell. Infect. Microbiol. 2021, 11, 609722. [Google Scholar] [CrossRef]
  109. He, H.; Qin, Q.; Xu, F.; Chen, Y.; Rao, S.; Wang, C.; Jiang, X.; Lu, X.; Xie, C. Oral polyphenol-armored nanomedicine for targeted modulation of gut microbiota–brain interactions in colitis. Sci. Adv. 2023, 9, eadf3887. [Google Scholar]
  110. Cho, Y.S.; Han, K.; Xu, J.; Moon, J.J. Novel strategies for modulating the gut microbiome for cancer therapy. Adv. Drug Deliv. Rev. 2024, 210, 115332. [Google Scholar] [CrossRef]
  111. Park, J.; Kim, M.; Kang, S.G.; Jannasch, A.H.; Cooper, B.; Patterson, J.; Kim, C.H. Short-chain fatty acids induce both effector and regulatory T cells by suppression of histone deacetylases and regulation of the mTOR–S6K pathway. Mucosal Immunol. 2015, 8, 80–93. [Google Scholar]
  112. Smith, P.M.; Howitt, M.R.; Panikov, N.; Michaud, M.; Gallini, C.A.; Bohlooly-y, M.; Glickman, J.N.; Garrett, W.S. The microbial metabolites, short-chain fatty acids, regulate colonic Treg cell homeostasis. Science 2013, 341, 569–573. [Google Scholar] [PubMed]
  113. Arpaia, N.; Campbell, C.; Fan, X.; Dikiy, S.; Van Der Veeken, J.; Deroos, P.; Liu, H.; Cross, J.R.; Pfeffer, K.; Coffer, P.J.; et al. Metabolites produced by commensal bacteria promote peripheral regulatory T-cell generation. Nature 2013, 504, 451–455. [Google Scholar] [PubMed]
  114. Silva, Y.P.; Bernardi, A.; Frozza, R.L. The role of short-chain fatty acids from gut microbiota in gut-brain communication. Front. Endocrinol. 2020, 11, 508738. [Google Scholar]
  115. Shashni, B.; Nagasaki, Y. Short-chain fatty acid-releasing nano-prodrugs for attenuating growth and metastasis of melanoma. Acta Biomater. 2023, 159, 226–236. [Google Scholar]
  116. Botticelli, A.; Vernocchi, P.; Marini, F.; Quagliariello, A.; Cerbelli, B.; Reddel, S.; Del Chierico, F.; Di Pietro, F.; Giusti, R.; Tomassini, A.; et al. Gut metabolomics profiling of non-small cell lung cancer (NSCLC) patients under immunotherapy treatment. J. Transl. Med. 2020, 18, 1–10. [Google Scholar]
  117. Coutzac, C.; Jouniaux, J.M.; Paci, A.; Schmidt, J.; Mallardo, D.; Seck, A.; Asvatourian, V.; Cassard, L.; Saulnier, P.; Lacroix, L.; et al. Systemic short chain fatty acids limit antitumor effect of CTLA-4 blockade in hosts with cancer. Nat. Commun. 2020, 11, 2168. [Google Scholar]
  118. Mirzaei, R.; Dehkhodaie, E.; Bouzari, B.; Rahimi, M.; Gholestani, A.; Hosseini-Fard, S.R.; Keyvani, H.; Teimoori, A.; Karampoor, S. Dual role of microbiota-derived short-chain fatty acids on host and pathogen. Biomed. Pharmacother. 2022, 145, 112352. [Google Scholar]
  119. Song, Q.; Zhao, H.; Zheng, C.; Wang, K.; Gao, H.; Feng, Q.; Zhang, H.; Zhang, Z.; Zhang, Y.; Wang, L. A bioinspired versatile spore coat nanomaterial for oral probiotics delivery. Adv. Funct. Mater. 2021, 31, 2104994. [Google Scholar]
  120. Rad, A.H.; Aghebati-Maleki, L.; Kafil, H.S.; Abbasi, A. Molecular mechanisms of postbiotics in colorectal cancer prevention and treatment. Crit. Rev. Food Sci. Nutr. 2021, 61, 1787–1803. [Google Scholar]
  121. Sanna, S.; van Zuydam, N.R.; Mahajan, A.; Kurilshikov, A.; Vich Vila, A.; Võsa, U.; Mujagic, Z.; Masclee, A.A.; Jonkers, D.M.; Oosting, M.; et al. Causal relationships among the gut microbiome, short-chain fatty acids and metabolic diseases. Nat. Genet. 2019, 51, 600–605. [Google Scholar]
  122. Erfanian, N.; Safarpour, H.; Tavakoli, T.; Mahdiabadi, M.A.; Nasseri, S.; Namaei, M.H. Investigating the therapeutic potential of Bifidobacterium breve and Lactobacillus rhamnosus postbiotics through apoptosis induction in colorectal HT-29 cancer cells. Iran. J. Microbiol. 2024, 16, 68. [Google Scholar] [CrossRef] [PubMed]
  123. Dik, V.K.; van Oijen, M.G.; Smeets, H.M.; Siersema, P.D. Frequent use of antibiotics is associated with colorectal cancer risk: Results of a nested case–control study. Dig. Dis. Sci. 2016, 61, 255–264. [Google Scholar] [CrossRef] [PubMed]
  124. Kong, R.; Liu, T.; Zhu, X.; Ahmad, S.; Williams, A.L.; Phan, A.T.; Zhao, H.; Scott, J.E.; Yeh, L.A.; Wong, S.T. Old drug new use—amoxapine and its metabolites as potent bacterial β-glucuronidase inhibitors for alleviating cancer drug toxicity. Clin. Cancer Res. 2014, 20, 3521–3530. [Google Scholar] [CrossRef] [PubMed]
  125. Lalani, A.K.A.; Xie, W.; Lin, X.; Steinharter, J.A.; Martini, D.J.; Duquette, A.; Bosse, D.; McKay, R.R.; Simantov, R.; Wei, X.X.; et al. Antibiotic use and outcomes with systemic therapy in metastatic renal cell carcinoma (mRCC). J. Clin. Oncol. 2018, 36, 6. [Google Scholar] [CrossRef]
  126. Derosa, L.; Hellmann, M.; Spaziano, M.; Halpenny, D.; Fidelle, M.; Rizvi, H.; Long, N.; Plodkowski, A.; Arbour, K.; Chaft, J.; et al. Negative association of antibiotics on clinical activity of immune checkpoint inhibitors in patients with advanced renal cell and non-small-cell lung cancer. Ann. Oncol. 2018, 29, 1437–1444. [Google Scholar] [CrossRef]
  127. Kaderbhai, C.; Richard, C.; Fumet, J.D.; Aarnink, A.; Foucher, P.; Coudert, B.; Favier, L.; Lagrange, A.; Limagne, E.; Boidot, R.; et al. Antibiotic use does not appear to influence response to nivolumab. Anticancer Res. 2017, 37, 3195–3200. [Google Scholar]
  128. Shi, Y.; Zheng, W.; Yang, K.; Harris, K.G.; Ni, K.; Xue, L.; Lin, W.; Chang, E.B.; Weichselbaum, R.R.; Fu, Y.X. Intratumoral accumulation of gut microbiota facilitates CD47-based immunotherapy via STING signaling. J. Exp. Med. 2020, 217, e20192282. [Google Scholar] [CrossRef]
  129. Yan, L.; Chen, Y.; Chen, F.; Tao, T.; Hu, Z.; Wang, J.; You, J.; Wong, B.C.; Chen, J.; Ye, W. Effect of Helicobacter pylori eradication on gastric cancer prevention: Updated report from a randomized controlled trial with 26.5 years of follow-up. Gastroenterology 2022, 163, 154–162. [Google Scholar] [CrossRef]
  130. Wang, M.; Rousseau, B.; Qiu, K.; Huang, G.; Zhang, Y.; Su, H.; Le Bihan-Benjamin, C.; Khati, I.; Artz, O.; Foote, M.B.; et al. Killing tumor-associated bacteria with a liposomal antibiotic generates neoantigens that induce anti-tumor immune responses. Nat. Biotechnol. 2024, 42, 1263–1274. [Google Scholar] [CrossRef]
Figure 1. Mechanisms of microbiome influence in cancer therapy.
Figure 1. Mechanisms of microbiome influence in cancer therapy.
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Figure 2. Microbiome-driven synergy with immunotherapy. Key microbial taxa, including Akkermansia muciniphila, Faecalibacterium prausnitzii, and Bacteroides fragilis, have demonstrated consistent associations with enhanced immune checkpoint inhibitor (ICI) efficacy. These effects are mediated through multiple pathways: (1) production of short-chain fatty acids (SCFAs), particularly butyrate, leading to histone deacetylase (HDAC) inhibition and increased T helper 1 (Th1) and cytotoxic T lymphocyte (CTL) responses; (2) inosine production that activates A2A receptors on T cells, promoting Th1 differentiation; (3) induction of interleukin-12 (IL-12) and enhancement of dendritic cell and CD8+ T cell activity; and (4) improvement of gut barrier integrity and modulation of systemic inflammation to mitigate immune-related toxicities.
Figure 2. Microbiome-driven synergy with immunotherapy. Key microbial taxa, including Akkermansia muciniphila, Faecalibacterium prausnitzii, and Bacteroides fragilis, have demonstrated consistent associations with enhanced immune checkpoint inhibitor (ICI) efficacy. These effects are mediated through multiple pathways: (1) production of short-chain fatty acids (SCFAs), particularly butyrate, leading to histone deacetylase (HDAC) inhibition and increased T helper 1 (Th1) and cytotoxic T lymphocyte (CTL) responses; (2) inosine production that activates A2A receptors on T cells, promoting Th1 differentiation; (3) induction of interleukin-12 (IL-12) and enhancement of dendritic cell and CD8+ T cell activity; and (4) improvement of gut barrier integrity and modulation of systemic inflammation to mitigate immune-related toxicities.
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Figure 3. Microbiome-associated mechanisms contributing to chemotherapy response. Certain bacterial species, such as Gammaproteobacteria, degrade chemotherapeutic agents like gemcitabine via bacterial cytidine deaminase. Intestinal Escherichia coli can reactivate the toxic metabolite SN-38 from its inactive glucuronidated form (SN-38G), increasing gastrointestinal toxicity. Dysbiosis-induced barrier disruption permits translocation of lipopolysaccharide (LPS), exacerbating systemic inflammation and chemotoxicity. Additionally, bacteria such as Fusobacterium nucleatum promote chemoresistance by activating autophagy through the Toll-like receptor 4 (TLR4)/MyD88 pathway, thereby inhibiting apoptosis and limiting drug efficacy.
Figure 3. Microbiome-associated mechanisms contributing to chemotherapy response. Certain bacterial species, such as Gammaproteobacteria, degrade chemotherapeutic agents like gemcitabine via bacterial cytidine deaminase. Intestinal Escherichia coli can reactivate the toxic metabolite SN-38 from its inactive glucuronidated form (SN-38G), increasing gastrointestinal toxicity. Dysbiosis-induced barrier disruption permits translocation of lipopolysaccharide (LPS), exacerbating systemic inflammation and chemotoxicity. Additionally, bacteria such as Fusobacterium nucleatum promote chemoresistance by activating autophagy through the Toll-like receptor 4 (TLR4)/MyD88 pathway, thereby inhibiting apoptosis and limiting drug efficacy.
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Table 1. Currently registered clinical trials on microbiome-modulated immunotherapy.
Table 1. Currently registered clinical trials on microbiome-modulated immunotherapy.
NCT No.Cancer TypeEnrollmentImmunotherapyMicrobial InterventionPhaseLocationStatus
5865730NSCLC, RCC122None (PD-1, PD-L1 agents)Oral administration of Oncobax®-AK (Akkermansia muciniphila)1/2Belgium, FranceRecruiting
6448572NSCLC21NivolumabEXL01 (Faecalibacterium prausnitzii)1/2FranceRecruiting
5487859RCC24Ipilimumab, Nivolumab, Pembrolizumab, Lenvatinib, Everolimus, CabozantinibAcarbose2USANot yet recruiting
6551272HCC34Atezolizumab, BevacizumabEXL01 (F. prausnitzii-based bacterial strain)2FranceNot yet recruiting
2960282Cancer21ICIFMTN/ASwitzerlandCompleted
3891979Pancreatic Adenocarcinoma0PembrolizumabCiprofloxacin + Metronidazole4USAWithdrawn
3595683Melanoma8PembrolizumabBifidobacterium longum EDP15032USAActive, not recruiting
3637803NSCLC, RCC, Melanoma, Bladder Cancer63PembrolizumabMRx0518 (a lyophilized proprietary bacterium strain)1/2USATerminated
3686202Solid tumors65Anti-PD-1/PD-L1MET-4 (Microbial Ecosystem Therapeutics-4)2/3CanadaActive, not recruiting
3775850CRC, Triple-negative breast cancer, NSCLC, Bladder, Gastroesophageal, RCC69PembrolizumabBifidobacterium longum EDP15031USA, CanadaCompleted
3817125Melanoma14NivolumabSER-401 (Live biotherapeutic products)1USACompleted
3829111RCC30Nivolumab + IpilimumabCBM588 (Butyricum CBM 588 probiotic strain)1USACompleted
4208958Melanoma, Gastric, Gastroesophageal Junction Adenocarcinoma, CRC56NivolumabVE800 (Live biotherapeutic products)1/2USACompleted
4601402Solid tumor, NSCLC, HNSCC, Urothelial Carcinoma11AvelumabLive biotherapeutic product GEN-0011USACompleted
4699721NSCLC60Nivolumab + Paclitaxel + CarboplatinBiFico (Bifidobacterium trifidum live powder)1ChinaActive, not recruiting
4909034NSCLC15PembrolizumabMS-20 (Fermented Soybean Extract MicroSoy-20)2TaiwanCompleted
5032014Liver46Anti-PD-1Probio-M9 (Lactobacillus rhamnosus)N/AChinaUnknown status
5094167NSCLC46Carrilizumab + PlatinumKex02 (Lactobacillus Bifidobacterium V9)N/AChinaUnknown status
5122546RCC31Nivolumab + CabozantinibCBM588 (C lostridium butyricum CBM 588 probiotic strain)1USAActive, not recruiting
5220124Bladder, Urothelial190ImmunotherapyLive combined Bifidobacterium, Lactobacillus and Enterococcus capsules4ChinaUnknown status
5354102NSCLC, Melanoma, RCC11BMC128 (live bio-therapeutic product composed of 4 commensal bacterial strains)BMC1281IsraelActive, not recruiting
5620004Advanced HCC30Carrilizumab + Apatinib MesylateBifidobacterium bifidum1/2ChinaUnknown status
5083416HNSCC29Nivolumab, Pembrolizumab, Atezolizumab, Avelumab, or DurvalumabProlonged nightly fastingN/AUSACompleted
Note: This table summarizes registered clinical trials investigating microbiome-modulating strategies in conjunction with cancer immunotherapies. Trials are listed with cancer types, enrollment numbers, immune checkpoint inhibitors or other immunotherapy agents used, the type of microbial intervention applied, phase, study location, and trial status (as of 18 March 2025). Trial identifiers (NCT numbers) are hyperlinked to their respective ClinicalTrials.gov pages. Abbreviations: NSCLC—non-small-cell lung cancer; RCC—renal cell carcinoma; HCC—hepatocellular carcinoma; CRC—colorectal cancer; HNSCC—head and neck squamous cell carcinoma; ICI—immune checkpoint inhibitor; FMT—fecal microbiota transplantation; PD-1—programmed death-1; PD-L1—programmed death-ligand 1.
Table 2. Currently registered clinical trials on microbiome-modulated chemotherapy.
Table 2. Currently registered clinical trials on microbiome-modulated chemotherapy.
NCT No.Cancer TypeEnrollmentChemotherapyMicrobial InterventionPhaseLocationStatus
2928523Acute myeloid leukaemia20Induction chemotherapySingle-arm: autologous FMT from pre-chemotherapy1/2FranceCompleted
2771470Lung cancer41Initiating chemotherapyRCT: Clostridium butyricum probiotic vs. placebo1ChinaCompleted
3314688Breast cancer173Initiating chemotherapyRCT: ACS recommended diet + exercise guidelinesN/AUSAActive, not recruiting
1410955CRC46Initiating irinotecanRCT: colon Dophilus probiotic vs. placebo3SlovakiaCompleted
2944617Metastatic kidney cancer21Initiating TKIsRCT: Activia yogurt (Bifidobacterium lactis)N/AUSACompleted
2819960CRC233Initiating irinotecanRCT: PROBIO-FIX INUM probiotic vs. placebo3SlovakiaCompleted
197873CRC84Initiating capecitabine, oxaliplatinRCT: Lactobacilli (GefilusR) vs. placeboN/AFinlandCompleted
3642548NSCLC180Initiating platinum-based chemotherapyRCT: Bifico vs. placebo3ChinaUnknown
3705442CRC76Treated with FOLFIRIRCT: Omni-Biotic 10 vs. placebo2CroatiaUnknown
4021589CRC40ChemotherapyWeileshu (probiotics)2ChinaCompleted
3870607Anal canal squamous cell cancer75Chemoradiotherapy (Ch-RT)Prebiotics + probiotics2BrazilUnknown
Note: This table presents registered clinical trials investigating microbial interventions in conjunction with chemotherapy for various cancer types retrieved from ClinicalTrials.gov as of 18 March 2025. Trials are categorized by cancer type, enrollment size, chemotherapeutic regimens (including irinotecan-, platinum-, or capecitabine-based protocols), type of microbial intervention (e.g., probiotics, prebiotics, dietary modifications, or fecal microbiota transplantation), study phase, location, and trial status (as of 18 March 2025). Trial identifiers (NCT numbers) are hyperlinked to their respective ClinicalTrials.gov pages. Abbreviations: CRC—colorectal cancer; NSCLC—non-small-cell lung cancer; FMT—fecal microbiota transplantation; RCT—randomized controlled trial; TKIs—tyrosine kinase inhibitors; FOLFIRI—folinic acid, fluorouracil, and irinotecan; ACS—American Cancer Society; PROBIO-FIX INUM—probiotic supplement containing Bifidobacterium animalis subsp. lactis BB-12® and Lactobacillus rhamnosus GG® (LGG®)
Table 3. Currently registered clinical trials of FMT modulating the gut microbiome in immunotherapy.
Table 3. Currently registered clinical trials of FMT modulating the gut microbiome in immunotherapy.
NCT No.Cancer TypeEnrollmentTreatmentMicrobial InterventionPhaseLocationStatus
5502913Lung Cancer80Immune Checkpoint InhibitorsFMT2IsraelRecruiting
5251389Melanoma24Anti-PD-1FMT1/2NetherlandsRecruiting
3819296Melanoma, Genitourinary, Malignant Solid Neoplasm800ICIsFMT from healthy donors2USARecruiting
4038619Genitourinary, Melanoma, Lung, Ovary, Uterus, Breast, Cervical40LoperamideFMT via colonoscopy1USARecruiting
6205862Colorectal Adenoma466NoneFMT2ChinaRecruiting
4975217PDAC10NoneFMT1USARecruiting
4988841Melanoma60Ipilimumab + NivolumabFecal microbiotherapy (MaaT013)2FranceRecruiting
3772899Melanoma20Pembrolizumab/NivolumabFMT capsules from healthy donors1CanadaActive, not recruiting
4163289RCC20Ipilimumab + NivolumabFMT capsules1CanadaActive, not recruiting
4729322Metastatic CRC15ICIsFMT capsules1/2ItalyActive, not recruiting
4951583NSCLC, Melanoma45Pembrolizumab, Ipilimumab + NivolumabInvestigational FMT2CanadaActive, not recruiting
5273255Malignancies18ICIsFMT via endoscopyN/ASwitzerlandCompleted
4924374Lung Cancer25Pembrolizumab, AtezolizumabFMT capsulesN/ASpainCompleted
3341143Melanoma20PembrolizumabFMT via colonoscopy from ICI responders2USACompleted
4056026Mesothelioma1Pembrolizumab (Keytruda)Single-dose FMT infusion1USACompleted
4130763GI System Cancer10Anti-PD-1FMT capsules1ChinaCompleted
3353402Melanoma40Anti-PD-1FMT capsules from ICI responders1IsraelUnknown
4116775Prostate Cancer32PembrolizumabFMT via endoscopy2USAUnknown
4264975Solid Carcinoma60ImmunotherapyFMTN/AKoreaUnknown
4521075Melanoma, NSCLC42NivolumabFMT capsules1/2IsraelUnknown
5008861NSCLC20Anti-PD-1/PD-L1FMT capsules1ChinaUnknown
4577729Malignant Melanoma5Pembrolizumab/NivolumabAllogenic FMT; Autologous FMTN/AAustriaTerminated
3812705Hematopoietic and Lymphoid Cell Neoplasm6N/AFMT2ChinaCompleted
5669846NSCLC26PembrolizumabResponder-derived FMT (R-FMT)2USARecruiting
5690048HCC48Atezolizumab + BevacizumabFMT2GermanyNot yet recruiting
Note: This table summarizes ongoing and completed clinical trials investigating the use of fecal microbiota transplantation (FMT) to modulate the gut microbiome in the context of cancer treatment. Included trials vary in cancer types, immunotherapy regimens (e.g., immune checkpoint inhibitors), and methods of FMT delivery (e.g., capsules, colonoscopy, or endoscopy). Trials also differ in donor source, such as healthy individuals or prior responders to immunotherapy. Key trial information includes cancer type, enrollment size, treatment, microbial intervention strategy, study phase, geographic location, and trial status (as of 18 March 2025). Trial identifiers (NCT numbers) are hyperlinked to their respective ClinicalTrials.gov pages. Abbreviations: FMT—fecal microbiota transplantation; ICI—immune checkpoint inhibitor; NSCLC—non-small-cell lung cancer; PDAC—pancreatic ductal adenocarcinoma; RCC—renal cell carcinoma; CRC—colorectal cancer; GI—gastrointestinal; HCC—hepatocellular carcinoma; PD-1—programmed death-1; PD-L1—programmed death-ligand 1.
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Kim, K.; Lee, M.; Shin, Y.; Lee, Y.; Kim, T.-J. Optimizing Cancer Treatment Through Gut Microbiome Modulation. Cancers 2025, 17, 1252. https://doi.org/10.3390/cancers17071252

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Kim K, Lee M, Shin Y, Lee Y, Kim T-J. Optimizing Cancer Treatment Through Gut Microbiome Modulation. Cancers. 2025; 17(7):1252. https://doi.org/10.3390/cancers17071252

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Kim, Kyuri, Mingyu Lee, Yoojin Shin, Yoonji Lee, and Tae-Jung Kim. 2025. "Optimizing Cancer Treatment Through Gut Microbiome Modulation" Cancers 17, no. 7: 1252. https://doi.org/10.3390/cancers17071252

APA Style

Kim, K., Lee, M., Shin, Y., Lee, Y., & Kim, T.-J. (2025). Optimizing Cancer Treatment Through Gut Microbiome Modulation. Cancers, 17(7), 1252. https://doi.org/10.3390/cancers17071252

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