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Medical treatment

David Surendran Sanders 1

1 Royal Hallamshire Hospital - NHS Trust, Royal Hallamshire Hospital; Sheffield/GB, Sheffield, United Kingdom

Event

UEG Week Berlin 2025

Topics

Immunology Small Intestine & Nutrition

Session

Coeliac or non-coeliac enteropathy?

Citation

United European Gastroenterology Journal 2025; 13 (Supplement 8)

Published

2025

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Advancing IBD precision medicine: The next frontier

Bram Verstockt 1

1 University Hospitals Leuven and KU Leuven, Translational Research in Gastrointestinal Disorders - IB, Leuven, Belgium

Event

UEG Week Berlin 2025

Topics

IBD Mechanisms & Personalised Medicine

Session

The art of making clinical research precise: Predicting therapy response in IBD

Citation

United European Gastroenterology Journal 2025; 13 (Supplement 8)

Published

2025

UEG Presentation

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MICROPLASTIC-INDUCED ALTERATIONS IN GUT MICROBIOME AND METABOLISM: INSIGHTS FROM AN EX VIVO BIOREACTOR MODEL

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Introduction

Microplastic particles (MPs), defined as plastic fragments smaller than 5 mm, are pervasive pollutants that accumulate in ecosystems and the human food chain (1). Literature points at various health risks, including the induction of carcinogenesis (2). Emerging evidence from animal models (3) suggests that MPs may influence the gut microbiome, but the impact on the human gut microbiome remains poorly understood.

Aims & Methods

This study aimed to evaluate how various MP types influence gut microbial composition and metabolism using an ex vivo bioreactor model, with a focus on exploring potential carcinogenic effects arising from MP–microbiome interactions.
Stool samples from healthy donors were used to inoculate bioreactor cultures, which were maintained under anaerobic conditions for five days with daily nutrient feeding. These cultures were exposed to five common MP types—polystyrene (PS), polypropylene (PP), low-density polyethylene (LDPE), poly(methyl methacrylate) (PMMA), and polyethylene terephthalate (PET)—at concentrations mimicking both estimated human exposure (4) and higher doses to assess dose-dependence. Cell viability and total bacterial counts, as well as culture pH, were measured throughout the experiment. To further explore potential microbiome and metabolic alterations, 16S rRNA gene sequencing and targeted metabolomics were performed.

Results

MP exposure did not lead to significant changes in total or viable bacterial cell counts. However, MP-treated cultures exhibited a consistent and significant decrease in pH compared to controls, suggesting changes in microbial metabolic activity. Microbiome sequencing revealed plastic-type-dependent alterations in microbial composition, with certain bacterial taxa increasing or decreasing in abundance depending on the MP type. These shifts occurred across multiple genera within diverse families, including Lachnospiraceae, Oscillospiraceae, Enterobacteriaceae, and Ruminococcaceae, with the majority of changes occurring withing the phylum Bacillota. These compositional changes were accompanied by shifts in the metabolomic profiles, some of which correlated with the observed pH changes. Several plastic types induced changes in valeric acid levels, while individual MP types were associated with alterations in distinct metabolites such as uracil, lactic acid, and acetic acid.

Conclusion

This study demonstrates that MPs can affect gut microbial activity and metabolism without significantly altering overall bacterial abundance in the short term. The variation in microbiome response across plastic types highlights the complexity of MP-microbiome interactions. Changes in faecal pH are known to be associated with various gastrointestinal diseases (5). Interestingly, some of the MP-induced changes in microbial composition resembled patterns linked to diseases such as depression and colorectal cancer. In contrast, other changes showed patterns that differed from those typically associated with conditions like Parkinson’s disease and irritable bowel syndrome, highlighting the complexity of these associations and the dependency on the context. The bioreactor model provided a controlled environment for identifying direct MP-microbiome interactions; however, in humans, additional factors like diet, immune response, and individual microbiome variations play a role in determining long-term effects. Exposure duration may also play a critical role in shaping the extent and nature of microbiome alterations (6), underscoring the need for further research into the effects of chronic MP exposure and associated health risks.

References

(1) Mamun, A. A., Prasetya, T. A. E., Dewi, I. R., & Ahmad, M. (2023). Microplastics in human food chains: Food becoming a threat to health safety. The Science of the total environment, 858(Pt 1), 159834. https://doi.org/10.1016/j.scitotenv.2022.159834
(2) Kumar, R., Manna, C., Padha, S., Verma, A., Sharma, P., Dhar, A., Ghosh, A., & Bhattacharya, P. (2022). Micro(nano)plastics pollution and human health: How plastics can induce carcinogenesis to humans?. Chemosphere, 298, 134267. https://doi.org/10.1016/j.chemosphere.2022.134267
(3) Hirt, N., & Body-Malapel, M. (2020). Immunotoxicity and intestinal effects of nano- and microplastics: a review of the literature. Particle and fibre toxicology, 17(1), 57. https://doi.org/10.1186/s12989-020-00387-7
(4) Senathirajah, K., Attwood, S., Bhagwat, G., Carbery, M., Wilson, S., & Palanisami, T. (2021). Estimation of the mass of microplastics ingested - A pivotal first step towards human health risk assessment. Journal of hazardous materials, 404(Pt B), 124004. https://doi.org/10.1016/j.jhazmat.2020.124004
(5) Yamamura, R., Inoue, K. Y., Nishino, K., & Yamasaki, S. (2023). Intestinal and fecal pH in human health. Frontiers in Microbiomes, 2, 1192316.
(6) Yin, L., Yang, M., Teng, A., Ni, C., Wang, P., & Tang, S. (2025). Unraveling Microplastic Effects on Gut Microbiota across Various Animals Using Machine Learning. ACS nano, 19(1), 369–380. https://doi.org/10.1021/acsnano.4c07885

MICROPLASTIC-INDUCED ALTERATIONS IN GUT MICROBIOME AND METABOLISM: INSIGHTS FROM AN EX VIVO BIOREACTOR MODEL

Christian Pacher-Deutsch 1, Kristina Žukauskaitė 1, Cigdem Akar 2, Maximilian Nepel 2, Lukas Kogler 3, Hansjörg Habisch 2, Serena Ducoli 4, Stefania Federici 4, Tobias Madl 5, Verena Pichler 6, Angela Horvath 1, Vanessa Stadlbauer 7

1 Center for Biomarker Research in Medicine (CBmed), Graz, Austria|||Medical University of Graz, Graz, Austria

2 Medical University of Graz, Graz, Austria

3 Center for Biomarker Research in Medicine (CBmed), Graz, Austria|||University of Vienna, Vienna, Austria|||Medical University of Vienna, Vienna, Austria

4 University of Brescia, Brescia, Italy

5 Medical University of Graz, Graz, Austria|||BioTechMed-Graz, Graz, Austria

6 Center for Biomarker Research in Medicine (CBmed), Graz, Austria|||University of Vienna, Vienna, Austria

7 Center for Biomarker Research in Medicine (CBmed), Graz, Austria|||Medical University of Graz, Graz, Austria|||BioTechMed-Graz, Graz, Austria

Event

UEG Week Berlin 2025

Topics

Gut Microbiota Colorectal

Submission format

Abstract

Session

The gut ecosystem: From pathogenesis to treatment

Citation

United European Gastroenterology Journal 2025; 13 (Supplement 8)

Published

2025

UEG Presentation

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GUT MYCOBIOME SIGNATURES PREDICT NEOADJUVANT IMMUNOCHEMOTHERAPY RESPONSE IN ESOPHAGEAL SQUAMOUS CELL CARCINOMA: A MACHINE LEARNING APPROACH WITH EXPERIMENTAL VALIDATION

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Introduction

Esophageal squamous cell carcinoma (ESCC) is associated with poor prognosis despite advances in neoadjuvant immunochemotherapy (NICT). With highly variable treatment responses, identifying reliable predictive biomarkers remains crucial. While gut microbiome influences on immunotherapy efficacy are increasingly recognized, the specific role of the fungal microbiome (mycobiome) in NICT outcomes for ESCC remains unexplored, representing a significant gap in developing personalized treatment strategies.

Aims & Methods

This study aimed to characterize gut mycobiome signatures in ESCC patients and develop fungal biomarker-based predictive models for NICT response. We conducted ITS2 sequencing on 136 fecal samples collected from 68 ESCC patients (pre- and post-NICT) and 19 healthy controls (HC). Patients were stratified as responders (R, n=26) or non-responders (NR, n=42) based on tumor regression grade (TRG) scores. We performed comprehensive analyses of mycobiome diversity, composition, co-occurrence networks, and functional pathways across groups. The Boruta algorithm was employed for feature selection to identify fungal biomarkers, followed by multilayer perceptron (MLP) machine learning with five-fold cross-validation to develop predictive models. Additionally, ESCC xenograft models were established to investigate gut mycobiome-immune interactions through fecal microbiota transplantation (FMT) and targeted fungal manipulation experiments.

Results

ESCC patients demonstrated significant mycobiome dysbiosis compared to healthy controls, characterized by reduced fungal alpha diversity and distinct beta diversity patterns. At baseline, ESCC patients showed enrichment of Rhodotorula minuta, Actinomucor elegans, and several Candida species. Responders exhibited significantly higher baseline fungal diversity than non-responders, with enrichment of Meyerozyma, Candida boidinii, Trichosporon dermatis, and Cryptococcus species, whereas non-responders showed predominance of Saccharomyces, Nakaseomyces, and pathogenic Candida species (C. glabrata, C. parapsilosis, C. albicans). Responders also displayed more complex, stable fungal co-occurrence networks with higher density and clustering coefficients. Post-NICT, both groups showed partial recovery of mycobiome diversity, with significant increases in beneficial fungal taxa. Functional pathway analysis revealed distinct metabolic profiles between responders and non-responders. Using the Boruta algorithm, we identified 23 genus-level and 22 species-level fungal biomarkers that demonstrated high predictive value. The MLP model based on genus-level markers achieved AUCs of 90.2% (training) and 91.9% (test), while the species-level model showed comparable performance. In animal experiments, mice receiving R-FMT exhibited reduced tumor growth and enhanced CD8+ T cell infiltration compared to NR-FMT recipients. Notably, Candida boidinii supplementation synergized with anti-PD-1 therapy, while Saccharomyces depletion enhanced treatment sensitivity.

Conclusion

Our findings establish the gut mycobiome as a powerful predictor of NICT response in ESCC, with machine learning models achieving >90% accuracy using fungal biomarkers. Experimental validation not only confirms mechanistic links between specific fungi and antitumor immunity but also demonstrates that targeted mycobiome modulation can enhance immunotherapy efficacy. This dual approach of prediction and intervention offers a novel framework for precision oncology in ESCC, potentially transforming clinical decision-making and treatment outcomes in this challenging malignancy.

References

1. Li J, Xu J, Zheng Y, et al. Esophageal cancer: Epidemiology, risk factors and screening. Chin J Cancer Res. 2021; 33(5): 535-547.
2. van Hagen P, Hulshof MC, van Lanschot JJ, et al. Preoperative chemoradiotherapy for esophageal or junctional cancer. N Engl J Med. 2012; 366(22): 2074-2084.
3. Schroeder W, Ghadimi M, Schloesser H, et al. Long-Term Outcome After Histopathological Complete Response with and Without Nodal Metastases Following Multimodal Treatment of Esophageal Cancer. Ann Surg Oncol. 2022.
4. Rosner S, Liu C, Forde PM, Hu C. Association of Pathologic Complete Response and Long-Term Survival Outcomes Among Patients Treated With Neoadjuvant Chemotherapy or Chemoradiotherapy for NSCLC: A Meta-Analysis. JTO Clin Res Rep. 2022; 3(9): 100384.
5. Coker OO, Nakatsu G, Dai RZ, et al. Enteric fungal microbiota dysbiosis and ecological alterations in colorectal cancer. Gut. 2019; 68(4): 654-662.
6. Dohlman AB, Klug J, Mesko M, et al. A pan-cancer mycobiome analysis reveals fungal involvement in gastrointestinal and lung tumors. Cell. 2022; 185(20): 3807-3822.
7. Wurster S, Albert ND, Kontoyiannis DP. Candida auris Bloodstream Infection Induces Upregulation of the PD-1/PD-L1 Immune Checkpoint Pathway in an Immunocompetent Mouse Model. Msphere. 2022; 7(2): e81721.