A gut-on-a-chip incorporating human faecal samples and peristalsis predicts responses to immune checkpoint inhibitors for melanoma

Study information

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study design

case-control

Citation

PMID PubMed identifier for scientific articles.

39939548

DOI Digital object identifier for electronic documents.

https://doi.org/10.1038/s41551-024-01318-z

URI Uniform resource identifier for web resources.

https://www.nature.com/articles/s41551-024-01318-z

Authors

Ballerini M, Galiè S, Tyagi P, Catozzi C, Raji H, Nabinejad A, Macandog ADG, Cordiale A, Slivinschi BI, Kugiejko KK, Freisa M, Occhetta P, Wargo JA, Ferrucci PF, Cocorocchio E, Segata N, Vignati A, Morgun A, Deleidi M, Manzo T, Rasponi M, Nezi L

Journal

Nature biomedical engineering

Year

2025

Patient responses to immune checkpoint inhibitors can be influenced by the gastrointestinal microbiome. Mouse models can be used to study microbiome-host crosstalk, yet their utility is constrained by substantial anatomical, functional, immunological and microbial differences between mice and humans. Here we show that a gut-on-a-chip system mimicking the architecture and functionality of the human intestine by including faecal microbiome and peristaltic-like movements recapitulates microbiome-host interactions and predicts responses to immune checkpoint inhibitors in patients with melanoma. The system is composed of a vascular channel seeded with human microvascular endothelial cells and an intestinal channel with intestinal organoids derived from human induced pluripotent stem cells, with the two channels separated by a collagen matrix. By incorporating faecal samples from patients with melanoma into the intestinal channel and by performing multiomic analyses, we uncovered epithelium-specific biomarkers and microbial factors that correlate with clinical outcomes in patients with melanoma and that the microbiome of non-responders has a reduced ability to buffer cellular stress and self-renew. The gut-on-a-chip model may help identify prognostic biomarkers and therapeutic targets.

Experiment 1

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Reviewed Marked as Reviewed by Svetlana up on 2025-2-26

Curated date: 2025/02/19

Curator: An05hka

Revision editor(s): An05hka

Subjects

Location of subjects: Italy

Host species Species from which microbiome was sampled. Contact us to have more species added.: Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: Response to immune checkpoint inhibitor response to ICI,Response to immune checkpoint inhibitor,response to immune checkpoint inhibitor

Group 0 name Corresponds to the control (unexposed) group for case-control studies: Non-Responsive Patients

Group 1 name Corresponds to the case (exposed) group for case-control studies: Responsive Patients

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Melanoma patients who are responsive to immunotherapy

Group 0 sample size Number of subjects in the control (unexposed) group: 5

Group 1 sample size Number of subjects in the case (exposed) group: 4

Lab analysis

Sequencing type: WMS

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: Not specified

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).: relative abundances

Statistical test: Mann-Whitney (Wilcoxon)

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05

MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: No

Signature 1

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Source: figure 6 a.

Description: Heat map of top (responsive)R- and (non-responsive) NR-associated taxa based on Wilcoxon test unadjusted P < 0.05.

Abundance in Group 1: increased abundance in Responsive Patients

NCBI	Quality Control	Links
Actinomyces radicidentis
Actinomyces sp. oral taxon 448
Bacilliculturomica massiliensis
Bacteroides sp. Marseille-P3684
Clostridium sp. SN20
Coprococcus eutactus
Clostridia unclassified SGB4447Clostridia unclassified SGB4447
Blautia SGB4831Blautia SGB4831
Bacilli unclassified SGB6422Bacilli unclassified SGB6422
Archnia SGB15898Archnia SGB15898

Revision editor(s): An05hka

Signature 2

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Curated date: 2025/02/19

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Revision editor(s): An05hka

Source: figure 6 a.

Description: Heat map of top (responsive)R- and (non-responsive) NR-associated taxa based on Wilcoxon test unadjusted P < 0.05

Abundance in Group 1: decreased abundance in Responsive Patients

NCBI	Quality Control	Links
Allisonella histaminiformans
Alphaproteobacteria bacterium
Anaerococcus prevotii
Candidatus Gallimonas merdae
Candidatus Neochristensenella gallicola
Catenibacterium sp. AM22-15
Clostridiaceae bacterium
Clostridium sp. AF34-10BH
Dorea phocaeensis
Enterococcus raffinosus
Mogibacterium kristiansenii
Thomasclavelia spiroformis
[Clostridium] hylemonae
Clostridia unclassified SGB6371Clostridia unclassified SGB6371
Gemmiger SGB15299Gemmiger SGB15299
Butyricimonas SGB1783Butyricimonas SGB1783
Butyricicoccus SGB14985Butyricicoccus SGB14985
Dysosmobacter welbionis

Revision editor(s): An05hka