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Pathobionts in the tumour microbiota predict survival following resection for colorectal cancer

BACKGROUND AND AIMS: The gut microbiota is implicated in the pathogenesis of colorectal cancer (CRC). We aimed to map the CRC mucosal microbiota and metabolome and define the influence of the tumoral microbiota on oncological outcomes. METHODS: A multicentre, prospective observational study was cond...

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Autores principales: Alexander, James L., Posma, Joram M., Scott, Alasdair, Poynter, Liam, Mason, Sam E., Doria, M. Luisa, Herendi, Lili, Roberts, Lauren, McDonald, Julie A. K., Cameron, Simon, Hughes, David J., Liska, Vaclav, Susova, Simona, Soucek, Pavel, der Sluis, Verena Horneffer-van, Gomez-Romero, Maria, Lewis, Matthew R., Hoyles, Lesley, Woolston, Andrew, Cunningham, David, Darzi, Ara, Gerlinger, Marco, Goldin, Robert, Takats, Zoltan, Marchesi, Julian R., Teare, Julian, Kinross, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10165813/
https://www.ncbi.nlm.nih.gov/pubmed/37158960
http://dx.doi.org/10.1186/s40168-023-01518-w
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author Alexander, James L.
Posma, Joram M.
Scott, Alasdair
Poynter, Liam
Mason, Sam E.
Doria, M. Luisa
Herendi, Lili
Roberts, Lauren
McDonald, Julie A. K.
Cameron, Simon
Hughes, David J.
Liska, Vaclav
Susova, Simona
Soucek, Pavel
der Sluis, Verena Horneffer-van
Gomez-Romero, Maria
Lewis, Matthew R.
Hoyles, Lesley
Woolston, Andrew
Cunningham, David
Darzi, Ara
Gerlinger, Marco
Goldin, Robert
Takats, Zoltan
Marchesi, Julian R.
Teare, Julian
Kinross, James
author_facet Alexander, James L.
Posma, Joram M.
Scott, Alasdair
Poynter, Liam
Mason, Sam E.
Doria, M. Luisa
Herendi, Lili
Roberts, Lauren
McDonald, Julie A. K.
Cameron, Simon
Hughes, David J.
Liska, Vaclav
Susova, Simona
Soucek, Pavel
der Sluis, Verena Horneffer-van
Gomez-Romero, Maria
Lewis, Matthew R.
Hoyles, Lesley
Woolston, Andrew
Cunningham, David
Darzi, Ara
Gerlinger, Marco
Goldin, Robert
Takats, Zoltan
Marchesi, Julian R.
Teare, Julian
Kinross, James
author_sort Alexander, James L.
collection PubMed
description BACKGROUND AND AIMS: The gut microbiota is implicated in the pathogenesis of colorectal cancer (CRC). We aimed to map the CRC mucosal microbiota and metabolome and define the influence of the tumoral microbiota on oncological outcomes. METHODS: A multicentre, prospective observational study was conducted of CRC patients undergoing primary surgical resection in the UK (n = 74) and Czech Republic (n = 61). Analysis was performed using metataxonomics, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS), targeted bacterial qPCR and tumour exome sequencing. Hierarchical clustering accounting for clinical and oncological covariates was performed to identify clusters of bacteria and metabolites linked to CRC. Cox proportional hazards regression was used to ascertain clusters associated with disease-free survival over median follow-up of 50 months. RESULTS: Thirteen mucosal microbiota clusters were identified, of which five were significantly different between tumour and paired normal mucosa. Cluster 7, containing the pathobionts Fusobacterium nucleatum and Granulicatella adiacens, was strongly associated with CRC (P(FDR) = 0.0002). Additionally, tumoral dominance of cluster 7 independently predicted favourable disease-free survival (adjusted p = 0.031). Cluster 1, containing Faecalibacterium prausnitzii and Ruminococcus gnavus, was negatively associated with cancer (P(FDR) = 0.0009), and abundance was independently predictive of worse disease-free survival (adjusted p = 0.0009). UPLC-MS analysis revealed two major metabolic (Met) clusters. Met 1, composed of medium chain (MCFA), long-chain (LCFA) and very long-chain (VLCFA) fatty acid species, ceramides and lysophospholipids, was negatively associated with CRC (P(FDR) = 2.61 × 10(−11)); Met 2, composed of phosphatidylcholine species, nucleosides and amino acids, was strongly associated with CRC (P(FDR) = 1.30 × 10(−12)), but metabolite clusters were not associated with disease-free survival (p = 0.358). An association was identified between Met 1 and DNA mismatch-repair deficiency (p = 0.005). FBXW7 mutations were only found in cancers predominant in microbiota cluster 7. CONCLUSIONS: Networks of pathobionts in the tumour mucosal niche are associated with tumour mutation and metabolic subtypes and predict favourable outcome following CRC resection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-023-01518-w.
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spelling pubmed-101658132023-05-09 Pathobionts in the tumour microbiota predict survival following resection for colorectal cancer Alexander, James L. Posma, Joram M. Scott, Alasdair Poynter, Liam Mason, Sam E. Doria, M. Luisa Herendi, Lili Roberts, Lauren McDonald, Julie A. K. Cameron, Simon Hughes, David J. Liska, Vaclav Susova, Simona Soucek, Pavel der Sluis, Verena Horneffer-van Gomez-Romero, Maria Lewis, Matthew R. Hoyles, Lesley Woolston, Andrew Cunningham, David Darzi, Ara Gerlinger, Marco Goldin, Robert Takats, Zoltan Marchesi, Julian R. Teare, Julian Kinross, James Microbiome Research BACKGROUND AND AIMS: The gut microbiota is implicated in the pathogenesis of colorectal cancer (CRC). We aimed to map the CRC mucosal microbiota and metabolome and define the influence of the tumoral microbiota on oncological outcomes. METHODS: A multicentre, prospective observational study was conducted of CRC patients undergoing primary surgical resection in the UK (n = 74) and Czech Republic (n = 61). Analysis was performed using metataxonomics, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS), targeted bacterial qPCR and tumour exome sequencing. Hierarchical clustering accounting for clinical and oncological covariates was performed to identify clusters of bacteria and metabolites linked to CRC. Cox proportional hazards regression was used to ascertain clusters associated with disease-free survival over median follow-up of 50 months. RESULTS: Thirteen mucosal microbiota clusters were identified, of which five were significantly different between tumour and paired normal mucosa. Cluster 7, containing the pathobionts Fusobacterium nucleatum and Granulicatella adiacens, was strongly associated with CRC (P(FDR) = 0.0002). Additionally, tumoral dominance of cluster 7 independently predicted favourable disease-free survival (adjusted p = 0.031). Cluster 1, containing Faecalibacterium prausnitzii and Ruminococcus gnavus, was negatively associated with cancer (P(FDR) = 0.0009), and abundance was independently predictive of worse disease-free survival (adjusted p = 0.0009). UPLC-MS analysis revealed two major metabolic (Met) clusters. Met 1, composed of medium chain (MCFA), long-chain (LCFA) and very long-chain (VLCFA) fatty acid species, ceramides and lysophospholipids, was negatively associated with CRC (P(FDR) = 2.61 × 10(−11)); Met 2, composed of phosphatidylcholine species, nucleosides and amino acids, was strongly associated with CRC (P(FDR) = 1.30 × 10(−12)), but metabolite clusters were not associated with disease-free survival (p = 0.358). An association was identified between Met 1 and DNA mismatch-repair deficiency (p = 0.005). FBXW7 mutations were only found in cancers predominant in microbiota cluster 7. CONCLUSIONS: Networks of pathobionts in the tumour mucosal niche are associated with tumour mutation and metabolic subtypes and predict favourable outcome following CRC resection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-023-01518-w. BioMed Central 2023-05-08 /pmc/articles/PMC10165813/ /pubmed/37158960 http://dx.doi.org/10.1186/s40168-023-01518-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Alexander, James L.
Posma, Joram M.
Scott, Alasdair
Poynter, Liam
Mason, Sam E.
Doria, M. Luisa
Herendi, Lili
Roberts, Lauren
McDonald, Julie A. K.
Cameron, Simon
Hughes, David J.
Liska, Vaclav
Susova, Simona
Soucek, Pavel
der Sluis, Verena Horneffer-van
Gomez-Romero, Maria
Lewis, Matthew R.
Hoyles, Lesley
Woolston, Andrew
Cunningham, David
Darzi, Ara
Gerlinger, Marco
Goldin, Robert
Takats, Zoltan
Marchesi, Julian R.
Teare, Julian
Kinross, James
Pathobionts in the tumour microbiota predict survival following resection for colorectal cancer
title Pathobionts in the tumour microbiota predict survival following resection for colorectal cancer
title_full Pathobionts in the tumour microbiota predict survival following resection for colorectal cancer
title_fullStr Pathobionts in the tumour microbiota predict survival following resection for colorectal cancer
title_full_unstemmed Pathobionts in the tumour microbiota predict survival following resection for colorectal cancer
title_short Pathobionts in the tumour microbiota predict survival following resection for colorectal cancer
title_sort pathobionts in the tumour microbiota predict survival following resection for colorectal cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10165813/
https://www.ncbi.nlm.nih.gov/pubmed/37158960
http://dx.doi.org/10.1186/s40168-023-01518-w
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