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

James L Alexander; Joram M Posma; Alasdair Scott; Liam Poynter; Sam E Mason; M Luisa Doria; Lili Herendi; Lauren Roberts; Julie A K McDonald; Simon Cameron; David J Hughes; Vaclav Liska; Simona Susova; Pavel Soucek; Verena Horneffer-van der Sluis; Maria Gomez-Romero; Matthew R Lewis; Lesley Hoyles; Andrew Woolston; David Cunningham; Ara Darzi; Marco Gerlinger; Robert Goldin; Zoltan Takats; Julian R Marchesi; Julian Teare; James Kinross

doi:10.1186/s40168-023-01518-w

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

Microbiome. 2023 May 8;11(1):100. doi: 10.1186/s40168-023-01518-w.

Authors

James L Alexander^{1

2}, Joram M Posma³, Alasdair Scott⁴, Liam Poynter⁴, Sam E Mason⁴, M Luisa Doria⁴, Lili Herendi⁵, Lauren Roberts¹, Julie A K McDonald⁶, Simon Cameron⁷, David J Hughes⁸, Vaclav Liska⁹, Simona Susova¹⁰, Pavel Soucek¹⁰, Verena Horneffer-van der Sluis⁵, Maria Gomez-Romero⁵, Matthew R Lewis⁵, Lesley Hoyles^{1

11}, Andrew Woolston¹², David Cunningham¹³, Ara Darzi⁴, Marco Gerlinger^{12

13}, Robert Goldin¹, Zoltan Takats⁵, Julian R Marchesi¹⁴, Julian Teare⁴, James Kinross⁴

Affiliations

¹ Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Imperial College London, 10th Floor, QEQM Building, St. Mary's Hospital, Praed Street, London, W2 1NY, UK.
² Department of Gastroenterology, Imperial College Healthcare NHS Trust, London, UK.
³ Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
⁴ Department of Surgery & Cancer, Imperial College London, London, UK.
⁵ Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, UK.
⁶ Department of Life Sciences, MRC Centre for Molecular Bacteriology and Infection, Imperial College London, London, UK.
⁷ Institute of Global Food Security, School of Biosciences, Queen's University Belfast, Belfast, UK.
⁸ Cancer Biology and Therapeutics Group, School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Dublin, Ireland.
⁹ Department of Surgery, Faculty Hospital and Faculty of Medicine in Pilsen, Charles University in Prague, Pilsen, Czech Republic.
¹⁰ Faculty of Medicine in Pilsen, Biomedical Centre, Charles University in Prague, Pilsen, Czech Republic.
¹¹ Department of Biosciences, Nottingham Trent University, Nottingham, NG11 8NS, UK.
¹² Translational Oncogenomics Laboratory, The Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK.
¹³ GI Cancer Unit, Department of Medical Oncology, Royal Marsden NHS Foundation Trust, London, UK.
¹⁴ Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Imperial College London, 10th Floor, QEQM Building, St. Mary's Hospital, Praed Street, London, W2 1NY, UK. j.marchesi@imperial.ac.uk.

Abstract

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. Video Abstract.

Keywords: Colorectal cancer; Gut microbiota; Metabolome; Metataxonomics.

Publication types

Observational Study
Video-Audio Media
Research Support, Non-U.S. Gov't

MeSH terms

Chromatography, Liquid
Colorectal Neoplasms* / surgery
Gastrointestinal Microbiome* / genetics
Humans
Microbiota* / genetics
Tandem Mass Spectrometry

Abstract

Publication types

MeSH terms

Grants and funding