Microbiome (May 2023)

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
https://doi.org/10.1186/s40168-023-01518-w
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 14

Abstract

Read online

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