Identification and characterization of four bacteriome- and mycobiome-derived subtypes in tumour and adjacent mucosa tissue of colorectal cancer patients.

Objective: Here, we systematically investigated alterations in the bacteriome and mycobiome of CRC patients in tumours and matched adjacent mucosa resulting in the identification of microbiome-based subtypes associated with host clinico-pathological and molecular characteristics. Design: Diversity and composition of bacteriome and mycobiome of tumour and adjacent mucosa, resulting subtypes were computationally deconvoluted from RNA sequencing, using >10000 samples from in-house and publically available patient cohorts. Results: The bacteriome of tumours had higher dominance and lower α-diversity compared to matched adjacent local and distant mucosa. Tumours were enriched with Proteobacteria ( Gammaproteobacteria class), Fusobacteria (including Fusobacterium Nucleatum species) and Basidiomycota fungi ( Malasseziaceae family). Tumours were depleted of Bacteroidetes ( Bacteroidia class), Firmicutes ( Clostridia class) and Ascomycota ( Sordariomycetes and Saccharomycotina ). Tumours and adjacent mucosa samples were classified into 4 microbial subtypes, termed C1 to C4, based on the bacteriome and mycobiome composition. The bacterial Propionibacteriaceae , Enterobacteriaceae , Fusobacteriaceae , Bacteroidaceae and Ruminococcaceae and the fungal Malasseziaceae , Saccharomycetaceae and Aspergillaceae were among the key families driving the microbial subtyping. Microbial subtypes were associated with distinct tumour histology and patient phenotypes and served as an independent prognostic marker for disease-free survival. Key associations between microbial subtypes and alterations in host immune response and signalling pathways were validated in the TCGA pan-cancer cohort. The microbial subtyping demonstrated stratification value in the pan-cancer settings beyond merely representing differences in survival by cancer type. Conclusions: This study demonstrates the translational potential of microbial subtyping in CRC patient stratification, and provides avenues to design tailored microbiota modulation therapy to further precision oncology. ### Competing Interest Statement The authors have declared no competing interest.