Colorectal cancer mutational profiles correlate with defined microbial communities in the tumor microenvironment

Abstract

AbstractVariation in the gut microbiome has been linked to colorectal cancer (CRC), as well as to host genetic variation. However, we do not know whether, in addition to baseline host genetics, somatic mutational profiles in CRC tumors interact with the surrounding tumor microbiome, and if so, whether these changes can be used to understand microbe-host interactions with potential functional biological relevance. Here, we characterized the association between CRC microbial communities and tumor mutations using microbiome profiling and whole-exome sequencing in 44 pairs of tumors and matched normal tissues. We found statistically significant associations between loss-of-function mutations in tumor genes and shifts in the abundances of specific sets of bacterial taxa, suggestive of potential functional interaction. This correlation allows us to statistically predict interactions between loss-of-function tumor mutations in cancer-related genes and pathways, including MAPK and Wnt signaling, solely based on the composition of the microbiome. These results can serve as a starting point for fine-grained exploration of the functional interactions between discrete alterations in tumor DNA and proximal microbial communities in CRC. In addition, these findings can lead to the development of improved microbiome-based CRC screening methods, as well as individualized microbiota-targeting therapies.Author summaryAlthough the gut microbiome - the collection of microorganisms that inhabit our gastrointestinal tract - has been implicated in colorectal cancer, colorectal tumors are caused by genetic mutations in host DNA. Here, we explored whether various mutations in colorectal tumors are correlated with specific changes in the bacterial communities that live in and on these tumors. We find that the genes and biological pathways that are mutated in tumors are correlated with variation in the composition of the microbiome. In fact, these changes in the microbiome are consistent enough that we can use them to statistically predict tumor mutations solely based on the microbiome. Our results may be used to understand the roles of specific microbes in CRC biology, and could also be the starting point of microbiome-based diagnostics for not only detection of CRC, but characterization of tumor mutational profiles.