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Microbial dysbiosis and polyamine metabolism as predictive markers for early detection of pancreatic cancer.

ABSTRACT: The lack of tools for early detection of pancreatic ductal adenocarcinoma (PDAC) is directly correlated with the abysmal survival rates in patients. In addition to several potential detection tools under active investigation, we tested the gut microbiome and its metabolic complement as one of the earliest detection tools that could be useful in patients at high risk for PDAC. We used a combination of 16s rRNA pyrosequencing and whole-genome sequencing of gut fecal microbiota in a genetically engineered PDAC murine model (KRASG12DTP53R172HPdxCre or KPC). Metabolic reconstruction of microbiome was done using the HUMAnN2 pipeline. Serum polyamine levels were measured from murine and patient samples using chromogenic assay. Our results showed a Proteobacterial and Firmicutes dominance in gut microbiota in early stages of PDAC development. Upon in silico reconstruction of active metabolic pathways within the altered microbial flora, polyamine and nucleotide biosynthetic pathways were significantly elevated. These metabolic products are known to be actively assimilated by the host and eventually utilized by rapidly dividing cells for proliferation validating their importance in the context of tumorigenesis. In KPC mice, as well as PDAC patients, we show significantly elevated serum polyamine concentrations. Therefore, at the early stages of tumorigenesis, there is a strong correlation between microbial changes and release of metabolites that foster host tumorigenesis, thereby fulfilling the 'vicious cycle hypothesis' of the role of microbiome in health and disease states. Our results provide a potential, precise, noninvasive tool for early detection of PDAC, which may result in improved outcomes.

SUBMITTER: Mendez R

PROVIDER: S-EPMC7350554 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe essential roles of gut microbiome have been emphasized in modulating human health and disease. Fusobacterium nucleatum (F. nucleatum), an obligate Gram-negative microorganism residing in oral cavity, gastrointestinal tract and elsewhere, has been recently considered as a potential oncobacterium associated with human cancers. However, the consequence of its enrichment was not extensively explored in terms of microbial homeostasis and stability at the early stage of disease development.ResultOur analysis on longitudinal metagenomic data generated by the Integrative Human Microbiome Project (iHMP) showed that F. nucleatum was frequently found in inflammatory bowel diseases (IBD) subjects with reduced microbial diversity. Using non-parametric logarithmic linear discriminant analysis (LDA) effect size (LEfSe) algorithm, 12 IBD- and 14 non-IBD-specific bacterial species were identified in the fecal metagenome and the IBD-specific ones were over-represented in the F. nucleatum-experienced subjects during long-term surveillance. In addition, F. nucleatum experience severely abrogated intra-personal stability of microbiome in IBD patients and induced highly variable gut microbiome between subjects. From the longitudinal comparison between microbial distributions prior and posterior to F. nucleatum detection, 41 species could be proposed as indicative "classifiers" for dysbiotic gut state. By multiple logistic regression models established on these classifiers, the high probability of experiencing F. nucleatum was significantly correlated with decreased alpha-diversity and increased number of biomarker species for IBD and colorectal cancer (CRC). Finally, microbial clustering confirmed that biomarker species for IBD and non-IBD conditions as well as CRC signature markers were well distinguishable and could be utilized for explaining gut symbiosis and dysbiosis.ConclusionF. nucleatum opportunistically appeared under early dysbiotic condition in gut, and discriminative classifier species associated with F. nucleatum were successfully applied to predict microbial alterations in both IBD and non-IBD conditions. Our prediction model and microbial classifier biomarkers for estimating gut dysbiosis should provide a novel aspect of microbial homeostasis/dynamics and useful information on non-invasive biomarker screening.

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Microbial dysbiosis and polyamine metabolism as predictive markers for early detection of pancreatic cancer.

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