Non-invasive microbiome-derived multi-omic biomarkers for early-stage colorectal cancer detection

SCHEME: CORE

CALL: 2015

DOMAIN: BM - Life Sciences, Biology and Medicine

FIRST NAME: Paul

LAST NAME: Wilmes

INDUSTRY PARTNERSHIP / PPP: No

INDUSTRY / PPP PARTNER:

HOST INSTITUTION: University of Luxembourg

KEYWORDS: biomarker / colorectal cancer / extracellular RNA / integrated omics / metagenomics / microbiome

START: 2016-01-01

END: 2019-04-30

WEBSITE: https://www.uni.lu

Submitted Abstract

Aberrations in microbial community structure and function along the human gastrointestinal tract (GIT), specifically enrichments in adhesive and/or invasive facultative oral pathogens, including Fusobacterium spp., Peptostreptococcus stomatis and Porphyromonas asaccharolytica, are associated with colorectal cancer (CRC). Members of the project consortium have recently identified taxonomic markers by metagenomic sequencing of fecal samples, which allow accurate distinction between CRC patients and tumor-free controls. When combined with the standard fecal occult blood test (FOBT), the resulting biomarker model results in improved detection accuracy. Although functional gene enrichments are apparent in the already obtained metagenomic data, we hypothesize that by resolving information on transcript, protein and metabolite levels, we will be able to link specific CRC-associated microbial functional traits to the aforementioned populations of interest in samples from the two most CRC-relevant body sites, i.e. the oral cavity and colon/rectum, respectively. To achieve this, we will leverage novel methodologies recently developed within the project consortium for integrated omics of microbial communities (combined metagenomic, metatranscriptomic, metaproteomic and metabolomics analyses). Furthermore, given the enrichment of specific Gram-negative microbial taxa, in addition to the loss of epithelial barrier function at CRC tumor sites, we hypothesize that extracellular RNA of tumour-associated bacteria will be present and detectable in the blood of CRC patients thereby allowing complementary microbiome-enabled blood-based diagnostics of CRC. For this, we will relate RNAseq data from blood to microbial populations enriched on tumours. Using advanced computational, bioinformatics and modelling approaches, we will integrate the functional data from the different samples and refine/develop multivariate biomarker models for early non-invasive CRC detection prior to colonoscopy. Furthermore, the results obtained from the project will advance our understanding of CRC biology in identifying potential links between the oral microbiome, tumor-associated and intestinal microbiota. Such knowledge along with the developed biomarker models may allow a reduction in CRC-associated mortality in the future.

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