Publication
Alterations in Enteric Virome Are Associated With Colorectal Cancer and Survival Outcomes
Publisher:
Elsevier BV
Date:
08-2018
DOI:
10.1053/J.GASTRO.2018.04.018
Abstract: Patients with colorectal cancer (CRC) have a different gut microbiome signature than in iduals without CRC. Little is known about the viral component of CRC-associated microbiome. We aimed to identify and validate viral taxonomic markers of CRC that might be used in detection of the disease or predicting outcome. We performed shotgun metagenomic analyses of viromes of fecal s les from 74 patients with CRC (cases) and 92 in iduals without CRC (controls) in Hong Kong (discovery cohort). Viral sequences were classified by taxonomic alignment against an integrated microbial reference genome database. Viral markers associated with CRC were validated using fecal s les from 3 separate cohorts: 111 patients with CRC and 112 controls in Hong Kong, 46 patients with CRC and 63 controls in Austria, and 91 patients with CRC and 66 controls in France and Germany. Using abundance profiles of CRC-associated virome genera, we constructed random survival forest models to identify those associated with patient survival times. The ersity of the gut bacteriophage community was significantly increased in patients with CRC compared with controls. Twenty-two viral taxa discriminated cases from controls with an area under the receiver operating characteristic curve of 0.802 in the discovery cohort. The viral markers were validated in 3 cohorts, with area under the receiver operating characteristic curves of 0.763, 0.736, and 0.715, respectively. Clinical subgroup analysis showed that dysbiosis of the gut virome was associated with early- and late-stage CRC. A combination of 4 taxonomic markers associated with reduced survival of patients with CRC (log-rank test, P = 8.1 × 10 In a metagenomic analysis of fecal s les from patients and controls, we identified virome signatures associated with CRC. These data might be used to develop tools to identify in iduals with CRC or predict outcomes.