Objective To evaluate the potential for diagnosing colorectal cancer (CRC) from faecal metagenomes. Design We performed metagenome-wide association studies on faecal samples from 74 patients with CRC and 54 controls from China, and validated the results in 16 patients and 24 controls from Denmark. We further validated the biomarkers in two published cohorts from France and Austria. Finally, we employed targeted quantitative PCR (qPCR) assays to evaluate diagnostic potential of selected biomarkers in an independent Chinese cohort of 47 patients and 109 controls. Results Besides confirming known associations of Fusobacterium nucleatum and Peptostreptococcus stomatis with CRC, we found significant associations with several species, including Parvimonas micra and Solobacterium moorei. We identified 20 microbial gene markers that differentiated CRC and control microbiomes, and validated 4 markers in the Danish cohort. In the French and Austrian cohorts, these four genes distinguished CRC metagenomes from controls with areas under the receiver-operating curve (AUC) of 0.72 and 0.77, respectively. qPCR measurements of two of these genes accurately classified patients with CRC in the independent Chinese cohort with AUC=0.84 and OR of 23. These genes were enriched in early-stage (I–II) patient microbiomes, highlighting the potential for using faecal metagenomic biomarkers for early diagnosis of CRC. Conclusions We present the first metagenomic profiling study of CRC faecal microbiomes to discover and validate microbial biomarkers in ethnically different cohorts, and to independently validate selected biomarkers using an affordable clinically relevant technology. Our study thus takes a step further towards affordable non-invasive early diagnostic biomarkers for CRC from faecal samples.

Objective: Non-alcoholic fatty liver disease (NAFLD)-associated hepatocellular carcinoma (HCC) is an increasing healthcare burden worldwide. We examined the role of dietary cholesterol in driving NAFLD–HCC through modulating gut microbiota and its metabolites. Design: High-fat/high-cholesterol (HFHC), high-fat/low-cholesterol or normal chow diet was fed to C57BL/6 male littermates for 14 months. Cholesterol-lowering drug atorvastatin was administered to HFHC-fed mice. Germ-free mice were transplanted with stools from mice fed different diets to determine the direct role of cholesterol modulated-microbiota in NAFLD–HCC. Gut microbiota was analysed by 16S rRNA sequencing and serum metabolites by liquid chromatography–mass spectrometry (LC–MS) metabolomic analysis. Faecal microbial compositions were examined in 59 hypercholesterolemia patients and 39 healthy controls. Results: High dietary cholesterol led to the sequential progression of steatosis, steatohepatitis, fibrosis and eventually HCC in mice, concomitant with insulin resistance. Cholesterol-induced NAFLD–HCC formation was associated with gut microbiota dysbiosis. The microbiota composition clustered distinctly along stages of steatosis, steatohepatitis and HCC. Mucispirillum, Desulfovibrio, Anaerotruncus and Desulfovibrionaceae increased sequentially; while Bifidobacterium and Bacteroides were depleted in HFHC-fed mice, which was corroborated in human hypercholesteremia patients. Dietary cholesterol induced gut bacterial metabolites alteration including increased taurocholic acid and decreased 3-indolepropionic acid. Germ-free mice gavaged with stools from mice fed HFHC manifested hepatic lipid accumulation, inflammation and cell proliferation. Moreover, atorvastatin restored cholesterol-induced gut microbiota dysbiosis and completely prevented NAFLD–HCC development. Conclusions: Dietary cholesterol drives NAFLD–HCC formation by inducing alteration of gut microbiota and metabolites in mice. Cholesterol inhibitory therapy and gut microbiota manipulation may be effective strategies for NAFLD–HCC prevention.

Gut microbial dysbiosis contributes to the development of colorectal cancer (CRC). Here we catalogue the microbial communities in human gut mucosae at different stages of colorectal tumorigenesis. We analyse the gut mucosal microbiome of 47 paired samples of adenoma and adenoma-adjacent mucosae, 52 paired samples of carcinoma and carcinoma-adjacent mucosae and 61 healthy controls. Probabilistic partitioning of relative abundance profiles reveals that a metacommunity predominated by members of the oral microbiome is primarily associated with CRC. Analysis of paired samples shows differences in community configurations between lesions and the adjacent mucosae. Correlations of bacterial taxa indicate early signs of dysbiosis in adenoma, and co-exclusive relationships are subsequently more common in cancer. We validate these alterations in CRC-associated microbiome by comparison with two previously published data sets. Our results suggest that a taxonomically defined microbial consortium is implicated in the development of CRC.

Objectives: We aimed to characterise the microbial changes associated with histological stages of gastric tumourigenesis. Design: We performed 16S rRNA gene analysis of gastric mucosal samples from 81 cases including superficial gastritis (SG), atrophic gastritis (AG), intestinal metaplasia (IM) and gastric cancer (GC) from Xi’an, China, to determine mucosal microbiome dysbiosis across stages of GC. We validated the results in mucosal samples of 126 cases from Inner Mongolia, China. Results: We observed significant mucosa microbial dysbiosis in IM and GC subjects, with significant enrichment of 21 and depletion of 10 bacterial taxa in GC compared with SG (q<0.05). Microbial network analysis showed increasing correlation strengths among them with disease progression (p<0.001). Five GC-enriched bacterial taxa whose species identifications correspond to Peptostreptococcus stomatis , Streptococcus anginosus , Parvimonas micra , Slackia exigua and Dialister pneumosintes had significant centralities in the GC ecological network (p<0.05) and classified GC from SG with an area under the receiver-operating curve (AUC) of 0.82. Moreover, stronger interactions among gastric microbes were observed in Helicobacter pylori -negative samples compared with H. pylori -positive samples in SG and IM. The fold changes of selected bacteria, and strengths of their interactions were successfully validated in the Inner Mongolian cohort, in which the five bacterial markers distinguished GC from SG with an AUC of 0.81. Conclusions: In addition to microbial compositional changes, we identified differences in bacterial interactions across stages of gastric carcinogenesis. The significant enrichments and network centralities suggest potentially important roles of P. stomatis , D. pneumosintes , S. exigua , P. micra and S. anginosus in GC progression.