Long term follow-up of colorectal cancer screening 1 attendees identifies differences in 2 Phascolarctobacterium spp. using 16S rRNA and 3 metagenome sequencing

the

[1]  R. Donegan,et al.  The role of host heme in bacterial infection , 2022, Biological chemistry.

[2]  J. Ferlay,et al.  Global burden of colorectal cancer in 2020 and 2040: incidence and mortality estimates from GLOBOCAN , 2022, Gut.

[3]  H. Clevers,et al.  Gut Microbiota in Colorectal Cancer: Associations, Mechanisms, and Clinical Approaches , 2021, Annual Review of Cancer Biology.

[4]  M. Reberšek.  Gut microbiome and its role in colorectal cancer , 2021, BMC Cancer.

[5]  Biao Yuan,et al.  Fecal Bacteria as Non-Invasive Biomarkers for Colorectal Adenocarcinoma , 2021, Frontiers in Oncology.

[6]  P. Manghi,et al.  Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 , 2020, bioRxiv.

[7]  R. Knight,et al.  Host variables confound gut microbiota studies of human disease , 2020, Nature.

[8]  Gavin M Douglas,et al.  PICRUSt2 for prediction of metagenome functions , 2020, Nature Biotechnology.

[9]  Paul Wilmes,et al.  Microbiome in Colorectal Cancer: How to Get from Meta-omics to Mechanism? , 2020, Trends in microbiology.

[10]  Shuaicheng Li,et al.  Establishing high-accuracy biomarkers for colorectal cancer by comparing fecal microbiomes in patients with healthy families , 2020, Gut microbes.

[11]  Bangmao Wang,et al.  Clostridium butyricum, a butyrate-producing probiotic, inhibits intestinal tumor development through modulating Wnt signaling and gut microbiota. , 2019, Cancer letters.

[12]  J. Vendrell,et al.  Gut microbiota-derived succinate: Friend or foe in human metabolic diseases? , 2019, Reviews in Endocrine and Metabolic Disorders.

[13]  Jun Yu,et al.  Gut microbiota in colorectal cancer: mechanisms of action and clinical applications , 2019, Nature Reviews Gastroenterology & Hepatology.

[14]  Francesco Asnicar,et al.  Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 , 2019, Nature Biotechnology.

[15]  Cheng Hu,et al.  Altered intestinal microbiota associated with colorectal cancer , 2019, Frontiers of Medicine.

[16]  Takuji Yamada,et al.  Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer , 2019, Nature Medicine.

[17]  Paul Theodor Pyl,et al.  Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer , 2019, Nature Medicine.

[18]  H. Asadzadeh Aghdaei,et al.  The association between fecal microbiota and different types of colorectal polyp as precursors of colorectal cancer. , 2018, Microbial pathogenesis.

[19]  Alexander S. Banks,et al.  Accumulation of succinate controls activation of adipose tissue thermogenesis , 2018, Nature.

[20]  W. D. de Vos,et al.  Reproducibility and repeatability of six high-throughput 16S rDNA sequencing protocols for microbiota profiling. , 2018, Journal of microbiological methods.

[21]  Hadley Wickham,et al.  ggplot2 - Elegant Graphics for Data Analysis (2nd Edition) , 2017 .

[22]  Yeojun Yun,et al.  Fecal Microbiota Differences According to the Risk of Advanced Colorectal Neoplasms , 2017, Journal of clinical gastroenterology.

[23]  S. O'keefe.  Diet, microorganisms and their metabolites, and colon cancer , 2016, Nature Reviews Gastroenterology &Hepatology.

[24]  Jun Yu,et al.  Quantitation of faecal Fusobacterium improves faecal immunochemical test in detecting advanced colorectal neoplasia , 2016, Gut.

[25]  F. Bäckhed,et al.  Microbiota-Produced Succinate Improves Glucose Homeostasis via Intestinal Gluconeogenesis. , 2016, Cell metabolism.

[26]  Måns Magnusson,et al.  MultiQC: summarize analysis results for multiple tools and samples in a single report , 2016, Bioinform..

[27]  Paul J. McMurdie,et al.  DADA2: High resolution sample inference from Illumina amplicon data , 2016, Nature Methods.

[28]  P. Schloss,et al.  Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions , 2016, Genome Medicine.

[29]  Qiang Feng,et al.  Metagenomic analysis of faecal microbiome as a tool towards targeted non-invasive biomarkers for colorectal cancer , 2015, Gut.

[30]  M. Zappa,et al.  Impact of Screening Program on Incidence of Colorectal Cancer: A Cohort Study in Italy , 2015, The American Journal of Gastroenterology.

[31]  J. Goedert,et al.  Collection media and delayed freezing effects on microbial composition of human stool , 2015, Microbiome.

[32]  S. Chiou,et al.  Effectiveness of fecal immunochemical testing in reducing colorectal cancer mortality from the One Million Taiwanese Screening Program , 2015, Cancer.

[33]  Qiang Feng,et al.  Gut microbiome development along the colorectal adenoma–carcinoma sequence , 2015, Nature Communications.

[34]  A. Mira,et al.  Microbial mucosal colonic shifts associated with the development of colorectal cancer reveal the presence of different bacterial and archaeal biomarkers , 2015, Journal of Gastroenterology.

[35]  W. Huber,et al.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.

[36]  M. Hernán,et al.  Effect of flexible sigmoidoscopy screening on colorectal cancer incidence and mortality: a randomized clinical trial. , 2014, JAMA.

[37]  P. Schloss,et al.  The Human Gut Microbiome as a Screening Tool for Colorectal Cancer , 2014, Cancer Prevention Research.

[38]  Björn Usadel,et al.  Trimmomatic: a flexible trimmer for Illumina sequence data , 2014, Bioinform..

[39]  Robert G. Beiko,et al.  A Phylogenomic View of Ecological Specialization in the Lachnospiraceae, a Family of Digestive Tract-Associated Bacteria , 2014, Genome biology and evolution.

[40]  Susan Holmes,et al.  phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data , 2013, PloS one.

[41]  A. Klindworth,et al.  Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies , 2012, Nucleic acids research.

[42]  Marcel Martin.  Cutadapt removes adapter sequences from high-throughput sequencing reads , 2011 .

[43]  Cole Trapnell,et al.  Ultrafast and memory-efficient alignment of short DNA sequences to the human genome , 2009, Genome Biology.

[44]  E. Haglind,et al.  Survival benefit in a randomized clinical trial of faecal occult blood screening for colorectal cancer , 2008, The British journal of surgery.

[45]  H. Flint,et al.  The microbiology of butyrate formation in the human colon. , 2002, FEMS microbiology letters.

[46]  M. Vatn,et al.  Design, Organization and Management of a Controlled Population Screening Study for Detection of Colorectal Neoplasia: Attendance Rates in the NORCCAP Study (Norwegian Colorectal Cancer Prevention) , 2002, Scandinavian journal of gastroenterology.

[47]  J. Hardcastle,et al.  Colorectal cancer , 1993, Europe Against Cancer European Commission Series for General Practitioners.