Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-04-01

AUTHORS

Andrew Maltez Thomas, Paolo Manghi, Francesco Asnicar, Edoardo Pasolli, Federica Armanini, Moreno Zolfo, Francesco Beghini, Serena Manara, Nicolai Karcher, Chiara Pozzi, Sara Gandini, Davide Serrano, Sonia Tarallo, Antonio Francavilla, Gaetano Gallo, Mario Trompetto, Giulio Ferrero, Sayaka Mizutani, Hirotsugu Shiroma, Satoshi Shiba, Tatsuhiro Shibata, Shinichi Yachida, Takuji Yamada, Jakob Wirbel, Petra Schrotz-King, Cornelia M. Ulrich, Hermann Brenner, Manimozhiyan Arumugam, Peer Bork, Georg Zeller, Francesca Cordero, Emmanuel Dias-Neto, João Carlos Setubal, Adrian Tett, Barbara Pardini, Maria Rescigno, Levi Waldron, Alessio Naccarati, Nicola Segata

ABSTRACT

Several studies have investigated links between the gut microbiome and colorectal cancer (CRC), but questions remain about the replicability of biomarkers across cohorts and populations. We performed a meta-analysis of five publicly available datasets and two new cohorts and validated the findings on two additional cohorts, considering in total 969 fecal metagenomes. Unlike microbiome shifts associated with gastrointestinal syndromes, the gut microbiome in CRC showed reproducibly higher richness than controls (P < 0.01), partially due to expansions of species typically derived from the oral cavity. Meta-analysis of the microbiome functional potential identified gluconeogenesis and the putrefaction and fermentation pathways as being associated with CRC, whereas the stachyose and starch degradation pathways were associated with controls. Predictive microbiome signatures for CRC trained on multiple datasets showed consistently high accuracy in datasets not considered for model training and independent validation cohorts (average area under the curve, 0.84). Pooled analysis of raw metagenomes showed that the choline trimethylamine-lyase gene was overabundant in CRC (P = 0.001), identifying a relationship between microbiome choline metabolism and CRC. The combined analysis of heterogeneous CRC cohorts thus identified reproducible microbiome biomarkers and accurate disease-predictive models that can form the basis for clinical prognostic tests and hypothesis-driven mechanistic studies. More... »

PAGES

667-678

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  • Journal

    TITLE

    Nature Medicine

    ISSUE

    4

    VOLUME

    25

    Author Affiliations

  • Medical Genomics Laboratory, CIPE/A.C. Camargo Cancer Center, São Paulo, Brazil
  • Department CIBIO, University of Trento, Trento, Italy
  • IEO, European Institute of Oncology IRCCS, Milan, Italy
  • Italian Institute for Genomic Medicine, Turin, Italy
  • Department of Colorectal Surgery, Clinica S. Rita, Vercelli, Italy
  • Department of Computer Science, University of Turin, Turin, Italy
  • Research Fellow of Japan Society for the Promotion of Science, Tokyo, Japan
  • School of Life Science and Technology, Tokyo Institute of Technology, Tokyo, Japan
  • Division of Cancer Genomics, National Cancer Center Research Institute, Tokyo, Japan
  • Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
  • Department of Cancer Genome Informatics, Osaka University, Osaka, Japan
  • PRESTO, Japan Science and Technology Agency, Saitama, Japan
  • Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
  • Division of Preventive Oncology, National Center for Tumor Diseases and German Cancer Research Center, Heidelberg, Germany
  • Huntsman Cancer Institute and Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
  • German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
  • Faculty of Healthy Sciences, University of Southern Denmark, Odense, Denmark
  • Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany
  • Laboratory of Neurosciences, Institute of Psychiatry, University of São Paulo, São Paulo, Brazil
  • Biocomplexity Institute of Virginia Tech, Blacksburg, VA, USA
  • Department of Medical Sciences, University of Turin, Turin, Italy
  • Mucosal Immunology and Microbiota Unit, Humanitas Research Hospital, Milan, Italy
  • Institute for Implementation Science in Population Health, City University of New York, New York, NY, USA
  • Department of Molecular Biology of Cancer, Institute of Experimental Medicine, Prague, Czech Republic
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41591-019-0405-7

    DOI

    http://dx.doi.org/10.1038/s41591-019-0405-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1113160258

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30936548


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