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@ARTICLE{Thomas:143427,
      author       = {A. M. Thomas and P. Manghi and F. Asnicar and E. Pasolli
                      and F. Armanini and M. Zolfo and F. Beghini and S. Manara
                      and N. Karcher and C. Pozzi and S. Gandini and D. Serrano
                      and S. Tarallo and A. Francavilla and G. Gallo and M.
                      Trompetto and G. Ferrero and S. Mizutani and H. Shiroma and
                      S. Shiba and T. Shibata and S. Yachida and T. Yamada and J.
                      Wirbel and P. Schrotz-King$^*$ and C. M. Ulrich and H.
                      Brenner$^*$ and M. Arumugam and P. Bork and G. Zeller and F.
                      Cordero and E. Dias-Neto and J. C. Setubal and A. Tett and
                      B. Pardini and M. Rescigno and L. Waldron and A. Naccarati
                      and N. Segata},
      title        = {{M}etagenomic analysis of colorectal cancer datasets
                      identifies cross-cohort microbial diagnostic signatures and
                      a link with choline degradation.},
      journal      = {Nature medicine},
      volume       = {25},
      number       = {4},
      issn         = {1546-170X},
      address      = {New York, NY},
      publisher    = {Nature America Inc.},
      reportid     = {DKFZ-2019-01015},
      pages        = {667 - 678},
      year         = {2019},
      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.},
      cin          = {C120 / C070 / L101},
      ddc          = {610},
      cid          = {I:(DE-He78)C120-20160331 / I:(DE-He78)C070-20160331 /
                      I:(DE-He78)L101-20160331},
      pnm          = {313 - Cancer risk factors and prevention (POF3-313)},
      pid          = {G:(DE-HGF)POF3-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:30936548},
      doi          = {10.1038/s41591-019-0405-7},
      url          = {https://inrepo02.dkfz.de/record/143427},
}