Altered diversity and composition of the gut microbiome in patients with cervical cancer View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-12

AUTHORS

Zhongqiu Wang, Qingxin Wang, Jing Zhao, Linlin Gong, Yan Zhang, Xia Wang, Zhiyong Yuan

ABSTRACT

Gut microbiota have been implicated in the development of many human diseases, including both digestive diseases and non-digestive diseases. In this study, we investigated whether the gut bacteria differed in cervical cancer (CCa) patients compared with healthy controls by 16S rRNA sequencing analysis. Subjects including eight CCa and five healthy controls were included. Microbiota profiles in fecal DNA were characterized by PCR amplification of the 16S rRNA V4 variable region and deep sequencing using the Illumina HiSeq platform. The CCa-associated gut microbiota had an increasing trend in alpha diversity, although statistical significance was not reached. Inter-group variability in community structure by beta diversity analysis showed a clear separation between cancer patients and healthy controls. Gut microbiota profiles were different between patients and controls; namely, the proportions of Proteobacteria phylum was notably higher in patients with CCa (ρ = 0.012). Seven genera differentiated significantly in relative abundance between CCa and controls (all ρ < 0.05), including Escherichia-Shigella, Roseburia, Pseudomonas, Lachnoclostridium, Lachnospiraceae_UCG-004, Dorea and Succinivibrio. The characteristic microbiome in CCa patients was also identified by linear discriminant analysis effect size (LEfSe). The phylum Proteobacteria, and the genus Parabacteroides, Escherichia_Shigells and Roseburia may provide novel potential biomarkers for CCa. Taken together, this is the first study on gut microbiota in patients with CCa, and demonstrated the significantly altered diversity and composition. More... »

PAGES

40

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13568-019-0763-z

DOI

http://dx.doi.org/10.1186/s13568-019-0763-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112964678

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30904962


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0605", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Microbiology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Tianjin Medical University Cancer Institute and Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411918.4", 
          "name": [
            "Department of Radiation Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin\u2019s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, West Huanhu Road, West River District, 300060, Tianjin, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Zhongqiu", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tianjin Medical University Cancer Institute and Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411918.4", 
          "name": [
            "Department of Radiation Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin\u2019s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, West Huanhu Road, West River District, 300060, Tianjin, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Qingxin", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tianjin Medical University Cancer Institute and Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411918.4", 
          "name": [
            "Department of Radiation Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin\u2019s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, West Huanhu Road, West River District, 300060, Tianjin, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhao", 
        "givenName": "Jing", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tianjin Medical University Cancer Institute and Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411918.4", 
          "name": [
            "Department of Radiation Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin\u2019s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, West Huanhu Road, West River District, 300060, Tianjin, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gong", 
        "givenName": "Linlin", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Gastroenterology, Nanjing First Hospital, Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Yan", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tianjin Medical University Cancer Institute and Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411918.4", 
          "name": [
            "Department of Gastrointestinal Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin\u2019s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, West Huanhu Road, West River District, 300060, Tianjin, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Xia", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tianjin Medical University Cancer Institute and Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411918.4", 
          "name": [
            "Department of Radiation Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin\u2019s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, West Huanhu Road, West River District, 300060, Tianjin, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yuan", 
        "givenName": "Zhiyong", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/gb-2011-12-6-r60", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000243423", 
          "https://doi.org/10.1186/gb-2011-12-6-r60"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jnci/djv147", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003621350"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/infdis/jiu330", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004458557"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nbt.2942", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006520065", 
          "https://doi.org/10.1038/nbt.2942"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.112730.110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007579011"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1113/jp273106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007611331"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.f.303", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009032055", 
          "https://doi.org/10.1038/nmeth.f.303"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.f.303", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009032055", 
          "https://doi.org/10.1038/nmeth.f.303"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btr381", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013175803"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/odi.12472", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013454970"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1053/j.gastro.2014.03.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013999818"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1053/j.gastro.2012.11.032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017282095"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nri2850", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019341742", 
          "https://doi.org/10.1038/nri2850"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nri2850", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019341742", 
          "https://doi.org/10.1038/nri2850"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf03256249", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019610104", 
          "https://doi.org/10.1007/bf03256249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.1000080107", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019627885"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrrheum.2011.121", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020354203", 
          "https://doi.org/10.1038/nrrheum.2011.121"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tem.2010.03.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021353491"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2334-13-271", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022710626", 
          "https://doi.org/10.1186/1471-2334-13-271"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkh340", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025846396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature11209", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027248000", 
          "https://doi.org/10.1038/nature11209"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.2604", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027743851", 
          "https://doi.org/10.1038/nmeth.2604"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrmicro2974", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028265001", 
          "https://doi.org/10.1038/nrmicro2974"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btr507", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031241489"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/aem.03006-05", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034568952"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.femsec.2005.03.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035031400"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.mimet.2007.02.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036764231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.mimet.2007.02.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036764231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/mbio.00366-12", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044481326"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/aem.00062-07", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045980007"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.biopha.2014.12.041", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050275191"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ac051447z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054997432"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ac051447z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054997432"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2531532", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069976974"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/gutjnl-2016-313235", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083735266"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/gutjnl-2016-313235", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083735266"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/liv.13485", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085723227"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1053/j.gastro.2017.08.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091235762"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1053/j.gastro.2017.08.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091235762"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bpobgyn.2017.08.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091493811"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bpobgyn.2017.08.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091493811"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/s41467-017-00900-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092092284", 
          "https://doi.org/10.1038/s41467-017-00900-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.yexmp.2017.11.014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092959292"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.arcmed.2017.11.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100089373"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "Gut microbiota have been implicated in the development of many human diseases, including both digestive diseases and non-digestive diseases. In this study, we investigated whether the gut bacteria differed in cervical cancer (CCa) patients compared with healthy controls by 16S rRNA sequencing analysis. Subjects including eight CCa and five healthy controls were included. Microbiota profiles in fecal DNA were characterized by PCR amplification of the 16S rRNA V4 variable region and deep sequencing using the Illumina HiSeq platform. The CCa-associated gut microbiota had an increasing trend in alpha diversity, although statistical significance was not reached. Inter-group variability in community structure by beta diversity analysis showed a clear separation between cancer patients and healthy controls. Gut microbiota profiles were different between patients and controls; namely, the proportions of Proteobacteria phylum was notably higher in patients with CCa (\u03c1\u2009=\u20090.012). Seven genera differentiated significantly in relative abundance between CCa and controls (all \u03c1\u2009<\u20090.05), including Escherichia-Shigella, Roseburia, Pseudomonas, Lachnoclostridium, Lachnospiraceae_UCG-004, Dorea and Succinivibrio. The characteristic microbiome in CCa patients was also identified by linear discriminant analysis effect size (LEfSe). The phylum Proteobacteria, and the genus Parabacteroides, Escherichia_Shigells and Roseburia may provide novel potential biomarkers for CCa. Taken together, this is the first study on gut microbiota in patients with CCa, and demonstrated the significantly altered diversity and composition.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s13568-019-0763-z", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1045217", 
        "issn": [
          "2191-0855"
        ], 
        "name": "AMB Express", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "9"
      }
    ], 
    "name": "Altered diversity and composition of the gut microbiome in patients with cervical cancer", 
    "pagination": "40", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s13568-019-0763-z"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "17c53cb12ada8c05fdc9f98167147ce596a0cace3a5dc331414a6c659a8ed2f0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112964678"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101561785"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30904962"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s13568-019-0763-z", 
      "https://app.dimensions.ai/details/publication/pub.1112964678"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-15T09:00", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000375_0000000375/records_91441_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs13568-019-0763-z"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13568-019-0763-z'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13568-019-0763-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13568-019-0763-z'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13568-019-0763-z'


 

This table displays all metadata directly associated to this object as RDF triples.

228 TRIPLES      21 PREDICATES      66 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s13568-019-0763-z schema:about anzsrc-for:06
2 anzsrc-for:0605
3 schema:author N65e51f5f91df40c59b74ab0d799dcaa8
4 schema:citation sg:pub.10.1007/bf03256249
5 sg:pub.10.1038/nature11209
6 sg:pub.10.1038/nbt.2942
7 sg:pub.10.1038/nmeth.2604
8 sg:pub.10.1038/nmeth.f.303
9 sg:pub.10.1038/nri2850
10 sg:pub.10.1038/nrmicro2974
11 sg:pub.10.1038/nrrheum.2011.121
12 sg:pub.10.1038/s41467-017-00900-1
13 sg:pub.10.1186/1471-2334-13-271
14 sg:pub.10.1186/gb-2011-12-6-r60
15 https://doi.org/10.1016/j.arcmed.2017.11.015
16 https://doi.org/10.1016/j.biopha.2014.12.041
17 https://doi.org/10.1016/j.bpobgyn.2017.08.012
18 https://doi.org/10.1016/j.femsec.2005.03.012
19 https://doi.org/10.1016/j.mimet.2007.02.005
20 https://doi.org/10.1016/j.tem.2010.03.005
21 https://doi.org/10.1016/j.yexmp.2017.11.014
22 https://doi.org/10.1021/ac051447z
23 https://doi.org/10.1053/j.gastro.2012.11.032
24 https://doi.org/10.1053/j.gastro.2014.03.001
25 https://doi.org/10.1053/j.gastro.2017.08.022
26 https://doi.org/10.1073/pnas.1000080107
27 https://doi.org/10.1093/bioinformatics/btr381
28 https://doi.org/10.1093/bioinformatics/btr507
29 https://doi.org/10.1093/infdis/jiu330
30 https://doi.org/10.1093/jnci/djv147
31 https://doi.org/10.1093/nar/gkh340
32 https://doi.org/10.1101/gr.112730.110
33 https://doi.org/10.1111/liv.13485
34 https://doi.org/10.1111/odi.12472
35 https://doi.org/10.1113/jp273106
36 https://doi.org/10.1128/aem.00062-07
37 https://doi.org/10.1128/aem.03006-05
38 https://doi.org/10.1128/mbio.00366-12
39 https://doi.org/10.1136/gutjnl-2016-313235
40 https://doi.org/10.2307/2531532
41 schema:datePublished 2019-12
42 schema:datePublishedReg 2019-12-01
43 schema:description Gut microbiota have been implicated in the development of many human diseases, including both digestive diseases and non-digestive diseases. In this study, we investigated whether the gut bacteria differed in cervical cancer (CCa) patients compared with healthy controls by 16S rRNA sequencing analysis. Subjects including eight CCa and five healthy controls were included. Microbiota profiles in fecal DNA were characterized by PCR amplification of the 16S rRNA V4 variable region and deep sequencing using the Illumina HiSeq platform. The CCa-associated gut microbiota had an increasing trend in alpha diversity, although statistical significance was not reached. Inter-group variability in community structure by beta diversity analysis showed a clear separation between cancer patients and healthy controls. Gut microbiota profiles were different between patients and controls; namely, the proportions of Proteobacteria phylum was notably higher in patients with CCa (ρ = 0.012). Seven genera differentiated significantly in relative abundance between CCa and controls (all ρ < 0.05), including Escherichia-Shigella, Roseburia, Pseudomonas, Lachnoclostridium, Lachnospiraceae_UCG-004, Dorea and Succinivibrio. The characteristic microbiome in CCa patients was also identified by linear discriminant analysis effect size (LEfSe). The phylum Proteobacteria, and the genus Parabacteroides, Escherichia_Shigells and Roseburia may provide novel potential biomarkers for CCa. Taken together, this is the first study on gut microbiota in patients with CCa, and demonstrated the significantly altered diversity and composition.
44 schema:genre research_article
45 schema:inLanguage en
46 schema:isAccessibleForFree false
47 schema:isPartOf Nc062cb95b3dd432f970e66727f5edfc9
48 Nd3bea7c144664cc585d4bd4b04da1801
49 sg:journal.1045217
50 schema:name Altered diversity and composition of the gut microbiome in patients with cervical cancer
51 schema:pagination 40
52 schema:productId N18012d3b455e462198fa5e984b2c2f95
53 N24574cb1697b450ca86864ab9cc21baa
54 N29f0b5c0e6554ddabb0cb00424573abc
55 Na710da9e38cf40628cf9048f666ac52f
56 Nfcc71d9b682c4c3897d60aabdc780305
57 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112964678
58 https://doi.org/10.1186/s13568-019-0763-z
59 schema:sdDatePublished 2019-04-15T09:00
60 schema:sdLicense https://scigraph.springernature.com/explorer/license/
61 schema:sdPublisher N25d1dec0b67141b6ab039a9526d12c7d
62 schema:url https://link.springer.com/10.1186%2Fs13568-019-0763-z
63 sgo:license sg:explorer/license/
64 sgo:sdDataset articles
65 rdf:type schema:ScholarlyArticle
66 N0c52e12a1f89483f88990be1ab5e2a98 schema:affiliation https://www.grid.ac/institutes/grid.411918.4
67 schema:familyName Zhao
68 schema:givenName Jing
69 rdf:type schema:Person
70 N0e017ba82f7743739dd62e2a0627bdbf rdf:first N0c52e12a1f89483f88990be1ab5e2a98
71 rdf:rest Nb9a971d0c3a34ae6b6b5f88fe99ce727
72 N18012d3b455e462198fa5e984b2c2f95 schema:name doi
73 schema:value 10.1186/s13568-019-0763-z
74 rdf:type schema:PropertyValue
75 N24574cb1697b450ca86864ab9cc21baa schema:name nlm_unique_id
76 schema:value 101561785
77 rdf:type schema:PropertyValue
78 N25d1dec0b67141b6ab039a9526d12c7d schema:name Springer Nature - SN SciGraph project
79 rdf:type schema:Organization
80 N269a3899b90e43a69b4be2e4c3e1b195 schema:affiliation https://www.grid.ac/institutes/grid.411918.4
81 schema:familyName Wang
82 schema:givenName Qingxin
83 rdf:type schema:Person
84 N29f0b5c0e6554ddabb0cb00424573abc schema:name readcube_id
85 schema:value 17c53cb12ada8c05fdc9f98167147ce596a0cace3a5dc331414a6c659a8ed2f0
86 rdf:type schema:PropertyValue
87 N45ccab76704c40d79875794a7c6a6909 rdf:first N6bc6466e85384283a41b35e3971ffdc1
88 rdf:rest rdf:nil
89 N65e51f5f91df40c59b74ab0d799dcaa8 rdf:first Ne032a884dd054f59875b60b2594fa75f
90 rdf:rest Nc8faca8f8a5342e2a18ad67d0af2ecd2
91 N6bc6466e85384283a41b35e3971ffdc1 schema:affiliation https://www.grid.ac/institutes/grid.411918.4
92 schema:familyName Yuan
93 schema:givenName Zhiyong
94 rdf:type schema:Person
95 N740b6228631b4947a7df61a2c04de59b rdf:first Nd320331408c84adab5ff45e296534772
96 rdf:rest N45ccab76704c40d79875794a7c6a6909
97 N7d49c370c1ed4d418f39be30282f15de schema:name Department of Gastroenterology, Nanjing First Hospital, Nanjing Medical University, 300 Guangzhou Road, 210029, Nanjing, China
98 rdf:type schema:Organization
99 N92a18e643391459bbbe8f5afc9183b93 rdf:first Nede61b98c0484e4f8af1107e75c42aa4
100 rdf:rest N740b6228631b4947a7df61a2c04de59b
101 Na710da9e38cf40628cf9048f666ac52f schema:name pubmed_id
102 schema:value 30904962
103 rdf:type schema:PropertyValue
104 Nb9a971d0c3a34ae6b6b5f88fe99ce727 rdf:first Nfb83b88ded79465facdd7d980b35e48d
105 rdf:rest N92a18e643391459bbbe8f5afc9183b93
106 Nc062cb95b3dd432f970e66727f5edfc9 schema:issueNumber 1
107 rdf:type schema:PublicationIssue
108 Nc8faca8f8a5342e2a18ad67d0af2ecd2 rdf:first N269a3899b90e43a69b4be2e4c3e1b195
109 rdf:rest N0e017ba82f7743739dd62e2a0627bdbf
110 Nd320331408c84adab5ff45e296534772 schema:affiliation https://www.grid.ac/institutes/grid.411918.4
111 schema:familyName Wang
112 schema:givenName Xia
113 rdf:type schema:Person
114 Nd3bea7c144664cc585d4bd4b04da1801 schema:volumeNumber 9
115 rdf:type schema:PublicationVolume
116 Ne032a884dd054f59875b60b2594fa75f schema:affiliation https://www.grid.ac/institutes/grid.411918.4
117 schema:familyName Wang
118 schema:givenName Zhongqiu
119 rdf:type schema:Person
120 Nede61b98c0484e4f8af1107e75c42aa4 schema:affiliation N7d49c370c1ed4d418f39be30282f15de
121 schema:familyName Zhang
122 schema:givenName Yan
123 rdf:type schema:Person
124 Nfb83b88ded79465facdd7d980b35e48d schema:affiliation https://www.grid.ac/institutes/grid.411918.4
125 schema:familyName Gong
126 schema:givenName Linlin
127 rdf:type schema:Person
128 Nfcc71d9b682c4c3897d60aabdc780305 schema:name dimensions_id
129 schema:value pub.1112964678
130 rdf:type schema:PropertyValue
131 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
132 schema:name Biological Sciences
133 rdf:type schema:DefinedTerm
134 anzsrc-for:0605 schema:inDefinedTermSet anzsrc-for:
135 schema:name Microbiology
136 rdf:type schema:DefinedTerm
137 sg:journal.1045217 schema:issn 2191-0855
138 schema:name AMB Express
139 rdf:type schema:Periodical
140 sg:pub.10.1007/bf03256249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019610104
141 https://doi.org/10.1007/bf03256249
142 rdf:type schema:CreativeWork
143 sg:pub.10.1038/nature11209 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027248000
144 https://doi.org/10.1038/nature11209
145 rdf:type schema:CreativeWork
146 sg:pub.10.1038/nbt.2942 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006520065
147 https://doi.org/10.1038/nbt.2942
148 rdf:type schema:CreativeWork
149 sg:pub.10.1038/nmeth.2604 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027743851
150 https://doi.org/10.1038/nmeth.2604
151 rdf:type schema:CreativeWork
152 sg:pub.10.1038/nmeth.f.303 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009032055
153 https://doi.org/10.1038/nmeth.f.303
154 rdf:type schema:CreativeWork
155 sg:pub.10.1038/nri2850 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019341742
156 https://doi.org/10.1038/nri2850
157 rdf:type schema:CreativeWork
158 sg:pub.10.1038/nrmicro2974 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028265001
159 https://doi.org/10.1038/nrmicro2974
160 rdf:type schema:CreativeWork
161 sg:pub.10.1038/nrrheum.2011.121 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020354203
162 https://doi.org/10.1038/nrrheum.2011.121
163 rdf:type schema:CreativeWork
164 sg:pub.10.1038/s41467-017-00900-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092092284
165 https://doi.org/10.1038/s41467-017-00900-1
166 rdf:type schema:CreativeWork
167 sg:pub.10.1186/1471-2334-13-271 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022710626
168 https://doi.org/10.1186/1471-2334-13-271
169 rdf:type schema:CreativeWork
170 sg:pub.10.1186/gb-2011-12-6-r60 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000243423
171 https://doi.org/10.1186/gb-2011-12-6-r60
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1016/j.arcmed.2017.11.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100089373
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1016/j.biopha.2014.12.041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050275191
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1016/j.bpobgyn.2017.08.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091493811
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1016/j.femsec.2005.03.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035031400
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1016/j.mimet.2007.02.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036764231
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1016/j.tem.2010.03.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021353491
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1016/j.yexmp.2017.11.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092959292
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1021/ac051447z schema:sameAs https://app.dimensions.ai/details/publication/pub.1054997432
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1053/j.gastro.2012.11.032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017282095
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1053/j.gastro.2014.03.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013999818
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1053/j.gastro.2017.08.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091235762
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1073/pnas.1000080107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019627885
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1093/bioinformatics/btr381 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013175803
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1093/bioinformatics/btr507 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031241489
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1093/infdis/jiu330 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004458557
202 rdf:type schema:CreativeWork
203 https://doi.org/10.1093/jnci/djv147 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003621350
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1093/nar/gkh340 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025846396
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1101/gr.112730.110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007579011
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1111/liv.13485 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085723227
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1111/odi.12472 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013454970
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1113/jp273106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007611331
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1128/aem.00062-07 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045980007
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1128/aem.03006-05 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034568952
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1128/mbio.00366-12 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044481326
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1136/gutjnl-2016-313235 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083735266
222 rdf:type schema:CreativeWork
223 https://doi.org/10.2307/2531532 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069976974
224 rdf:type schema:CreativeWork
225 https://www.grid.ac/institutes/grid.411918.4 schema:alternateName Tianjin Medical University Cancer Institute and Hospital
226 schema:name Department of Gastrointestinal Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, West Huanhu Road, West River District, 300060, Tianjin, China
227 Department of Radiation Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, West Huanhu Road, West River District, 300060, Tianjin, China
228 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...