Application of amplicon-based targeted sequencing with the molecular barcoding system to detect uncommon minor EGFR mutations in patients with treatment-naïve ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Kei Namba, Shuta Tomida, Takehiro Matsubara, Yuta Takahashi, Eisuke Kurihara, Yusuke Ogoshi, Takahiro Yoshioka, Tatsuaki Takeda, Hidejiro Torigoe, Hiroki Sato, Kazuhiko Shien, Hiromasa Yamamoto, Junichi Soh, Kazunori Tsukuda, Shinichi Toyooka

ABSTRACT

BACKGROUND: In lung cancer, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor sensitizing mutations co-existing with rare minor EGFR mutations are known as compound mutations. These minor EGFR mutations can lead to acquired resistance after EGFR tyrosine kinase inhibitor treatment, so determining the mutation status of patients is important. However, using amplicon-based targeted deep sequencing based on next-generation sequencing to characterize mutations is prone to sequencing error. We therefore assessed the benefit of incorporating molecular barcoding with high-throughput sequencing to investigate genomic heterogeneity in treatment-naïve patients who have undergone resection of their non-small cell lung cancer (NSCLC) EGFR mutations. METHODS: We performed amplicon-based targeted sequencing with the molecular barcoding system (MBS) to detect major common EGFR mutations and uncommon minor mutations at a 0.5% allele frequency in fresh-frozen lung cancer samples. RESULTS: Profiles of the common mutations of EGFR identified by MBS corresponded with the results of clinical testing in 63 (98.4%) out of 64 cases. Uncommon mutations of EGFR were detected in seven cases (10.9%). Among the three types of major EGFR mutations, patients with the G719X mutation had a significantly higher incidence of compound mutations than those with the L858R mutation or exon 19 deletion (p = 0.0052). This was validated in an independent cohort from the Cancer Genome Atlas dataset (p = 0.018). CONCLUSIONS: Our findings demonstrate the feasibility of using the MBS to establish an accurate NSCLC patient genotype. This work will help understand the molecular basis of EGFR compound mutations in NSCLC, and could aid the development of new treatment modalities. More... »

PAGES

175

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12885-019-5374-1

DOI

http://dx.doi.org/10.1186/s12885-019-5374-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112395627

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30808329


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/2008/1112", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Oncology and Carcinogenesis", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Namba", 
        "givenName": "Kei", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Department of Biobank, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tomida", 
        "givenName": "Shuta", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University Hospital", 
          "id": "https://www.grid.ac/institutes/grid.412342.2", 
          "name": [
            "Okayama University Hospital Biobank, Okayama University Hospital, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Matsubara", 
        "givenName": "Takehiro", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Takahashi", 
        "givenName": "Yuta", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kurihara", 
        "givenName": "Eisuke", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ogoshi", 
        "givenName": "Yusuke", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Department of Gastroenterological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yoshioka", 
        "givenName": "Takahiro", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Department of Clinical Pharmacy, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Okayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Takeda", 
        "givenName": "Tatsuaki", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Torigoe", 
        "givenName": "Hidejiro", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sato", 
        "givenName": "Hiroki", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shien", 
        "givenName": "Kazuhiko", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yamamoto", 
        "givenName": "Hiromasa", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Soh", 
        "givenName": "Junichi", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tsukuda", 
        "givenName": "Kazunori", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Okayama University", 
          "id": "https://www.grid.ac/institutes/grid.261356.5", 
          "name": [
            "Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Toyooka", 
        "givenName": "Shinichi", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1073/pnas.0405220101", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000546271"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/jto.0000000000000130", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000815976"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jnci/dji055", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002547449"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/1078-0432.ccr-14-2789", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003328507"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/jto.0000000000000048", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005377277"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1200/jco.2012.42.1586", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010837039"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3322/caac.21254", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011682275"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1200/jco.2005.00.992", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011727967"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa0904554", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012351385"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nprot.2014.170", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012801607", 
          "https://doi.org/10.1038/nprot.2014.170"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3322/caac.21262", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013257560"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/jto.0b013e31818071f3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017240492"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pmed.0030485", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018320956"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2147/ott.s118071", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018418260"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/jto.0b013e3182781e35", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018972171"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa0810699", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020150048"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1200/jco.2010.31.4492", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023850071"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg2626", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023911485", 
          "https://doi.org/10.1038/nrg2626"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg2626", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023911485", 
          "https://doi.org/10.1038/nrg2626"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.1208715109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027689259"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/0008-5472.can-05-0331", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028389586"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2105-12-451", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028554628", 
          "https://doi.org/10.1186/1471-2105-12-451"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12864-015-1806-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031132558", 
          "https://doi.org/10.1186/s12864-015-1806-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1099314", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033538744"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0506580102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037705714"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0506580102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037705714"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/1078-0432.ccr-10-3408", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041302274"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1634/theoncologist.2008-0093", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042682835"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa040938", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042907590"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2147/ott.s78984", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048581492"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1164/rccm.200803-389oc", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049026777"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1349-7006.2007.00607.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049057560"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.lungcan.2006.04.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049417670"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/bjc.2014.210", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050939993", 
          "https://doi.org/10.1038/bjc.2014.210"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1671", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052596395", 
          "https://doi.org/10.1038/ng1671"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1671", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052596395", 
          "https://doi.org/10.1038/ng1671"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng.3564", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053389438", 
          "https://doi.org/10.1038/ng.3564"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pmed.0020073", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053684878"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/15384047.2016.1139235", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058401639"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/15384047.2016.1139235", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058401639"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/1078-0432.ccr-15-1046", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063224968"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/scitranslmed.aan6566", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092711415"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.18632/oncotarget.18042", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100446620"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "BACKGROUND: In lung cancer, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor sensitizing mutations co-existing with rare minor EGFR mutations are known as compound mutations. These minor EGFR mutations can lead to acquired resistance after EGFR tyrosine kinase inhibitor treatment, so determining the mutation status of patients is important. However, using amplicon-based targeted deep sequencing based on next-generation sequencing to characterize mutations is prone to sequencing error. We therefore assessed the benefit of incorporating molecular barcoding with high-throughput sequencing to investigate genomic heterogeneity in treatment-na\u00efve patients who have undergone resection of their non-small cell lung cancer (NSCLC) EGFR mutations.\nMETHODS: We performed amplicon-based targeted sequencing with the molecular barcoding system (MBS) to detect major common EGFR mutations and uncommon minor mutations at a 0.5% allele frequency in fresh-frozen lung cancer samples.\nRESULTS: Profiles of the common mutations of EGFR identified by MBS corresponded with the results of clinical testing in 63 (98.4%) out of 64 cases. Uncommon mutations of EGFR were detected in seven cases (10.9%). Among the three types of major EGFR mutations, patients with the G719X mutation had a significantly higher incidence of compound mutations than those with the L858R mutation or exon 19 deletion (p\u2009=\u20090.0052). This was validated in an independent cohort from the Cancer Genome Atlas dataset (p\u2009=\u20090.018).\nCONCLUSIONS: Our findings demonstrate the feasibility of using the MBS to establish an accurate NSCLC patient genotype. This work will help understand the molecular basis of EGFR compound mutations in NSCLC, and could aid the development of new treatment modalities.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s12885-019-5374-1", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.5899351", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.5910348", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1024632", 
        "issn": [
          "1471-2407"
        ], 
        "name": "BMC Cancer", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "19"
      }
    ], 
    "name": "Application of amplicon-based targeted sequencing with the molecular barcoding system to detect uncommon minor EGFR mutations in patients with treatment-na\u00efve lung adenocarcinoma", 
    "pagination": "175", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "ba7fde1b508457b384dd8d43921cd249c5de7872552feff7a83af4544c9994d9"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30808329"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100967800"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12885-019-5374-1"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112395627"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12885-019-5374-1", 
      "https://app.dimensions.ai/details/publication/pub.1112395627"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T11:27", 
    "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/v90/0000000356_0000000356/records_57898_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs12885-019-5374-1"
  }
]
 

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/s12885-019-5374-1'

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/s12885-019-5374-1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12885-019-5374-1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12885-019-5374-1'


 

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

285 TRIPLES      21 PREDICATES      68 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12885-019-5374-1 schema:about anzsrc-for:11
2 anzsrc-for:1112
3 schema:author N9219abf865ae4ee09f579e8c4e4ab32a
4 schema:citation sg:pub.10.1038/bjc.2014.210
5 sg:pub.10.1038/ng.3564
6 sg:pub.10.1038/ng1671
7 sg:pub.10.1038/nprot.2014.170
8 sg:pub.10.1038/nrg2626
9 sg:pub.10.1186/1471-2105-12-451
10 sg:pub.10.1186/s12864-015-1806-8
11 https://doi.org/10.1016/j.lungcan.2006.04.008
12 https://doi.org/10.1056/nejmoa040938
13 https://doi.org/10.1056/nejmoa0810699
14 https://doi.org/10.1056/nejmoa0904554
15 https://doi.org/10.1073/pnas.0405220101
16 https://doi.org/10.1073/pnas.0506580102
17 https://doi.org/10.1073/pnas.1208715109
18 https://doi.org/10.1080/15384047.2016.1139235
19 https://doi.org/10.1093/jnci/dji055
20 https://doi.org/10.1097/jto.0000000000000048
21 https://doi.org/10.1097/jto.0000000000000130
22 https://doi.org/10.1097/jto.0b013e31818071f3
23 https://doi.org/10.1097/jto.0b013e3182781e35
24 https://doi.org/10.1111/j.1349-7006.2007.00607.x
25 https://doi.org/10.1126/science.1099314
26 https://doi.org/10.1126/scitranslmed.aan6566
27 https://doi.org/10.1158/0008-5472.can-05-0331
28 https://doi.org/10.1158/1078-0432.ccr-10-3408
29 https://doi.org/10.1158/1078-0432.ccr-14-2789
30 https://doi.org/10.1158/1078-0432.ccr-15-1046
31 https://doi.org/10.1164/rccm.200803-389oc
32 https://doi.org/10.1200/jco.2005.00.992
33 https://doi.org/10.1200/jco.2010.31.4492
34 https://doi.org/10.1200/jco.2012.42.1586
35 https://doi.org/10.1371/journal.pmed.0020073
36 https://doi.org/10.1371/journal.pmed.0030485
37 https://doi.org/10.1634/theoncologist.2008-0093
38 https://doi.org/10.18632/oncotarget.18042
39 https://doi.org/10.2147/ott.s118071
40 https://doi.org/10.2147/ott.s78984
41 https://doi.org/10.3322/caac.21254
42 https://doi.org/10.3322/caac.21262
43 schema:datePublished 2019-12
44 schema:datePublishedReg 2019-12-01
45 schema:description BACKGROUND: In lung cancer, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor sensitizing mutations co-existing with rare minor EGFR mutations are known as compound mutations. These minor EGFR mutations can lead to acquired resistance after EGFR tyrosine kinase inhibitor treatment, so determining the mutation status of patients is important. However, using amplicon-based targeted deep sequencing based on next-generation sequencing to characterize mutations is prone to sequencing error. We therefore assessed the benefit of incorporating molecular barcoding with high-throughput sequencing to investigate genomic heterogeneity in treatment-naïve patients who have undergone resection of their non-small cell lung cancer (NSCLC) EGFR mutations. METHODS: We performed amplicon-based targeted sequencing with the molecular barcoding system (MBS) to detect major common EGFR mutations and uncommon minor mutations at a 0.5% allele frequency in fresh-frozen lung cancer samples. RESULTS: Profiles of the common mutations of EGFR identified by MBS corresponded with the results of clinical testing in 63 (98.4%) out of 64 cases. Uncommon mutations of EGFR were detected in seven cases (10.9%). Among the three types of major EGFR mutations, patients with the G719X mutation had a significantly higher incidence of compound mutations than those with the L858R mutation or exon 19 deletion (p = 0.0052). This was validated in an independent cohort from the Cancer Genome Atlas dataset (p = 0.018). CONCLUSIONS: Our findings demonstrate the feasibility of using the MBS to establish an accurate NSCLC patient genotype. This work will help understand the molecular basis of EGFR compound mutations in NSCLC, and could aid the development of new treatment modalities.
46 schema:genre research_article
47 schema:inLanguage en
48 schema:isAccessibleForFree true
49 schema:isPartOf N13e98ed485604d038196a1538893b360
50 Nfc4782657ea0458486073505bcbebdb5
51 sg:journal.1024632
52 schema:name Application of amplicon-based targeted sequencing with the molecular barcoding system to detect uncommon minor EGFR mutations in patients with treatment-naïve lung adenocarcinoma
53 schema:pagination 175
54 schema:productId N05c62e843b404ded85de4a545b94ada2
55 N59dbeae20339413eb5a0004720a75133
56 N61f9742f847f44118676b4bd26f48a8a
57 N8b91f65be06f445692a487468bf3892d
58 N95baa99e8b734666b40d950a4724669f
59 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112395627
60 https://doi.org/10.1186/s12885-019-5374-1
61 schema:sdDatePublished 2019-04-11T11:27
62 schema:sdLicense https://scigraph.springernature.com/explorer/license/
63 schema:sdPublisher Nd6a23036fb844a55b93c76b4ecbe857a
64 schema:url https://link.springer.com/10.1186%2Fs12885-019-5374-1
65 sgo:license sg:explorer/license/
66 sgo:sdDataset articles
67 rdf:type schema:ScholarlyArticle
68 N0273707a1b5b4f61b121bef44a5f1566 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
69 schema:familyName Namba
70 schema:givenName Kei
71 rdf:type schema:Person
72 N05143fec48d3477bbf10efff93f04674 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
73 schema:familyName Kurihara
74 schema:givenName Eisuke
75 rdf:type schema:Person
76 N05c62e843b404ded85de4a545b94ada2 schema:name pubmed_id
77 schema:value 30808329
78 rdf:type schema:PropertyValue
79 N07ad2facbac94f7da8cf0b1be636c0da schema:affiliation https://www.grid.ac/institutes/grid.261356.5
80 schema:familyName Tsukuda
81 schema:givenName Kazunori
82 rdf:type schema:Person
83 N0c47ea7bbf304409a00a635e243753a7 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
84 schema:familyName Torigoe
85 schema:givenName Hidejiro
86 rdf:type schema:Person
87 N13e98ed485604d038196a1538893b360 schema:issueNumber 1
88 rdf:type schema:PublicationIssue
89 N2836f549c45c49399d306da5bf5273f1 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
90 schema:familyName Yoshioka
91 schema:givenName Takahiro
92 rdf:type schema:Person
93 N28d98ac6f6db4c53a9c2b9cfee4ad5d3 rdf:first N45b9fdb9b6c749feaf16494f6affc4f7
94 rdf:rest Nae92e80f0c024c7dbadab8afb39242a7
95 N2956da8ca3184d99a032a1393baea869 rdf:first N39549846d61340088a208455043d7186
96 rdf:rest N2e65e501859448048076fefe5ef52445
97 N2e65e501859448048076fefe5ef52445 rdf:first Nd883b08b5b8f4e09beef8d286b552803
98 rdf:rest Nfa453991909e421aa3c8efe10744272f
99 N39549846d61340088a208455043d7186 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
100 schema:familyName Yamamoto
101 schema:givenName Hiromasa
102 rdf:type schema:Person
103 N45b9fdb9b6c749feaf16494f6affc4f7 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
104 schema:familyName Takeda
105 schema:givenName Tatsuaki
106 rdf:type schema:Person
107 N49487c410fed41b0a649a35ded40c4ee schema:affiliation https://www.grid.ac/institutes/grid.261356.5
108 schema:familyName Sato
109 schema:givenName Hiroki
110 rdf:type schema:Person
111 N59dbeae20339413eb5a0004720a75133 schema:name nlm_unique_id
112 schema:value 100967800
113 rdf:type schema:PropertyValue
114 N5d8e455a913d4c3da45aa04d3c370b5d rdf:first Na2d9f154c5234f7ba92c2390725bfe93
115 rdf:rest N5d91fb98479243ad86c78ba14f9534b1
116 N5d91fb98479243ad86c78ba14f9534b1 rdf:first Nab89cbf0bed143feb2a9ac3e811e7393
117 rdf:rest Ne50025094a1246d8b9870f801ab46bfc
118 N60da3691d7e9426e96f5a1000ca6d970 rdf:first N49487c410fed41b0a649a35ded40c4ee
119 rdf:rest Ne66214df7c6a41958cfdd891f4d97e91
120 N61f9742f847f44118676b4bd26f48a8a schema:name dimensions_id
121 schema:value pub.1112395627
122 rdf:type schema:PropertyValue
123 N8b91f65be06f445692a487468bf3892d schema:name doi
124 schema:value 10.1186/s12885-019-5374-1
125 rdf:type schema:PropertyValue
126 N9219abf865ae4ee09f579e8c4e4ab32a rdf:first N0273707a1b5b4f61b121bef44a5f1566
127 rdf:rest N5d8e455a913d4c3da45aa04d3c370b5d
128 N95baa99e8b734666b40d950a4724669f schema:name readcube_id
129 schema:value ba7fde1b508457b384dd8d43921cd249c5de7872552feff7a83af4544c9994d9
130 rdf:type schema:PropertyValue
131 Na09b3715e6d041d8b171aaa4b0cddebe schema:affiliation https://www.grid.ac/institutes/grid.261356.5
132 schema:familyName Toyooka
133 schema:givenName Shinichi
134 rdf:type schema:Person
135 Na2d9f154c5234f7ba92c2390725bfe93 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
136 schema:familyName Tomida
137 schema:givenName Shuta
138 rdf:type schema:Person
139 Nab89cbf0bed143feb2a9ac3e811e7393 schema:affiliation https://www.grid.ac/institutes/grid.412342.2
140 schema:familyName Matsubara
141 schema:givenName Takehiro
142 rdf:type schema:Person
143 Nae92e80f0c024c7dbadab8afb39242a7 rdf:first N0c47ea7bbf304409a00a635e243753a7
144 rdf:rest N60da3691d7e9426e96f5a1000ca6d970
145 Ncaeb6f35f7084c4e840a8d3420b107da rdf:first Nf5ba3c4a604c482480980c3ac2fd4915
146 rdf:rest Nef239ff908d34b4fb1943b343d80dc09
147 Ncd472c83a29a4fbb97bfecdce1c83636 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
148 schema:familyName Shien
149 schema:givenName Kazuhiko
150 rdf:type schema:Person
151 Nd6a23036fb844a55b93c76b4ecbe857a schema:name Springer Nature - SN SciGraph project
152 rdf:type schema:Organization
153 Nd883b08b5b8f4e09beef8d286b552803 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
154 schema:familyName Soh
155 schema:givenName Junichi
156 rdf:type schema:Person
157 Ne0812544454a4cffa356a2874b90b763 rdf:first Na09b3715e6d041d8b171aaa4b0cddebe
158 rdf:rest rdf:nil
159 Ne50025094a1246d8b9870f801ab46bfc rdf:first Nf25ae550f2b14c11aa169506c6d1ec71
160 rdf:rest Ne7ad0cfa7ea840d2af0ef42182dc5599
161 Ne66214df7c6a41958cfdd891f4d97e91 rdf:first Ncd472c83a29a4fbb97bfecdce1c83636
162 rdf:rest N2956da8ca3184d99a032a1393baea869
163 Ne7ad0cfa7ea840d2af0ef42182dc5599 rdf:first N05143fec48d3477bbf10efff93f04674
164 rdf:rest Ncaeb6f35f7084c4e840a8d3420b107da
165 Nef239ff908d34b4fb1943b343d80dc09 rdf:first N2836f549c45c49399d306da5bf5273f1
166 rdf:rest N28d98ac6f6db4c53a9c2b9cfee4ad5d3
167 Nf25ae550f2b14c11aa169506c6d1ec71 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
168 schema:familyName Takahashi
169 schema:givenName Yuta
170 rdf:type schema:Person
171 Nf5ba3c4a604c482480980c3ac2fd4915 schema:affiliation https://www.grid.ac/institutes/grid.261356.5
172 schema:familyName Ogoshi
173 schema:givenName Yusuke
174 rdf:type schema:Person
175 Nfa453991909e421aa3c8efe10744272f rdf:first N07ad2facbac94f7da8cf0b1be636c0da
176 rdf:rest Ne0812544454a4cffa356a2874b90b763
177 Nfc4782657ea0458486073505bcbebdb5 schema:volumeNumber 19
178 rdf:type schema:PublicationVolume
179 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
180 schema:name Medical and Health Sciences
181 rdf:type schema:DefinedTerm
182 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
183 schema:name Oncology and Carcinogenesis
184 rdf:type schema:DefinedTerm
185 sg:grant.5899351 http://pending.schema.org/fundedItem sg:pub.10.1186/s12885-019-5374-1
186 rdf:type schema:MonetaryGrant
187 sg:grant.5910348 http://pending.schema.org/fundedItem sg:pub.10.1186/s12885-019-5374-1
188 rdf:type schema:MonetaryGrant
189 sg:journal.1024632 schema:issn 1471-2407
190 schema:name BMC Cancer
191 rdf:type schema:Periodical
192 sg:pub.10.1038/bjc.2014.210 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050939993
193 https://doi.org/10.1038/bjc.2014.210
194 rdf:type schema:CreativeWork
195 sg:pub.10.1038/ng.3564 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053389438
196 https://doi.org/10.1038/ng.3564
197 rdf:type schema:CreativeWork
198 sg:pub.10.1038/ng1671 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052596395
199 https://doi.org/10.1038/ng1671
200 rdf:type schema:CreativeWork
201 sg:pub.10.1038/nprot.2014.170 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012801607
202 https://doi.org/10.1038/nprot.2014.170
203 rdf:type schema:CreativeWork
204 sg:pub.10.1038/nrg2626 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023911485
205 https://doi.org/10.1038/nrg2626
206 rdf:type schema:CreativeWork
207 sg:pub.10.1186/1471-2105-12-451 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028554628
208 https://doi.org/10.1186/1471-2105-12-451
209 rdf:type schema:CreativeWork
210 sg:pub.10.1186/s12864-015-1806-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031132558
211 https://doi.org/10.1186/s12864-015-1806-8
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1016/j.lungcan.2006.04.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049417670
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1056/nejmoa040938 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042907590
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1056/nejmoa0810699 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020150048
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1056/nejmoa0904554 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012351385
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1073/pnas.0405220101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000546271
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1073/pnas.0506580102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037705714
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1073/pnas.1208715109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027689259
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1080/15384047.2016.1139235 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058401639
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1093/jnci/dji055 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002547449
230 rdf:type schema:CreativeWork
231 https://doi.org/10.1097/jto.0000000000000048 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005377277
232 rdf:type schema:CreativeWork
233 https://doi.org/10.1097/jto.0000000000000130 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000815976
234 rdf:type schema:CreativeWork
235 https://doi.org/10.1097/jto.0b013e31818071f3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017240492
236 rdf:type schema:CreativeWork
237 https://doi.org/10.1097/jto.0b013e3182781e35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018972171
238 rdf:type schema:CreativeWork
239 https://doi.org/10.1111/j.1349-7006.2007.00607.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1049057560
240 rdf:type schema:CreativeWork
241 https://doi.org/10.1126/science.1099314 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033538744
242 rdf:type schema:CreativeWork
243 https://doi.org/10.1126/scitranslmed.aan6566 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092711415
244 rdf:type schema:CreativeWork
245 https://doi.org/10.1158/0008-5472.can-05-0331 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028389586
246 rdf:type schema:CreativeWork
247 https://doi.org/10.1158/1078-0432.ccr-10-3408 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041302274
248 rdf:type schema:CreativeWork
249 https://doi.org/10.1158/1078-0432.ccr-14-2789 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003328507
250 rdf:type schema:CreativeWork
251 https://doi.org/10.1158/1078-0432.ccr-15-1046 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063224968
252 rdf:type schema:CreativeWork
253 https://doi.org/10.1164/rccm.200803-389oc schema:sameAs https://app.dimensions.ai/details/publication/pub.1049026777
254 rdf:type schema:CreativeWork
255 https://doi.org/10.1200/jco.2005.00.992 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011727967
256 rdf:type schema:CreativeWork
257 https://doi.org/10.1200/jco.2010.31.4492 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023850071
258 rdf:type schema:CreativeWork
259 https://doi.org/10.1200/jco.2012.42.1586 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010837039
260 rdf:type schema:CreativeWork
261 https://doi.org/10.1371/journal.pmed.0020073 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053684878
262 rdf:type schema:CreativeWork
263 https://doi.org/10.1371/journal.pmed.0030485 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018320956
264 rdf:type schema:CreativeWork
265 https://doi.org/10.1634/theoncologist.2008-0093 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042682835
266 rdf:type schema:CreativeWork
267 https://doi.org/10.18632/oncotarget.18042 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100446620
268 rdf:type schema:CreativeWork
269 https://doi.org/10.2147/ott.s118071 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018418260
270 rdf:type schema:CreativeWork
271 https://doi.org/10.2147/ott.s78984 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048581492
272 rdf:type schema:CreativeWork
273 https://doi.org/10.3322/caac.21254 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011682275
274 rdf:type schema:CreativeWork
275 https://doi.org/10.3322/caac.21262 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013257560
276 rdf:type schema:CreativeWork
277 https://www.grid.ac/institutes/grid.261356.5 schema:alternateName Okayama University
278 schema:name Department of Biobank, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan
279 Department of Clinical Pharmacy, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Okayama, Japan
280 Department of Gastroenterological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan
281 Departments of Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan
282 rdf:type schema:Organization
283 https://www.grid.ac/institutes/grid.412342.2 schema:alternateName Okayama University Hospital
284 schema:name Okayama University Hospital Biobank, Okayama University Hospital, 2-5-1 Shikata-cho, Kita-ku, 700-8558, Okayama City, Japan
285 rdf:type schema:Organization
 




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


...