Intraoperative imaging of hepatic cancers using γ-glutamyltranspeptidase-specific fluorophore enabling real-time identification and estimation of recurrence View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-06-14

AUTHORS

Yoichi Miyata, Takeaki Ishizawa, Mako Kamiya, Suguru Yamashita, Kiyoshi Hasegawa, Aya Ushiku, Junji Shibahara, Masashi Fukayama, Yasuteru Urano, Norihiro Kokudo

ABSTRACT

γ-Glutamyltranspeptidase (GGT) is upregulated in a variety of human cancers including primary and secondary hepatic tumors. This motivated us to use γ-glutamyl hydroxymethyl rhodamine green (gGlu-HMRG), a novel fluorophore emitting light at around 520 nm following enzymatic reaction with GGT, as a tool for the intraoperative identification of hepatic tumors. gGlu-HMRG was topically applied to 103 freshly resected hepatic specimens. Fluorescence imaging using gGlu-HMRG identified hepatic tumors with the sensitivity/specificity of 48%/96% for hepatocellular carcinoma, 100%/100% for intrahepatic cholangiocarcinoma, and 87%/100% for colorectal liver metastasis. High gGlu-HMRG fluorescence intensity was positively associated with the incidence of microscopic vascular invasion in HCC and the risk of early postoperative recurrence in CRLM. These results suggest that gGlu-HMRG imaging could not only be a useful intraoperative navigation tool but also provide information related to postoperative disease recurrence. More... »

PAGES

3542

References to SciGraph publications

  • 2015-07-13. Rapid intraoperative visualization of breast lesions with γ-glutamyl hydroxymethyl rhodamine green in SCIENTIFIC REPORTS
  • 2016-06-09. Rapid diagnosis of lymph node metastasis in breast cancer using a new fluorescent method with γ-glutamyl hydroxymethyl rhodamine green in SCIENTIFIC REPORTS
  • 2014-08-12. Pretherapeutic gamma-glutamyltransferase is an independent prognostic factor for patients with renal cell carcinoma in BRITISH JOURNAL OF CANCER
  • 2009-04-22. Preoperative serum gamma-glutamyl transferase to alanine aminotransferase ratio is a convenient prognostic marker for Child-Pugh A hepatocellular carcinoma after operation in JOURNAL OF GASTROENTEROLOGY
  • 2015-10-02. Feasibility of Using an Enzymatically Activatable Fluorescence Probe for the Rapid Evaluation of Pancreatic Tissue Obtained Using Endoscopic Ultrasound-Guided Fine Needle Aspiration: a Pilot Study in MOLECULAR IMAGING AND BIOLOGY
  • 2013-11-20. Mechanistic Background and Clinical Applications of Indocyanine Green Fluorescence Imaging of Hepatocellular Carcinoma in ANNALS OF SURGICAL ONCOLOGY
  • 2008-12-07. Selective molecular imaging of viable cancer cells with pH-activatable fluorescence probes in NATURE MEDICINE
  • 2016-07-07. Fluorescent imaging of superficial head and neck squamous cell carcinoma using a γ-glutamyltranspeptidase-activated targeting agent: a pilot study in BMC CANCER
  • 2003-06-10. Diagnostic value of protein induced by vitamin K absence (PIVKAII) and hepatoma-specific band of serum gamma-glutamyl transferase (GGTII) as hepatocellular carcinoma markers complementary to α-fetoprotein in BRITISH JOURNAL OF CANCER
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41598-017-03760-3

    DOI

    http://dx.doi.org/10.1038/s41598-017-03760-3

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1085943317

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28615696


    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/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "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"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Adult", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Aged", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Aged, 80 and over", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Carcinoma, Hepatocellular", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Cholangiocarcinoma", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Colorectal Neoplasms", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Female", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Liver Neoplasms", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Male", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Middle Aged", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Monitoring, Intraoperative", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Optical Imaging", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Recurrence", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sensitivity and Specificity", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "gamma-Glutamyltransferase", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan", 
              "id": "http://www.grid.ac/institutes/grid.26999.3d", 
              "name": [
                "Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Miyata", 
            "givenName": "Yoichi", 
            "id": "sg:person.013243332734.44", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013243332734.44"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Gastroenterological Surgery, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan", 
              "id": "http://www.grid.ac/institutes/grid.486756.e", 
              "name": [
                "Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan", 
                "Department of Gastroenterological Surgery, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ishizawa", 
            "givenName": "Takeaki", 
            "id": "sg:person.01267647573.52", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01267647573.52"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "PRESTO, Japan Science and Technology Agency, Saitama, Japan", 
              "id": "http://www.grid.ac/institutes/grid.419082.6", 
              "name": [
                "Laboratory of Chemical Biology and Molecular Imaging, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan", 
                "PRESTO, Japan Science and Technology Agency, Saitama, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kamiya", 
            "givenName": "Mako", 
            "id": "sg:person.0742343456.94", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0742343456.94"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan", 
              "id": "http://www.grid.ac/institutes/grid.26999.3d", 
              "name": [
                "Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Yamashita", 
            "givenName": "Suguru", 
            "id": "sg:person.0656702263.53", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0656702263.53"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan", 
              "id": "http://www.grid.ac/institutes/grid.26999.3d", 
              "name": [
                "Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Hasegawa", 
            "givenName": "Kiyoshi", 
            "id": "sg:person.01065410232.04", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01065410232.04"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan", 
              "id": "http://www.grid.ac/institutes/grid.26999.3d", 
              "name": [
                "Department of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ushiku", 
            "givenName": "Aya", 
            "id": "sg:person.01075176430.73", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01075176430.73"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan", 
              "id": "http://www.grid.ac/institutes/grid.26999.3d", 
              "name": [
                "Department of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Shibahara", 
            "givenName": "Junji", 
            "id": "sg:person.0635007357.60", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0635007357.60"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan", 
              "id": "http://www.grid.ac/institutes/grid.26999.3d", 
              "name": [
                "Department of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fukayama", 
            "givenName": "Masashi", 
            "id": "sg:person.01004770244.75", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01004770244.75"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "CREST, Japan Agency for Medical Research and Development, Tokyo, Japan", 
              "id": "http://www.grid.ac/institutes/grid.419082.6", 
              "name": [
                "Laboratory of Chemical Biology and Molecular Imaging, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan", 
                "Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan", 
                "CREST, Japan Agency for Medical Research and Development, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Urano", 
            "givenName": "Yasuteru", 
            "id": "sg:person.01321235732.27", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01321235732.27"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan", 
              "id": "http://www.grid.ac/institutes/grid.26999.3d", 
              "name": [
                "Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kokudo", 
            "givenName": "Norihiro", 
            "id": "sg:person.0735351167.82", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0735351167.82"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s00535-009-0050-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041574131", 
              "https://doi.org/10.1007/s00535-009-0050-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1245/s10434-013-3360-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036991606", 
              "https://doi.org/10.1245/s10434-013-3360-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep12080", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034359126", 
              "https://doi.org/10.1038/srep12080"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/bjc.2014.450", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010799236", 
              "https://doi.org/10.1038/bjc.2014.450"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nm.1854", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000519678", 
              "https://doi.org/10.1038/nm.1854"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12885-016-2421-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038944986", 
              "https://doi.org/10.1186/s12885-016-2421-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11307-015-0898-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043743304", 
              "https://doi.org/10.1007/s11307-015-0898-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep27525", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001367454", 
              "https://doi.org/10.1038/srep27525"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.bjc.6601018", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039653722", 
              "https://doi.org/10.1038/sj.bjc.6601018"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2017-06-14", 
        "datePublishedReg": "2017-06-14", 
        "description": "Abstract\u03b3-Glutamyltranspeptidase (GGT) is upregulated in a variety of human cancers including primary and secondary hepatic tumors. This motivated us to use \u03b3-glutamyl hydroxymethyl rhodamine green (gGlu-HMRG), a novel fluorophore emitting light at around 520\u2009nm following enzymatic reaction with GGT, as a tool for the intraoperative identification of hepatic tumors. gGlu-HMRG was topically applied to 103 freshly resected hepatic specimens. Fluorescence imaging using gGlu-HMRG identified hepatic tumors with the sensitivity/specificity of 48%/96% for hepatocellular carcinoma, 100%/100% for intrahepatic cholangiocarcinoma, and 87%/100% for colorectal liver metastasis. High gGlu-HMRG fluorescence intensity was positively associated with the incidence of microscopic vascular invasion in HCC and the risk of early postoperative recurrence in CRLM. These results suggest that gGlu-HMRG imaging could not only be a useful intraoperative navigation tool but also provide information related to postoperative disease recurrence.", 
        "genre": "article", 
        "id": "sg:pub.10.1038/s41598-017-03760-3", 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.6822241", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.5900776", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1045337", 
            "issn": [
              "2045-2322"
            ], 
            "name": "Scientific Reports", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "7"
          }
        ], 
        "keywords": [
          "hepatic tumors", 
          "gGlu-HMRG", 
          "colorectal liver metastases", 
          "\u03b3-glutamyl hydroxymethyl rhodamine green", 
          "microscopic vascular invasion", 
          "secondary hepatic tumors", 
          "early postoperative recurrence", 
          "postoperative disease recurrence", 
          "sensitivity/specificity", 
          "hepatic specimens", 
          "liver metastases", 
          "postoperative recurrence", 
          "disease recurrence", 
          "intrahepatic cholangiocarcinoma", 
          "vascular invasion", 
          "estimation of recurrence", 
          "intraoperative identification", 
          "hepatocellular carcinoma", 
          "hepatic cancer", 
          "recurrence", 
          "intraoperative imaging", 
          "tumors", 
          "human cancers", 
          "cancer", 
          "imaging", 
          "rhodamine green", 
          "CRLM", 
          "cholangiocarcinoma", 
          "carcinoma", 
          "metastasis", 
          "HCC", 
          "incidence", 
          "GGT", 
          "fluorescence imaging", 
          "risk", 
          "invasion", 
          "specificity", 
          "identification", 
          "specimens", 
          "fluorescence intensity", 
          "tool", 
          "navigation tools", 
          "real-time identification", 
          "results", 
          "variety", 
          "information", 
          "intensity", 
          "reaction", 
          "light", 
          "green", 
          "emitting light", 
          "enzymatic reactions", 
          "fluorophores", 
          "estimation"
        ], 
        "name": "Intraoperative imaging of hepatic cancers using \u03b3-glutamyltranspeptidase-specific fluorophore enabling real-time identification and estimation of recurrence", 
        "pagination": "3542", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1085943317"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/s41598-017-03760-3"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "28615696"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/s41598-017-03760-3", 
          "https://app.dimensions.ai/details/publication/pub.1085943317"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-12-01T06:36", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20221201/entities/gbq_results/article/article_722.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1038/s41598-017-03760-3"
      }
    ]
     

    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.10.1038/s41598-017-03760-3'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-017-03760-3'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-017-03760-3'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-017-03760-3'


     

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

    294 TRIPLES      21 PREDICATES      104 URIs      87 LITERALS      23 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/s41598-017-03760-3 schema:about N0e25505da2ce41e98241aa1871944b38
    2 N1a496b6c37744532a85cf3686fb6d98f
    3 N3899c85139394750a41e6535e00e1f37
    4 N6ec47cba11c54d328c08d6b4af450cde
    5 N7afea1a025774806a6497cd7664ecabf
    6 N819af9bb363247fba580c581ca3c5d59
    7 N822074e1f54948d7bbd64d7a640667fd
    8 Na47954aa5d814de3bc792ed1ecfa12a9
    9 Ncd2942bfa5764da28e5122644b229c4f
    10 Ncd6eb532e96f4cc6b49bc3343dc690f6
    11 Ndc9c9cdac903426ab0ab0c69d4796184
    12 Ndcb2deff75124d5da0af3701780d83f7
    13 Nea5ba7c8679645ab8af3ae556b5125f3
    14 Nf148f3985e704a30a6e38cd462586e3f
    15 Nfa1a76527a7f45f3bcd21e3020d6a044
    16 Nfb760915a4c542a682abe0c676018133
    17 anzsrc-for:11
    18 anzsrc-for:1112
    19 schema:author Ne90af62800a0435f876b26e03e8ec4f7
    20 schema:citation sg:pub.10.1007/s00535-009-0050-x
    21 sg:pub.10.1007/s11307-015-0898-5
    22 sg:pub.10.1038/bjc.2014.450
    23 sg:pub.10.1038/nm.1854
    24 sg:pub.10.1038/sj.bjc.6601018
    25 sg:pub.10.1038/srep12080
    26 sg:pub.10.1038/srep27525
    27 sg:pub.10.1186/s12885-016-2421-z
    28 sg:pub.10.1245/s10434-013-3360-4
    29 schema:datePublished 2017-06-14
    30 schema:datePublishedReg 2017-06-14
    31 schema:description Abstractγ-Glutamyltranspeptidase (GGT) is upregulated in a variety of human cancers including primary and secondary hepatic tumors. This motivated us to use γ-glutamyl hydroxymethyl rhodamine green (gGlu-HMRG), a novel fluorophore emitting light at around 520 nm following enzymatic reaction with GGT, as a tool for the intraoperative identification of hepatic tumors. gGlu-HMRG was topically applied to 103 freshly resected hepatic specimens. Fluorescence imaging using gGlu-HMRG identified hepatic tumors with the sensitivity/specificity of 48%/96% for hepatocellular carcinoma, 100%/100% for intrahepatic cholangiocarcinoma, and 87%/100% for colorectal liver metastasis. High gGlu-HMRG fluorescence intensity was positively associated with the incidence of microscopic vascular invasion in HCC and the risk of early postoperative recurrence in CRLM. These results suggest that gGlu-HMRG imaging could not only be a useful intraoperative navigation tool but also provide information related to postoperative disease recurrence.
    32 schema:genre article
    33 schema:isAccessibleForFree true
    34 schema:isPartOf N3533e7d30c074646b38c0d026d004d4b
    35 Nf92f6eca8ca14987abb47033b06eaa91
    36 sg:journal.1045337
    37 schema:keywords CRLM
    38 GGT
    39 HCC
    40 cancer
    41 carcinoma
    42 cholangiocarcinoma
    43 colorectal liver metastases
    44 disease recurrence
    45 early postoperative recurrence
    46 emitting light
    47 enzymatic reactions
    48 estimation
    49 estimation of recurrence
    50 fluorescence imaging
    51 fluorescence intensity
    52 fluorophores
    53 gGlu-HMRG
    54 green
    55 hepatic cancer
    56 hepatic specimens
    57 hepatic tumors
    58 hepatocellular carcinoma
    59 human cancers
    60 identification
    61 imaging
    62 incidence
    63 information
    64 intensity
    65 intrahepatic cholangiocarcinoma
    66 intraoperative identification
    67 intraoperative imaging
    68 invasion
    69 light
    70 liver metastases
    71 metastasis
    72 microscopic vascular invasion
    73 navigation tools
    74 postoperative disease recurrence
    75 postoperative recurrence
    76 reaction
    77 real-time identification
    78 recurrence
    79 results
    80 rhodamine green
    81 risk
    82 secondary hepatic tumors
    83 sensitivity/specificity
    84 specificity
    85 specimens
    86 tool
    87 tumors
    88 variety
    89 vascular invasion
    90 γ-glutamyl hydroxymethyl rhodamine green
    91 schema:name Intraoperative imaging of hepatic cancers using γ-glutamyltranspeptidase-specific fluorophore enabling real-time identification and estimation of recurrence
    92 schema:pagination 3542
    93 schema:productId N2a2dae2216fd4c20855d9477fc9c6dcd
    94 N61a6b8b276bd4a99a41a9972b2511b81
    95 Ndc0a6dbcbf7341c9b53197f6fde6ffa3
    96 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085943317
    97 https://doi.org/10.1038/s41598-017-03760-3
    98 schema:sdDatePublished 2022-12-01T06:36
    99 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    100 schema:sdPublisher Nab9a89b350c3474292a89f8888ca5989
    101 schema:url https://doi.org/10.1038/s41598-017-03760-3
    102 sgo:license sg:explorer/license/
    103 sgo:sdDataset articles
    104 rdf:type schema:ScholarlyArticle
    105 N0c70270526a2416cb41871daad6a8bf7 rdf:first sg:person.0742343456.94
    106 rdf:rest Ndf53d68ed7ab49d0bfcf6a9a047bf06c
    107 N0e25505da2ce41e98241aa1871944b38 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    108 schema:name Humans
    109 rdf:type schema:DefinedTerm
    110 N1a496b6c37744532a85cf3686fb6d98f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    111 schema:name Cholangiocarcinoma
    112 rdf:type schema:DefinedTerm
    113 N2a2dae2216fd4c20855d9477fc9c6dcd schema:name dimensions_id
    114 schema:value pub.1085943317
    115 rdf:type schema:PropertyValue
    116 N3514994d078b4cad86d740ff7db480df rdf:first sg:person.01065410232.04
    117 rdf:rest Na1568fcd57f04699919f7d1f0656e228
    118 N3533e7d30c074646b38c0d026d004d4b schema:issueNumber 1
    119 rdf:type schema:PublicationIssue
    120 N3899c85139394750a41e6535e00e1f37 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    121 schema:name gamma-Glutamyltransferase
    122 rdf:type schema:DefinedTerm
    123 N4f5bbba5aa094bfc97b8c90f7e116eac rdf:first sg:person.01267647573.52
    124 rdf:rest N0c70270526a2416cb41871daad6a8bf7
    125 N61a6b8b276bd4a99a41a9972b2511b81 schema:name doi
    126 schema:value 10.1038/s41598-017-03760-3
    127 rdf:type schema:PropertyValue
    128 N6cce3dba0d7448319438e4dad5f6966f rdf:first sg:person.01321235732.27
    129 rdf:rest N6fc47b88f1404fcd970248c0b8a1cd49
    130 N6ec47cba11c54d328c08d6b4af450cde schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    131 schema:name Carcinoma, Hepatocellular
    132 rdf:type schema:DefinedTerm
    133 N6fc47b88f1404fcd970248c0b8a1cd49 rdf:first sg:person.0735351167.82
    134 rdf:rest rdf:nil
    135 N7afea1a025774806a6497cd7664ecabf schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    136 schema:name Colorectal Neoplasms
    137 rdf:type schema:DefinedTerm
    138 N819af9bb363247fba580c581ca3c5d59 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    139 schema:name Female
    140 rdf:type schema:DefinedTerm
    141 N822074e1f54948d7bbd64d7a640667fd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    142 schema:name Aged, 80 and over
    143 rdf:type schema:DefinedTerm
    144 Na1568fcd57f04699919f7d1f0656e228 rdf:first sg:person.01075176430.73
    145 rdf:rest Ncf157a419f3c4836922bcdf8e476f3cc
    146 Na47954aa5d814de3bc792ed1ecfa12a9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    147 schema:name Adult
    148 rdf:type schema:DefinedTerm
    149 Nab9a89b350c3474292a89f8888ca5989 schema:name Springer Nature - SN SciGraph project
    150 rdf:type schema:Organization
    151 Nbb834d6f72be4ef99f4a1aec1359bc45 rdf:first sg:person.01004770244.75
    152 rdf:rest N6cce3dba0d7448319438e4dad5f6966f
    153 Ncd2942bfa5764da28e5122644b229c4f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    154 schema:name Aged
    155 rdf:type schema:DefinedTerm
    156 Ncd6eb532e96f4cc6b49bc3343dc690f6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    157 schema:name Monitoring, Intraoperative
    158 rdf:type schema:DefinedTerm
    159 Ncf157a419f3c4836922bcdf8e476f3cc rdf:first sg:person.0635007357.60
    160 rdf:rest Nbb834d6f72be4ef99f4a1aec1359bc45
    161 Ndc0a6dbcbf7341c9b53197f6fde6ffa3 schema:name pubmed_id
    162 schema:value 28615696
    163 rdf:type schema:PropertyValue
    164 Ndc9c9cdac903426ab0ab0c69d4796184 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    165 schema:name Recurrence
    166 rdf:type schema:DefinedTerm
    167 Ndcb2deff75124d5da0af3701780d83f7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    168 schema:name Liver Neoplasms
    169 rdf:type schema:DefinedTerm
    170 Ndf53d68ed7ab49d0bfcf6a9a047bf06c rdf:first sg:person.0656702263.53
    171 rdf:rest N3514994d078b4cad86d740ff7db480df
    172 Ne90af62800a0435f876b26e03e8ec4f7 rdf:first sg:person.013243332734.44
    173 rdf:rest N4f5bbba5aa094bfc97b8c90f7e116eac
    174 Nea5ba7c8679645ab8af3ae556b5125f3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    175 schema:name Optical Imaging
    176 rdf:type schema:DefinedTerm
    177 Nf148f3985e704a30a6e38cd462586e3f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    178 schema:name Sensitivity and Specificity
    179 rdf:type schema:DefinedTerm
    180 Nf92f6eca8ca14987abb47033b06eaa91 schema:volumeNumber 7
    181 rdf:type schema:PublicationVolume
    182 Nfa1a76527a7f45f3bcd21e3020d6a044 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    183 schema:name Middle Aged
    184 rdf:type schema:DefinedTerm
    185 Nfb760915a4c542a682abe0c676018133 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    186 schema:name Male
    187 rdf:type schema:DefinedTerm
    188 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    189 schema:name Medical and Health Sciences
    190 rdf:type schema:DefinedTerm
    191 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
    192 schema:name Oncology and Carcinogenesis
    193 rdf:type schema:DefinedTerm
    194 sg:grant.5900776 http://pending.schema.org/fundedItem sg:pub.10.1038/s41598-017-03760-3
    195 rdf:type schema:MonetaryGrant
    196 sg:grant.6822241 http://pending.schema.org/fundedItem sg:pub.10.1038/s41598-017-03760-3
    197 rdf:type schema:MonetaryGrant
    198 sg:journal.1045337 schema:issn 2045-2322
    199 schema:name Scientific Reports
    200 schema:publisher Springer Nature
    201 rdf:type schema:Periodical
    202 sg:person.01004770244.75 schema:affiliation grid-institutes:grid.26999.3d
    203 schema:familyName Fukayama
    204 schema:givenName Masashi
    205 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01004770244.75
    206 rdf:type schema:Person
    207 sg:person.01065410232.04 schema:affiliation grid-institutes:grid.26999.3d
    208 schema:familyName Hasegawa
    209 schema:givenName Kiyoshi
    210 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01065410232.04
    211 rdf:type schema:Person
    212 sg:person.01075176430.73 schema:affiliation grid-institutes:grid.26999.3d
    213 schema:familyName Ushiku
    214 schema:givenName Aya
    215 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01075176430.73
    216 rdf:type schema:Person
    217 sg:person.01267647573.52 schema:affiliation grid-institutes:grid.486756.e
    218 schema:familyName Ishizawa
    219 schema:givenName Takeaki
    220 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01267647573.52
    221 rdf:type schema:Person
    222 sg:person.01321235732.27 schema:affiliation grid-institutes:grid.419082.6
    223 schema:familyName Urano
    224 schema:givenName Yasuteru
    225 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01321235732.27
    226 rdf:type schema:Person
    227 sg:person.013243332734.44 schema:affiliation grid-institutes:grid.26999.3d
    228 schema:familyName Miyata
    229 schema:givenName Yoichi
    230 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013243332734.44
    231 rdf:type schema:Person
    232 sg:person.0635007357.60 schema:affiliation grid-institutes:grid.26999.3d
    233 schema:familyName Shibahara
    234 schema:givenName Junji
    235 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0635007357.60
    236 rdf:type schema:Person
    237 sg:person.0656702263.53 schema:affiliation grid-institutes:grid.26999.3d
    238 schema:familyName Yamashita
    239 schema:givenName Suguru
    240 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0656702263.53
    241 rdf:type schema:Person
    242 sg:person.0735351167.82 schema:affiliation grid-institutes:grid.26999.3d
    243 schema:familyName Kokudo
    244 schema:givenName Norihiro
    245 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0735351167.82
    246 rdf:type schema:Person
    247 sg:person.0742343456.94 schema:affiliation grid-institutes:grid.419082.6
    248 schema:familyName Kamiya
    249 schema:givenName Mako
    250 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0742343456.94
    251 rdf:type schema:Person
    252 sg:pub.10.1007/s00535-009-0050-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1041574131
    253 https://doi.org/10.1007/s00535-009-0050-x
    254 rdf:type schema:CreativeWork
    255 sg:pub.10.1007/s11307-015-0898-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043743304
    256 https://doi.org/10.1007/s11307-015-0898-5
    257 rdf:type schema:CreativeWork
    258 sg:pub.10.1038/bjc.2014.450 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010799236
    259 https://doi.org/10.1038/bjc.2014.450
    260 rdf:type schema:CreativeWork
    261 sg:pub.10.1038/nm.1854 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000519678
    262 https://doi.org/10.1038/nm.1854
    263 rdf:type schema:CreativeWork
    264 sg:pub.10.1038/sj.bjc.6601018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039653722
    265 https://doi.org/10.1038/sj.bjc.6601018
    266 rdf:type schema:CreativeWork
    267 sg:pub.10.1038/srep12080 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034359126
    268 https://doi.org/10.1038/srep12080
    269 rdf:type schema:CreativeWork
    270 sg:pub.10.1038/srep27525 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001367454
    271 https://doi.org/10.1038/srep27525
    272 rdf:type schema:CreativeWork
    273 sg:pub.10.1186/s12885-016-2421-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1038944986
    274 https://doi.org/10.1186/s12885-016-2421-z
    275 rdf:type schema:CreativeWork
    276 sg:pub.10.1245/s10434-013-3360-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036991606
    277 https://doi.org/10.1245/s10434-013-3360-4
    278 rdf:type schema:CreativeWork
    279 grid-institutes:grid.26999.3d schema:alternateName Department of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
    280 Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
    281 schema:name Department of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
    282 Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
    283 rdf:type schema:Organization
    284 grid-institutes:grid.419082.6 schema:alternateName CREST, Japan Agency for Medical Research and Development, Tokyo, Japan
    285 PRESTO, Japan Science and Technology Agency, Saitama, Japan
    286 schema:name CREST, Japan Agency for Medical Research and Development, Tokyo, Japan
    287 Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan
    288 Laboratory of Chemical Biology and Molecular Imaging, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
    289 PRESTO, Japan Science and Technology Agency, Saitama, Japan
    290 rdf:type schema:Organization
    291 grid-institutes:grid.486756.e schema:alternateName Department of Gastroenterological Surgery, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan
    292 schema:name Department of Gastroenterological Surgery, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan
    293 Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
    294 rdf:type schema:Organization
     




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


    ...