Quantitative assessment of invasive mena isoforms (Menacalc) as an independent prognostic marker in breast cancer View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-10

AUTHORS

Seema Agarwal, Frank B Gertler, Michele Balsamo, John S Condeelis, Robert L Camp, Xiaonan Xue, Juan Lin, Thomas E Rohan, David L Rimm

ABSTRACT

INTRODUCTION: Mena, an Ena/VASP protein family member, is a key actin regulatory protein. Mena is up-regulated in breast cancers and promotes invasion and motility of tumor cells. Mena has multiple splice variants, including Mena invasive (MenaINV) and Mena11a, which are expressed in invasive or non-invasive tumor cells, respectively. We developed a multiplex quantitative immunofluorescence (MQIF) approach to assess the fraction of Mena lacking 11a sequence as a method to infer the presence of invasive tumor cells represented as total Mena minus Mena11a (called Menacalc) and determined its association with metastasis in breast cancer. METHODS: The MQIF method was applied to two independent primary breast cancer cohorts (Cohort 1 with 501 and Cohort 2 with 296 patients) using antibodies against Mena and its isoform, Mena11a. Menacalc was determined for each patient and assessed for association with risk of disease-specific death. RESULTS: Total Mena or Mena11a isoform expression failed to show any statistically significant association with outcome in either cohort. However, assessment of Menacalc showed that relatively high levels of this biomarker is associated with poor outcome in two independent breast cancer cohorts (log rank P = 0.0004 for Cohort 1 and 0.0321 for Cohort 2). Multivariate analysis on combined cohorts revealed that high Menacalc is associated with poor outcome, independent of age, node status, receptor status and tumor size. CONCLUSIONS: High Menacalc levels identify a subgroup of breast cancer patients with poor disease-specific survival, suggesting that Menacalc may serve as a biomarker for metastasis. More... »

PAGES

r124

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/bcr3318

DOI

http://dx.doi.org/10.1186/bcr3318

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1048001816

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22971274


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"
      }, 
      {
        "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": "Biomarkers, Tumor", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Breast Neoplasms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cohort Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Expression", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Immunohistochemistry", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Microfilament Proteins", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Middle Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Prognosis", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Protein Isoforms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Reproducibility of Results", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Risk Factors", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Survival Analysis", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Tumor Burden", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Yale University", 
          "id": "https://www.grid.ac/institutes/grid.47100.32", 
          "name": [
            "Department of Pathology, Yale University School of Medicine, 06520, New Haven, CT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Agarwal", 
        "givenName": "Seema", 
        "id": "sg:person.01073522325.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01073522325.43"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Massachusetts Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.116068.8", 
          "name": [
            "Department of Biology and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 02138, Cambridge, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gertler", 
        "givenName": "Frank B", 
        "id": "sg:person.0755724733.10", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0755724733.10"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Massachusetts Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.116068.8", 
          "name": [
            "Department of Biology and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 02138, Cambridge, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Balsamo", 
        "givenName": "Michele", 
        "id": "sg:person.01065574377.64", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01065574377.64"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Albert Einstein College of Medicine", 
          "id": "https://www.grid.ac/institutes/grid.251993.5", 
          "name": [
            "Department of Anatomy and Structural Biology, Gruss Lipper Biophotonics Center, Albert Einstein College of Medicine, 10461, Bronx, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Condeelis", 
        "givenName": "John S", 
        "id": "sg:person.01054601762.73", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01054601762.73"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Yale University", 
          "id": "https://www.grid.ac/institutes/grid.47100.32", 
          "name": [
            "Department of Pathology, Yale University School of Medicine, 06520, New Haven, CT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Camp", 
        "givenName": "Robert L", 
        "id": "sg:person.012367147604.10", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012367147604.10"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Albert Einstein College of Medicine", 
          "id": "https://www.grid.ac/institutes/grid.251993.5", 
          "name": [
            "Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 10461, Bronx, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xue", 
        "givenName": "Xiaonan", 
        "id": "sg:person.015121664537.31", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015121664537.31"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Albert Einstein College of Medicine", 
          "id": "https://www.grid.ac/institutes/grid.251993.5", 
          "name": [
            "Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 10461, Bronx, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lin", 
        "givenName": "Juan", 
        "id": "sg:person.0600327571.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0600327571.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Albert Einstein College of Medicine", 
          "id": "https://www.grid.ac/institutes/grid.251993.5", 
          "name": [
            "Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 10461, Bronx, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rohan", 
        "givenName": "Thomas E", 
        "id": "sg:person.012603353577.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012603353577.80"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Yale University", 
          "id": "https://www.grid.ac/institutes/grid.47100.32", 
          "name": [
            "Department of Pathology, Yale University School of Medicine, 06520, New Haven, CT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rimm", 
        "givenName": "David L", 
        "id": "sg:person.0754207153.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0754207153.13"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.devcel.2008.09.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003143948"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/0008-5472.can-04-1136", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003849052"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/1078-0432.ccr-08-2179", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006243400"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pgen.1002218", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008760534"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10585-011-9388-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016283469", 
          "https://doi.org/10.1007/s10585-011-9388-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0092-8674(00)81341-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018539855"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/bcr2784", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021123983", 
          "https://doi.org/10.1186/bcr2784"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-60327-811-9_12", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026754818", 
          "https://doi.org/10.1007/978-1-60327-811-9_12"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1203543", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027317432"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.devcel.2008.05.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027518913"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1200/jco.2010.32.9706", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029175884"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nm791", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030132345", 
          "https://doi.org/10.1038/nm791"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nm791", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030132345", 
          "https://doi.org/10.1038/nm791"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ncb0208-118", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030405879", 
          "https://doi.org/10.1038/ncb0208-118"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrc2148", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031584740", 
          "https://doi.org/10.1038/nrc2148"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10585-008-9225-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032751094", 
          "https://doi.org/10.1007/s10585-008-9225-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cell.2011.09.024", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039482183"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1242/jcs.038125", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039765586"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1242/jcs.086231", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040814049"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/labinvest.3780204", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045657100", 
          "https://doi.org/10.1038/labinvest.3780204"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/labinvest.3780204", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045657100", 
          "https://doi.org/10.1038/labinvest.3780204"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/1078-0432.ccr-08-0436", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045768997"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tcb.2010.10.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050667548"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/cncr.24277", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053641027"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/cncr.24277", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053641027"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1043/1543-2165-134.4.613", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078141336"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2012-10", 
    "datePublishedReg": "2012-10-01", 
    "description": "INTRODUCTION: Mena, an Ena/VASP protein family member, is a key actin regulatory protein. Mena is up-regulated in breast cancers and promotes invasion and motility of tumor cells. Mena has multiple splice variants, including Mena invasive (MenaINV) and Mena11a, which are expressed in invasive or non-invasive tumor cells, respectively. We developed a multiplex quantitative immunofluorescence (MQIF) approach to assess the fraction of Mena lacking 11a sequence as a method to infer the presence of invasive tumor cells represented as total Mena minus Mena11a (called Menacalc) and determined its association with metastasis in breast cancer.\nMETHODS: The MQIF method was applied to two independent primary breast cancer cohorts (Cohort 1 with 501 and Cohort 2 with 296 patients) using antibodies against Mena and its isoform, Mena11a. Menacalc was determined for each patient and assessed for association with risk of disease-specific death.\nRESULTS: Total Mena or Mena11a isoform expression failed to show any statistically significant association with outcome in either cohort. However, assessment of Menacalc showed that relatively high levels of this biomarker is associated with poor outcome in two independent breast cancer cohorts (log rank P = 0.0004 for Cohort 1 and 0.0321 for Cohort 2). Multivariate analysis on combined cohorts revealed that high Menacalc is associated with poor outcome, independent of age, node status, receptor status and tumor size.\nCONCLUSIONS: High Menacalc levels identify a subgroup of breast cancer patients with poor disease-specific survival, suggesting that Menacalc may serve as a biomarker for metastasis.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/bcr3318", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2699024", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2435795", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1022375", 
        "issn": [
          "1465-5411", 
          "1465-542X"
        ], 
        "name": "Breast Cancer Research", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "5", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "14"
      }
    ], 
    "name": "Quantitative assessment of invasive mena isoforms (Menacalc) as an independent prognostic marker in breast cancer", 
    "pagination": "r124", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "e4abc7ec3cbfda9fa805c0830f0ae956f47defca6218af14d37c2be4febc2855"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "22971274"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100927353"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/bcr3318"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1048001816"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/bcr3318", 
      "https://app.dimensions.ai/details/publication/pub.1048001816"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T14:11", 
    "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/v90/0000000001_0000000264/records_8660_00000516.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2Fbcr3318"
  }
]
 

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/bcr3318'

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/bcr3318'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/bcr3318'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/bcr3318'


 

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

281 TRIPLES      21 PREDICATES      69 URIs      38 LITERALS      26 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/bcr3318 schema:about N1f65fc75f5d04829a6b6915335ccfbae
2 N31f1d529b7da44749d913e293442de26
3 N35bc7f22628d49618f2d1ef2b4fae576
4 N4dc096f2008c4f0c9f1841473c3ab4d7
5 N503679a91d644a04952aae32be569a8b
6 N54c469a6d4304a6ca7c3c52970bf7683
7 N633f0737cf9d436290c69455c9410865
8 N6d5f174446064acebe4de241a79e5824
9 N6e3e75e3293448e98f700efba098fe4d
10 N72f67c4ac87e4699862da2cfdc470bc4
11 N8b459777143643ccbf8c780050758cfd
12 Na7272a6627814adfb6f98940da8f9d46
13 Nb5336980422c4afaa708c6ca3f63f259
14 Nba4d1585e12143398d795253b6a5d89a
15 Nd8894be01e30432f9131e76378ea8ac9
16 Ndd89b800878c4a7baec74e9a9d40c84f
17 Ne76c4fc62a6c474eb5f3db5a97aa3cf8
18 anzsrc-for:11
19 anzsrc-for:1112
20 schema:author Nf3658d7af5f1412f887610876454e322
21 schema:citation sg:pub.10.1007/978-1-60327-811-9_12
22 sg:pub.10.1007/s10585-008-9225-8
23 sg:pub.10.1007/s10585-011-9388-6
24 sg:pub.10.1038/labinvest.3780204
25 sg:pub.10.1038/ncb0208-118
26 sg:pub.10.1038/nm791
27 sg:pub.10.1038/nrc2148
28 sg:pub.10.1186/bcr2784
29 https://doi.org/10.1002/cncr.24277
30 https://doi.org/10.1016/j.cell.2011.09.024
31 https://doi.org/10.1016/j.devcel.2008.05.013
32 https://doi.org/10.1016/j.devcel.2008.09.003
33 https://doi.org/10.1016/j.tcb.2010.10.001
34 https://doi.org/10.1016/s0092-8674(00)81341-0
35 https://doi.org/10.1043/1543-2165-134.4.613
36 https://doi.org/10.1126/science.1203543
37 https://doi.org/10.1158/0008-5472.can-04-1136
38 https://doi.org/10.1158/1078-0432.ccr-08-0436
39 https://doi.org/10.1158/1078-0432.ccr-08-2179
40 https://doi.org/10.1200/jco.2010.32.9706
41 https://doi.org/10.1242/jcs.038125
42 https://doi.org/10.1242/jcs.086231
43 https://doi.org/10.1371/journal.pgen.1002218
44 schema:datePublished 2012-10
45 schema:datePublishedReg 2012-10-01
46 schema:description INTRODUCTION: Mena, an Ena/VASP protein family member, is a key actin regulatory protein. Mena is up-regulated in breast cancers and promotes invasion and motility of tumor cells. Mena has multiple splice variants, including Mena invasive (MenaINV) and Mena11a, which are expressed in invasive or non-invasive tumor cells, respectively. We developed a multiplex quantitative immunofluorescence (MQIF) approach to assess the fraction of Mena lacking 11a sequence as a method to infer the presence of invasive tumor cells represented as total Mena minus Mena11a (called Menacalc) and determined its association with metastasis in breast cancer. METHODS: The MQIF method was applied to two independent primary breast cancer cohorts (Cohort 1 with 501 and Cohort 2 with 296 patients) using antibodies against Mena and its isoform, Mena11a. Menacalc was determined for each patient and assessed for association with risk of disease-specific death. RESULTS: Total Mena or Mena11a isoform expression failed to show any statistically significant association with outcome in either cohort. However, assessment of Menacalc showed that relatively high levels of this biomarker is associated with poor outcome in two independent breast cancer cohorts (log rank P = 0.0004 for Cohort 1 and 0.0321 for Cohort 2). Multivariate analysis on combined cohorts revealed that high Menacalc is associated with poor outcome, independent of age, node status, receptor status and tumor size. CONCLUSIONS: High Menacalc levels identify a subgroup of breast cancer patients with poor disease-specific survival, suggesting that Menacalc may serve as a biomarker for metastasis.
47 schema:genre research_article
48 schema:inLanguage en
49 schema:isAccessibleForFree true
50 schema:isPartOf Na2aef40c0f824902abad50d7d9c2c052
51 Nbf0caaf6798e4007bb5855261664d4ee
52 sg:journal.1022375
53 schema:name Quantitative assessment of invasive mena isoforms (Menacalc) as an independent prognostic marker in breast cancer
54 schema:pagination r124
55 schema:productId N20119c3764574f2bbb635ca8b3562836
56 N3a6b5688165d45a79966875c55c7af14
57 N4461dc48dbc84161a44fe63557ea5797
58 Ne059c3eb61174e9f91358147389e6359
59 Nf142755f8675462f9acaa557706bb89e
60 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048001816
61 https://doi.org/10.1186/bcr3318
62 schema:sdDatePublished 2019-04-10T14:11
63 schema:sdLicense https://scigraph.springernature.com/explorer/license/
64 schema:sdPublisher Neccf9d9e7c5c41f9a83a4fb78ac0e81d
65 schema:url http://link.springer.com/10.1186%2Fbcr3318
66 sgo:license sg:explorer/license/
67 sgo:sdDataset articles
68 rdf:type schema:ScholarlyArticle
69 N05284fa0b09f407a9b9753874bf11bec rdf:first sg:person.0755724733.10
70 rdf:rest Nd2055bbe414d4c53aea7134adf191029
71 N1f65fc75f5d04829a6b6915335ccfbae schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
72 schema:name Protein Isoforms
73 rdf:type schema:DefinedTerm
74 N20119c3764574f2bbb635ca8b3562836 schema:name dimensions_id
75 schema:value pub.1048001816
76 rdf:type schema:PropertyValue
77 N31f1d529b7da44749d913e293442de26 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
78 schema:name Biomarkers, Tumor
79 rdf:type schema:DefinedTerm
80 N35bc7f22628d49618f2d1ef2b4fae576 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
81 schema:name Microfilament Proteins
82 rdf:type schema:DefinedTerm
83 N3a6b5688165d45a79966875c55c7af14 schema:name doi
84 schema:value 10.1186/bcr3318
85 rdf:type schema:PropertyValue
86 N4461dc48dbc84161a44fe63557ea5797 schema:name readcube_id
87 schema:value e4abc7ec3cbfda9fa805c0830f0ae956f47defca6218af14d37c2be4febc2855
88 rdf:type schema:PropertyValue
89 N4dc096f2008c4f0c9f1841473c3ab4d7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
90 schema:name Prognosis
91 rdf:type schema:DefinedTerm
92 N503679a91d644a04952aae32be569a8b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
93 schema:name Reproducibility of Results
94 rdf:type schema:DefinedTerm
95 N521127082a954255a23471dd3fdf94aa rdf:first sg:person.012367147604.10
96 rdf:rest Nbcdc911e9e334bde8a217464c7564deb
97 N54c469a6d4304a6ca7c3c52970bf7683 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
98 schema:name Breast Neoplasms
99 rdf:type schema:DefinedTerm
100 N633f0737cf9d436290c69455c9410865 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
101 schema:name Tumor Burden
102 rdf:type schema:DefinedTerm
103 N6d5f174446064acebe4de241a79e5824 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
104 schema:name Survival Analysis
105 rdf:type schema:DefinedTerm
106 N6e3e75e3293448e98f700efba098fe4d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
107 schema:name Immunohistochemistry
108 rdf:type schema:DefinedTerm
109 N72f67c4ac87e4699862da2cfdc470bc4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
110 schema:name Female
111 rdf:type schema:DefinedTerm
112 N87088aa2dc4c4eb3a81f8ed109e64500 rdf:first sg:person.012603353577.80
113 rdf:rest Nfbf38f4b16334929b59bf9b50aa399a2
114 N8b459777143643ccbf8c780050758cfd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Aged
116 rdf:type schema:DefinedTerm
117 Na2aef40c0f824902abad50d7d9c2c052 schema:volumeNumber 14
118 rdf:type schema:PublicationVolume
119 Na7272a6627814adfb6f98940da8f9d46 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
120 schema:name Humans
121 rdf:type schema:DefinedTerm
122 Nb5336980422c4afaa708c6ca3f63f259 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
123 schema:name Gene Expression
124 rdf:type schema:DefinedTerm
125 Nba4d1585e12143398d795253b6a5d89a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
126 schema:name Adult
127 rdf:type schema:DefinedTerm
128 Nbcdc911e9e334bde8a217464c7564deb rdf:first sg:person.015121664537.31
129 rdf:rest Nc124f08ed79044e2a209bd747448241d
130 Nbf0caaf6798e4007bb5855261664d4ee schema:issueNumber 5
131 rdf:type schema:PublicationIssue
132 Nc124f08ed79044e2a209bd747448241d rdf:first sg:person.0600327571.48
133 rdf:rest N87088aa2dc4c4eb3a81f8ed109e64500
134 Nc234cfac5cc449c6bc2badf2b55f042d rdf:first sg:person.01054601762.73
135 rdf:rest N521127082a954255a23471dd3fdf94aa
136 Nd2055bbe414d4c53aea7134adf191029 rdf:first sg:person.01065574377.64
137 rdf:rest Nc234cfac5cc449c6bc2badf2b55f042d
138 Nd8894be01e30432f9131e76378ea8ac9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Risk Factors
140 rdf:type schema:DefinedTerm
141 Ndd89b800878c4a7baec74e9a9d40c84f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
142 schema:name Middle Aged
143 rdf:type schema:DefinedTerm
144 Ne059c3eb61174e9f91358147389e6359 schema:name pubmed_id
145 schema:value 22971274
146 rdf:type schema:PropertyValue
147 Ne76c4fc62a6c474eb5f3db5a97aa3cf8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
148 schema:name Cohort Studies
149 rdf:type schema:DefinedTerm
150 Neccf9d9e7c5c41f9a83a4fb78ac0e81d schema:name Springer Nature - SN SciGraph project
151 rdf:type schema:Organization
152 Nf142755f8675462f9acaa557706bb89e schema:name nlm_unique_id
153 schema:value 100927353
154 rdf:type schema:PropertyValue
155 Nf3658d7af5f1412f887610876454e322 rdf:first sg:person.01073522325.43
156 rdf:rest N05284fa0b09f407a9b9753874bf11bec
157 Nfbf38f4b16334929b59bf9b50aa399a2 rdf:first sg:person.0754207153.13
158 rdf:rest rdf:nil
159 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
160 schema:name Medical and Health Sciences
161 rdf:type schema:DefinedTerm
162 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
163 schema:name Oncology and Carcinogenesis
164 rdf:type schema:DefinedTerm
165 sg:grant.2435795 http://pending.schema.org/fundedItem sg:pub.10.1186/bcr3318
166 rdf:type schema:MonetaryGrant
167 sg:grant.2699024 http://pending.schema.org/fundedItem sg:pub.10.1186/bcr3318
168 rdf:type schema:MonetaryGrant
169 sg:journal.1022375 schema:issn 1465-5411
170 1465-542X
171 schema:name Breast Cancer Research
172 rdf:type schema:Periodical
173 sg:person.01054601762.73 schema:affiliation https://www.grid.ac/institutes/grid.251993.5
174 schema:familyName Condeelis
175 schema:givenName John S
176 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01054601762.73
177 rdf:type schema:Person
178 sg:person.01065574377.64 schema:affiliation https://www.grid.ac/institutes/grid.116068.8
179 schema:familyName Balsamo
180 schema:givenName Michele
181 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01065574377.64
182 rdf:type schema:Person
183 sg:person.01073522325.43 schema:affiliation https://www.grid.ac/institutes/grid.47100.32
184 schema:familyName Agarwal
185 schema:givenName Seema
186 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01073522325.43
187 rdf:type schema:Person
188 sg:person.012367147604.10 schema:affiliation https://www.grid.ac/institutes/grid.47100.32
189 schema:familyName Camp
190 schema:givenName Robert L
191 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012367147604.10
192 rdf:type schema:Person
193 sg:person.012603353577.80 schema:affiliation https://www.grid.ac/institutes/grid.251993.5
194 schema:familyName Rohan
195 schema:givenName Thomas E
196 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012603353577.80
197 rdf:type schema:Person
198 sg:person.015121664537.31 schema:affiliation https://www.grid.ac/institutes/grid.251993.5
199 schema:familyName Xue
200 schema:givenName Xiaonan
201 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015121664537.31
202 rdf:type schema:Person
203 sg:person.0600327571.48 schema:affiliation https://www.grid.ac/institutes/grid.251993.5
204 schema:familyName Lin
205 schema:givenName Juan
206 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0600327571.48
207 rdf:type schema:Person
208 sg:person.0754207153.13 schema:affiliation https://www.grid.ac/institutes/grid.47100.32
209 schema:familyName Rimm
210 schema:givenName David L
211 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0754207153.13
212 rdf:type schema:Person
213 sg:person.0755724733.10 schema:affiliation https://www.grid.ac/institutes/grid.116068.8
214 schema:familyName Gertler
215 schema:givenName Frank B
216 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0755724733.10
217 rdf:type schema:Person
218 sg:pub.10.1007/978-1-60327-811-9_12 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026754818
219 https://doi.org/10.1007/978-1-60327-811-9_12
220 rdf:type schema:CreativeWork
221 sg:pub.10.1007/s10585-008-9225-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032751094
222 https://doi.org/10.1007/s10585-008-9225-8
223 rdf:type schema:CreativeWork
224 sg:pub.10.1007/s10585-011-9388-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016283469
225 https://doi.org/10.1007/s10585-011-9388-6
226 rdf:type schema:CreativeWork
227 sg:pub.10.1038/labinvest.3780204 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045657100
228 https://doi.org/10.1038/labinvest.3780204
229 rdf:type schema:CreativeWork
230 sg:pub.10.1038/ncb0208-118 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030405879
231 https://doi.org/10.1038/ncb0208-118
232 rdf:type schema:CreativeWork
233 sg:pub.10.1038/nm791 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030132345
234 https://doi.org/10.1038/nm791
235 rdf:type schema:CreativeWork
236 sg:pub.10.1038/nrc2148 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031584740
237 https://doi.org/10.1038/nrc2148
238 rdf:type schema:CreativeWork
239 sg:pub.10.1186/bcr2784 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021123983
240 https://doi.org/10.1186/bcr2784
241 rdf:type schema:CreativeWork
242 https://doi.org/10.1002/cncr.24277 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053641027
243 rdf:type schema:CreativeWork
244 https://doi.org/10.1016/j.cell.2011.09.024 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039482183
245 rdf:type schema:CreativeWork
246 https://doi.org/10.1016/j.devcel.2008.05.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027518913
247 rdf:type schema:CreativeWork
248 https://doi.org/10.1016/j.devcel.2008.09.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003143948
249 rdf:type schema:CreativeWork
250 https://doi.org/10.1016/j.tcb.2010.10.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050667548
251 rdf:type schema:CreativeWork
252 https://doi.org/10.1016/s0092-8674(00)81341-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018539855
253 rdf:type schema:CreativeWork
254 https://doi.org/10.1043/1543-2165-134.4.613 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078141336
255 rdf:type schema:CreativeWork
256 https://doi.org/10.1126/science.1203543 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027317432
257 rdf:type schema:CreativeWork
258 https://doi.org/10.1158/0008-5472.can-04-1136 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003849052
259 rdf:type schema:CreativeWork
260 https://doi.org/10.1158/1078-0432.ccr-08-0436 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045768997
261 rdf:type schema:CreativeWork
262 https://doi.org/10.1158/1078-0432.ccr-08-2179 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006243400
263 rdf:type schema:CreativeWork
264 https://doi.org/10.1200/jco.2010.32.9706 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029175884
265 rdf:type schema:CreativeWork
266 https://doi.org/10.1242/jcs.038125 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039765586
267 rdf:type schema:CreativeWork
268 https://doi.org/10.1242/jcs.086231 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040814049
269 rdf:type schema:CreativeWork
270 https://doi.org/10.1371/journal.pgen.1002218 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008760534
271 rdf:type schema:CreativeWork
272 https://www.grid.ac/institutes/grid.116068.8 schema:alternateName Massachusetts Institute of Technology
273 schema:name Department of Biology and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, 02138, Cambridge, MA, USA
274 rdf:type schema:Organization
275 https://www.grid.ac/institutes/grid.251993.5 schema:alternateName Albert Einstein College of Medicine
276 schema:name Department of Anatomy and Structural Biology, Gruss Lipper Biophotonics Center, Albert Einstein College of Medicine, 10461, Bronx, NY, USA
277 Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 10461, Bronx, NY, USA
278 rdf:type schema:Organization
279 https://www.grid.ac/institutes/grid.47100.32 schema:alternateName Yale University
280 schema:name Department of Pathology, Yale University School of Medicine, 06520, New Haven, CT, USA
281 rdf:type schema:Organization
 




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


...