A quantitative multimodal metabolomic assay for colorectal cancer View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-01-04

AUTHORS

Farshad Farshidfar, Karen A. Kopciuk, Robert Hilsden, S. Elizabeth McGregor, Vera C. Mazurak, W. Donald Buie, Anthony MacLean, Hans J. Vogel, Oliver F. Bathe

ABSTRACT

BackgroundEarly diagnosis of colorectal cancer (CRC) simplifies treatment and improves treatment outcomes. We previously described a diagnostic metabolomic biomarker derived from semi-quantitative gas chromatography-mass spectrometry. Our objective was to determine whether a quantitative assay of additional metabolomic features, including parts of the lipidome could enhance diagnostic power; and whether there was an advantage to deriving a combined diagnostic signature with a broader metabolomic representation.MethodsThe well-characterized Biocrates P150 kit was used to quantify 163 metabolites in patients with CRC (N = 62), adenoma (N = 31), and age- and gender-matched disease-free controls (N = 81). Metabolites included in the analysis included phosphatidylcholines, sphingomyelins, acylcarnitines, and amino acids. Using a training set of 32 CRC and 21 disease-free controls, a multivariate metabolomic orthogonal partial least squares (OPLS) classifier was developed. An independent set of 28 CRC and 20 matched healthy controls was used for validation. Features characterizing 31 colorectal adenomas from their healthy matched controls were also explored, and a multivariate OPLS classifier for colorectal adenoma could be proposed.ResultsThe metabolomic profile that distinguished CRC from controls consisted of 48 metabolites (R2Y = 0.83, Q2Y = 0.75, CV-ANOVA p-value < 0.00001). In this quantitative assay, the coefficient of variance for each metabolite was <10%, and this dramatically enhanced the separation of these groups. Independent validation resulted in AUROC of 0.98 (95% CI, 0.93–1.00) and sensitivity and specificity of 93% and 95%. Similarly, we were able to distinguish adenoma from controls (R2Y = 0.30, Q2Y = 0.20, CV-ANOVA p-value = 0.01; internal AUROC = 0.82 (95% CI, 0.72–0.93)). When combined with the previously generated GC-MS signatures for CRC and adenoma, the candidate biomarker performance improved slightly.ConclusionThe diagnostic power for metabolomic tests for colorectal neoplasia can be improved by utilizing a multimodal approach and combining metabolites from diverse chemical classes. In addition, quantification of metabolites enhances separation of disease-specific metabolomic profiles. Our future efforts will be focused on developing a quantitative assay for the metabolites comprising the optimal diagnostic biomarker. More... »

PAGES

26

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12885-017-3923-z

DOI

http://dx.doi.org/10.1186/s12885-017-3923-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100194585

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29301511


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": "Adenoma", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Amino Acids", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Biomarkers, Tumor", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Carnitine", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Colorectal Neoplasms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Early Detection of Cancer", 
        "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": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mass Spectrometry", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Metabolome", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Metabolomics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Middle Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Phosphatidylcholines", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sphingomyelins", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Oncology, University of Calgary, Calgary, AB, Canada", 
          "id": "http://www.grid.ac/institutes/grid.22072.35", 
          "name": [
            "Department of Surgery, University of Calgary, Calgary, AB, Canada", 
            "Department of Oncology, University of Calgary, Calgary, AB, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Farshidfar", 
        "givenName": "Farshad", 
        "id": "sg:person.01253745362.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01253745362.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Population Health Research, Alberta Health Services, Calgary, AB, Canada", 
          "id": "http://www.grid.ac/institutes/grid.413574.0", 
          "name": [
            "Department Mathematics and Statistics, University of Calgary, Calgary, AB, Canada", 
            "Population Health Research, Alberta Health Services, Calgary, AB, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kopciuk", 
        "givenName": "Karen A.", 
        "id": "sg:person.01223356633.10", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01223356633.10"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Forzani & MacPhail Colon Cancer Screening Centre, Calgary, AB, Canada", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Department of Medicine, University of Calgary, Calgary, AB, Canada", 
            "Forzani & MacPhail Colon Cancer Screening Centre, Calgary, AB, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hilsden", 
        "givenName": "Robert", 
        "id": "sg:person.01165640331.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01165640331.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Population Health Research, Alberta Health Services, Calgary, AB, Canada", 
          "id": "http://www.grid.ac/institutes/grid.413574.0", 
          "name": [
            "Department of Oncology, University of Calgary, Calgary, AB, Canada", 
            "Population Health Research, Alberta Health Services, Calgary, AB, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "McGregor", 
        "givenName": "S. Elizabeth", 
        "id": "sg:person.01261400416.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01261400416.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Canada", 
          "id": "http://www.grid.ac/institutes/grid.17089.37", 
          "name": [
            "Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mazurak", 
        "givenName": "Vera C.", 
        "id": "sg:person.0663327635.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0663327635.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Surgery, University of Calgary, Calgary, AB, Canada", 
          "id": "http://www.grid.ac/institutes/grid.22072.35", 
          "name": [
            "Department of Surgery, University of Calgary, Calgary, AB, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Buie", 
        "givenName": "W. Donald", 
        "id": "sg:person.01136414614.60", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136414614.60"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Surgery, University of Calgary, Calgary, AB, Canada", 
          "id": "http://www.grid.ac/institutes/grid.22072.35", 
          "name": [
            "Department of Surgery, University of Calgary, Calgary, AB, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "MacLean", 
        "givenName": "Anthony", 
        "id": "sg:person.0711260173.53", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0711260173.53"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biological Sciences, University of Calgary, Calgary, AB, Canada", 
          "id": "http://www.grid.ac/institutes/grid.22072.35", 
          "name": [
            "Department of Biological Sciences, University of Calgary, Calgary, AB, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vogel", 
        "givenName": "Hans J.", 
        "id": "sg:person.01065466412.66", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01065466412.66"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Surgical Oncology, Tom Baker Cancer Centre, 1331 \u2013 29th St NW, T2N 4N2, Calgary, AB, Canada", 
          "id": "http://www.grid.ac/institutes/grid.413574.0", 
          "name": [
            "Department of Surgery, University of Calgary, Calgary, AB, Canada", 
            "Department of Oncology, University of Calgary, Calgary, AB, Canada", 
            "Division of Surgical Oncology, Tom Baker Cancer Centre, 1331 \u2013 29th St NW, T2N 4N2, Calgary, AB, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bathe", 
        "givenName": "Oliver F.", 
        "id": "sg:person.01057564204.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01057564204.51"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s11306-007-0099-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022973183", 
          "https://doi.org/10.1007/s11306-007-0099-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng.2985", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048121271", 
          "https://doi.org/10.1038/ng.2985"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gm341", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022312204", 
          "https://doi.org/10.1186/gm341"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-230x-10-140", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040429680", 
          "https://doi.org/10.1186/1471-230x-10-140"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/bjc.2016.243", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016876945", 
          "https://doi.org/10.1038/bjc.2016.243"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10654-014-9901-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043063812", 
          "https://doi.org/10.1007/s10654-014-9901-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11306-011-0293-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004591576", 
          "https://doi.org/10.1007/s11306-011-0293-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11306-011-0357-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038023758", 
          "https://doi.org/10.1007/s11306-011-0357-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1741-7015-8-13", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010330938", 
          "https://doi.org/10.1186/1741-7015-8-13"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-01-04", 
    "datePublishedReg": "2018-01-04", 
    "description": "BackgroundEarly diagnosis of colorectal cancer (CRC) simplifies treatment and improves treatment outcomes. We previously described a diagnostic metabolomic biomarker derived from semi-quantitative gas chromatography-mass spectrometry. Our objective was to determine whether a quantitative assay of additional metabolomic features, including parts of the lipidome could enhance diagnostic power; and whether there was an advantage to deriving a combined diagnostic signature with a broader metabolomic representation.MethodsThe well-characterized Biocrates P150 kit was used to quantify 163 metabolites in patients with CRC (N\u00a0=\u00a062), adenoma (N\u00a0=\u00a031), and age- and gender-matched disease-free controls (N\u00a0=\u00a081). Metabolites included in the analysis included phosphatidylcholines, sphingomyelins, acylcarnitines, and amino acids. Using a training set of 32 CRC and 21 disease-free controls, a multivariate metabolomic orthogonal partial least squares (OPLS) classifier was developed. An independent set of 28 CRC and 20 matched healthy controls was used for validation. Features characterizing 31 colorectal adenomas from their healthy matched controls were also explored, and a multivariate OPLS classifier for colorectal adenoma could be proposed.ResultsThe metabolomic profile that distinguished CRC from controls consisted of 48 metabolites (R2Y\u00a0=\u00a00.83, Q2Y\u00a0=\u00a00.75, CV-ANOVA p-value\u00a0<\u00a00.00001). In this quantitative assay, the coefficient of variance for each metabolite was <10%, and this dramatically enhanced the separation of these groups. Independent validation resulted in AUROC of 0.98 (95% CI, 0.93\u20131.00) and sensitivity and specificity of 93% and 95%. Similarly, we were able to distinguish adenoma from controls (R2Y\u00a0=\u00a00.30, Q2Y\u00a0=\u00a00.20, CV-ANOVA p-value\u00a0=\u00a00.01; internal AUROC\u00a0=\u00a00.82 (95% CI, 0.72\u20130.93)). When combined with the previously generated GC-MS signatures for CRC and adenoma, the candidate biomarker performance improved slightly.ConclusionThe diagnostic power for metabolomic tests for colorectal neoplasia can be improved by utilizing a multimodal approach and combining metabolites from diverse chemical classes. In addition, quantification of metabolites enhances separation of disease-specific metabolomic profiles. Our future efforts will be focused on developing a quantitative assay for the metabolites comprising the optimal diagnostic biomarker.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/s12885-017-3923-z", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1024632", 
        "issn": [
          "1471-2407"
        ], 
        "name": "BMC Cancer", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "18"
      }
    ], 
    "keywords": [
      "disease-free controls", 
      "colorectal adenomas", 
      "metabolomic profiles", 
      "diagnostic power", 
      "BackgroundEarly diagnosis", 
      "colorectal neoplasia", 
      "colorectal cancer", 
      "healthy controls", 
      "treatment outcomes", 
      "metabolomic biomarkers", 
      "diagnostic biomarkers", 
      "adenomas", 
      "metabolomic tests", 
      "biomarker performance", 
      "quantitative assay", 
      "CRC", 
      "simplifies treatment", 
      "metabolomic features", 
      "multimodal approach", 
      "metabolomics assays", 
      "biomarkers", 
      "metabolites", 
      "assays", 
      "quantification of metabolites", 
      "diverse chemical classes", 
      "diagnostic signature", 
      "coefficient of variance", 
      "patients", 
      "future efforts", 
      "independent validation", 
      "control", 
      "neoplasia", 
      "cancer", 
      "diagnosis", 
      "acylcarnitines", 
      "AUROC", 
      "outcomes", 
      "age", 
      "chromatography-mass spectrometry", 
      "treatment", 
      "amino acids", 
      "chemical classes", 
      "MethodsThe", 
      "lipidome", 
      "gas chromatography-mass spectrometry", 
      "kit", 
      "group", 
      "profile", 
      "sphingomyelin", 
      "specificity", 
      "phosphatidylcholine", 
      "partial least squares classifier", 
      "sensitivity", 
      "test", 
      "validation", 
      "features", 
      "acid", 
      "objective", 
      "optimal diagnostic biomarker", 
      "addition", 
      "quantification", 
      "signatures", 
      "analysis", 
      "variance", 
      "independent set", 
      "efforts", 
      "part", 
      "training set", 
      "spectrometry", 
      "approach", 
      "class", 
      "advantages", 
      "separation", 
      "set", 
      "classifier", 
      "coefficient", 
      "performance", 
      "power", 
      "least squares classifier", 
      "representation"
    ], 
    "name": "A quantitative multimodal metabolomic assay for colorectal cancer", 
    "pagination": "26", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1100194585"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12885-017-3923-z"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "29301511"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12885-017-3923-z", 
      "https://app.dimensions.ai/details/publication/pub.1100194585"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-12-01T06:37", 
    "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_756.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/s12885-017-3923-z"
  }
]
 

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

HOW TO GET THIS DATA PROGRAMMATICALLY:

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

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12885-017-3923-z'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12885-017-3923-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12885-017-3923-z'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12885-017-3923-z'


 

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

315 TRIPLES      21 PREDICATES      130 URIs      113 LITERALS      23 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12885-017-3923-z schema:about N02e5064981b14f4292f943fdf4aa5825
2 N0625a46537e1469ab5cf50dcb39ffda1
3 N115df759e3b540a9b580d5046b4239af
4 N1a4f91651aa24e9ba5734c87b78aa34d
5 N230f9841ed0740179610814effa8b136
6 N28a9016f731a408e97f04df74eb83d33
7 N5087c828771645d88855a54bb8a8e437
8 N66dcfa302cb54ba6a45528a855d4754d
9 N842b266ee0954f5b8dc1f4ca4a40e4db
10 N8bc1395d6e4d4dbcb4b1b8758e5d232e
11 N9406f0c6d5894aaab374bed1ef4e5872
12 N96ea7c2ff91644c08f0e4cd7bef3bcbc
13 Nb481991916744dffab2b8591681b7dbf
14 Nbc5cf4dca2484a80a8f123bb8629775c
15 Ndea11edf9a9d46c8ad667066e2db7ae7
16 Nfb438658257a4dfa9ca42a3a29249585
17 anzsrc-for:11
18 anzsrc-for:1112
19 schema:author N2b2cac54c94b4f91927a2c3414a6dc34
20 schema:citation sg:pub.10.1007/s10654-014-9901-8
21 sg:pub.10.1007/s11306-007-0099-6
22 sg:pub.10.1007/s11306-011-0293-4
23 sg:pub.10.1007/s11306-011-0357-5
24 sg:pub.10.1038/bjc.2016.243
25 sg:pub.10.1038/ng.2985
26 sg:pub.10.1186/1471-230x-10-140
27 sg:pub.10.1186/1741-7015-8-13
28 sg:pub.10.1186/gm341
29 schema:datePublished 2018-01-04
30 schema:datePublishedReg 2018-01-04
31 schema:description BackgroundEarly diagnosis of colorectal cancer (CRC) simplifies treatment and improves treatment outcomes. We previously described a diagnostic metabolomic biomarker derived from semi-quantitative gas chromatography-mass spectrometry. Our objective was to determine whether a quantitative assay of additional metabolomic features, including parts of the lipidome could enhance diagnostic power; and whether there was an advantage to deriving a combined diagnostic signature with a broader metabolomic representation.MethodsThe well-characterized Biocrates P150 kit was used to quantify 163 metabolites in patients with CRC (N = 62), adenoma (N = 31), and age- and gender-matched disease-free controls (N = 81). Metabolites included in the analysis included phosphatidylcholines, sphingomyelins, acylcarnitines, and amino acids. Using a training set of 32 CRC and 21 disease-free controls, a multivariate metabolomic orthogonal partial least squares (OPLS) classifier was developed. An independent set of 28 CRC and 20 matched healthy controls was used for validation. Features characterizing 31 colorectal adenomas from their healthy matched controls were also explored, and a multivariate OPLS classifier for colorectal adenoma could be proposed.ResultsThe metabolomic profile that distinguished CRC from controls consisted of 48 metabolites (R2Y = 0.83, Q2Y = 0.75, CV-ANOVA p-value < 0.00001). In this quantitative assay, the coefficient of variance for each metabolite was <10%, and this dramatically enhanced the separation of these groups. Independent validation resulted in AUROC of 0.98 (95% CI, 0.93–1.00) and sensitivity and specificity of 93% and 95%. Similarly, we were able to distinguish adenoma from controls (R2Y = 0.30, Q2Y = 0.20, CV-ANOVA p-value = 0.01; internal AUROC = 0.82 (95% CI, 0.72–0.93)). When combined with the previously generated GC-MS signatures for CRC and adenoma, the candidate biomarker performance improved slightly.ConclusionThe diagnostic power for metabolomic tests for colorectal neoplasia can be improved by utilizing a multimodal approach and combining metabolites from diverse chemical classes. In addition, quantification of metabolites enhances separation of disease-specific metabolomic profiles. Our future efforts will be focused on developing a quantitative assay for the metabolites comprising the optimal diagnostic biomarker.
32 schema:genre article
33 schema:isAccessibleForFree true
34 schema:isPartOf Nb43042ea00d240c2b3ecbb6245849a94
35 Nfb68ba3f4ecc452dad78dac0c5a98812
36 sg:journal.1024632
37 schema:keywords AUROC
38 BackgroundEarly diagnosis
39 CRC
40 MethodsThe
41 acid
42 acylcarnitines
43 addition
44 adenomas
45 advantages
46 age
47 amino acids
48 analysis
49 approach
50 assays
51 biomarker performance
52 biomarkers
53 cancer
54 chemical classes
55 chromatography-mass spectrometry
56 class
57 classifier
58 coefficient
59 coefficient of variance
60 colorectal adenomas
61 colorectal cancer
62 colorectal neoplasia
63 control
64 diagnosis
65 diagnostic biomarkers
66 diagnostic power
67 diagnostic signature
68 disease-free controls
69 diverse chemical classes
70 efforts
71 features
72 future efforts
73 gas chromatography-mass spectrometry
74 group
75 healthy controls
76 independent set
77 independent validation
78 kit
79 least squares classifier
80 lipidome
81 metabolites
82 metabolomic biomarkers
83 metabolomic features
84 metabolomic profiles
85 metabolomic tests
86 metabolomics assays
87 multimodal approach
88 neoplasia
89 objective
90 optimal diagnostic biomarker
91 outcomes
92 part
93 partial least squares classifier
94 patients
95 performance
96 phosphatidylcholine
97 power
98 profile
99 quantification
100 quantification of metabolites
101 quantitative assay
102 representation
103 sensitivity
104 separation
105 set
106 signatures
107 simplifies treatment
108 specificity
109 spectrometry
110 sphingomyelin
111 test
112 training set
113 treatment
114 treatment outcomes
115 validation
116 variance
117 schema:name A quantitative multimodal metabolomic assay for colorectal cancer
118 schema:pagination 26
119 schema:productId N0f2b9e40a69b49eca0ffad737135e85a
120 N11540825aaa245bdad178c8352752c3e
121 N1bbad5e93f67485591e33f3bba9d5407
122 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100194585
123 https://doi.org/10.1186/s12885-017-3923-z
124 schema:sdDatePublished 2022-12-01T06:37
125 schema:sdLicense https://scigraph.springernature.com/explorer/license/
126 schema:sdPublisher N1cc1fe2175464740baa1df33328bb4ee
127 schema:url https://doi.org/10.1186/s12885-017-3923-z
128 sgo:license sg:explorer/license/
129 sgo:sdDataset articles
130 rdf:type schema:ScholarlyArticle
131 N02e5064981b14f4292f943fdf4aa5825 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
132 schema:name Metabolomics
133 rdf:type schema:DefinedTerm
134 N0625a46537e1469ab5cf50dcb39ffda1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
135 schema:name Adenoma
136 rdf:type schema:DefinedTerm
137 N0f2b9e40a69b49eca0ffad737135e85a schema:name doi
138 schema:value 10.1186/s12885-017-3923-z
139 rdf:type schema:PropertyValue
140 N11540825aaa245bdad178c8352752c3e schema:name dimensions_id
141 schema:value pub.1100194585
142 rdf:type schema:PropertyValue
143 N115df759e3b540a9b580d5046b4239af schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
144 schema:name Amino Acids
145 rdf:type schema:DefinedTerm
146 N1a4f91651aa24e9ba5734c87b78aa34d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
147 schema:name Colorectal Neoplasms
148 rdf:type schema:DefinedTerm
149 N1bbad5e93f67485591e33f3bba9d5407 schema:name pubmed_id
150 schema:value 29301511
151 rdf:type schema:PropertyValue
152 N1cc1fe2175464740baa1df33328bb4ee schema:name Springer Nature - SN SciGraph project
153 rdf:type schema:Organization
154 N230f9841ed0740179610814effa8b136 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Biomarkers, Tumor
156 rdf:type schema:DefinedTerm
157 N28a9016f731a408e97f04df74eb83d33 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
158 schema:name Sphingomyelins
159 rdf:type schema:DefinedTerm
160 N2b04e7c45dd74ca89424771a9728e1aa rdf:first sg:person.01165640331.46
161 rdf:rest N40ea078647494ae1a721fac0826b3b40
162 N2b2cac54c94b4f91927a2c3414a6dc34 rdf:first sg:person.01253745362.08
163 rdf:rest Nf65388c441724fd699279c2f34f3912e
164 N2d8e97184fea4f0b8fef3c7c9ed4600b rdf:first sg:person.0711260173.53
165 rdf:rest Nc6619763180b441cb1efcd6395aeb2cb
166 N40ea078647494ae1a721fac0826b3b40 rdf:first sg:person.01261400416.08
167 rdf:rest Nb957223a7f2f4416854f593d7af24e24
168 N5087c828771645d88855a54bb8a8e437 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
169 schema:name Carnitine
170 rdf:type schema:DefinedTerm
171 N66dcfa302cb54ba6a45528a855d4754d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
172 schema:name Humans
173 rdf:type schema:DefinedTerm
174 N842b266ee0954f5b8dc1f4ca4a40e4db schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
175 schema:name Phosphatidylcholines
176 rdf:type schema:DefinedTerm
177 N8bc1395d6e4d4dbcb4b1b8758e5d232e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
178 schema:name Mass Spectrometry
179 rdf:type schema:DefinedTerm
180 N9406f0c6d5894aaab374bed1ef4e5872 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
181 schema:name Aged
182 rdf:type schema:DefinedTerm
183 N96ea7c2ff91644c08f0e4cd7bef3bcbc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
184 schema:name Female
185 rdf:type schema:DefinedTerm
186 Nb43042ea00d240c2b3ecbb6245849a94 schema:volumeNumber 18
187 rdf:type schema:PublicationVolume
188 Nb481991916744dffab2b8591681b7dbf schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
189 schema:name Middle Aged
190 rdf:type schema:DefinedTerm
191 Nb957223a7f2f4416854f593d7af24e24 rdf:first sg:person.0663327635.18
192 rdf:rest Ne8d09dff0ab44ab69ad508272b1937e8
193 Nbc5cf4dca2484a80a8f123bb8629775c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
194 schema:name Metabolome
195 rdf:type schema:DefinedTerm
196 Nc6619763180b441cb1efcd6395aeb2cb rdf:first sg:person.01065466412.66
197 rdf:rest Nef3818d69f234758b5ba2f6dd11814f5
198 Ndea11edf9a9d46c8ad667066e2db7ae7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
199 schema:name Early Detection of Cancer
200 rdf:type schema:DefinedTerm
201 Ne8d09dff0ab44ab69ad508272b1937e8 rdf:first sg:person.01136414614.60
202 rdf:rest N2d8e97184fea4f0b8fef3c7c9ed4600b
203 Nef3818d69f234758b5ba2f6dd11814f5 rdf:first sg:person.01057564204.51
204 rdf:rest rdf:nil
205 Nf65388c441724fd699279c2f34f3912e rdf:first sg:person.01223356633.10
206 rdf:rest N2b04e7c45dd74ca89424771a9728e1aa
207 Nfb438658257a4dfa9ca42a3a29249585 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
208 schema:name Male
209 rdf:type schema:DefinedTerm
210 Nfb68ba3f4ecc452dad78dac0c5a98812 schema:issueNumber 1
211 rdf:type schema:PublicationIssue
212 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
213 schema:name Medical and Health Sciences
214 rdf:type schema:DefinedTerm
215 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
216 schema:name Oncology and Carcinogenesis
217 rdf:type schema:DefinedTerm
218 sg:journal.1024632 schema:issn 1471-2407
219 schema:name BMC Cancer
220 schema:publisher Springer Nature
221 rdf:type schema:Periodical
222 sg:person.01057564204.51 schema:affiliation grid-institutes:grid.413574.0
223 schema:familyName Bathe
224 schema:givenName Oliver F.
225 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01057564204.51
226 rdf:type schema:Person
227 sg:person.01065466412.66 schema:affiliation grid-institutes:grid.22072.35
228 schema:familyName Vogel
229 schema:givenName Hans J.
230 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01065466412.66
231 rdf:type schema:Person
232 sg:person.01136414614.60 schema:affiliation grid-institutes:grid.22072.35
233 schema:familyName Buie
234 schema:givenName W. Donald
235 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136414614.60
236 rdf:type schema:Person
237 sg:person.01165640331.46 schema:affiliation grid-institutes:None
238 schema:familyName Hilsden
239 schema:givenName Robert
240 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01165640331.46
241 rdf:type schema:Person
242 sg:person.01223356633.10 schema:affiliation grid-institutes:grid.413574.0
243 schema:familyName Kopciuk
244 schema:givenName Karen A.
245 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01223356633.10
246 rdf:type schema:Person
247 sg:person.01253745362.08 schema:affiliation grid-institutes:grid.22072.35
248 schema:familyName Farshidfar
249 schema:givenName Farshad
250 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01253745362.08
251 rdf:type schema:Person
252 sg:person.01261400416.08 schema:affiliation grid-institutes:grid.413574.0
253 schema:familyName McGregor
254 schema:givenName S. Elizabeth
255 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01261400416.08
256 rdf:type schema:Person
257 sg:person.0663327635.18 schema:affiliation grid-institutes:grid.17089.37
258 schema:familyName Mazurak
259 schema:givenName Vera C.
260 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0663327635.18
261 rdf:type schema:Person
262 sg:person.0711260173.53 schema:affiliation grid-institutes:grid.22072.35
263 schema:familyName MacLean
264 schema:givenName Anthony
265 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0711260173.53
266 rdf:type schema:Person
267 sg:pub.10.1007/s10654-014-9901-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043063812
268 https://doi.org/10.1007/s10654-014-9901-8
269 rdf:type schema:CreativeWork
270 sg:pub.10.1007/s11306-007-0099-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022973183
271 https://doi.org/10.1007/s11306-007-0099-6
272 rdf:type schema:CreativeWork
273 sg:pub.10.1007/s11306-011-0293-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004591576
274 https://doi.org/10.1007/s11306-011-0293-4
275 rdf:type schema:CreativeWork
276 sg:pub.10.1007/s11306-011-0357-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038023758
277 https://doi.org/10.1007/s11306-011-0357-5
278 rdf:type schema:CreativeWork
279 sg:pub.10.1038/bjc.2016.243 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016876945
280 https://doi.org/10.1038/bjc.2016.243
281 rdf:type schema:CreativeWork
282 sg:pub.10.1038/ng.2985 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048121271
283 https://doi.org/10.1038/ng.2985
284 rdf:type schema:CreativeWork
285 sg:pub.10.1186/1471-230x-10-140 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040429680
286 https://doi.org/10.1186/1471-230x-10-140
287 rdf:type schema:CreativeWork
288 sg:pub.10.1186/1741-7015-8-13 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010330938
289 https://doi.org/10.1186/1741-7015-8-13
290 rdf:type schema:CreativeWork
291 sg:pub.10.1186/gm341 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022312204
292 https://doi.org/10.1186/gm341
293 rdf:type schema:CreativeWork
294 grid-institutes:None schema:alternateName Forzani & MacPhail Colon Cancer Screening Centre, Calgary, AB, Canada
295 schema:name Department of Medicine, University of Calgary, Calgary, AB, Canada
296 Forzani & MacPhail Colon Cancer Screening Centre, Calgary, AB, Canada
297 rdf:type schema:Organization
298 grid-institutes:grid.17089.37 schema:alternateName Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Canada
299 schema:name Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Canada
300 rdf:type schema:Organization
301 grid-institutes:grid.22072.35 schema:alternateName Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
302 Department of Oncology, University of Calgary, Calgary, AB, Canada
303 Department of Surgery, University of Calgary, Calgary, AB, Canada
304 schema:name Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
305 Department of Oncology, University of Calgary, Calgary, AB, Canada
306 Department of Surgery, University of Calgary, Calgary, AB, Canada
307 rdf:type schema:Organization
308 grid-institutes:grid.413574.0 schema:alternateName Division of Surgical Oncology, Tom Baker Cancer Centre, 1331 – 29th St NW, T2N 4N2, Calgary, AB, Canada
309 Population Health Research, Alberta Health Services, Calgary, AB, Canada
310 schema:name Department Mathematics and Statistics, University of Calgary, Calgary, AB, Canada
311 Department of Oncology, University of Calgary, Calgary, AB, Canada
312 Department of Surgery, University of Calgary, Calgary, AB, Canada
313 Division of Surgical Oncology, Tom Baker Cancer Centre, 1331 – 29th St NW, T2N 4N2, Calgary, AB, Canada
314 Population Health Research, Alberta Health Services, Calgary, AB, Canada
315 rdf:type schema:Organization
 




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


...