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1000 Titel
  • Breast-cancer detection using blood-based infrared molecular fingerprints
1000 Autor/in
  1. Kepesidis, Kosmas V. |
  2. Bozic-Iven, Masa |
  3. Huber, Marinus |
  4. Abdel-Aziz, Nashwa |
  5. Kullab, Sharif |
  6. Abdelwarith, Ahmed |
  7. Al Diab, Abdulrahman |
  8. Al Ghamdi, Mohammed |
  9. Hilal, Muath Abu |
  10. Bahadoor, Mohun R. K. |
  11. Sharma, Abhishake |
  12. Dabouz, Farida |
  13. Arafah, Maria |
  14. Azzeer, Abdallah M. |
  15. Krausz, Ferenc |
  16. Alsaleh, Khalid |
  17. Zigman, Mihaela |
  18. Nabholtz, Jean-Marc |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-12-02
1000 Erschienen in
1000 Quellenangabe
  • 21(1):1287
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s12885-021-09017-7 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8638519/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Background!#!Breast cancer screening is currently predominantly based on mammography, tainted with the occurrence of both false positivity and false negativity, urging for innovative strategies, as effective detection of early-stage breast cancer bears the potential to reduce mortality. Here we report the results of a prospective pilot study on breast cancer detection using blood plasma analyzed by Fourier-transform infrared (FTIR) spectroscopy - a rapid, cost-effective technique with minimal sample volume requirements and potential to aid biomedical diagnostics. FTIR has the capacity to probe health phenotypes via the investigation of the full repertoire of molecular species within a sample at once, within a single measurement in a high-throughput manner. In this study, we take advantage of cross-molecular fingerprinting to probe for breast cancer detection.!##!Methods!#!We compare two groups: 26 patients diagnosed with breast cancer to a same-sized group of age-matched healthy, asymptomatic female participants. Training with support-vector machines (SVM), we derive classification models that we test in a repeated 10-fold cross-validation over 10 times. In addition, we investigate spectral information responsible for BC identification using statistical significance testing.!##!Results!#!Our models to detect breast cancer achieve an average overall performance of 0.79 in terms of area under the curve (AUC) of the receiver operating characteristic (ROC). In addition, we uncover a relationship between the effect size of the measured infrared fingerprints and the tumor progression.!##!Conclusion!#!This pilot study provides the foundation for further extending and evaluating blood-based infrared probing approach as a possible cross-molecular fingerprinting modality to tackle breast cancer detection and thus possibly contribute to the future of cancer screening.
1000 Sacherschließung
lokal Female [MeSH]
lokal Area Under Curve [MeSH]
lokal Disease Progression [MeSH]
lokal Early Detection of Cancer/methods [MeSH]
lokal Adult [MeSH]
lokal Humans [MeSH]
lokal Liquid biopsy
lokal Prospective Studies [MeSH]
lokal Breast cancer
lokal Breast Neoplasms/blood [MeSH]
lokal Support Vector Machine [MeSH]
lokal Middle Aged [MeSH]
lokal DNA Fingerprinting [MeSH]
lokal Feasibility Studies [MeSH]
lokal Liquid Biopsy/methods [MeSH]
lokal Spectroscopy, Fourier Transform Infrared/methods [MeSH]
lokal ROC Curve [MeSH]
lokal Research
lokal Pilot Projects [MeSH]
lokal Machine Learning [MeSH]
lokal Case-Control Studies [MeSH]
lokal Breast Neoplasms/diagnosis [MeSH]
lokal Breast Neoplasms/pathology [MeSH]
lokal Infrared spectroscopy
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/S2VwZXNpZGlzLCBLb3NtYXMgVi4=|https://frl.publisso.de/adhoc/uri/Qm96aWMtSXZlbiwgTWFzYQ==|https://frl.publisso.de/adhoc/uri/SHViZXIsIE1hcmludXM=|https://frl.publisso.de/adhoc/uri/QWJkZWwtQXppeiwgTmFzaHdh|https://frl.publisso.de/adhoc/uri/S3VsbGFiLCBTaGFyaWY=|https://frl.publisso.de/adhoc/uri/QWJkZWx3YXJpdGgsIEFobWVk|https://frl.publisso.de/adhoc/uri/QWwgRGlhYiwgQWJkdWxyYWhtYW4=|https://frl.publisso.de/adhoc/uri/QWwgR2hhbWRpLCBNb2hhbW1lZA==|https://frl.publisso.de/adhoc/uri/SGlsYWwsIE11YXRoIEFidQ==|https://frl.publisso.de/adhoc/uri/QmFoYWRvb3IsIE1vaHVuIFIuIEsu|https://frl.publisso.de/adhoc/uri/U2hhcm1hLCBBYmhpc2hha2U=|https://frl.publisso.de/adhoc/uri/RGFib3V6LCBGYXJpZGE=|https://frl.publisso.de/adhoc/uri/QXJhZmFoLCBNYXJpYQ==|https://frl.publisso.de/adhoc/uri/QXp6ZWVyLCBBYmRhbGxhaCBNLg==|https://frl.publisso.de/adhoc/uri/S3JhdXN6LCBGZXJlbmM=|https://frl.publisso.de/adhoc/uri/QWxzYWxlaCwgS2hhbGlk|https://frl.publisso.de/adhoc/uri/WmlnbWFuLCBNaWhhZWxh|https://frl.publisso.de/adhoc/uri/TmFiaG9sdHosIEplYW4tTWFyYw==
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  • DeepGreen-ID: 9462f1881dbb4fb68bd8aba146d06e9e ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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1000 Erstellt am 2023-04-27T09:36:25.314+0200
1000 Erstellt von 322
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1000 Zuletzt bearbeitet 2023-10-19T14:54:43.645+0200
1000 Objekt bearb. Thu Oct 19 14:54:43 CEST 2023
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