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Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer
Recent omics analyses of human biofluids provide opportunities to probe selected species of biomolecules for disease diagnostics. Fourier-transform infrared (FTIR) spectroscopy investigates the full repertoire of molecular species within a sample at once. Here, we present a multi-institutional study...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8547961/ https://www.ncbi.nlm.nih.gov/pubmed/34696827 http://dx.doi.org/10.7554/eLife.68758 |
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author | Huber, Marinus Kepesidis, Kosmas V Voronina, Liudmila Fleischmann, Frank Fill, Ernst Hermann, Jacqueline Koch, Ina Milger-Kneidinger, Katrin Kolben, Thomas Schulz, Gerald B Jokisch, Friedrich Behr, Jürgen Harbeck, Nadia Reiser, Maximilian Stief, Christian Krausz, Ferenc Zigman, Mihaela |
author_facet | Huber, Marinus Kepesidis, Kosmas V Voronina, Liudmila Fleischmann, Frank Fill, Ernst Hermann, Jacqueline Koch, Ina Milger-Kneidinger, Katrin Kolben, Thomas Schulz, Gerald B Jokisch, Friedrich Behr, Jürgen Harbeck, Nadia Reiser, Maximilian Stief, Christian Krausz, Ferenc Zigman, Mihaela |
author_sort | Huber, Marinus |
collection | PubMed |
description | Recent omics analyses of human biofluids provide opportunities to probe selected species of biomolecules for disease diagnostics. Fourier-transform infrared (FTIR) spectroscopy investigates the full repertoire of molecular species within a sample at once. Here, we present a multi-institutional study in which we analysed infrared fingerprints of plasma and serum samples from 1639 individuals with different solid tumours and carefully matched symptomatic and non-symptomatic reference individuals. Focusing on breast, bladder, prostate, and lung cancer, we find that infrared molecular fingerprinting is capable of detecting cancer: training a support vector machine algorithm allowed us to obtain binary classification performance in the range of 0.78–0.89 (area under the receiver operating characteristic curve [AUC]), with a clear correlation between AUC and tumour load. Intriguingly, we find that the spectral signatures differ between different cancer types. This study lays the foundation for high-throughput onco-IR-phenotyping of four common cancers, providing a cost-effective, complementary analytical tool for disease recognition. |
format | Online Article Text |
id | pubmed-8547961 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-85479612021-10-27 Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer Huber, Marinus Kepesidis, Kosmas V Voronina, Liudmila Fleischmann, Frank Fill, Ernst Hermann, Jacqueline Koch, Ina Milger-Kneidinger, Katrin Kolben, Thomas Schulz, Gerald B Jokisch, Friedrich Behr, Jürgen Harbeck, Nadia Reiser, Maximilian Stief, Christian Krausz, Ferenc Zigman, Mihaela eLife Medicine Recent omics analyses of human biofluids provide opportunities to probe selected species of biomolecules for disease diagnostics. Fourier-transform infrared (FTIR) spectroscopy investigates the full repertoire of molecular species within a sample at once. Here, we present a multi-institutional study in which we analysed infrared fingerprints of plasma and serum samples from 1639 individuals with different solid tumours and carefully matched symptomatic and non-symptomatic reference individuals. Focusing on breast, bladder, prostate, and lung cancer, we find that infrared molecular fingerprinting is capable of detecting cancer: training a support vector machine algorithm allowed us to obtain binary classification performance in the range of 0.78–0.89 (area under the receiver operating characteristic curve [AUC]), with a clear correlation between AUC and tumour load. Intriguingly, we find that the spectral signatures differ between different cancer types. This study lays the foundation for high-throughput onco-IR-phenotyping of four common cancers, providing a cost-effective, complementary analytical tool for disease recognition. eLife Sciences Publications, Ltd 2021-10-26 /pmc/articles/PMC8547961/ /pubmed/34696827 http://dx.doi.org/10.7554/eLife.68758 Text en © 2021, Huber et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Medicine Huber, Marinus Kepesidis, Kosmas V Voronina, Liudmila Fleischmann, Frank Fill, Ernst Hermann, Jacqueline Koch, Ina Milger-Kneidinger, Katrin Kolben, Thomas Schulz, Gerald B Jokisch, Friedrich Behr, Jürgen Harbeck, Nadia Reiser, Maximilian Stief, Christian Krausz, Ferenc Zigman, Mihaela Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer |
title | Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer |
title_full | Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer |
title_fullStr | Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer |
title_full_unstemmed | Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer |
title_short | Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer |
title_sort | infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8547961/ https://www.ncbi.nlm.nih.gov/pubmed/34696827 http://dx.doi.org/10.7554/eLife.68758 |
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