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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...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2021
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
Descripción
Sumario: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.