Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer

eLife

Ina Koch¹  Liudmila Voronina²  Jacqueline Hermann²  Frank Fleischmann²  Ferenc Krausz³  Mihaela Zigman³  Marinus Huber³  Kosmas V Kepesidis³  Ernst Fill⁴  Maximilian Reiser⁵  Katrin Milger-Kneidinger⁶  Jürgen Behr⁶  Thomas Kolben⁷  Nadia Harbeck⁷  Gerald B Schulz⁸  Christian Stief⁸  Friedrich Jokisch⁸ 

[1] Asklepios Biobank for Lung Diseases, Department of Thoracic Surgery, Member of the German Center for Lung Research, DZL, Asklepios Fachkliniken München-Gauting, Munich, Germany;Ludwig Maximilians University Munich (LMU), Department of Laser Physics, Garching, Germany;Ludwig Maximilians University Munich (LMU), Department of Laser Physics, Garching, Germany;Max Planck Institute of Quantum Optics (MPQ), Laboratory for Attosecond Physics, Garching, Germany;Max Planck Institute of Quantum Optics (MPQ), Laboratory for Attosecond Physics, Garching, Germany;University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Clinical Radiology, Munich, Germany;University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Internal Medicine V, Munich, Germany;University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Obstetrics and Gynecology, Breast Center and Comprehensive Cancer Center (CCLMU), Munich, Germany;University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Urology, Munich, Germany;

关键词: infrared spectroscopy;    liquid biopsy;    cancer detection;    phenotyping;    Human;   

DOI  :  10.7554/eLife.68758

来源: eLife Sciences Publications, Ltd

【 摘 要 】

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.

【 授权许可】

CC BY