Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer.
Marinus HuberKosmas V KepesidisLiudmila VoroninaFrank FleischmannErnst FillJacqueline HermannIna KochKatrin Milger-KneidingerThomas KolbenGerald B SchulzFriedrich JokischJürgen BehrNadia HarbeckMaximilian ReiserChristian StiefFerenc KrauszMihaela ŽigmanPublished in: eLife (2021)
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.
Keyphrases
- papillary thyroid
- high throughput
- deep learning
- squamous cell
- machine learning
- prostate cancer
- endothelial cells
- childhood cancer
- gene expression
- high resolution
- computed tomography
- magnetic resonance imaging
- quantum dots
- squamous cell carcinoma
- induced pluripotent stem cells
- loop mediated isothermal amplification
- liquid chromatography