Researchers from across the attoworld-community have been heavily invested in exploring the potential and capability of blood-based infrared molecular fingerprinting for disease diagnosis. Over the past decade, the BIRD-team has been developing a standardized approach and performing tests to evaluate whether such an approach could aid medical decision-making. Specifically, in collaboration with several medical professionals, they aim to determine whether infrared molecular fingerprinting could serve as an in vitro diagnostic tool to advance the primary diagnosis of common cancers.

Using Fourier-transform infrared spectroscopy to obtain infrared fingerprints from cell-free blood, they have already shown that the approach can, in principle, detect these diseases. After significant technological development and the establishment of a new ultrafast laser-based spectrometer, the researchers recently assessed the new minimally-invasive spectroscopic medical testing technique in the framework of the Lasers4Life clinical study. This study represents the largest set of measurements conducted using this technique to date.

Machine learning was employed to analyse the extensive experimental dataset and identify patterns in the electric-field molecular fingerprints indicative of a particular cancer type. The findings revealed that lung cancer is best detectable this way among the four investigated cancer types. These results have just been published in the article titled ‘Electric-field molecular fingerprinting to detect cancer’ in renowned journal ACS Central Science, led by Mihaela Žigman.

This achievement is the result of a long-term collaborative effort with the BIRD, FRIS and Data Science teams joining forces and working closely with clinical partners from five different clinics at the LMU University Hospital and Asklepios Lungenklinik Gauting.

The team believes this is just the beginning. They press ahead to further improve the technique, motivated to bring these ultrafast laser-based technologies closer to real-world medical applications.

The article will further be featured on the supplementary cover of the journal.

 

Original Publication:

K. Kepesidis, P. Jacob, W. Schweinberger, M. Huber, N. Feiler, F. Fleischmann, M. Trubetskov, L. Voronina, J. Aschauer, T. Eissa, L. Gigou, P. Karandušovský, I. Pupeza, A. Weigel, A. Azzeer, C. Stief, M. Chaloupka , N. Reinmuth, J. Behr, T. Kolben, N. Harbeck, M. Reiser, F. Krausz, M. Žigman.

electric-field molecular fingerprinting to probe cancer

ACS Central Science, Published April 9, 2025

DOI: 10.1021/acscentsci.4c02164

 

Graphic: Philip Jacob