Molecular Origin of Blood‐Based Infrared Spectroscopic Fingerprints**

Abstract

Infrared spectroscopyo fl iquid biopsies is at imeand cost-effective approach that may advance biomedical diagnostics.H owever,t he molecular nature of disease-related changes of infrared molecular fingerprints (IMFs) remains poorly understood, impeding the methodsa pplicability.H ere we probe 148 human blood sera and reveal the origin of the variations in their IMFs.Tothat end, we supplemented infrared spectroscopyw ith biochemical fractionation and proteomic profiling,p roviding molecular information about serum composition. Using lung cancer as an example of am edical condition, we demonstrate that the disease-related differences in IMFs are dominated by contributions from twelve highly abundant proteins-that, if used as ap attern, may be instrumental for detecting malignancy.T ying proteomic to spectral information and machine learning advances our understanding of the infrared spectra of liquid biopsies, af ramework that could be applied to probing of any disease.

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

“…Both conditions (lung cancer and COPD) are often accompanied by an inflammatory response. Considering that the spectral signatures relevant for cancer detection are based on typical molecular changes that also occur in inflammatory conditions ( Voronina et al, 2021 ), the presence of COPD likely masks, at least in part, cancer-relevant signals.…”

“…Although widely used in the IR community, due to the very many molecular assignments possible for each spectral position, unambiguous statements of molecular changes herein are not feasible. Instead, a much deeper analysis is required, as recently revealed by Sangster et al, 2006 ; Voronina et al, 2021 . The latter work involves combination of infrared spectroscopy and quantitative mass spectrometry on the part of the lung cancer sample set used in the current study as well, identifying the molecular origin of the differential infrared fingerprints.…”

“…Molecular specificity is inherently limited in IR spectroscopy due to the spectral overlap of absorption bands of individual molecules. This might be tackled by chemical pre-fractionation ( Hughes et al, 2014 ; Petrich et al, 2009 ; Voronina et al, 2021 ) or by combining IR spectroscopy to methods like liquid chromatography. However, such a pre-fractioning, but also IR fingerprinting itself, would benefit even more from increased spectroscopic sensitivity.…”

“…Altogether, there is a need for studies that address the issues listed above by (i) systematically investigating the pre-analytical factors ( Cameron et al, 2020 ; Huber et al, 2021 ), (ii) studying the molecular origin of the infrared fingerprints ( Voronina et al, 2021 ), and (iii) adequately applying machine learning tools with involvement of a sufficient number of participants. To date, the latter requirement has only been met in studies investigating the applicability of infrared fingerprinting to bladder ( Ollesch et al, 2014 ), breast ( Backhaus et al, 2010 ), and brain cancer detection ( Butler et al, 2019 ).…”

Advanced mass spectrometric and spectroscopic methods coupled with machine learning for in vitro diagnosis

“…Copyright 2019, Elsevier. (C) General workflow that combined FTIR with support vector machine (SVM) for probing molecular changes in disease 131 . Copyright 2021, Wiley‐VCH.…”