Changes in protein concentrations within human blood are used as an indicator for nutritional state, hydration and underlying illnesses. They are often measured at regular clinical appointments and the current analytical process can result in long waiting times for results and the need for return patient visits. Attenuated total reflectance -Fourier transform infrared (ATR-FTIR) spectroscopy has the ability to detect minor molecular differences, qualitatively and quantitatively, in biofluid samples, without extensive sample preparation. ATR-FTIR can return an analytical measurement almost instantaneously and therefore could be deemed as an ideal technique for monitoring molecular alterations in blood within the clinic.To determine the suitability of using ATR-FTIR spectroscopy to enable protein quantification in a clinical setting, pooled human serum samples spiked with varying concentrations of human serum albumin (HSA) and immunoglobulin G (IgG) were analysed, before analysing patient clinical samples. Using a validated partial least squares method, the spiked samples (IgG) produced a linearity as high as 0.998 and a RMSEV of 0.49 ± 0.05 mg mL -1 , with the patient samples producing R 2 values of 0.992 and a corresponding RMSEV of 0.66 ± 0.05 mg mL -1 . This claim was validated using two blind testing models, leave one patient out cross validation and k-fold cross validation, achieving optimum linearity and RMSEV values of 0.934 and 1.99 ± 0.79 mg mL -1 , respectively. This demonstrates that ATR-FTIR is able to quantify protein within clinically relevant complex matrices and concentrations, such as serum samples, rapidly and with simple sample preparation. The ability to provide a quantification step, along with rapid disease classification, from a spectroscopic signature will aid clinical translation of vibrational spectroscopy to assist with problems currently faced with patient diagnostic pathways.

In recent years, the diagnosis of brain tumors has been investigated with attenuated total reflection‐Fourier transform infrared (ATR‐FTIR) spectroscopy on dried human serum samples to eliminate spectral interferences of the water component, with promising results. This research evaluates ATR‐FTIR on both liquid and air‐dried samples to investigate “digital drying” as an alternative approach for the analysis of spectra obtained from liquid samples. Digital drying approaches, consisting of water subtraction and least‐squares method, have demonstrated a greater random forest (RF) classification performance than the air‐dried spectra approach when discriminating cancer vs control samples, reaching sensitivity values higher than 93.0% and specificity values higher than 83.0%. Moreover, quantum cascade laser infrared (QCL‐IR) based spectroscopic imaging is utilized on liquid samples to assess the implications of a deep‐penetration light source on disease classification. The RF classification of QCL‐IR data has provided sensitivity and specificity amounting to 85.1% and 75.3% respectively.

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IntroductionSpectroscopic and spectrometric analysis of biological samples is regarded as quick, cost effective, easy to operate, and spectroscopic sample preparation involves minimal sample preparation.ResultsTechniques like infrared (IR) spectroscopy, surface‐enhanced laser desorption/ionization (SELDI)‐mass spectroscopy (MS), and matrix‐assisted laser desorption/ionization (MALDI) ‐MS could enable early diagnosis of cancer, disease monitoring, and assessment of treatment responses allowing refinement, if required.DiscussionCarrying out analytical testing within outpatient clinics would dramatically cut the time spent by patients attending different appointments, at different locations, save hospital time and resources but importantly would theoretically enable a reduction in mortality and morbidity. While the advantages of such a prospect seem obvious, this review aims to evaluate the use of human serum spectroscopic and spectrometric analysis as a diagnostic tool for brain cancers, creating a platform for the future of cancer diagnostics.