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Patients living with brain tumours have the highest average years of life lost of any cancer, ultimately reducing average life expectancy by 20 years. Diagnosis depends on brain imaging and most often confirmatory tissue biopsy for histology. The majority of patients experience non-specific symptoms, such as headache, and may be reviewed in primary care on multiple occasions before diagnosis is made. Sixty-two per cent of patients are diagnosed on brain imaging performed when they deteriorate and present to the emergency department. Histological diagnosis from invasive surgical biopsy is necessary prior to definitive treatment, because imaging techniques alone have difficulty in distinguishing between several types of brain cancer. However, surgery itself does not necessarily control tumour growth, and risks morbidity for the patient. Due to their similar features on brain scans, glioblastoma, primary central nervous system lymphoma and brain metastases have been known to cause radiological confusion. Non-invasive tests that support stratification of tumour subtype would enhance early personalisation of treatment selection and reduce the delay and risks associated with surgery for many patients. Techniques involving vibrational spectroscopy, such as attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy, have previously demonstrated analytical capabilities for cancer diagnostics. In this study, infrared spectra from 641 blood serum samples obtained from brain cancer and control patients have been collected. Firstly, we highlight the capability of ATR-FTIR to distinguish between healthy controls and brain cancer at sensitivities and specificities above 90%, before defining subtle differences in protein secondary structures between patient groups through Amide I deconvolution. We successfully differentiate several types of brain lesions (glioblastoma, meningioma, primary central nervous system lymphoma and metastasis) with balanced accuracies &gt, 80%. A reliable blood serum test capable of stratifying brain tumours in secondary care could potentially avoid surgery and speed up the time to definitive therapy, which would be of great value for both neurologists and patients.

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.

International audience; 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 R2 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 application of vibrational spectroscopy in biomedical research has rapidly expanded; covering aspects of pharmaceutical development, to point-of-care technologies. Vibrational spectroscopy techniques such as Fourier-transform IR (FTIR), and Raman spectroscopy have been at the forefront of this movement, with their complementary information able to shine light onto a range of medical applications. As a relative newcomer to biomedical applications, two-dimensional (2D)-IR is also gaining traction in the field. Here we describe the recent development of these techniques as analytical tools in medical science, and their relative advancements towards the clinic.

Simple Summary Gliomas represent the vast majority of primary brain tumours and are of significant medical importance due to the poor clinical course of affected patients. The isocitrate dehydrogenase 1 (IDH1) mutation is associated with improved prognosis, compared to patients with IDH1-wildtype lesions of the same stage. In this proof-of-concept study, Fourier transform infrared spectroscopy was used to determine the IDH1 molecular status in fixed glioma sections. Classification algorithms successfully distinguished the two IDH1 classes with high accuracies (>80%). Knowledge of the IDH1 status would be beneficial, as maximum resection may be preferred in patients with IDH1-mutant gliomas, whilst a more limited resection can be best for IDH1-wildtype gliomas. Furthermore, we examined blood serum in an attempt to identify the biomolecular alterations caused by the IDH1 mutation. Non-invasive approaches that can detect the molecular status may guide some patients to an alternative treatment prior to surgery. Abstract Mutations in the isocitrate dehydrogenase 1 (IDH1) gene are found in a high proportion of diffuse gliomas. The presence of the IDH1 mutation is a valuable diagnostic, prognostic and predictive biomarker for the management of patients with glial tumours. Techniques involving vibrational spectroscopy, e.g., Fourier transform infrared (FTIR) spectroscopy, have previously demonstrated analytical capabilities for cancer detection, and have the potential to contribute to diagnostics. The implementation of FTIR microspectroscopy during surgical biopsy could present a fast, label-free method for molecular genetic classification. For example, the rapid determination of IDH1 status in a patient with a glioma diagnosis could inform intra-operative decision-making between alternative surgical strategies. In this study, we utilized synchrotron-based FTIR microanalysis to probe tissue microarray sections from 79 glioma patients, and distinguished the positive class (IDH1-mutated) from the IDH1-wildtype glioma, with a sensitivity and specificity of 82.4% and 83.4%, respectively. We also examined the ability of attenuated total reflection (ATR)-FTIR spectroscopy in detecting the biomolecular events and global epigenetic and metabolic changes associated with mutations in the IDH1 enzyme, in blood serum samples collected from an additional 72 brain tumour patients. Centrifugal filtration enhanced the diagnostic ability of the classification models, with balanced accuracies up to ~69%. Identification of the molecular status from blood serum prior to biopsy could further direct some patients to alternative treatment strategies.

“Large” nanoparticles potentially are a good starting point in order to derive informative NIR/IR SERS analysis of biological samples., As biospectroscopy techniques continue to be developed for screening or diagnosis within a point-of-care setting, an important development for this field will be high-throughput optimization. For many of these techniques, it is therefore necessary to adapt and develop parameters to generate a robust yet simple approach delivering high-quality spectra from biological samples. Specifically, this is important for surface-enhanced Raman spectroscopy (SERS) wherein there are multiple variables that can be optimised to achieve an enhancement of the Raman signal from a sample. One hypothesis is that “large” diameter (>100 nm) gold nanoparticles provide a greater enhancement at near-infrared (NIR) and infrared (IR) wavelengths than those