A review of novel analytical diagnostics for liquid biopsies: spectroscopic and spectrometric serum profiling of primary and secondary brain tumors

Infrared spectroscopy combined with chemometrics in transflectance mode: An alternative approach in the photodiagnosis of COVID-19 using saliva

The Coronavirus Disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has required the search for sensitive, rapid, specific, and lower-cost diagnostic methods to meet the high demand. The gold standard method of laboratory diagnosis is real-time reverse transcription polymerase chain reaction (RT-PCR). However, this method is costly and results can take time. In the literature, several studies have already described the potential of Fourier transform infrared spectroscopy (FTIR) as a tool in the biomedical field, including the diagnosis of viral infections, while being fast and inexpensive. In view of this, the objective of this study was to develop an FTIR model for the diagnosis of COVID-19. For this analysis, all private clients who had performed a face-to-face collection at the Univates Clinical Analysis Laboratory (LAC Univates) within a period of six months were invited to participate. Data from clients who agreed to participate in the study were collected, as well as nasopharyngeal secretions and a saliva sample. For the development of models, the RT-PCR result of nasopharyngeal secretions was used as a reference method. Absorptions with high discrimination (p < 0.001) between GI (28 patients, RT-PCR test positive to SARS-CoV-2 virus) and GII (173 patients who did not have the virus detected in the test) were most relevant at 3512 cm-1, 3385 cm-1 and 1321 cm-1 after 2nd derivative data transformation. To carry out the diagnostic modeling, chemometrics via FTIR and Discriminant Analysis of Orthogonal Partial Least Squares (OPLS-DA) by salivary transflectance mode with one latent variable and one orthogonal signal correction component were used. The model generated predictions with 100 % sensitivity, specificity and accuracy. With the proposed model, in a single application of an individual's saliva in the FTIR equipment, results related to the detection of SARS-CoV-2 can be obtained in a few minutes of spectral evaluation.

Cellular Conversations in Glioblastoma Progression, Diagnosis and Treatment

Glioblastoma (GBM) is the most frequent malignancy among primary brain tumors in adults and one of the worst 5-year survival rates (< 7%) among all human cancers. Till now, treatments that target particular cell or intracellular metabolism have not improved patients' survival. GBM recruits healthy brain cells and subverts their processes to create a microenvironment that contributes to supporting tumor progression. This microenvironment encompasses a complex network in which malignant cells interact with each other and with normal and immune cells to promote tumor proliferation, angiogenesis, metastasis, immune suppression, and treatment resistance. Communication can be direct via cell-to-cell contact, mainly through adhesion molecules, tunneling nanotubes, gap junctions, or indirect by conventional paracrine signaling by cytokine, neurotransmitter, and extracellular vesicles. Understanding these communication routes could open up new avenues for the treatment of this lethal tumor. Hence, therapeutic approaches based on glioma cells` communication have recently drawn attention. This review summarizes recent findings on the crosstalk between glioblastoma cells and their tumor microenvironment, and the impact of this conversation on glioblastoma progression. We also discuss the mechanism of communication of glioma cells and their importance as therapeutic targets and diagnostic and prognostic biomarkers. Overall, understanding the biological mechanism of specific interactions in the tumor microenvironment may help in predicting patient prognosis and developing novel therapeutic strategies to target GBM.

Matrix-assisted laser desorption ionisation (MALDI) mass spectrometry (MS): basics and clinical applications

Background Matrix-assisted laser desorption ionisation (MALDI) mass spectrometry (MS) has been used for more than 30 years. Compared with other analytical techniques, it offers ease of use, high throughput, robustness, cost-effectiveness, rapid analysis and sensitivity. As advantages, current clinical techniques (e.g. immunoassays) are unable to directly measure the biomarker; rather, they measure secondary signals. MALDI-MS has been extensively researched for clinical applications, and it is set for a breakthrough as a routine tool for clinical diagnostics. Content This review reports on the principles of MALDI-MS and discusses current clinical applications and the future clinical prospects for MALDI-MS. Furthermore, the review assesses the limitations currently experienced in clinical assays, the advantages and the impact of MALDI-MS to transform clinical laboratories. Summary MALDI-MS is widely used in clinical microbiology for the screening of microbial isolates; however, there is scope to apply MALDI-MS in the diagnosis, prognosis, therapeutic drug monitoring and biopsy imaging in many diseases. Outlook There is considerable potential for MALDI-MS in clinic as a tool for screening, profiling and imaging because of its high sensitivity and specificity over alternative techniques.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and "digital drying"

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.

Developing infrared spectroscopic detection for stratifying brain tumour patients: glioblastoma multiforme vs. lymphoma

Over a third of brain tumour patients visit their general practitioner more than five times prior to diagnosis in the UK, leading to 62% of patients being diagnosed as emergency presentations. Unfortunately, symptoms are non-specific to brain tumours, and the majority of these patients complain of headaches on multiple occasions before being referred to a neurologist. As there are currently no methods in place for the early detection of brain cancer, the affected patients' average life expectancy is reduced by 20 years. These statistics indicate that the current pathway is ineffective, and there is a vast need for a rapid diagnostic test. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy is sensitive to the hallmarks of cancer, as it analyses the full range of macromolecular classes. The combination of serum spectroscopy and advanced data analysis has previously been shown to rapidly and objectively distinguish brain tumour severity. Recently, a novel high-throughput ATR accessory has been developed, which could be cost-effective to the National Health Service in the UK, and valuable for clinical translation. In this study, 765 blood serum samples have been collected from healthy controls and patients diagnosed with various types of brain cancer, contributing to one of the largest spectroscopic studies to date. Three robust machine learning techniques - random forest, partial least squares-discriminant analysis and support vector machine - have all provided promising results. The novel high-throughput technology has been validated by separating brain cancer and non-cancer with balanced accuracies of 90% which is comparable to the traditional fixed diamond crystal methodology. Furthermore, the differentiation of brain tumour type could be useful for neurologists, as some are difficult to distinguish through medical imaging alone. For example, the highly aggressive glioblastoma multiforme and primary cerebral lymphoma can appear similar on magnetic resonance imaging (MRI) scans, thus are often misdiagnosed. Here, we report the ability of infrared spectroscopy to distinguish between glioblastoma and lymphoma patients, at a sensitivity and specificity of 90.1% and 86.3%, respectively. A reliable serum diagnostic test could avoid the need for surgery and speed up time to definitive chemotherapy and radiotherapy.

Investigating pre-analytical requirements for serum and plasma based infrared spectro-diagnostic

Infrared spectroscopy is a rapid, easy-to-operate, label-free and therefore cost-effective technique. Many studies performed on biofluids (eg, serum, plasma, urine, sputum, bile and cerebrospinal fluid) have demonstrated its promising application as a clinical diagnostic tool. Given all these characteristics, infrared spectroscopy appears to be an ideal candidate to be implemented into the clinics. However, before considering its translation, a clear effort is needed to standardise protocols for biofluid spectroscopic analysis. To reach this goal, careful investigations to identify and track errors that can occur during the pre-analytical phase is a crucial step. Here, we report for the first time, results of investigations into pre-analytical factors that can affect the quality of the spectral data acquired on serum and plasma, such as the impact of long-term freezing time storage of samples as well as the month-to-month reproducibility of the spectroscopic analysis. The spectral data discrimination has revealed to be majorly impacted by a residual water content variation in serum and plasma dried samples.

Current and Future Trends on Diagnosis and Prognosis of Glioblastoma: From Molecular Biology to Proteomics

Glioblastoma multiforme is the most aggressive malignant tumor of the central nervous system. Due to the absence of effective pharmacological and surgical treatments, the identification of early diagnostic and prognostic biomarkers is of key importance to improve the survival rate of patients and to develop new personalized treatments. On these bases, the aim of this review article is to summarize the current knowledge regarding the application of molecular biology and proteomics techniques for the identification of novel biomarkers through the analysis of different biological samples obtained from glioblastoma patients, including DNA, microRNAs, proteins, small molecules, circulating tumor cells, extracellular vesicles, etc. Both benefits and pitfalls of molecular biology and proteomics analyses are discussed, including the different mass spectrometry-based analytical techniques, highlighting how these investigation strategies are powerful tools to study the biology of glioblastoma, as well as to develop advanced methods for the management of this pathology.

Biofluid spectroscopic disease diagnostics: A review on the processes and spectral impact of drying

The complex patterns observed from evaporated liquid drops have been examined extensively over the last 20 years. Complete understanding of drop deposition is vital in many medical processes, and one which is essential to the translation of biofluid spectroscopic disease diagnostics. The promising use of spectroscopy in disease diagnosis has been hindered by the complicated patterns left by dried biological fluids which may inhibit the clinical translation of this technology. Coffee-ring formation, cracking and gelation patterns have all been observed in biofluid drops, and with surface homogeneity being a key element to many spectroscopic techniques, experimental issues have been found to arise. A better understanding of the fundamental processes involved in a drying droplet could allow efficient progression in this research field, and ultimately benefit the population with the development of a reliable cancer diagnostic.

Clinical applications of infrared and Raman spectroscopy: state of play and future challenges

This review examines the state-of-the-art of clinical applications of infrared absorption and Raman spectroscopy, outstanding challenges, and progress towards translation.

Anaphylatoxin C3a: A potential biomarker for esophageal cancer diagnosis

Esophageal carcinoma is a common malignancy worldwide, with a low 5-year survival rate. As the majority of cases are diagnosed at an advanced stage, there is an urgent need for an effective biomarker for early diagnosis of esophageal cancer patients. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) was applied to detect the serum protein expression in esophageal cancer patients using ProteinChip software, and the results were analyzed and screened using Biomarker Patterns and SPSS16.0 software. The ELISA method was conducted to determine the concentration of anaphylatoxin C3a, which is one of the complement proteins, in the serum of esophageal cancer patients and non-esophageal cancer participants. A total of 144 effective differential expression protein peaks in the window of 1-10 kDa were obtained (P<0.05). M/Z 8,926.478 (P<10^-6) protein peak was employed as the diagnostic biomarker for esophageal carcinoma. This established diagnostic biomarker has a sensitivity of 95% (19/20) and an accuracy of 100% (19/19) for positive prediction. The results suggested that anaphylatoxin C3a may be a promising biomarker in the diagnosis of esophageal carcinoma, and may play a key role in promoting esophageal carcinogenesis.

A review of novel analytical diagnostics for liquid biopsies: spectroscopic and spectrometric serum profiling of primary and secondary brain tumors

INTRODUCTION

Spectroscopic and spectrometric analysis of biological samples is regarded as quick, cost effective, easy to operate, and spectroscopic sample preparation involves minimal sample preparation.

RESULTS

Techniques 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.

DISCUSSION

Carrying 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.