Saliva as a first-line diagnostic tool: A spectral challenge for identification of cancer biomarkers

One-Drop Serum Screening Test to Monitor Tissue Iron Accumulation

Although iron is an essential element for vital body functions, iron overload (IO) is accompanied by significant cellular damage due to its accumulation within organs. Thus, early diagnosis and accurate identification of the affected organs are critical for preventing irreversible damage and improving patient survival rates. Diagnosing tissue iron deposits relieves invasive biopsies with atomic absorption spectrometry (reserved for specific cases) or noninvasive but costly and time-consuming imaging techniques like computerized tomography and magnetic resonance, which provide limited analytical data and are unsuitable for routine screening. As an alternative, Fourier transform infrared spectroscopy combined with machine learning has emerged as a promising approach for supporting medical decision-making. In this study, we developed a minimally invasive method to identify IO and quantify iron levels in blood and tissues (heart, liver, spleen, and kidney) without biopsies. PLS-DA classification models and PLS regression models were constructed based on samples categorized into a control group (n = 10) and three iron-administered groups at 250 mg kg-1 (n = 14), 500 mg·kg-1 (n = 13), and 1000 mg·kg-1 (n = 15). Iron levels were measured in blood samples and tissue biopsies (spleen, heart, liver, and kidney). The binary classification models (control vs iron-administered) and multiclass models (control, 250, 500, and 1000 mg·kg-1) demonstrated satisfactory performance into train and validation groups. PLS regression models for quantifying iron concentrations in blood and tissues exhibited excellent linearity and low associated errors across both calibration and test groups. Permutation tests confirmed that all models found a real class structure in the data, were not random, and were built using true chemical information. The chemical insights from the spectra may reflect adaptations associated with iron-induced dysregulation. Alterations in biomolecules could reflect systemic stress responses and may result from free radicals generated by the iron-induced Fenton reaction. Moreover, key spectral regions revealed functional interrelationships, particularly between spleen and liver, and heart and kidneys. In summary, the findings support the potential of this innovative for future research to identify IO and quantify iron levels in human blood and different human tissues using only a single drop of blood without tissue biopsies.

Recent advances in bioactive materials: Future perspectives and opportunities in oral cancer biosensing

Bioactive materials and biosensing technologies are emerging as pivotal tools in the early detection and management of oral cancer, a disease characterized by high morbidity and mortality rates. Recent advancements in nanotechnology have facilitated the development of innovative biosensors that utilize bioactive materials for non-invasive diagnostics, particularly through salivary analysis. These biosensors, including electrochemical, optical, and molecular types, target specific biomarkers such as DNA, RNA, and proteins associated with oral cancer. For instance, metal oxide nanoparticles and gold nanoparticles have shown promise in enhancing the sensitivity and specificity of these diagnostic tools. The integration of these nanomaterials allows for real-time monitoring of biomarker levels in saliva, providing a rapid and accurate means of detecting oral cancer at its nascent stages. Furthermore, the utilization of biosensors can circumvent the limitations of traditional biopsy methods, which are often invasive and time-consuming. By focusing on salivary diagnostics, researchers aim to develop point-of-care testing devices that can be used in various settings, thus improving accessibility to early screening for at-risk populations. This innovative approach not only enhances diagnostic accuracy but also holds potential for personalized treatment strategies by enabling continuous monitoring of disease progression and response to therapy. As research continues to evolve, the combination of bioactive materials with advanced biosensing technologies promises to revolutionize oral cancer diagnostics, ultimately leading to improved patient outcomes through earlier intervention and tailored therapeutic approaches.

Decoding E-Cigarette Secrets: Unveiling Saliva and E-Liquid Composition through Fourier-Transform Infrared Spectroscopy

Electronic cigarettes (e-cigs), initially introduced as smoking cessation aids, have given rise to a new wave of nicotine dependence. A critical question that has emerged is the potential adverse effects of e-cig use on oral health, particularly how the vapor emitted from these devices may alter the salivary composition of users. Here, we investigate the salivary composition of e-cig users and analyze the e-liquids (flavorings) using Fourier-transform infrared (FTIR) spectroscopy. Saliva samples were categorized into two groups: e-cigarette users (25 individuals) and nonsmokers/nonusers (25 individuals). Additionally, 26 e-liquid samples used by the e-cig users were collected, with 17 obtained before use and 9 after use. The analysis provided reliable results in distinguishing between the two groups. Notably, partial least-squares discriminant analysis (PLS-DA) demonstrated a high degree of accuracy (>90%) in differentiating the sample groups. Our findings revealed a higher concentration of polysaccharides, aromatic amino acids, and inorganic phosphates, along with a lower concentration of esterases in the saliva of e-cigarette users. These alterations in salivary composition may be linked to an increased risk of type 2 diabetes, hypertension, cardiovascular diseases, kidney diseases, and tumor formation, having a negative impact on oral immunity. In contrast, no significant molecular or compositional changes were observed in the e-liquids after use. Our results underscore the importance of continued research into potential biomarkers and the long-term health effects associated with the growing prevalence of e-cigarette use as a form of nicotine consumption.

Advancing cerumen analysis: exploring innovative vibrational spectroscopy techniques with respect to their potential as new point-of-care diagnostic tools

Cerumen, commonly known as earwax, is a complex mixture composed of secretions from ceruminous glands. These secretions are heterogeneous mixtures mainly composed of lipids and proteins. Despite its prevalence, the potential diagnostic value of cerumen remains largely unexplored. Here, we present an in-depth analysis of cerumen utilizing well-known vibrational approaches such as conventional Raman spectroscopy or surface-enhanced Raman spectroscopy (SERS) together with advanced vibrational spectroscopy techniques such as coherent Raman scattering (CRS), i.e. broadband coherent anti-Stokes Raman scattering (CARS) or stimulated Raman scattering (SRS), as well as optical photothermal infrared (OPTIR) spectroscopy. Through the integration of these vibrational spectroscopic methods, lipids and proteins can be identified as the main components of cerumen; however, they contribute to the final spectral information to various extents depending on the vibrational detection scheme applied. The inherently weak Raman signal could be enhanced by linear (SERS) and non-linear (CRS) processes, resulting in efficient acquisition of fingerprint information and allowing for the detection of marker modes, which cannot be addressed by conventional Raman spectroscopy. OPTIR spectroscopy provides complementary information to Raman spectroscopy, however, without the contribution of a fluorescence background. Our findings underscore the utility of these cutting-edge techniques in unveiling the intricate molecular landscape of cerumen, paving the way for novel point-of-care diagnostic methodologies and therapeutic interventions.

Explorations of the chemical constitution and aqueous solution status of caries-arresting silver(I)-diammine fluoride and silver(I)-fluoride products using high-resolution 19F NMR analysis. Spectroscopic and SEM investigations of their interactions with human saliva: evidence for the in vivo salivary-catalysed autoconstruction of Ag/AgCl-based nanoparticles (IV-SCAN)-part I

Introduction

Silver(I)-diammine fluoride (SDF) and silver(I)-fluoride (SF) complexes have been successfully employed for the arrest of dental caries for many years. However, to date there are very few studies available reporting on the molecular structural compositional and solution status of these agents [typically applied as highly-concentrated 38% (w/v) solutions]. Here, we explored the solution status and chemical constitution of commercially-available SDF and SF products, and secondly investigated the multicomponent interplay of these products with biomolecules present in intact human whole-mouth salivary supernatants (WMSSs) in vitro.

Methods

High-resolution 19F NMR analysis was employed to explore SDF and SF product solutions, and to determine WMSS fluoride (F-) concentrations, whereas ammonia (NH3) release form SDF was tracked by 1H NMR spectroscopy. SEM and thin-film FTIR-ATR analyses were employed to explore the atomic and molecular compositions of sequentially-generated AgCl deposits and chromophoric Ag/AgCl nanoparticles (CSNPs); the time-dependent generation of the latter was followed spectrophotometrically.

Results

19F NMR spectra of aqueous SF solutions contained a very broad F- signal (Δv1/2 70 Hz), demonstrating that much of its solvated F- content was rapidly exchanging with Ag(I) on the NMR timescale, but those of SDF had a much sharper resonance, similar to that of "free" F- (4 Hz). Moreover, further NMR results revealed that a popular SDF product contained high molar excesses of both F- and NH3. Treatment of WMSSs with SDF and SF generated an off-white precipitate, which slowly developed into CSNPs at 23°C; SEM demonstrated high contents of both silver and chloride in this material (ca.1:1 atomic content ratio). FTIR-ATR analysis found that the CSNPs formed contained a range of salivary biomolecules, which appear to encapsulate the Ag/AgCl core (significant thiocyanate contents were also found). In conclusion, NMR results acquired demonstrated that SF, but not SDF, product solutions feature rapidly-exchanging F - between its "free" and Ag(I)-bound forms, and that SDF contains large excesses of both F- and its NH3 ligands. Characterised AgCl deposits and CSNPs were sequentially produced from the interactions of these complexes with WMSS biomolecules.

Discussion

In view of their well-known microbicidal and cariostatic properties, the observed autobioconstruction of CSNPs involving salivary catalysis is of much therapeutic significance.

Salivary biomarkers: The early diagnosis of Alzheimer's disease

The precise identification of Alzheimer's disease and other prevalent neurodegenerative diseases remains a difficult issue that requires the development of early detection of the disease and inexpensive biomarkers that can replace the present cerebrospinal fluid and imaging biomarkers. Blood biomarkers, such as amyloid and neurofilament light, have been emphasized as an important and practical tool in a testing or examination procedure thanks to advancements in ultra-sensitive detection techniques. Although saliva is not currently being researched for neurodegenerative diseases, it is an important source of biomarkers that can be used for the identification of diseases and has some advantages over other biofluids. While this may be true for most people, getting saliva from elderly people presents some significant challenges. In this overview, we will first discuss how saliva is created and how aging-related illnesses may affect the amount and kind of saliva produced. The findings support the use of salivary amyloid protein, tau species, and novel biomarkers in the diagnosis of Alzheimer's disease.

Sequential co-reduction of nitrate and carbon dioxide enables selective urea electrosynthesis

Despite the recent achievements in urea electrosynthesis from co-reduction of nitrogen wastes (such as NO3-) and CO2, the product selectivity remains fairly mediocre due to the competing nature of the two parallel reduction reactions. Here we report a catalyst design that affords high selectivity to urea by sequentially reducing NO3- and CO2 at a dynamic catalytic centre, which not only alleviates the competition issue but also facilitates C-N coupling. We exemplify this strategy on a nitrogen-doped carbon catalyst, where a spontaneous switch between NO3- and CO2 reduction paths is enabled by reversible hydrogenation on the nitrogen functional groups. A high urea yield rate of 596.1 µg mg-1 h-1 with a promising Faradaic efficiency of 62% is obtained. These findings, rationalized by in situ spectroscopic techniques and theoretical calculations, are rooted in the proton-involved dynamic catalyst evolution that mitigates overwhelming reduction of reactants and thereby minimizes the formation of side products.

Spectroscopic imaging to assess biochemical alterations in liver carcinoma cells exposed to transition metals

Despite the invaluable role of transition metals in every living organism, it should be remembered that failure to maintain the proper balance and exceed the appropriate dose may have the opposite effect. In the era of such a popular and propagated need for supplementation in the media, one should bear in mind the harmful effects that may become the result of improper and excessive intake of transition metals. This article establishes the feasibility of Raman (RS) and Fourier-transform infrared (FT-IR) spectroscopic imaging at the single-cell level to investigate the cellular response to various transition metals. These two non-destructive and perfectly complementary methods allow for in-depth monitoring of changes taking place within the cell under the influence of the agent used. HepG2 liver carcinoma cells were exposed to chromium, iron, cobalt, molybdenum, and nickel at 1 and 2 mM concentrations. Spectroscopic results were further supported by biological evaluation of selected caspases concentration. The caspase- 3, 6, 8, 9, and 12 concentrations were determined with the use of the enzyme-linked immunosorbent assay (ELISA) method. This study shows the induction of apoptosis in the intrinsic pathway by all studied transition metals. Cellular metabolism alterations are induced by mitochondrial metabolism changes and endoplasmic reticulum (ER) metabolism variations. Moreover, nickel induces not only the intrinsic pathway of apoptosis but also the extrinsic pathway of this process.

A Review on Saliva-Based Health Diagnostics: Biomarker Selection and Future Directions

The human body has a unique way of saying when something is wrong with it. The molecules in the body fluids can be helpful in the early detection of diseases by enabling health and preventing disease progression. These biomarkers enabling better healthcare are becoming an extensive area of research interest. Biosensors that detect these biomarkers are becoming the future, especially Point Of Care (POC) biosensors that remove the need to be physically present in the hospital. Detection of complex and systemic diseases using biosensors has a long way to go. Saliva-based biosensors are gaining attention among body fluids due to their non-invasive collection and ability to detect periodontal disease and identify systemic diseases. The possibility of saliva-based diagnostic biosensors has gained much publicity, with companies sending home kits for ancestry prediction. Saliva-based testing for covid 19 has revealed effective clinical use and relevance of the economic collection. Based on universal biomarkers, the detection of systemic diseases is a booming research arena. Lots of research on saliva-based biosensors is available, but it still poses challenges and limitations as POC devices. This review paper talks about the relevance of saliva and its usefulness as a biosensor. Also, it has recommendations that need to be considered to enable it as a possible diagnostic tool.

Graphical Abstract

Unlocking the Diagnostic Potential of Saliva: A Comprehensive Review of Infrared Spectroscopy and Its Applications in Salivary Analysis

Infrared (IR) spectroscopy is a noninvasive and rapid analytical technique that provides information on the chemical composition, structure, and conformation of biomolecules in saliva. This technique has been widely used to analyze salivary biomolecules, owing to its label-free advantages. Saliva contains a complex mixture of biomolecules including water, electrolytes, lipids, carbohydrates, proteins, and nucleic acids which are potential biomarkers for several diseases. IR spectroscopy has shown great promise for the diagnosis and monitoring of diseases such as dental caries, periodontitis, infectious diseases, cancer, diabetes mellitus, and chronic kidney disease, as well as for drug monitoring. Recent advancements in IR spectroscopy, such as Fourier-transform infrared (FTIR) spectroscopy and attenuated total reflectance (ATR) spectroscopy, have further enhanced its utility in salivary analysis. FTIR spectroscopy enables the collection of a complete IR spectrum of the sample, whereas ATR spectroscopy enables the analysis of samples in their native form, without the need for sample preparation. With the development of standardized protocols for sample collection and analysis and further advancements in IR spectroscopy, the potential for salivary diagnostics using IR spectroscopy is vast.

Nanoscale insight into biochemical changes in cervical cancer cells exposed to adaptogenic drug

This paper describes for the first time the application of atomic force microscopy-based infrared spectroscopy (AFM-IR) to evaluate cellular response to adaptogen, based on an in vitro model of cervical cancer. HeLa cervical cells were exposed to different concentrations of withaferin A, a very promising anti-cancer adaptogenic substance. AFM-IR approach was used to image single cells post-adaptogen treatment and to track subtle biochemical changes in cells at the nanoscale level. Partial least squares (PLS) regression was applied to build predictive models that allowed for the identification of spectral markers of adaptogen-induced alterations Spectroscopic studies were enriched with fluorescence staining to determine whether the adaptogen affects cell morphology. The results showed that with the increase in the concentration of adaptogen, changes in the cell nucleus and the actin cytoskeleton become more and more significant. It has been demonstrated that the AFM-IR technique can successfully study the cellular response to the anti-cancer agent at the single-cell level with nanoscale spatial resolution. On the basis of the promising findings presented in this paper, it is possible to conclude that withaferin A has great potential in inhibiting the proliferation of cervical cancer cells in a dose-dependent manner. It has been found that both the increase in the concentration of withaferin A and the increase in incubation time with the adaptogen resulted in a decrease in the intensity of the bands assigned to nucleic acids. This may be due to DNA condensation, internuclear cleavage, or degradation during apoptosis. The findings also suggest changes in the secondary structure of proteins that may be a consequence of disruption of the actin cytoskeleton, progressive apoptosis, or significant biochemical changes. Furthermore, noticeable changes were also observed in the bands originating from lipids vibrations, and an increased share of the band near 2920 cm^-1, considered an important marker of apoptosis, was noted. The metabolism of carbohydrates in cells also changes under the influence of the adaptogen. AFM-IR provides nanoscale insight into the structural and morphological properties of cells after drug treatment and is an indisputable milestone in the development of new anti-cancer approaches.

Salivary ATR-FTIR Spectroscopy Coupled with Support Vector Machine Classification for Screening of Type 2 Diabetes Mellitus

The blood diagnosis of diabetes mellitus (DM) is highly accurate; however, it is an invasive, high-cost, and painful procedure. In this context, the combination of ATR-FTIR spectroscopy and machine learning techniques in other biological samples has been used as an alternative tool to develop a non-invasive, fast, inexpensive, and label-free diagnostic or screening platform for several diseases, including DM. In this study, we used the ATR-FTIR tool associated with linear discriminant analysis (LDA) and a support vector machine (SVM) classifier in order to identify changes in salivary components to be used as alternative biomarkers for the diagnosis of type 2 DM. The band area values of 2962 cm^-1, 1641 cm^-1, and 1073 cm^-1 were higher in type 2 diabetic patients than in non-diabetic subjects. The best classification of salivary infrared spectra was by SVM, showing a sensitivity of 93.3% (42/45), specificity of 74% (17/23), and accuracy of 87% between non-diabetic subjects and uncontrolled type 2 DM patients. The SHAP features of infrared spectra indicate the main salivary vibrational modes of lipids and proteins that are responsible for discriminating DM patients. In summary, these data highlight the potential of ATR-FTIR platforms coupled with machine learning as a reagent-free, non-invasive, and highly sensitive tool for screening and monitoring diabetic patients.

The Role of the Preanalytical Step for Human Saliva Analysis via Vibrational Spectroscopy

Saliva is an easily sampled matrix containing a variety of biochemical information, which can be correlated with the individual health status. The fast, straightforward analysis of saliva by vibrational (ATR-FTIR and Raman) spectroscopy is a good premise for large-scale preclinical studies to aid translation into clinics. In this work, the effects of saliva collection (spitting/swab) and processing (two different deproteinization procedures) were explored by principal component analysis (PCA) of ATR-FTIR and Raman data and by investigating the effects on the main saliva metabolites by reversed-phase chromatography (RPC-HPLC-DAD). Our results show that, depending on the bioanalytical information needed, special care must be taken when saliva is collected with swabs because the polymeric material significantly interacts with some saliva components. Moreover, the analysis of saliva before and after deproteinization by FTIR and Raman spectroscopy allows to obtain complementary biological information.

Adaptogenic activity of withaferin A on human cervical carcinoma cells using high-definition vibrational spectroscopic imaging

Despite invaluable advances in cervical cancer therapy, treatment regimens for recurrent or persistent cancers and low-toxicity alternative treatment options are scarce. In recent years, substances classified as adaptogens have been identified as promising drug sources for preventing and treating cancer-based diseases on their ability to attack multiple molecular targets. This paper establishes the effectiveness of inhibition of the neoplastic process by a withaferin A (WFA), an adaptogenic substance, based on an in vitro model of cervical cancer. This study explores for the first time the potential of high-definition vibrational spectroscopy methods, i.e. Fourier-transform infrared (FT-IR) and Raman spectroscopic (RS) imaging at the single-cell level to evaluate the efficacy of the adaptogenic drug. HeLa cervical cancer cells were incubated with various concentrations of WFA at different incubation times. The multimodal spectroscopic approach combined with partial least squares (PLS) regression allowed the identification of molecular changes (e.g., lipids, protein secondary structures, or nucleic acids) induced by WFA at the cellular level. The results clearly illustrate the enormous potential of WFA in inhibiting the proliferation of cervical cancer cells. WFA inhibited the growth of the studied cancer cell line in a dose-dependent manner. Such studies provide comprehensive information on the sensitivity of cells to adaptogenic drugs. This is a fundamental step towards determining the rate and nature of adaptogen-induced changes in cancer cells.

Saliva may predict quality of life in psoriasis as measured by Fourier transform infrared spectroscopy (FTIR) and chemometrics

BACKGROUND

Psoriasis is a chronic skin disease, with several comorbidities, such as psoriatic arthritis, inflammatory bowel disease, metabolic syndrome, and impaired quality of life and work activity. The Dermatology Life Quality Index (DLQI) is the most commonly used quality of life index in psoriatic patients, as it is a marker of severe disease. This study evaluated the association between salivary Fourier transform Infrared Spectroscopy (FTIR) metabolic fingerprints and severity of psoriasis as measured by DLQI, using chemometric algorithms.

MATERIALS AND METHODS

Saliva was collected from 56 (27 with DLQI ≤ 10 [GI]; 29 with DLQI > 10 [GII]) psoriatic patients diagnosed and assessed by DLQI for disease severity by a dermatologist and analyzed by the transflectance technique in mid-infrared. Hierarchic cluster analysis (HCA), principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and orthogonal partial least squares (OPLS) algorithms were used to associate salivary FTIR spectra with the respective DLQI scores.

RESULTS

Second derivative (2D) discriminated GI and GII at 2522 cm^-1 (p < 0.0001). HCA and PCA partially discriminated GI from GII at 4000-450 cm^-1 (p = 0.042 and 0.00821, respectively). Data processing with 1^st derivative (1D), 3 latent variables (LV) and 1 orthogonal signal correction (OSC) component at 2550-1801 cm^-1 generated an FTIR/OPLS-DA model with 100% accuracy to classify the severity of psoriasis, and an FTIR/OPLS model to quantify DLQI (range 0-28) with high performance: root mean square error of prediction (RMSEP) < 0.01 and coefficient of determination (R²) > 0.9999.

CONCLUSIONS

Salivary FTIR combined with chemometric algorithms such as OPLS-DA and OPLS can be used as a clinical tool to classify or predict the severity of psoriasis according to DLQI in patients with confirmed psoriasis.

Non/mini-invasive monitoring of diabetes-induced myocardial damage by Fourier transform infrared spectroscopy: Evidence from biofluids

Early identification of diabetic cardiomyopathy (DCM) can help clinicians develop targeted treatment plans and forensic pathologists make accurate postmortem diagnoses. In the present study, diabetes-induced metabolic abnormalities in the myocardium and biofluids (plasma, urine, and saliva) of db/db mice of various ages (7, 12, and 21 weeks) were investigated by attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy. The results indicated that the diabetic and control groups had significantly different changes in the function groups of lipids, phosphate macromolecules (mostly nucleic acids), protein compositions and conformations, and carbohydrates (primarily glucose) in the myocardium and biofluids. The prediction model for quantifying DCM severity was developed on db/db mice's myocardial spectra using a genetic algorithm (GA)-partial least squares (PLS) regression method. Following that, the linear correlations between the predicted values for DCM severity and spectra for db/db biofluids were evaluated using the GA-PLS regression algorithm. The results showed there were good linear correlations between the predicted values for DCM severity and spectra for plasma (R² = 0.929), saliva (R² = 0.967), urine (R² = 0.954), and combination of plasma and saliva (R² = 0.980). This study provides a novel perspective on detecting diabetes-related biofluid and cardiac metabolic abnormalities and demonstrates the potential of biofluid infrared spectro-diagnostic models for non/mini-invasive assessment of DCM.

Diagnosis of liver cancer by FTIR spectra of serum

Liver cancer is the most common fatal malignant tumor in the world. Early diagnosis of liver cancer can improve the survival rate of the patients with liver disease. In this paper, Fourier transform infrared (FTIR) spectroscopy combined with curve fitting and chemometrics was used to distinguish the serum from patients from that of healthy people. The curve fitting results in protein range of 1700-1600 cm^-1 showed that there were differences in the secondary structure of protein in serum between the patients with liver cancer and healthy people. Principal component analysis (PCA) in lipid range of 2900-2800 cm^-1 could distinguish the serum of patients with liver cancer from that of healthy people. The first two principal components PC1 and PC2 explained 95% of the total data variance. The sensitivity and specificity of partial least squares discriminant analysis (PLS-DA) in lipid range of 2900-2800 cm^-1 reached 92.85% and 95.23% respectively. It is shown that FTIR spectroscopy might be developed as an effective method for the diagnosis of liver cancer.

Diagnostic approach to thyroid cancer based on amino acid metabolomics in saliva by ultra-performance liquid chromatography with high resolution mass spectrometry

Thyroid cancer is a malignant disease with dramatically low advanced-stage 10-year survival. Meanwhile, the metabolites in saliva are becoming a wealthy source of disease biomarkers. However, there is a lack of non-invasive analytical methods for the identification of biomarkers in saliva for the preoperative diagnosis of thyroid cancer. Therefore, we developed an ultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) method to simultaneously determine the metabolic levels of 10 amino acids in saliva, aiming to study the amino acid metabolism profile to promote early diagnosis of thyroid cancer. We tested unstimulated whole saliva from patients with papillary thyroid carcinoma (PTC; n = 61) and healthy controls (HC; n = 61), and used receiver operating characteristic (ROC) curves to establish the diagnostic value of potential markers. The method validation results showed good precision, linearity (R² > 0.99), recovery (92.2 %-110.3 %), intra- and inter-day precision (RSD < 7 % and RSD < 9 %, respectively). The concentration of 10 amino acids was significantly different between PTC and HC in human salivary analysis (P < 0.05), the area under the curve (AUC) values of a single marker for the diagnosis of PTC were ranging from 0.678 to 0.833. A panel of alanine, valine, proline, phenylalanine was selected in combination yielded the AUC of 0.936, which will improve the accuracy of early diagnosis of thyroid cancer (sensitivity: 91.2 %; specificity: 85.2 %). This study proved the possibility of salivary amino acid biomarkers for PTC early diagnosis, providing a simple auxiliary way for the non-invasive diagnosis of thyroid cancer.

A Tissue Section-Based Near-Infrared Spectroscopical Analysis of Salivary Gland Tumors

Simple Summary

Salivary gland tumors (SGTs) are a group of rare tumors that vary in clinical and histological behavior. Histological classification is difficult and requires an experienced pathologist. Based on recent research in other medical fields, this study investigated the value of near-infrared (NIR) spectroscopy in the diagnosis of SGTs supplementary to the histological investigation. The acquired spectra were analyzed with chemometric techniques. Enzymatic treatment (neuraminidase) resulted in spectral peak differences between healthy controls and different SGT types. Some malignant SGTs had higher spectral changes, suggesting bigger alterations in glycosylation of salivary mucins. Future biochemical research based on the further enzymatic dissection of SGTs and infrared spectroscopy could help pathologists to better understand the nature of these types of tumors.

Abstract

SGTs vary in histological behavior. Mucins, a major component in salivary glands, consist of a glycosylated and sialylated protein core. Rapid evolutions in glycobiology have demonstrated the important role of glycoproteins in cancer development. NIR spectroscopy is a method for the biochemical analysis of substrates. NIR spectra can be analyzed using specific chemometrics. Our aim was to explore the diagnostic possibilities of NIR spectroscopy in SGTs. 238 Hematoxylin and Eosine stained (H&E) SGT tissue sections were examined using NIR spectroscopy. 45 deparaffinized tissue sections were treated with neuraminidase to identify wavelengths in the NIR spectrum related to sialylation. NIR spectra were analyzed with chemometrics. NIR spectra could distinguish malignant SGTs from controls and benign SGTs. Prediction models based on the entire spectral range resulted in a 73.1% accurate classification of malignant SGTs and controls, while, based on neuraminidase experimental spectral peak differences (1436 nm; 1713 nm; 1783 nm; 1924 nm; 2032 nm; 2064 nm; 2178 nm; 2216 nm), an improved overall correct classification rate of 91.9% was obtained between healthy subjects and malignant tumors. H&E tissue section-based NIR spectroscopy can identify malignant SGTs from controls, promising an alternative method in the diagnosis of SGTs.

Tracking of the biochemical changes upon pleomorphic adenoma progression using vibrational microspectroscopy

Head and neck tumors can be very challenging to treat because of the risk of problems or complications after surgery. Therefore, prompt and accurate diagnosis is extremely important to drive appropriate treatment decisions, which may reduce the chance of recurrence. This paper presents the original research exploring the feasibility of Fourier transform infrared (FT-IR) and Raman spectroscopy (RS) methods to investigate biochemical alterations upon the development of the pleomorphic adenoma. Principal component analysis (PCA) was used for a detailed assessment of the observed changes and to determine the spectroscopic basis for salivary gland neoplastic pathogenesis. It is implied that within the healthy margin, as opposed to the tumoral tissue, there are parts that differ significantly in lipid content. This observation shed new light on the crucial role of lipids in tissue physiology and tumorigenesis. Thus, a novel approach that eliminates the influence of lipids on the elucidation of biochemical changes is proposed. The performed analysis suggests that the highly heterogeneous healthy margin contains more unsaturated triacylglycerols, while the tumoral section is rich in proteins. The difference in protein content was also observed for these two tissue types, i.e. the healthy tissue possesses more proteins in the anti-parallel β-sheet conformation, whereas the tumoral tissue is dominated by proteins rich in unordered random coils. Furthermore, the pathogenic tissue shows a higher content of carbohydrates and reveals noticeable differences in nucleic acid content. Finally, FT-IR and Raman spectroscopy methods were proposed as very promising methods in the discrimination of tumoral and healthy tissues of the salivary gland.

Molecular Origin of Blood-Based Infrared Spectroscopic Fingerprints*

Infrared spectroscopy of liquid biopsies is a time- and cost-effective approach that may advance biomedical diagnostics. However, the molecular nature of disease-related changes of infrared molecular fingerprints (IMFs) remains poorly understood, impeding the method's applicability. Here we probe 148 human blood sera and reveal the origin of the variations in their IMFs. To that end, we supplemented infrared spectroscopy with biochemical fractionation and proteomic profiling, providing molecular information about serum composition. Using lung cancer as an example of a medical condition, we demonstrate that the disease-related differences in IMFs are dominated by contributions from twelve highly abundant proteins-that, if used as a pattern, may be instrumental for detecting malignancy. Tying proteomic to spectral information and machine learning advances our understanding of the infrared spectra of liquid biopsies, a framework that could be applied to probing of any disease.

Analysis of Saliva Lipids in Breast and Prostate Cancer by IR Spectroscopy

We have developed a method for studying the lipid profile of saliva, combining preliminary extraction and IR spectroscopic detection. The case-control study involved patients with a histologically verified diagnosis of breast and prostate cancer and healthy volunteers. The comparison group included patients with non-malignant pathologies of the breast (fibroadenomas) and prostate gland (prostatic intraepithelial neoplasia). Saliva was used as a material for biochemical studies. It has been shown that the lipid profile of saliva depends on gender, and for males it also depends on the age group. In cancer pathologies, the lipid profile changes significantly and also depends on gender and age characteristics. The ratio of 1458/1396 cm-1 for both breast and prostate cancer has a potential diagnostic value. In both cases, this ratio decreases compared to healthy controls. For prostate cancer, the ratio of 2923/2957 cm-1 is also potentially informative, which grows against the background of prostate pathologies. It is noted that, in all cases, changes in the proposed ratios are more pronounced in the early stages of diseases, which increases the relevance of their study in biomedical applications.

SP, N. M, Barik AK, Pai KM, Unnikrishnan VK, George SD, Kartha VB, Chidangil S. Photonics of human saliva: potential optical methods for the screening of abnormal health conditions and infections

Human saliva can be treated as a pool of biological markers able to reflect on the state of personal health. Recent years have witnessed an increase in the use of optical devices for the analysis of body fluids. Several groups have carried out studies investigating the potential of saliva as a non-invasive and reliable clinical specimen for use in medical diagnostics. This brief review aims to highlight the optical technologies, mainly surface plasmon resonance (SPR), Raman, and Fourier transform infrared (FTIR) spectroscopy, which are being used for the probing of saliva for diverse biomedical applications. Advances in bio photonics offer the promise of unambiguous, objective and fast detection of abnormal health conditions and viral infections (such as COVID-19) from the analysis of saliva.

In search of the correlation between nanomechanical and biomolecular properties of prostate cancer cells with different metastatic potential

Nanomechanical properties of living cells, as measured with atomic force microscopy (AFM), are increasingly recognized as criteria that differentiate normal and pathologically altered cells. Locally measured cell elastic properties, described by the parameter known as Young's modulus, are currently proposed as a new diagnostic parameter that can be used at the early stage of cancer detection. In this study, local mechanical properties of normal human prostate (RWPE-1) cells and a range of malignant (22Rv1) and metastatic prostate cells (LNCaP, Du145 and PC3) were investigated. It was found that non-malignant prostate cells are stiffer than cancer cells while the metastatic cells are much softer than malignant cells from the primary tumor site. Next, the biochemical properties of the cells were measured using confocal Raman (RS) and Fourier-transform infrared (FT-IR) spectroscopies to reveal these cells' biochemical composition as malignant transformation proceeds. Nanomechanical and biochemical profiles of five different prostate cell lines were subsequently analyzed using partial least squares regression (PLSR) in order to identify which spectral features of the RS and FT-IR spectra correlate with the cell's elastic properties. The PLSR-based model could predict Young's modulus values based on both RS and FT-IR spectral information. These outcomes show not only that AFM, RS and FT-IR techniques can be used for discrimination between normal and cancer cells, but also that a linear correlation between mechanical response and biomolecular composition of the cells that undergo malignant transformation can be found. This knowledge broadens our understanding of how prostate cancer cells evolve thorough the multistep process of tumor pathogenesis.