Identification of volatile metabolites in human saliva from patients with oral squamous cell carcinoma via zeolite-based thin-film microextraction coupled with GC-MS

Non-coding RNAs in oral cancer: Emerging biomarkers and therapeutic frontier

Around the world, oral cancer (OC) is a major public health problem, resulting in a significant number of deaths each year. Early detection and treatment are crucial for improving patient outcomes. Recent progress in DNA sequencing and transcriptome profiling has revealed extensive non-coding RNAs (ncRNAs) transcription, underscoring their regulatory importance. NcRNAs influence genomic transcription and translation and molecular signaling pathways, making them valuable for various clinical applications. Combining spatial transcriptomics (ST) and spatial metabolomics (SM) with single-cell RNA sequencing provides deeper insights into tumor microenvironments, enhancing diagnostic and therapeutic precision for OC. Additionally, the exploration of salivary biomarkers offers a non-invasive diagnostic avenue. This article explores the potential of ncRNAs as diagnostic and therapeutic tools for OC.

Development of a disposable paper-based thin film solid-phase microextraction sampling kit to quantify ketone body

Diabetes ketoacidosis (DKA) is a life-threatening complication and requires immediate medical attention in the case of diabetes subjects, especially in the case of type 1 diabetes mellitus. In the condition of DKA, the body produces an excess amount of ketone bodies after unregulated fat degradation, causing blood to become acidic and hampering the regular metabolic activities of the body. The current diagnostic technique for DKA condition is based on monitoring ketone bodies, especially β-hydroxybutyric acid, from human urine and blood samples. The detection of serum ketone bodies in pathology is sometimes limited due to false positive results and the lack of standardization for precise quantification of analytes. In this study, a paper-based patch operating on the thin film solid-phase microextraction (TF-SPME) principle was developed and it was coupled with gas chromatography-mass spectrometry for simple quantification of β-hydroxybutyric acid (BHB) ketone body from a phosphate-buffered saline matrix. To fabricate the paper-based TF-SPME patches, a regular A4 sheet paper sheet was utilized as the substrate and uniform coating by multiwalled carbon nanotubes (MWCNT), polydimethylsiloxane (PDMS) and divinyl benzene (DVB) compounds was performed with an automatic film applicator. The 70 μm paper-based coated sheet was trimmed into 4 cm × 1 cm dimension pieces to obtain multiple patches from a single sheet. Extraction of the BHB ketone body into the closed vials was performed by exploiting the individual DVB/PDMS and DVB/CNT/PDMS paper patches followed by desorption with acetonitrile before quantification by gas chromatography-mass spectrometry analysis. Our study showed that the BHB extraction efficiency of DVB/PDMS-coated patches was higher than that of DVB/CNT/PDMS. The outcome showed a good linearity (R 2 = 0.99) within the 500-20 000 ng mL-1 concentration range of BHB by paper-based DVB/PDMS patches. This study demonstrated the feasibility of utilizing simple, cost-effective paper-based disposable TF-SPME patches as a sampling kit for future screening of diabetes ketoacidosis without the need for prolonged traditional sample preparation in pathology.

The human volatilome meets cancer diagnostics: past, present, and future of noninvasive applications

BACKGROUND

Cancer is a significant public health problem, causing dozens of millions of deaths annually. New cancer screening programs are urgently needed for early cancer detection, as this approach can improve treatment outcomes and increase patient survival. The search for affordable, noninvasive, and highly accurate cancer detection methods revealed a valuable source of tumor-derived metabolites in the human metabolome through the exploration of volatile organic compounds (VOCs) in noninvasive biofluids.

AIM OF REVIEW

This review discusses volatilomics-based approaches for cancer detection using noninvasive biomatrices (breath, saliva, skin secretions, urine, feces, and earwax). We presented the historical background, the latest approaches, and the required stages for clinical validation of volatilomics-based methods, which are still lacking in terms of making noninvasive methods available and widespread to the population. Furthermore, insights into the usefulness and challenges of volatilomics in clinical implementation steps for each biofluid are highlighted.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We outline the methodologies for using noninvasive biomatrices with up-and-coming clinical applications in cancer diagnostics. Several challenges and advantages associated with the use of each biomatrix are discussed, aiming at encouraging the scientific community to strengthen efforts toward the necessary steps to speed up the clinical translation of volatile-based cancer detection methods, as well as discussing in favor of (i) hybrid applications (i.e., using more than one biomatrix) to describe metabolite modulations that can be "cancer volatile fingerprints" and (ii) in multi-omics approaches integrating genomics, transcriptomics, and proteomics into the volatilomic data, which might be a breakthrough for diagnostic purposes, onco-pathway assessment, and biomarker validations.

Biological biomarkers of oral cancer

The oral squamous cell carcinoma (OSCC) 5 year survival rate of 41% has marginally improved in the last few years, with less than a 1% improvement per year from 2005 to 2017, with higher survival rates when detected at early stages. Based on histopathological grading of oral dysplasia, it is estimated that severe dysplasia has a malignant transformation rate of 7%-50%. Despite these numbers, oral dysplasia grading does not reliably predict its clinical behavior. Thus, more accurate markers predicting oral dysplasia progression to cancer would enable better targeting of these lesions for closer follow-up, especially in the early stages of the disease. In this context, molecular biomarkers derived from genetics, proteins, and metabolites play key roles in clinical oncology. These molecular signatures can help predict the likelihood of OSCC development and/or progression and have the potential to detect the disease at an early stage and, support treatment decision-making and predict treatment responsiveness. Also, identifying reliable biomarkers for OSCC detection that can be obtained non-invasively would enhance management of OSCC. This review will discuss biomarkers for OSCC that have emerged from different biological areas, including genomics, transcriptomics, proteomics, metabolomics, immunomics, and microbiomics.

Partial role of volatile organic compounds in behavioural responses of mice to bedding from cancer-affected congeners

Tumours induce changes in body odours. We compared volatile organic compounds (VOCs) in soiled bedding of a lung adenocarcinoma male mouse model in which cancer had (CC) versus had not (NC) been induced by doxycycline at three conditions: before (T0), after 2 weeks (T2; early tumour development), after 12 weeks (T12; late tumour development) of the induction. In an earlier study, wild-derived mice behaviourally discriminated between CC and NC soiled bedding at T2 and T12. Here, we sought to identify VOCs present in the same soiled bedding that could have triggered the behavioural discrimination. Solid phase micro-extraction was performed to extract VOCs from 3 g-sample stimuli. While wild-derived mice could discriminate the odour of cancerous mice at a very early stage of tumour development (T2), the present study did not identify VOCs that could explain this behaviour. However, consistent with the earlier behavioural study, four VOCs, including two well-known male mouse sex pheromones, were found to be present in significantly different proportions in soiled bedding of CC as compared to NC at T12. We discuss the potential involvement of non-volatile molecules such as proteins and peptides in behavioural discrimination of early tumour development (T2), and point-out VOCs that could help diagnose cancer.

Salivary Metabolites Produced by Oral Microbes in Oral Diseases and Oral Squamous Cell Carcinoma: A Review

In recent years, salivary metabolome studies have provided new biological information and salivary biomarkers to diagnose different diseases at early stages. The saliva in the oral cavity is influenced by many factors that are reflected in the salivary metabolite profile. Oral microbes can alter the salivary metabolite profile and may express oral inflammation or oral diseases. The released microbial metabolites in the saliva represent the altered biochemical pathways in the oral cavity. This review highlights the oral microbial profile and microbial metabolites released in saliva and its use as a diagnostic biofluid for different oral diseases. The importance of salivary metabolites produced by oral microbes as risk factors for oral diseases and their possible relationship in oral carcinogenesis is discussed.

The metabolic reprogramming of γ-aminobutyrate in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common head and neck malignancy. The oncometabolites have been studied in OSCC, but the mechanism of metabolic reprogramming remains unclear. To identify the potential metabolic markers to distinguish malignant oral squamous cell carcinoma (OSCC) tissue from adjacent healthy tissue and study the mechanism of metabolic reprogramming in OSCC. We compared the metabolites between cancerous and paracancerous tissues of OSCC patients by 1HNMR analysis. We established OSCC derived cell lines and analyzed their difference of RNA expression by RNA sequencing. We investigated the metabolism of γ-aminobutyrate in OSCC derived cells by real time PCR and western blotting. Our data revealed that much more γ-aminobutyrate was produced in cancerous tissues of OSCC patients. The investigation based on OSCC derived cells showed that the increase of γ-aminobutyrate was promoted by the synthesis of glutamate beyond the mitochondria. In OSCC cancerous tissue derived cells, the glutamate was catalyzed to glutamine by glutamine synthetase (GLUL), and then the generated glutamine was metabolized to glutamate by glutaminase (GLS). Finally, the glutamate produced by glutamate-glutamine-glutamate cycle was converted to γ-aminobutyrate by glutamate decarboxylase 2 (GAD2). Our study is not only benefit for understanding the pathological mechanisms of OSCC, but also has application prospects for the diagnosis of OSCC.

Ingredients in Commercially Available Mouthwashes

OBJECTIVES

Mouthwashes, a cornerstone of oral and dental hygiene, play a pivotal role in combating the formation of dental plaque, a leading cause of periodontal disease and dental caries. This study aimed to review the composition of mouthwashes found on retail shelves in Turkey and evaluate their prevalence and side effects, if any.

METHODS

The mouthwashes examined were sourced from the 5 largest chain stores in each district of Istanbul. A comprehensive list of the constituents was meticulously recorded. The research was supported by an extensive compilation of references from scholarly databases such as Google Scholar, PubMed, and ScienceDirect. Through rigorous analysis, the relative proportions of mouthwash ingredients and components were determined.

RESULTS

A total of 45 distinctive variations of mouthwashes, representing 17 prominent brands, were identified. Amongst the 116 ingredients discovered, 70 were evaluated for potential adverse effects and undesirable side effects. The aroma of the mouthwash (n = 45; 100%), as welll as their sodium fluoride (n = 28; 62.22%), sodium saccharin (n = 29; 64.44%), sorbitol (n = 21; 46.6%), and propylene glycol (n = 28; 62.22%) content were the main undesireable features.

CONCLUSIONS

The limited array of mouthwashes found on store shelves poses a concern for both oral and public health. Furthermore, the intricate composition of these products, consisting of numerous ingredients with the potential for adverse effects, warrants serious attention. Both clinicians and patients should acknowledge the importance and unwarranted side effects of the compnents of the mouthwashes.

Salivary metabolomics in oral potentially malignant disorders and oral cancer patients-a systematic review with meta-analysis

OBJECTIVES

The aim of this systematic review and meta-analysis is to assess the diagnostic potential of salivary metabolomics in the detection of oral potentially malignant disorders (OPMDs) and oral cancer (OC).

MATERIALS AND METHODS

A systematic review was performed in accordance with the 3rd edition of the Centre for Reviews and Dissemination (CRD) and Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Electronic searches for articles were carried out in the PubMed, Web of Science, and Scopus databases. The quality assessment of the included studies was evaluated using the Newcastle-Ottawa Quality Assessment Scale (NOS) and the new version of the QUADOMICS tool. Meta-analysis was conducted whenever possible. The effect size was presented using the Forest plot, whereas the presence of publication bias was examined through Begg's funnel plot.

RESULTS

A total of nine studies were included in the systematic review. The metabolite profiling was heterogeneous across all the studies. The expression of several salivary metabolites was found to be significantly altered in OPMDs and OCs as compared to healthy controls. Meta-analysis was able to be conducted only for N-acetylglucosamine. There was no significant difference (SMD = 0.15; 95% CI - 0.25-0.56) in the level of N-acetylglucosamine between OPMDs, OC, and the control group.

CONCLUSION

Evidence for N-acetylglucosamine as a salivary biomarker for oral cancer is lacking. Although several salivary metabolites show changes between healthy, OPMDs, and OC, their diagnostic potential cannot be assessed in this review due to a lack of data. Therefore, further high-quality studies with detailed analysis and reporting are required to establish the diagnostic potential of the salivary metabolites in OPMDs and OC.

CLINICAL RELEVANCE

While some salivary metabolites exhibit significant changes in oral potentially malignant disorders (OPMDs) and oral cancer (OC) compared to healthy controls, the current evidence, especially for N-acetylglucosamine, is inadequate to confirm their reliability as diagnostic biomarkers. Additional high-quality studies are needed for a more conclusive assessment of salivary metabolites in oral disease diagnosis.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

Urinary VOCs as biomarkers of early stage lung tumour development in mice

BACKGROUND

Lung cancer is the primary cause of cancer-induced death. In addition to prevention and improved treatment, it has increasingly been established that early detection is critical to successful remission.

OBJECTIVE

The aim of this study was to identify volatile organic compounds (VOCs) in urine that could help diagnose mouse lung cancer at an early stage of its development.

METHODS

We analysed the VOC composition of urine in a genetically engineered lung adenocarcinoma mouse model with oncogenic EGFR doxycycline-inducible lung-specific expression. We compared the urinary VOCs of 10 cancerous mice and 10 healthy mice (controls) before and after doxycycline induction, every two weeks for 12 weeks, until full-blown carcinomas appeared. We used SPME fibres and gas chromatography - mass spectrometry to detect variations in cancer-related urinary VOCs over time.

RESULTS

This study allowed us to identify eight diagnostic biomarkers that help discriminate early stages of cancer tumour development (i.e., before MRI imaging techniques could identify it).

CONCLUSION

The analysis of mice urinary VOCs have shown that cancer can induce changes in odour profiles at an early stage of cancer development, opening a promising avenue for early diagnosis of lung cancer in other models.

Application of Zeolites and Zeolitic Imidazolate Frameworks in Dentistry-A Narrative Review

Zeolites and zeolitic imidazolate frameworks (ZIFs) are crystalline aluminosilicates with porous structure, which are closely linked with nanomaterials. They are characterized by enhanced ion exchange capacity, physical-chemical stability, thermal stability and biocompatibility, making them a promising material for dental applications. This review aimed to provide an overview of the application of zeolites and ZIFs in dentistry. The common zeolite compounds for dental application include silver zeolite, zinc zeolite, calcium zeolite and strontium zeolite. The common ZIFs for dental application include ZIF-8 and ZIF-67. Zeolites and ZIFs have been employed in various areas of dentistry, such as restorative dentistry, endodontics, prosthodontics, implantology, periodontics, orthodontics and oral surgery. In restorative dentistry, zeolites and ZIFs are used as antimicrobial additives in dental adhesives and restorative materials. In endodontics, zeolites are used in root-end fillings, root canal irritants, root canal sealers and bone matrix scaffolds for peri-apical diseases. In prosthodontics, zeolites can be incorporated into denture bases, tissue conditioners, soft denture liners and dental prostheses. In implantology, zeolites and ZIFs are applied in dental implants, bone graft materials, bone adhesive hydrogels, drug delivery systems and electrospinning. In periodontics, zeolites can be applied as antibacterial agents for deep periodontal pockets, while ZIFs can be embedded in guided tissue regeneration membranes and guided bone regeneration membranes. In orthodontics, zeolites can be applied in orthodontic appliances. Additionally, for oral surgery, zeolites can be used in oral cancer diagnostic marker membranes, maxillofacial prosthesis silicone elastomer and tooth extraction medicines, while ZIFs can be incorporated to osteogenic glue or used as a carrier for antitumour drugs. In summary, zeolites have a broad application in dentistry and are receiving more attention from clinicians and researchers.

Diagnosis of Carcinogenic Pathologies through Breath Biomarkers: Present and Future Trends

The assessment of volatile breath biomarkers has been targeted with a lot of interest by the scientific and medical communities during the past decades due to their suitability for an accurate, painless, non-invasive, and rapid diagnosis of health states and pathological conditions. This paper reviews the most relevant bibliographic sources aiming to gather the most pertinent volatile organic compounds (VOCs) already identified as putative cancer biomarkers. Here, a total of 265 VOCs and the respective bibliographic sources are addressed regarding their scientifically proven suitability to diagnose a total of six carcinogenic diseases, namely lung, breast, gastric, colorectal, prostate, and squamous cell (oesophageal and laryngeal) cancers. In addition, future trends in the identification of five other forms of cancer, such as bladder, liver, ovarian, pancreatic, and thyroid cancer, through perspective volatile breath biomarkers are equally presented and discussed. All the results already achieved in the detection, identification, and quantification of endogenous metabolites produced by all kinds of normal and abnormal processes in the human body denote a promising and auspicious future for this alternative diagnostic tool, whose future passes by the development and employment of newer and more accurate collection and analysis techniques, and the certification for utilisation in real clinical scenarios.

Determination of hexanal and heptanal in saliva samples by an adapted magnetic headspace adsorptive microextraction for diagnosis of lung cancer

In this work, an analytical method for the determination of two endogenous aldehydes (hexanal and heptanal) as lung cancer biomarkers in saliva samples is presented for the first time. The method is based on a modification of magnetic headspace adsorptive microextraction (M-HS-AME) followed by gas chromatography coupled to mass spectrometry (GC-MS). For this purpose, an external magnetic field generated by a neodymium magnet is used to hold the magnetic sorbent (i.e., CoFe₂O₄ magnetic nanoparticles embedded into a reversed-phase polymer) in the headspace of a microtube to extract the volatilized aldehydes. Subsequently, the analytes are desorbed in the appropriate solvent and the extract is injected into the GC-MS system for separation and determination. Under the optimized conditions, the method was validated and showed good analytical features in terms of linearity (at least up to 50 ng mL^-1), limits of detection (0.22 and 0.26 ng mL^-1 for hexanal and heptanal, respectively), and repeatability (RSD ≤12%). This new approach was successfully applied to saliva samples from healthy volunteers and those with lung cancer, obtaining notably differences between both groups. These results reveal the prospect of the method as potential diagnostic tool for lung cancer by saliva analysis. This work contributes to the Analytical Chemistry field presenting a double novelty: on the one hand, the use of M-HS-AME in bioanalysis is unprecedentedly proposed, thus expanding the analytical potential of this technique, and, on the other hand, the determination of hexanal and heptanal is carried out in saliva samples for the first time.

Saliva biomarkers in oral disease

Saliva is a versatile biofluid that contains a wide variety of biomarkers reflecting both physiologic and pathophysiologic states. Saliva collection is noninvasive and highly applicable for tests requiring serial sampling. Furthermore, advances in test accuracy, sensitivity and precision for saliva has improved diagnostic performance as well as the identification of novel markers especially in oral disease processes. These include dental caries, periodontitis, oral squamous cell carcinoma (OSCC) and Sjögren's syndrome (SS). Numerous growth factors, enzymes, interleukins and cytokines have been identified and are the subject of much research investigation. This review highlights current procedures for successful determination of saliva biomarkers including preanalytical factors associated with sampling, storage and pretreatment as well as subsequent analysis. Moreover, it provides an overview of the diagnostic applications of these salivary biomarkers in common oral diseases.

Differences in the Volatilomic Urinary Biosignature of Prostate Cancer Patients as a Feasibility Study for the Detection of Potential Biomarkers

Prostate cancer (PCa) continues to be the second most common malignant tumour and the main cause of oncological death in men. Investigating endogenous volatile organic metabolites (VOMs) produced by various metabolic pathways is emerging as a novel, effective, and non-invasive source of information to establish the volatilomic biosignature of PCa. In this study, headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GC-MS) was used to establish the urine volatilomic profile of PCa and identify VOMs that can discriminate between the two investigated groups. This non-invasive approach was applied to oncological patients (PCa group, n = 26) and cancer-free individuals (control group, n = 30), retrieving a total of 147 VOMs from various chemical families. This included terpenes, norisoprenoid, sesquiterpenes, phenolic, sulphur and furanic compounds, ketones, alcohols, esters, aldehydes, carboxylic acid, benzene and naphthalene derivatives, hydrocarbons, and heterocyclic hydrocarbons. The data matrix was subjected to multivariate analysis, namely partial least-squares discriminant analysis (PLS-DA). Accordingly, this analysis showed that the group under study presented different volatomic profiles and suggested potential PCa biomarkers. Nevertheless, a larger cohort of samples is required to boost the predictability and accuracy of the statistical models developed.

Hybrid volatilomics in cancer diagnosis by HS-GC-FID fingerprinting

Assessing volatile organic compounds (VOCs) as cancer signatures is one of the most promising techniques toward developing non-invasive, simple, and affordable diagnosis. Here, we have evaluated the feasibility of employing static headspace extraction (HS) followed by gas chromatography with flame ionization detector (GC-FID) as a screening tool to discriminate between cancer patients (head and neck-HNC,n= 15; and gastrointestinal cancer-GIC,n= 19) and healthy controls (n= 37) on the basis of a non-target (fingerprinting) analysis of oral fluid and urine. We evaluated the discrimination considering a single bodily fluid and adopting the hybrid approach, in which the oral fluid and urinary VOCs profiles were combined through data fusion. We used supervised orthogonal partial least squares discriminant analysis for classification, and we assessed the prediction power of the models by analyzing the values of goodness of prediction (Q²Y), area under the curve (AUC), sensitivity, and specificity. The individual models HNC urine, HNC oral fluid, and GIC oral fluid successfully discriminated between healthy controls and positive samples (Q²Y = 0.560, 0.525, and 0.559; AUC = 0.814, 0.850, and 0.926; sensitivity = 84.8, 70.2, and 78.6%; and specificity = 82.3; 81.5; 87.5%, respectively), whereas GIC urine was not adequate (Q²Y = 0.292, AUC = 0.694, sensitivity = 66.1%, and specificity = 77.0%). Compared to the respective individual models, Q²Y for the hybrid models increased (0.623 for hybrid HNC and 0.562 for hybrid GIC). However, sensitivity was higher for HNC urine and GIC oral fluid than for hybrid HNC (75.6%) and hybrid GIC (69.8%), respectively. These results suggested that HS-GC-FID fingerprinting is suitable and holds great potential for cancer screening. Additionally, the hybrid approach tends to increase the predictive power if the individual models present suitable quality parameter values. Otherwise, it is more advantageous to use a single body fluid for analysis.

Mapping of Urinary Volatile Organic Compounds by a Rapid Analytical Method Using Gas Chromatography Coupled to Ion Mobility Spectrometry (GC–IMS)

Volatile organic compounds (VOCs) are a differentiated class of molecules, continuously generated in the human body and released as products of metabolic pathways. Their concentrations vary depending on pathophysiological conditions. They are detectable in a wide variety of biological samples, such as exhaled breath, faeces, and urine. In particular, urine represents an easily accessible specimen widely used in clinics. The most used techniques for VOCs detections are expensive and time-consuming, thus not allowing for rapid clinical analysis. In this perspective, the aim of this study is a comprehensive characterisation of the urine volatilome by the development of an alternative rapid analytical method. Briefly, 115 urine samples are collected; sample treatment is not needed. VOCs are detected in the urine headspace using gas chromatography coupled to ion mobility spectrometry (GC–IMS) by an extremely fast analysis (10 min). The method is analytically validated; the analysis is sensitive and robust with results comparable to those reported with other techniques. Twenty-three molecules are identified, including ketones, aldehydes, alcohols, and sulphur compounds, whose concentration is altered in several pathological states such as cancer and metabolic disorders. Therefore, it opens new perspectives for fast diagnosis and screening, showing great potential for clinical applications.

Advances in the Diagnosis, Monitoring, and Progression of Oral Cancer through Saliva: An Update

The early detection of cancer, and in particular oral cancer, has been a priority objective of study in recent years. Saliva has been proposed as an easy-to-obtain means of providing the necessary information to diagnose malignant lesions in the oral cavity, since it can be obtained very easily and completely noninvasively. There are a number of molecules, known as biomarkers, which may be involved in the malignant transformation of oral lesions, and which have different natures. The involvement of proteins (“proteomics”), metabolites (“metabolomics”), and even certain genes in the structural changes of altered tissue has been investigated in order to establish validated parameters for the early diagnosis of oral cancer. In addition, the development of new analytical assay methods that can reduce costs and obtain better results in terms of sensitivity and specificity has been a key point in recent research in this field. Even though there are numerous biomarkers with results showing high sensitivity and specificity, there is still a need for more studies, with a larger sample and with analytical methods that can constitute a real advance in time and cost. Although salivary biomarkers are a promising new diagnostic tool for oral cancer, for the moment they do not replace biopsy as the “gold standard”.

Finding the combination of multiple biomarkers to diagnose oral squamous cell carcinoma - A data mining approach

Data mining has proven to be a reliable method to analyze and discover useful knowledge about various diseases, including cancer research. In particular, data mining and machine learning algorithms to study oral squamous cell carcinoma (OSCC), the most common form of oral cancer, is a new area of research. This malignant neoplasm can be studied using saliva samples. Saliva is an important biofluid that must be used to verify potential biomarkers associated with oral cancer. In this study, first, we provide an overview of OSSC diagnoses based on machine learning and salivary metabolites. To our knowledge, this is the first study to apply advanced data mining techniques to diagnose OSCC. Then, we give new results of classification and feature selection algorithms used to identify potential salivary biomarkers of OSCC. To accomplish this task, we used the filter feature selection random forest importance algorithm and a wrapper methodology to evaluate the importance of metabolites obtained from gas chromatography mass-spectrometry (GC-MS) in the context of differentiation of OSCC and the control group. Salivary samples (n = 68) were collected for the control group, and the OSCC group were from patients matched for gender, age, and smoking habit. The classification process occurred based on Random Forest (RF) classification algorithm along with 10-cross validation. The results showed that glucuronic acid, maleic acid, and batyl alcohol can classify the samples with an area under the curve (AUC) of 0.91 versus an AUC of 0.76 using all 51 metabolites analyzed. The methodology used in this study can assist healthcare professionals and be adopted to discover diagnostic biomarkers for other diseases.

Salivary Metabolomics for Oral Squamous Cell Carcinoma Diagnosis: A Systematic Review

Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer in which the consumption of tobacco and alcohol is considered to be the main aetiological factor. Salivary metabolome profiling could identify novel biochemical pathways involved in the pathogenesis of various diseases. This systematic review was designed to answer the question “Are salivary metabolites reliable for the diagnosis of oral squamous cell carcinoma?”. Following the inclusion and exclusion criteria, nineteen studies were included (according to PRISMA statement guidelines). In all included studies, the diagnostic material was unstimulated whole saliva, whose metabolome changes were determined by different spectroscopic methods. At the metabolic level, OSCC patients differed significantly not only from healthy subjects but also from patients with oral leukoplakia, lichen planus or other oral potentially malignant disorders. Among the detected salivary metabolites, there were the indicators of the impaired metabolic pathways, such as choline metabolism, amino acid pathways, polyamine metabolism, urea cycle, creatine metabolism, glycolysis or glycerolipid metabolism. In conclusion, saliva contains many potential metabolites, which can be used reliably to early diagnose and monitor staging in patients with OSCC. However, further investigations are necessary to confirm these findings and to identify new salivary metabolic biomarkers.

Odors and cancer: Current status and future directions

Cancer is the second leading cause of death in the world. Because tumors detected at early stages are easier to treat, the search for biomarkers-especially non-invasive ones-that allow early detection of malignancies remains a central goal to reduce cancer mortality. Cancer, like other pathologies, often alters body odors, and much has been done by scientists over the last few decades to assess the value of volatile organic compounds (VOCs) as signatures of cancers. We present here a quantitative review of 208 studies carried out between 1984 and 2020 that explore VOCs as potential biomarkers of cancers. We analyzed the main findings of these studies, listing and classifying VOCs related to different cancer types while considering both sampling methods and analysis techniques. Considering this synthesis, we discuss several of the challenges and the most promising prospects of this research direction in the war against cancer.

Feasibility of a Portable Electronic Nose for Detection of Oral Squamous Cell Carcinoma in Sudan

BACKGROUND

Oral squamous cell carcinoma (OSCC) is increasing at an alarming rate particularly in low-income countries. This urges for research into noninvasive, user-friendly diagnostic tools that can be used in limited-resource settings. This study aims to test and validate the feasibility of e-nose technology for detecting OSCC in the limited-resource settings of the Sudanese population.

METHODS

Two e-nose devices (Aeonose™, eNose Company, Zutphen, The Netherlands) were used to collect breath samples from OSCC (n = 49) and control (n = 35) patients. Patients were divided into a training group for building an artificial neural network (ANN) model and a blinded control group for model validation. The Statistical Package for the Social Sciences (SPSS) software was used for the analysis of baseline characteristics and regression. Aethena proprietary software was used for data analysis using artificial neural networks based on patterns of volatile organic compounds.

RESULTS

A diagnostic accuracy of 81% was observed, with 88% sensitivity and 71% specificity.

CONCLUSIONS

This study demonstrates that e-nose is an efficient tool for OSCC detection in limited-resource settings, where it offers a valuable cost-effective strategy to tackle the burden posed by OSCC.

A literature survey of all volatiles from healthy human breath and bodily fluids: the human volatilome

This paper comprises an updated version of the 2014 review which reported 1846 volatile organic compounds (VOCs) identified from healthy humans. In total over 900 additional VOCs have been reported since the 2014 review and the VOCs from semen have been added. The numbers of VOCs found in breath and the other bodily fluids are: blood 379, breath 1488, faeces 443, milk 290, saliva 549, semen 196, skin 623 and urine 444. Compounds were assigned CAS registry numbers and named according to a common convention where possible. The compounds have been included in a single table with the source reference(s) for each VOC, an update on our 2014 paper. VOCs have also been grouped into tables according to their chemical class or functionality to permit easy comparison. Careful use of the database is needed, as a number of the identified VOCs only have level 2-putative assignment, and only a small fraction of the reported VOCs have been validated by standards. Some clear differences are observed, for instance, a lack of esters in urine with a high number in faeces and breath. However, the lack of compounds from matrices such a semen and milk compared to breath for example could be due to the techniques used or reflect the intensity of effort e.g. there are few publications on VOCs from milk and semen compared to a large number for breath. The large number of volatiles reported from skin is partly due to the methodologies used, e.g. by collecting skin sebum (with dissolved VOCs and semi VOCs) onto glass beads or cotton pads and then heating to a high temperature to desorb VOCs. All compounds have been included as reported (unless there was a clear discrepancy between name and chemical structure), but there may be some mistaken assignations arising from the original publications, particularly for isomers. It is the authors' intention that this work will not only be a useful database of VOCs listed in the literature but will stimulate further study of VOCs from healthy individuals; for example more work is required to confirm the identification of these VOCs adhering to the principles outlined in the metabolomics standards initiative. Establishing a list of volatiles emanating from healthy individuals and increased understanding of VOC metabolic pathways is an important step for differentiating between diseases using VOCs.

Metabolomics of Oral/Head and Neck Cancer

Oral/head and neck cancer is the sixth most common human malignancies in the world. Despite the treatment advances in surgery, chemotherapy, and radiotherapy, the patient survival has not been significantly improved in the past several decades. As a new methodological approach, metabolomics may help reveal the metabolic reprogramming mechanisms underlying head and neck cancer cell proliferation, invasion, and metastasis and may be used to identify metabolite biomarkers for clinical applications of the disease. In this chapter, we briefly review recent metabolomic applications in head and neck cancer.

Applications of porous frameworks in solid-phase microextraction

Porous frameworks are a term of attracting solid materials assembled by interconnection of molecules and ions. These trendy materials due to high chemical and thermal stability, well-defined pore size and structure, and high effective surface area gained attention to employ as extraction phase in sample pretreatment methods before analytical analysis. Solid-phase microextraction is an important subclass of sample preparation technique that up to now different configurations of this method have been introduced to get adaptable with different environments and analytical instruments. In this review, theoretical aspect and different modes of solid-phase microextraction method are investigated. Different classes of porous frameworks and their applications as extraction phase in the proposed microextraction method are evaluated. Types and features of supporting substrates and coating procedures of porous frameworks on them are reviewed. At the end, the prospective and the challenges ahead in this field are discussed.

Polyvinylidene difluoride film with embedded poly(amidoamine) modified graphene oxide for extraction of chlorpyrifos and diazinon

An effective, sensitive, relatively fast, and cost-effective method was developed to determine two types of selected organophosphorus pesticides (OPPs) including diazinon and chlorpyrifos in apple, peach, and four different water samples (river, sea, well, and agriculture wastewater samples) through applying poly(amidoamine)@graphene oxide-reinforced polyvinylidene difluoride thin-film microextraction (PAMAM@GO-PVDF-TFME). The extracted analytes were desorbed via organic solvent and determined using high-performance liquid chromatography-ultraviolet detection (HPLC-UV). The strong interactions between the sorbent and selected analytes (coordination bonds, intermolecular hydrogen bonding, π-π interactions, and hydrophobic effects) made this TFME capable of high extraction performance and capacity. Several factors involved in the PAMAM@GO-PVDF-TFME experiments such as desorption volume, desorption time, sample pH, extraction time, and stirring rate were screened via Plackett-Burman design and then optimized through Box-Behnken design with the purpose of reaching the highest extraction efficiency. The above method showed a good linear range (0.5-500 μg L^-1 and 1-500 μg L^-1) with the coefficient of determination better 0.9944, low limits of determination (0.12 and 0.20 μg L^-1), good enrichment factors (99 and 98), acceptable extraction recoveries (99 and 98%), and good spiking recoveries (90-98%) under the optimized condition at three different spike levels for chlorpyrifos and diazinon, respectively. The results confirmed that the presented method would be promising for the determination of various types of these pesticides in environmental and beverage samples.

Feasibility study on exhaled-breath analysis by untargeted Selected-Ion Flow-Tube Mass Spectrometry in children with cystic fibrosis, asthma, and healthy controls: Comparison of data pretreatment and classification techniques

Selected-Ion Flow-Tube Mass Spectrometry (SIFT-MS) has been applied in a clinical context as diagnostic tool for breath samples using target biomarkers. Exhaled breath sampling is non-invasive and therefore much more patient friendly compared to bronchoscopy, which is the golden standard for evaluating airway inflammation. In the actual pilot study, 55 exhaled breath samples of children with asthma, cystic-fibrosis and healthy individuals were included. Rather than focusing on the analysis of target biomarkers or on the identification of biomarkers, different data analysis strategies, including a variety of pretreatment, classification and discrimination techniques, are evaluated regarding their capacity to distinguish the three classes based on subtle differences in their full scan SIFT-MS spectra. Proper data-analysis strategies are required because these full scan spectra contain much external, i.e. unwanted, variation. Each SIFT-MS analysis generates three spectra resulting from ion-molecule reactions of analyte molecules with H₃O⁺, NO⁺ and O₂⁺. Models were built with Linear Discriminant Analysis, Quadratic Discriminant Analysis, Soft Independent Modelling by Class Analogy, Partial Least Squares - Discriminant Analysis, K-Nearest Neighbours, and Classification and Regression Trees. Perfect models, concerning overall sensitivity and specificity (100% for both) were found using Direct Orthogonal Signal Correction (DOSC) pretreatment. Given the uncertainty related to the classification models associated with DOSC pretreatments (i.e. good classification found also for random classes), other models are built applying other preprocessing approaches. A Partial Least Squares - Discriminant Analysis model with a combined pre-processing method considering single value imputation results in 100% sensitivity and specificity for calibration, but was less good predictive. Pareto scaling prior to Quadratic Discriminant Analysis resulted in 41/55 correctly classified samples for calibration and 34/55 for cross-validation. In future, the uncertainty with DOSC and the applicability of the promising preprocessing methods and models must be further studied applying a larger representative data set with a more extensive number of samples for each class. Nevertheless, this pilot study showed already some potential for the untargeted SIFT-MS application as a rapid pattern-recognition technique, useful in the diagnosis of clinical breath samples.

Evaluation of salivary VOC profile composition directed towards oral cancer and oral lesion assessment

OBJECTIVES

Endogenous substances have been analyzed in biological samples in order to be related with metabolic dysfunctions and diseases. The study aimed to investigate profiles of volatile organic compounds (VOCs) from fresh and incubated saliva donated by healthy controls, individuals with oral tissue lesions and with oral cancer, in order to assess case-specific biomarkers of oxidative stress.

MATERIALS AND METHODS

VOCs were pre-concentrated using headspace-solid phase microextraction and analyzed using gas chromatography-mass spectrometry. Then, VOCs positively modulated by incubation process were subtracted, yielding profiles with selected features. Principal component analysis and hierarchical cluster analysis were used to inspect data distribution, while univariate statistics was applied to indicate potential markers of oral cancer. Machine learning algorithm was implemented, aiming multiclass prediction.

RESULTS

The removal of bacterial contribution to VOC profiles allowed the obtaining of more specific case-related patterns. Artificial neural network model included 9 most relevant compounds (1-octen-3-ol, hexanoic acid, E-2-octenal, heptanoic acid, octanoic acid, E-2-nonenal, nonanoic acid, 2,4-decadienal and 9-undecenoic acid). Model performance was assessed using 10-fold cross validation and receiver operating characteristic curves. Obtained overall accuracy was 90%. Oral cancer cases were predicted with 100% of sensitivity and specificity.

CONCLUSIONS

The selected VOCs were ascribed to lipid oxidation mechanism and presented potential to differentiate oral cancer from other inflammatory conditions.

CLINICAL RELEVANCE

These results highlight the importance of interpretation of saliva composition and the clinical value of salivary VOCs. Elucidated metabolic alterations have the potential to aid the early detection of oral cancer and the monitoring of oral lesions.

Salivary metabolomics for cancer detection

Introduction: Saliva is an ideal biofluid that can be collected in a noninvasive manner, enabling safe and frequent screening of various diseases. Recent studies have revealed that salivary metabolomics analysis has the potential to detect both oral and systemic cancers. Area covered: We reviewed the technical aspects, as well as applications, of salivary metabolomics for cancer detection. The topics include the effects of preconditioning and the method of sample collection, sample storage, processing, measurement, data analysis, and validation of the results. We also examined the rational relationship between salivary biomarkers and tumors distant from the oral cavity. A strategy to establish standard operating protocols for obtaining reproducible quantification data is also discussed Expert opinion: Salivary metabolomics reflects oral and systematic health status, which potently enables cancer detection. The sensitivity and specificity of each marker and their combinations have been well evaluated, but a validation study is required. Further, the standard operating protocol for each procedure should be established to obtain reproducible data before clinical usage.

Analysis of urinary VOCs using mass spectrometric methods to diagnose cancer: A review

The development of non-invasive screening techniques for early cancer detection is one of the greatest scientific challenges of the 21st century. One promising emerging method is the analysis of volatile organic compounds (VOCs). VOCs are low molecular weight substances generated as final products of cellular metabolism and emitted through a variety of biological matrices, such as breath, blood, saliva and urine. Urine stands out for its non-invasive nature, availability in large volumes, and the high concentration of VOCs in the kidneys. This review provides an overview of the available data on urinary VOCs that have been investigated in cancer-focused clinical studies using mass spectrometric (MS) techniques. A literature search was conducted in ScienceDirect, Pubmed and Web of Science, using the keywords "Urinary VOCs", "VOCs biomarkers" and "Volatile cancer biomarkers" in combination with the term "Mass spectrometry". Only studies in English published between January 2011 and May 2020 were selected. The three most evaluated types of cancers in the reviewed studies were lung, breast and prostate, and the most frequently identified urinary VOC biomarkers were hexanal, dimethyl disulfide and phenol; with the latter seeming to be closely related to breast cancer. Additionally, the challenges of analyzing urinary VOCs using MS-based techniques and translation to clinical utility are discussed. The outcome of this review may provide valuable information to future studies regarding cancer urinary VOCs.

Diagnostic and Prognostic Value of Salivary Biochemical Markers in Oral Squamous Cell Carcinoma

The purpose of the work is a comprehensive assessment of biochemical saliva markers for the diagnosis and prognosis of oral cancer. The group of patients included 68 patients with oral squamous cell carcinoma, 50 with non-cancerous diseases of the oral cavity, and 114 healthy volunteers. Before the start of treatment, 23 biochemical parameters of saliva were determined. Participants were monitored for six years to assess survival rates. The statistical analysis was performed by means of Statistica 10.0 and R package. A complex of metabolic changes occurring in saliva in oral cancer is described. It was shown that none of the studied parameters could be used to diagnose oral cancer in an independent variant; the use of combinations of parameters is more informative. The high prognostic value of the content of malondialdehyde (MDA) and the Na/K-ratio in saliva before treatment was established. Thus, the content of MDA ˂ 7.34 nmol/mL and the Na/K-ratio > 1.09 c.u. is a prognostically unfavorable factor (HR = 7.88, 95% CI 1.10-54.62, p = 0.01876), which may be useful for optimizing the treatment of patients with oral cancer. It has been shown that saliva has great potential for the development of diagnostic and prognostic tests for oral cancer.

Metabolic landscape of oral squamous cell carcinoma

BACKGROUND

Head and neck cancers are the seventh most common type of cancer worldwide, with almost half of the cases affecting the oral cavity. Oral squamous cell carcinoma (OSCC) is the most common form of oral cancer, showing poor prognosis and high mortality. OSCC molecular pathogenesis is complex, resulting from a wide range of events that involve the interplay between genetic mutations and altered levels of transcripts, proteins, and metabolites. Metabolomics is a recently developed sub-area of omics sciences focused on the comprehensive analysis of small molecules involved in several biological pathways by high throughput technologies.

AIM OF REVIEW

This review summarizes and evaluates studies focused on the metabolomics analysis of OSCC and oral premalignant disorders to better interpret the complex process of oral carcinogenesis. Additionally, the metabolic biomarkers signatures identified so far are also included. Moreover, we discuss the limitations of these studies and make suggestions for future investigations.

KEY SCIENTIFIC CONCEPTS

Although many questions about the metabolic features of OSCC have already been answered in metabolomic studies, further validation and optimization are still required to translate these findings into clinical applications.

Study of Controlled Atmosphere Flexible Microtube Plasma Soft Ionization Mass Spectrometry for Detection of Volatile Organic Compounds as Potential Biomarkers in Saliva for Cancer

A new soft ionization device for mass spectrometry is presented using the flexible microtube plasma under controlled atmospheric conditions. The controlled atmosphere flexible microtube plasma consists of the plasma source itself connected to a gas chromatograph and a mass spectrometer using a borosilicate glass cross piece. Controlled atmosphere, for example, nitrogen and/or an oxygen mixture, is introduced to the system to create a clean ionization environment. Reproducibility issues are discussed, and solutions are presented manipulating the gas flow in the cross piece. A proof of concept is shown using a ketone mixture introduced to the mass spectrometer to optimize atmospheric conditions. Furthermore, application of the presented device for the sensitive and nonfragmenting ionization of volatile organic biomarkers relevant for cancer is carried out. Sample treatment for human saliva is described, and relevant candidate biomarkers are measured in the saliva matrix, showing a very good ionization efficiency and neglectable matrix effects with limits of detection below 80 ppt.

Unravelling the Potential of Salivary Volatile Metabolites in Oral Diseases. A Review

Fostered by the advances in the instrumental and analytical fields, in recent years the analysis of volatile organic compounds (VOCs) has emerged as a new frontier in medical diagnostics. VOCs analysis is a non-invasive, rapid and inexpensive strategy with promising potential in clinical diagnostic procedures. Since cellular metabolism is altered by diseases, the resulting metabolic effects on VOCs may serve as biomarkers for any given pathophysiologic condition. Human VOCs are released from biomatrices such as saliva, urine, skin emanations and exhaled breath and are derived from many metabolic pathways. In this review, the potential of VOCs present in saliva will be explored as a monitoring tool for several oral diseases, including gingivitis and periodontal disease, dental caries, and oral cancer. Moreover, the analytical state-of-the-art for salivary volatomics, e.g., the most common extraction techniques along with the current challenges and future perspectives will be addressed unequivocally.

Identification of characteristic compounds of moderate volatility in breast cancer cell lines

In this study, we were challenging to identify characteristic compounds in breast cancer cell lines. GC analysis of extracts from the culture media of breast cancer cell lines (MCF-7, SK-BR-3, and YMB-1) using a solid-phase Porapak Q extraction revealed that two compounds of moderate volatility, 1-hexadecanol and 5-(Z)-dodecenoic acid, were detected with markedly higher amount than those in the medium of fibroblast cell line (KMST-6). Furthermore, LC-TOF/MS analysis of the extracts clarified that in addition to the above two fatty acids, the amounts of five unsaturated fatty acids [decenoic acid (C10:1), decadienoic acid (C10:2), 5-(Z)-dodecenoic acid (C12:1), 5-(Z)-tetradecenoic acid (C14:1), and tetradecadienoic acid (C14:2)] in MCF-7 medium were higher than those in medium of KMST-6. Interestingly, H2O2-oxidation of 5-(Z)-dodecenoic acid and 5-(Z)-tetradecenoic acid produced volatile aldehydes that were reported as specific volatiles in breath from various cancer patients, such as heptanal, octanal, nonanal, decanal, 2-(E)-nonenal, and 2-(E)-octenal. Thus, we concluded that these identified compounds over-produced in breast cancer cells in this study could serve as potential precursors producing reported cancer-specific volatiles.

A Literature Review of the Potential Diagnostic Biomarkers of Head and Neck Neoplasms

Head and neck neoplasms have a poor prognosis because of their late diagnosis. Finding a biomarker to detect these tumors in an early phase could improve the prognosis and survival rate. This literature review provides an overview of biomarkers, covering the different -omics fields to diagnose head and neck neoplasms in the early phase. To date, not a single biomarker, nor a panel of biomarkers for the detection of head and neck tumors has been detected with clinical applicability. Limitations for the clinical implementation of the investigated biomarkers are mainly the heterogeneity of the study groups (e.g., small population in which the biomarker was tested, and/or only including high-risk populations) and a low sensitivity and/or specificity of the biomarkers under study. Further research on biomarkers to diagnose head and neck neoplasms in an early stage, is therefore needed.

Identification of salivary volatile organic compounds as potential markers of stomach and colorectal cancer: A pilot study

OBJECTIVES

The purpose of the pilot study was to determine the potential diagnostic capabilities for the analysis of oxygen-containing salivary volatile organic compounds (VOCs) in stomach and colorectal cancer.

METHODS

Saliva samples of 11 patients with stomach cancer, 18 patients with colorectal cancer, and 16 healthy volunteers were analyzed through capillary gas chromatography. The levels of lipid peroxidation products and catalase activity were determined in all samples. To assess saliva diagnostic potential, we constructed a Classification and Regression Tree (CART).

RESULTS

It was shown that the use of a combination of saliva VOCs (acetaldehyde, acetone, propanol-2, and ethanol) allowed classification into Cancer/Control groups with a sensitivity and specificity of 95.7 and 90.9%, respectively. To clarify the location of the tumor, it was necessary to add a methanol level; in this case, the sensitivity for detecting stomach and colorectal cancer was 80.0% and 92.3%, respectively, while the specificity in both cases was 100%. When the lipid peroxidation product content was added to the VOC indicators, they were selected as the main factors for constructing the decision tree. For classification into Cancer/Control groups, only the triene conjugate and Schiff base content in saliva was sufficient. The combination of VOCs in saliva and lipid peroxidation indices improved the sensitivity and specificity for classification to 100%.

CONCLUSION

Preliminary data were obtained on the sensitivity and specificity of the diagnosis of stomach and colorectal cancer, which confirmed the promise of further studies on saliva VOCs for the purpose of clinical laboratory diagnostics.

Modification of an atmospheric pressure photoionization source for online analysis of exhaled breath coupled with quadrupole time-of-flight mass spectrometry

Breath analysis is a promising method for metabolomics studies and clinical diagnosis, as it enables the observation of metabolites in a convenient and noninvasive way. In this work, an atmospheric pressure photoionization (APPI) source was modified for online analysis of exhaled breath by coupling with quadrupole time-of-flight mass spectrometry (QTOFMS). Three parameters, namely, the capillary voltage, the sampling flow and the curtain gas flow of the APPI source, were optimized. Five healthy volunteers, three males and two females, were enrolled to test the performance of modified APPI-QTOFMS by analyzing their exhaled breath. A total of 21 compounds were tentatively identified, and four metabolites, namely, dimethyl selenoxide, δ-valerolactam, hydroxymandelic acid and palmitic amide were detected in the exhaled breath for the first time. The result shows that modified APPI-QTOFMS can be used for the online study of exhaled breath. Graphical abstract.

Development, Optimization and Applications of Thin Film Solid Phase Microextraction (TF-SPME) Devices for Thermal Desorption: A Comprehensive Review

Through the development of solid phase microextraction (SPME) technologies, thin film solid phase microextraction (TF-SPME) has been repeatedly validated as a novel sampling device well suited for various applications. These applications, encompassing a wide range of sampling methods such as onsite, in vivo and routine analysis, benefit greatly from the convenience and sensitivity TF-SPME offers. TF-SPME, having both an increased extraction phase volume and surface area to volume ratio compared to conventional microextraction techniques, allows high extraction rates and enhanced capacity, making it a convenient and ideal sampling tool for ultra-trace level analysis. This review provides a comprehensive discussion on the development of TF-SPME and the applications it has provided thus far. Emphasis is given on its application to thermal desorption, with method development and optimization for this desorption method discussed in detail. Moreover, a detailed outlook on the current progress of TF-SPME development and its future is also discussed with emphasis on its applications to environmental, food and fragrance analysis.

Salivary Metabolomics of Total Body Irradiated Nonhuman Primates Reveals Long-Term Normal Tissue Responses to Radiation

PURPOSE

To identify metabolomic biomarkers of acute radiation exposure in saliva that show time-dependent changes.

METHODS AND MATERIALS

Nonhuman primates were exposed to 4 Gy of total body irradiation with γ-rays. Saliva was collected from 7 animals twice before and at days 1, 3, 5, 7, 15, 21, 28, and 60 after irradiation. Profiling was conducted with liquid chromatography time-of-flight mass spectrometry. Multivariate data analysis and potential biomarker identification was conducted through random Forests and the software MetaboAnalyst. Candidate biomarkers were validated through tandem mass spectrometry, and receiver operating characteristic curves were constructed to show the diagnostic ability of the signature over time.

RESULTS

Untargeted metabolomic analysis revealed significant and persistent effects up to the 60 days evaluated in this study. Biomarkers spanning primarily amino acids and nucleotides were identified, with a significant number showing long-term responses. Fifteen biomarkers showed high statistical significance in the first week after irradiation and 16 at >7 days after irradiation (false discovery rate-adjusted P < .05). The combination of the biomarkers in a single biosignature was able to accurately show the diagnostic ability of the signature in a binary classifier system with receiver operating characteristic curves.

CONCLUSIONS

Radiation can alter the metabolome in saliva, and metabolomics could effectively be used to monitor radiation responses, as a biodosimetry method, in the event of a radiological incident. Saliva metabolomics also has potential relevance in a clinical setting.