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Investigation of sweat VOC profiles in assessment of cancer biomarkers using HS-GC-MS
Abstract
Volatile organic compounds (VOCs) have been studied in biological samples in order to be related to the presence of diseases. Sweat can represent substances existing in blood, has less complex composition (compared with other biological matrices) and can be obtained in a non-invasive way. In this work, sweat patches were collected from healthy controls and volunteers with cancer. Static Headspace was used for VOCs extraction, analysis was performed by gas chromatography coupled to mass spectrometry. Principal Components Analysis was used to investigate data distribution. Random Forest was employed to develop classificatory models. Controls and positive cases could be distinguished with maximum sensitivity and specificity (100% of accuracy) in a model based on the incidence of 2-ethyl-1-hexanol, hexanal and octanal. Discrimination between controls, primary tumors and metastasis was achieved using a panel with 11 VOCs. Balanced accuracy of more than 70% was obtained for the classification of neoplasm site. Total n-aldehydes presented to be strongly correlated with staging of adenocarcinomas, while phenol and 2,6-dimethyl-7-octen-2-ol were correlated with Gleason score. These findings corroborate to the development of accessible screening tools based on VOC analysis and highlight the sweat as a promising matrix to be studied in the clinical context for cancer diagnosis.
... In total, 16 of the 28 compounds are of natural origin, including nonanal, hexanal, acetone, and ethanol. Compounds such as styrene, xylene, toluene, and ethylbenzene are pollutants found in the ambient air or cigarette smoke; these are not produced by the body but are still found in certain types of samples, such as exhaled air [113], cell culture [65,66], sweat patches [162], and urine samples [209]. We found all these compounds in at least three different odor source samples and at least nine of the 18 cancer studies (Fig. 4). ...
... Five compounds were found in at least 15 publications (i.e., 10%): hexanal, toluene, styrene, ethylbenzene and acetone. These compounds are not just found in lung cancer, e.g., hexanal was also detected in breast cancer [198] and colorectal cancer [162]. Forty four studies found that these five compounds may help distinguish between cancer patients and healthy individuals; the differentiating effect in 30 studies is associated with increased concentrations of these compounds in cancer patients while 11 studies found decreased concentrations. ...
... Among the list of 25 compounds, sixteen were found in gastric cancer but only in two or three publications. Only phenol common to colorectal cancer which increases in cancer patients was found in four publications studying exhaled air [48,216,217] and sweat patches [162]. Two studies [187,216] found increased levels of p-cresol in the exhaled breath of gastric cancer patients. ...
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 2019 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.
... The rest of the study is arranged in the following order: Section 1 describes the background of the research, Section 2 explains the proposed method. Section 3 presents the results 3 of experiments and discussions. Finally, Section 4 contains conclusions from the experiment. ...
... Afterward, the signal in the form of frequency was smoothened by using Equation 3 and returned in the time domain using IFFT using Equation 4. ...
Several methods have been used to detect infectious respiratory diseases, for example, by taking samples from blood, saliva, and phlegm. Although these methods generated high accuracy, they raised more problems that increased the risk of spreading and required more time to detect. Therefore, an accurate, quick, and low-cost device is required to help detect infectious respiratory diseases. This study proposes a new approach for detecting infectious respiratory diseases using an electronic nose (E-nose) through sweat samples from the human axilla. E-nose became safer by taking samples through the axillary because infectious respiratory diseases are not transmitted through sweat. This study proposes two new feature extraction techniques called stable value and highest slope. This study also proposes a stacked Deep Neural Network (DNN) for effective infectious respiratory disease detection. In the proposed stacked DNN, five fine-tuned DNN models obtained from hyperparameter tuning are stacked then the output of each DNN model became the input of the meta-model in the form of a fully connected layer. The proposed feature extraction method outperformed the existing feature extraction and was able to separate data between classes better. Furthermore, the proposed stacked DNN model generated an accuracy of 0.934 in the testing data, outperforming DNN single models and other state-of-the-art machine learning algorithms.
... Recently, two review papers have addressed "skin metabolomic" (Elpa et al., 2021) and "volatilome" (Opitz and Herbarth, 2018), to encompass the possibilities of using sweat as a source of biomarkers for cancer diagnosis. Examples include Nonanedioic or azelaic acid for lung cancer (Calderón-Santiago et al., 2015); n-aldehydes and 2-ethyl-1-hexanol ubiquitous in sweat of cancer patients and absent among healthy individuals (Monedeiro et al., 2020b). Table 4 provides examples of biomarkers within sweat and the associated cancer types. ...
... Most standard investigations on sweat are based on mass spectrometry and gas chromatography, and sample manipulation and preparation follows the protocols related to that method including thermal based extraction, centrifugations and addition of buffers (Jiang et al., 2019;Monedeiro et al., 2020b). ...
Liquid biopsy technologies have seen a significant improvement in the last decade, offering the possibility of reliable analysis and diagnosis from several biological fluids. The use of these technologies can overcome the limits of standard clinical methods, related to invasiveness and poor patient compliance. Along with this there are now mature examples of lab-on-chips (LOC) which are available and could be an emerging and breakthrough technology for the present and near-future clinical demands that provide sample treatment, reagent addition and analysis in a sample-in/answer-out approach. The possibility of combining non-invasive liquid biopsy and LOC technologies could greatly assist in the current need for minimizing exposure and transmission risks. The recent and ongoing pandemic outbreak of SARS-CoV-2, indeed, has heavily influenced all aspects of life worldwide. Ordinary tasks have been forced to switch from “in presence” to “distanced”, limiting the possibilities for a large number of activities in all fields of life outside of the home. Unfortunately, one of the settings in which physical distancing has assumed noteworthy consequences is the screening, diagnosis and follow-up of diseases.
In this review, we analyse biological fluids that are easily collected without the intervention of specialized personnel and the possibility that they may be used -or not-for innovative diagnostic assays. We consider their advantages and limitations, mainly due to stability and storage and their integration into Point-of-Care diagnostics, demonstrating that technologies in some cases are mature enough to meet current clinical needs.
... However, there are two major obstacles to identification and early treatment: first, there is a general paucity of easily identifiable signs and symptoms in the early stages of cancer, and even when there are signs, diagnosis frequently requires many expensive, invasive and time demanding procedures [3][4][5]. For these reasons, there is a global need for the research and development of low cost, rapid and non-invasive methodologies for early diagnosis, to reduce the time spent in different stages of health care systems and improve the chances of recovery [6,7]. ...
... Metabolomics is an emerging field that has significant untapped potential for biomarker discovery and translation to cancer screening and early diagnosis [8,9]. A recent and promising metabolomic approach is ''volatilomics", the study of volatile organic compounds (VOCs) produced in human body and emitted through breath, blood, urine, saliva, sweat, feces and other biological matrices [6,[10][11][12]. VOCs are low molecular weight substances that are generated as final products of cellular metabolism, exhibiting a high-vapor pressure and low boiling point (below 250°C) [11]. ...
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.
... 37,38 Finally, we identified two methyl ketones, i.e., 8-hydroxy-2-octanone and 4-methyl-2-heptanone, which could be produced by enzymatic degradation of branched fatty acids. 39 A549 cells in co-culture with inflammatory sputum supernatant were used for the first time as in vitro model to extend our understanding of biological inflammatory mechanisms beyond the chemical oxidative reactions. The pool of inflam-matory sputum supernatants collected from atopic asthmatic patients, contained high absolute sputum eosinophils and neutrophils counts. ...
... 38 These fatty acids can be further reduced in alcohols such as 1-nonanol by the fatty-acid reductase or transformed in methyl ketone such as 2-heptanone by an enzymatic reaction. 38,39 In addition, nonanal has been recently identified as exhaled breath biomarkers of neutrophilic asthma. 6 The amino acid metabolism could also increase the production of carbonyl compounds, such as cyclohexanone. ...
Exhaled breath analysis has a high potential for early non-invasive diagnosis of lung inflammatory diseases, such as asthma. The characterization and understanding of the inflammatory metabolic pathways involved into volatile organic compounds (VOCs) production could bring exhaled breath analysis into clinical practice and thus open new therapeutic routes for inflammatory diseases. In this study, lung inflammation was simulated in-vitro using A549 epithelial cells. We compared the VOC production from A549 epithelial cells after a chemically induced oxidative stress in-vitro, exposing the cells to H2O2, and a biological stress, exposing the cells to an inflammatory pool of sputum supernatants. Special attention was devoted to define proper negative and positive controls (8 different types) for our in-vitro models, including healthy sputum co-culture. Sputum from 25 asthmatic and 8 healthy patients were collected to create each pool of supernatants. Each sample type was analyzed in 4 replicates using solid-phase microextraction (SPME) comprehensive two-dimensional gas chromatography hyphenated to time-of-flight mass spectrometry (GC×GC-TOFMS). This approach offers high resolving power for complex VOC mixtures. According to the type of inflammation induced, significantly different VOCs were produced by the epithelial cells compared to all controls. For both chemical and biological challenges, an increase of carbonyl compounds (54 %) and hydrocarbons (31 %) was observed. Interestingly, only the biological inflammation model showed a significant cell proliferation together with an increased VOC production linked to asthma airway inflammation. This study presents a complete GC×GC-TOFMS workflow for in-vitro VOC analysis, and its potential to characterize complex lung inflammatory mechanisms.
... The development of new non-invasive and comfortable methods to diagnose various diseases is an urgent task in modern medicine. Exhaled breath [1], exhaled breath condensate [2], saliva [1,3], skin [1,4,5], and urine [1,6] are intensively studied to develop new diagnostic approaches. Exhaled breath is especially interesting for diagnostic purposes since it can be obtained without any discomfort for patients [7]. ...
Non-invasive, simple, and fast tests for lung cancer diagnostics are one of the urgent needs for clinical practice. The work describes the results of exhaled breath analysis of 112 lung cancer patients and 120 healthy individuals using gas chromatography-mass spectrometry (GC-MS). Volatile organic compound (VOC) peak areas and their ratios were considered for data analysis. VOC profiles of patients with various histological types, tumor localization, TNM stage, and treatment status were considered. The effect of non-pulmonary comorbidities (chronic heart failure, hypertension, anemia, acute cerebrovascular accident, obesity, diabetes) on exhaled breath composition of lung cancer patients was studied for the first time. Significant correlations between some VOC peak areas and their ratios and these factors were found. Diagnostic models were created using gradient boosted decision trees (GBDT) and artificial neural network (ANN). The performance of developed models was compared. ANN model was the most accurate: 82–88% sensitivity and 80–86% specificity on the test data.
... 1−3 Relevant studies have shown that human exhaled gases contain thousands of volatile organic compounds (VOCs), 4 among which endogenous VOCs can reflect human health status and be used for clinical diagnosis and health monitoring. 5,6 For example, the concentration changes of ethane and other alkanes are related to lipid peroxidation. 7 NO and CO can diagnose the presence of lung cancer. ...
Endogenous volatile organic compounds (VOCs) can reflect human health status and be used for clinical diagnosis and health monitoring. Dimethylamine and ammonia are the signature VOC gases of nephropathy. In order to find a potential gas sensitivity material for the detection of both signature VOC gases of nephropathy, this paper investigated the adsorption properties of dimethylamine and ammonia on Al- and Ga-doped BN monolayers based on density functional theory. Through analyzing the adsorption energy, adsorption distance, charge transfer, density of states, and HOMO/LUMO, the results indicated that the adsorption effect of Al- and Ga-doped BN monolayers to dimethylamine and ammonia is probably good, and these nanomaterials have the potential to be applied for nephropathy monitoring and clinical diagnosis.
... In 2015, Calderon-Santiago et al reported a study exploiting the sweat metabolome for lung cancer screening 20 . Monedeiro et al recently published a study in which, for the rst time, sweat patches were collected from healthy and diseased patients affected by different types of cancer including lung, prostate, gastric, kidney, head and neck, pancreas and colorectal cancer and lymphoma 21 . Using headspace GC-MS to analyse VOCs from these non-invasive specimen patient classi cation was obtained with a 100% predictive power. ...
Breast cancer is a global health issue affecting 2.3 million women per year, causing death in over 600,000. Mammography (and biopsy) is the gold standard for screening and diagnosis. Whilst effective, this test exposes individuals to radiation, has limitations to its sensitivity and specificity and may cause moderate to severe discomfort. Some women may also find this test culturally unacceptable. This proof-of-concept study, combining bottom-up proteomics with Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS) detection, explores the potential for a non-invasive technique for the early detection of breast cancer from fingertip smears. A cohort of 15 women with either benign breast disease (n = 5), early breast cancer (n = 5) or metastatic breast cancer (n = 5) were recruited from a single UK breast unit. Fingertips smears were taken from each patient and from each of the ten digits, either at the time of diagnosis or, for metastatic patients, during active treatment. A number of statistical analyses and machine learning approaches were investigated and applied to the resulting mass spectral dataset. The highest performing predictive method, a 3-class Multilayer Perceptron (MLP) neural network, yielded an accuracy score of 97.8% when categorising unseen MALDI MS spectra as either the benign, early or metastatic cancer classes. These findings support the need for further research into the use of sweat deposits (in the form of fingertip smears or fingerprints) for non-invasive screening of breast cancer.
... 5−8 GC is more prevalent in men compared to women and causes 760,000 deaths annually. 9,10 In the mid-1980s, volatile organic compounds (VOCs) emitted by various parts of the human body (including blood, 11 exhaled air, 12 saliva, 13 urine, 14 sweat, 15 and tissue samples 16 ) had become an interesting topic in cancer detection as potential biomarkers. 17 It is generally believed that these VOCs are the result of the excessive oxidative reactions that occur in cancer cells. ...
... Moreover, for breath analysis various sensors able to perform the analyses in real time, without any pre-concentration or storage, were created in the attempt to diagnose respiratory diseases [6][7][8] and even a standardized breath sampler was developed 1 . Except breath samples, other matrices, such as urine [9][10][11] , sweat 12 , human tissues 13 , saliva 14 , breast milk 15 , exudates 16 , or bacteria [17][18][19][20][21] were investigated in research articles and discussed in reviews 19,[22][23][24] in order to discover valuable biomarkers of certain diseases. In case of feces samples, literature in the field is related mostly to identification of those VOCs markers of colorectal-cancer [25][26][27][28] , but nevertheless considerably less progress has been made with feces compared with investigating other biological matrices, especially breath and urine. ...
VOCs (volatile organic compounds) are increasingly wished to be used in diagnosis of diseases. They present strategic advantages, when compared to classical methods used, such as simplicity and current availability of performant non-invasive sample collection methods/systems. However, standardized sampling methods are required in order to achieve reproducible results. In the current study we developed a method to be used for feces sampling using a Micro-Chamber/Thermal Extractor (µ-CTE). Design Expert software (with Box–Behnken design) was used to predict the solutions. Therefore, by using the simulation experimental plan that was further experimentally verified, extraction time of 19.6 min, at extraction temperature of 30.6 °C by using a flow rate of 48.7 mL/min provided the higher response. The developed method was validated by using correlation tests and Network analysis, which both proved the validity of the developed model.
... In addition to other compounds, there are also volatile organic compounds in sweat. Volatile organic compounds (VOCs) of sweat could be used as biomarkers for chemo signal [2,3]. Moreover, VOCs released by the cow during estrus have been proposed to have pheromonal properties. ...
The accurate estrus detection is essential for successful reproduction. Many scientists reported the importance of pheromonesfor accurate detection of estrus. In addition, the choice of the appropriate device and the appropriate extraction solvent is importantfor obtaining quickly and more estrus-specific pheromones. In this study, sweat samples were collected in heat cows and volatileorganic compounds (VOCs) in the gas chromatography mass spectrometry were evaluated using three different solvents (diethyl ether,dichloromethane, and hexane) for extraction. VOCs with different numbers and different ratios were identified in all three extractionsolvents. As the solvent, 9 compounds were detected in diethyl ether, 8 compounds in dichloromethane, and 12 compounds in hexane.Volatile odor compounds common to all three extraction solvents were L-Proline, 1-[O-(1-oxohexyl)–N-[N-[N6-(1-oxohexyl)-N2-[N-(1-oxohexyl)–L-valyl]–L-lysyl]–L-valyl]–L-tyrosyl]-, methyl ester/Tetradecane; 1,2-Benzenedicarboxylic acid, bis (2-methylpropyl)ester; Phenol, 2,2’–methylenebis [6-(1,1-dimethylethyl)–4–methyl-; Palmitin,1,2–di-. According to the results of the analysis, the mostvolatile compounds were detected when using hexane as the extraction solvent
... For analyzing volatile organic compounds (VOCs) present in sweat, gas chromatography coupled to mass spectrometry (GC-MS) is the standard analytical approach employed in this case [42]. It has been applied to analyze the sweat volatile organic compounds for the assessment of cancer biomarkers [43] and also to distinguish sex differences of the human sweat volatilome [44]. Interestingly, highresolution GC-MS using time of flight detector (TOF) has been also employed to analyze the sweat nonvolatile metabolome identifying 66 compounds predominated by carboxylic acids, amino acids and sugars after suitable sample pretreatment and derivatization steps for analysis of the non-volatile chemicals [45]. ...
Metabolome and proteome profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, omics analyses of sweat, one of the most readily available human biofluids, have lagged behind. This review capitalizes on the current knowledge and state of the art analytical advances of sweat metabolomics and proteomics. Moreover, current applications of sweat omics such as the discovery of disease biomarkers and monitoring athletic performance are also presented in this review. Another area of emerging knowledge that has been highlighted herein lies in the role of skin host-microbiome interactions in shaping the sweat metabolite-protein profiles. Discussion of future research directions describes the need to have a better grasp of sweat chemicals and to better understand how they function as aided by advances in omics tools. Overall, the role of sweat as an information-rich biofluid that could complement the exploration of the skin metabolome/proteome is emphasized.
... Sweat is a human bodily secretion dependent on various physiological conditions, and analyzing it may help diagnose lifethreatening diseases, such as cystic fibrosis, diabetes, and cancer, using multiple biomarkers. [63][64][65] Recently, Song et al. developed a TENG-based wireless sweat sensor that does not use any external power source to work beside human motion. 66 A freestanding-mode TENG (FTENG)-powered wearable sweat sensor system (FWS 3 ) is composed of various purpose-oriented segments, such as a sweat sensor patch and a flexible FTENG sensor connected with circuitry [see Fig. 5(b1)]. ...
In the current era of busy and eventful daily routines, the need for self-driven, robust, and low maintenance healthcare systems emerges significantly more than in earlier times. The nanogenerator (NG) technology provides a new pathway by utilizing nanostructured and eco-friendly materials toward biomedical systems by harvesting biomechanical energy. Triboelectric NGs (TENGs) have been well-developed to cater all these matters, giving self-powered, sustainable, environment-friendly, and low footprint devices. TENG comes up with great potential, therefore, we have summarized various dimensions of its applications in healthcare management, including prevention, detection, diagnosis, and treatment. We have reviewed different aspects of TENG healthcare systems that provide wearable, minimally invasive, and simple solutions while harvesting human motion as the power source. Here, recent advancements of triboelectric devices are compiled while discussing their significance, structure, capabilities, performance, and future potential. Meanwhile, the impact of TENG on protecting and treating various internal and external human organs, such as the heart, neural tissues, skin, and hair, has been described in detail. Moreover, TENG-based solutions have also included minimizing the effects of contemporary and lingering challenges such as air pollution and viral infectious diseases on human health. In the very end, we have concluded with the opportunities and possible solutions for anticipated challenges.
... Recently, a study identified a unique profile of VOCs in sweat samples for the diagnosis and staging of adenocarcinomas. In fact, it is suggested that sweat can represent substances in the blood, but owes an advantage of being less complex in chemistry than the blood 33 . The results in the present study also suggest the presence of a unique profile of VOCs in sweat samples of COVID-19 patients being detected by K9 dogs. ...
In January 2020, the coronavirus disease was declared, by the World Health Organization as a global public health emergency. Recommendations from the WHO COVID Emergency Committee continue to support strengthening COVID surveillance systems, including timely access to effective diagnostics. Questions were raised about the validity of considering the RT-PCR as the gold standard in COVID-19 diagnosis. It has been suggested that a variety of methods should be used to evaluate advocated tests. Dogs had been successfully trained and employed to detect diseases in humans. Here we show that upon training explosives detection dogs on sniffing COVID-19 odor in patients’ sweat, those dogs were able to successfully screen out 3249 individuals who tested negative for the SARS-CoV-2, from a cohort of 3290 individuals. Additionally, using Bayesian analysis, the sensitivity of the K9 test was found to be superior to the RT-PCR test performed on nasal swabs from a cohort of 3134 persons. Given its high sensitivity, short turn-around-time, low cost, less invasiveness, and ease of application, the detection dogs test lends itself as a better alternative to the RT-PCR in screening for SARS-CoV-2 in asymptomatic individuals.
... It is characterized by a wide range of stable chemical molecules with distinguishable properties including low molecular weight, low boiling point, and high vapor pressure in natural conditions 16,17 . VOCs have been studied in various biological matrices such as breath, blood, urine, tissue, etc. as a product of metabolic alterations in the organism, and these indicate the presence of certain diseases including cancer 18 . VOC analysis is also used as a diagnostic tool for finding and monitoring infectious diseases [19][20][21] . ...
Oral cancer (OC) is the sixth most common global malignancy and blazing dilemma all over India. Tobacco and alcohol consumption are the well-established risk factors for the onset of oral cancer. Gujarat is considered to be the high-risk region for oral cancer as it is the tobacco growing belt. Volatile organic compounds (VOCs) have shown a strong correlation with clinicopathological characteristics (CPC) of OC patients. The present study aims to investigate VOCs as potential biomarkers for developing OSCC. Metabolomic profile of 20 OSCC patients (n=20), 10 Healthy individuals (n=10) and 9 Tobacco consumers (n=9) were analysed using Gas chromatography-Mass spectrometry. Principle component analysis (PCA) and partial least squares structure-discriminant analysis (PLS-DA) model has been assembled to compare the metabolomic profile of each group, where highly expressed metabolites were identified for different groups. We observed ten VOCs from oral cancer patients, where propionic acid is found as potential biomarkers end up with vitamin K and propionate metabolism. One way ANOVA was performed to compare the mean difference between each group and the level of nine metabolites differed significantly in controls vs. oral cancer patients. The present study contributes to the design protocol for metabolomics-based biomarker discovery. The future research requires a more polishing touch to develop new vistas for the better prognosis of cancer patients.
Keywords: Metabolomics, GC-MS, OSCC, Biomarker, India, Tobacco
... For offline measurements, GC-MS is the most powerful tool, with a high sensitivity (sometimes lower than ppb range) and, more importantly, a high potential for both identification and quantification of unknown components from complex biological matrixes [4,[8][9][10]88,89]. Moreover, by using different columns and detectors a great versatility in targeted analyses can be achieved [90,91]. ...
Lung cancer, chronic obstructive pulmonary disease (COPD) and asthma are inflammatory diseases that have risen worldwide, posing a major public health issue, encompassing not only physical and psychological morbidity and mortality, but also incurring significant societal costs. The leading cause of death worldwide by cancer is that of the lung, which, in large part, is a result of the disease often not being detected until a late stage. Although COPD and asthma are conditions with considerably lower mortality, they are extremely distressful to people and involve high healthcare overheads. Moreover, for these diseases, diagnostic methods are not only costly but are also invasive, thereby adding to people’s stress. It has been appreciated for many decades that the analysis of trace volatile organic compounds (VOCs) in exhaled breath could potentially provide cheaper, rapid, and non-invasive screening procedures to diagnose and monitor the above diseases of the lung. However, after decades of research associated with breath biomarker discovery, no breath VOC tests are clinically available. Reasons for this include the little consensus as to which breath volatiles (or pattern of volatiles) can be used to discriminate people with lung diseases, and our limited understanding of the biological origin of the identified VOCs. Lung disease diagnosis using breath VOCs is challenging. Nevertheless, the numerous studies of breath volatiles and lung disease provide guidance as to what volatiles need further investigation for use in differential diagnosis, highlight the urgent need for non-invasive clinical breath tests, illustrate the way forward for future studies, and provide significant guidance to achieve the goal of developing non-invasive diagnostic tests for lung disease. This review provides an overview of these issues from evaluating key studies that have been undertaken in the years 2010–2019, in order to present objective and comprehensive updated information that presents the progress that has been made in this field. The potential of this approach is highlighted, while strengths, weaknesses, opportunities, and threats are discussed. This review will be of interest to chemists, biologists, medical doctors and researchers involved in the development of analytical instruments for breath diagnosis.
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.
Breast cancer is a global health issue affecting 2.3 million women per year, causing death in over 600,000. Mammography (and biopsy) is the gold standard for screening and diagnosis. Whilst effective, this test exposes individuals to radiation, has limitations to its sensitivity and specificity and may cause moderate to severe discomfort. Some women may also find this test culturally unacceptable. This proof-of-concept study, combining bottom-up proteomics with Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS) detection, explores the potential for a non-invasive technique for the early detection of breast cancer from fingertip smears. A cohort of 15 women with either benign breast disease (n = 5), early breast cancer (n = 5) or metastatic breast cancer (n = 5) were recruited from a single UK breast unit. Fingertips smears were taken from each patient and from each of the ten digits, either at the time of diagnosis or, for metastatic patients, during active treatment. A number of statistical analyses and machine learning approaches were investigated and applied to the resulting mass spectral dataset. The highest performing predictive method, a 3-class Multilayer Perceptron neural network, yielded an accuracy score of 97.8% when categorising unseen MALDI MS spectra as either the benign, early or metastatic cancer classes. These findings support the need for further research into the use of sweat deposits (in the form of fingertip smears or fingerprints) for non-invasive screening of breast cancer.
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 (OPLS-DA) 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.
The International League Against Epilepsy/American Epilepsy Society (ILAE/AES) Joint Translational Task Force established the TASK3 working groups to create common data elements (CDEs) for various preclinical epilepsy research disciplines. This is the second in a two-part series of omics papers, with the other including genomics, transcriptomics and epigenomics. The aim of the CDEs is to improve the standardization of experimental designs across a range of epilepsy research related methods. We have generated CDE tables with key parameters and case report forms (CRFs) containing the essential contents of the study protocols for proteomics, lipidomics and metabolomics of samples from rodent models and people with epilepsy. We discuss the important elements that need to be considered for the proteomics, lipidomics and metabolomics methodologies, providing a rationale for the parameters that should be documented.
The analysis of volatile organic compounds (VOCs) can provide important clinical information (entirely non-invasively); however, the exact extent to which VOCs from human skin can be signatures of health and disease is unknown. This systematic review summarises the published literature concerning the methodology, application, and volatile profiles of skin VOC studies. An online literature search was conducted in accordance with the preferred reporting items for systematic reviews and meta-analysis, to identify human skin VOC studies using untargeted mass spectrometry (MS) methods. The principal outcome was chemically verified VOCs detected from the skin. Each VOC was cross-referenced using the CAS number against the Human Metabolome and KEGG databases to evaluate biological origins. A total of 29 studies identified 822 skin VOCs from 935 participants. Skin VOCs were commonly sampled from the hand (n = 9) or forearm (n = 7) using an absorbent patch (n = 15) with analysis by gas chromatography MS (n = 23). Twenty-two studies profiled the skin VOCs of healthy subjects, demonstrating a volatolome consisting of aldehydes (18%), carboxylic acids (12%), alkanes (12%), fatty alcohols (9%), ketones (7%), benzenes and derivatives (6%), alkenes (2%), and menthane monoterpenoids (2%). Of the VOCs identified, 13% had putative endogenous origins, 46% had tentative exogenous origins, and 40% were metabolites from mixed metabolic pathways. This review has comprehensively profiled the human skin volatolome, demonstrating the presence of a distinct VOC signature of healthy skin, which can be used as a reference for future researchers seeking to unlock the clinical potential of skin volatolomics. As significant proportions of identified VOCs have putative exogenous origins, strategies to minimise their presence through methodological refinements and identifying confounding compounds are discussed.
The pandemic showed how early screening and precise monitoring of the individual state of health is a must to avoid serious outbreaks, with all the consequences for the public health and the international society itself. Observing also parallel application external to viral or bacterial agents, pre-screening for neoplasms has proven time and time again to lesser the costs of treatment, with higher chances of survival for the patients involved. Nonetheless, the development of reliable, fast responding medical devices is not always easily carried out, given the various nature of the diseases and markers observed. Nanostructured chemoresistive sensors have proven time and time again their capability to detect small quantities (up to part per billions) of the most various and exotic mixtures of volatile organic compounds, for the widest variety of applications, and in particular in medical-screening fields, for both mundane and oncological pathologies, since the last two decades. In this work, a review on the topic, researching on multiple pathologies and microorganism (and their correlated markers) was conducted. The experimental results on the various volatile organic compounds of medical interest were analyzed, given from foreign works and the sensors developed from the team, targeting both pure biomarkers from gas tubes and various emanations from biological samples of human origins, like blood and tissue from surgeries. It was finally observed how different chemoresistive sensors have the capacity to proper distinguish healthy and diseased/tumor affected patients, even with concentration of the markers resembling early stages of the pathologies.
Flow cytometers are well-established tools with fundamental importance in biology and medicine to examine and identify cell populations, density, size distributions, compositions, and disease diagnosis and monitoring. Still, these devices are expensive with a low level of integration for sample preparation. Miniaturized microfluidic cytometers, i.e., microcytometers, for monitoring cells in a wide range of biological samples are currently being developed, providing more affordable and integrated solutions. Several detection methods have been developed and applied in microcytometers such as electrical, optical, and magnetic sensing techniques, which are integrated with microfluidic technology. Magnetic microcytometers present several advantages when compared to optical systems such as the fact that these devices provide more stable labeling by using magnetic nanoparticles (MNPs) or beads (MBs) instead of fluorophores. In this chapter, we explore the evolution of the automation of whole cell detection and enumeration that led to the development of microcytometers and particularly examine the anatomy of magnetic microcytometers applied to cancer research. We then give an overview of the challenges of Circulating Tumor Cells enrichment and enumeration, and the progress of magnetic microcytometers in this field.
Microfluidics and biosensors have already demonstrated their potential in cancer research. Typical applications of microfluidic devices include the realistic modeling of the tumor microenvironment for mechanistic investigations or the real-time monitoring/screening of drug efficacy. Similarly, point-of-care biosensing platforms are instrumental for the early detection of predictive biomarkers and their accurate quantification. The combination of both technologies offers unprecedented advantages for the management of the disease, with an enormous potential to contribute to improving patient prognosis. Despite their high performance, these methodologies are still encountering obstacles for being adopted by the healthcare market, such as a lack of standardization, reproducibility, or high technical complexity. Therefore, the cancer research community is demanding better tools capable of boosting the efficiency of cancer diagnosis and therapy. During the last years, innovative microfluidic and biosensing technologies, both individually and combined, have emerged to improve cancer theranostics. In this chapter, we discuss how these emerging—and in some cases unconventional—microfluidics and biosensor technologies, tools, and concepts can enhance the predictive power of point-of-care devices and the development of more efficient cancer therapies.
Introduction
An early diagnosis is crucial in reducing mortality among people who have breast cancer (BC). There is a shortfall of characteristic early clinical symptoms in BC patients, highlighting the importance of investigating new methods for its early detection. A promising novel approach is the analysis of volatile organic compounds (VOCs) produced and emitted through the metabolism of cancer cells.
Methods
The purpose of this systematic review is to outline the published research regarding BC-associated VOCs. For this, headspace analysis of VOCs was explored in patient-derived body fluids, animal model-derived fluids, and BC cell lines to identify BC-specific VOCs. A systematic search in PubMed and Web of Science databases was conducted according to the PRISMA guidelines.
Results
Thirty-two studies met the criteria for inclusion in this review. Results highlight that VOC analysis can be promising as a potential novel screening tool. However, results of in vivo, in vitro and case-control studies have delivered inconsistent results leading to a lack of inter-matrix consensus between different VOC sampling methods.
Discussion
Discrepant VOC results among BC studies have been obtained, highly due to methodological discrepancies. Therefore, methodological issues leading to disparities have been reviewed and recommendations have been made on the standardisation of VOC collection and analysis methods for BC screening, thereby improving future VOC clinical validation studies.
Improving life expectancy necessitates prevention and early diagnosis of any disease state based on active self-monitoring of symptoms and longitudinal biochemical profiling. Non-invasive and continuous measurement of molecular biomarkers that reflect metabolism and health must however be established to realize this plan. Human samples non-invasively obtained via the skin are suitable in this context for in-situ biochemical monitoring. We present a brief classification of transdermal sampling in aqueous and gaseous phases and then introduce a new generation of transdermal monitoring devices for rapid and accurate assessment of important parameters. Finally, we have summarized the diversity of body-wide skin characteristics that have possible effects for transdermal sampling. Because of its passive nature, in-situ biochemical monitoring via transdermal sampling will potentially lead to a greater understanding of important biochemical markers and their temporal variation.
VOCs (volatile organic compounds) are increasingly wished to be used in diagnosis of diseases. They present strategic advantages, beside classical methods used, such as simplicity and non-invasively of performant sample collection methods/ systems available our days. However, standardized sampling methods are required in order to achieve reproducible results. In the current study we developed a method to be used for feces sampling using a Micro-Chamber/Thermal Extractor (µ-CTE). Design Expert software (with Box–Behnken design) was used to predict the solutions. Therefore by using the simulation experimental plan that was further experimentally verified, a sampling time of 19.6 min, at a sampling temperature of 30.6 °C by using a flow rate of 48.7 mL/min provided the higher response. The developed method was validated by using correlation tests and Network analysis, that both proved the validity of the developed model.
Volatile organic compounds (VOCs) have been assessed in breath samples as possible indicators of diseases. The present study aimed to quantify 29 VOCs (previously reported as potential biomarkers of lung diseases) in breath samples collected from controls and individuals with lung cancer , chronic obstructive pulmonary disease and asthma. Besides that, global VOC profiles were investigated. A needle trap device (NTD) was used as pre-concentration technique, associated to gas chromatography mass spectrometry (GC-MS) analysis. Univariate and multivariate approaches were applied to assess VOC distributions according to the studied diseases. Limits of quantitation ranged from 0.003 to 6.21 ppbv and calculated relative standard deviations did not exceed 10%. At least 15 of the quantified targets presented themselves as discriminating features. A random forest (RF) method was performed in order to classify enrolled conditions according to VOCs' latent patterns, considering VOCs responses in global profiles. The developed model was based on 12 discriminating features and provided overall balanced accuracy of 85.7%. Ultimately, multinomial logistic regression (MLR) analysis was conducted using the concentration of the nine most discriminative targets (2-propanol, 3-methylpentane, (E)-ocimene, limonene, m-cymene, benzonitrile, undecane, terpineol, phenol) as input and provided an average overall accuracy of 95.5% for multiclass prediction.
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.
Malignant mesothelioma (MM) is an incurable cancer. MM is often misdiagnosed, with a poor 5-year survival and limited treatment options. The discovery of endogenous volatile organic compounds (VOCs) is required in order to accelerate the development of a breath test as an alternative to conventional MM diagnosis. For the first time, this study used solid-phase microextraction (SPME) and gas chromatography-mass spectrometry (GC-MS) to identify VOCs released directly from the biphasic MM cell line MSTO-211H and the epithelioid MM cell line NCI-H28 as well as the non-malignant mesothelial cell line MET-5A. Multivariate statistical analysis showed separation between MSTO-211H, NCI-H28 and MET-5A results. 2-ethyl-1-hexanol was significantly increased in both MSTO-211H and NCI-H28 cells compared to MET-5A controls. In addition, ethyl propionate and cyclohexanol were significantly increased in MSTO-211H cells and dodecane was significantly increased in NCI-H28 cells. This is the first study reporting headspace analysis of these MM cell lines and the first to consider the effects of mesothelioma sub-type on VOC profile. Current results further highlight the potential for a diagnostic mesothelioma breath test as well as providing proof of concept for the differentiation between biphasic and epithelioid mesothelioma based on VOC profiles.
Lipid oxidation is the major chemical reaction limiting the shelf-life of foods, and it also contributes to a wide range of pathologies, including aging and cancer. This chapter provides an interesting new perspective on broad aspects of lipid oxidation. It first reviews details of lipid oxidation reactions and mechanisms in the context of traditional free radical chain reactions and also in terms of multiple reaction pathways in which internal cyclization to epidioxides and epoxides, addition to double bonds, disproportionation, and scissions compete with hydrogen abstractions by lipid peroxyl and alkoxyl radicals. Subsequent sections cover chemical, physical, and environmental factors that influence the rates and course of lipid oxidation; consequences of lipid oxidation (production of off-flavors and odors, degradation of membranes and tissues, co-oxidation of proteins and other molecules by lipid radicals, hydroperoxides, epoxides, and carbonyl products), and inhibition of lipid oxidation by antioxidants and environmental control.