Exhaled breath analysis: novel approach for early detection of lung cancer

High diagnostic value of miRNAs for NSCLC: quantitative analysis for both single and combined miRNAs in lung cancer

BACKGROUND

MicroRNAs (miRNAs) are good candidates as biomarkers for Lung cancer (LC). The aim of this article is to figure out the diagnostic value of both single and combined miRNAs in LC.

METHODS

Normative meta-analysis was conducted based on PRISMA. We assessed the diagnostic value by calculating the combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR) and the area under the curve (AUC) of single and combined miRNAs for LC and specific subgroups.

RESULTS

A total of 80 qualified studies with a total of 8971 patients and 10758 controls were included. In non-small cell lung carcinoma (NSCLC), we involved 20 single-miRNAs and found their Sen, Spe and AUC ranged from 0.52-0.81, 0.66-0.88, and 0.68-0.90, respectively, specially, miR-19 with the maximum Sen, miR-20 and miR-10 with the highest Spe as well as miR-17 with the maximum AUC. Additionally, we detected miR-21 with the maximum Sen of 0.74 [95%CI: 0.62-0.83], miR-146 with the maximum Spe and AUC of 0.93 [95%CI: 0.79-0.98] and 0.89 [95%CI: 0.86-0.92] for early-stage NSCLC. We also identified the diagnostic power of available panel (miR-210, miR-31 and miR-21) for NSCLC with satisfying Sen, Spe and AUC of 0.82 [95%CI: 0.78-0.84], 0.87 [95%CI: 0.84-0.89] and 0.91 [95%CI: 0.88-0.93], and furtherly constructed 2 models for better diagnosis.

CONCLUSIONS

We identified several single miRNAs and combined groups with high diagnostic power for NSCLC through pooled quantitative analysis, which shows that specific miRNAs are good biomarker candidates for NSCLC and further researches needed.

Salivary Biomarkers in Lung Cancer

A very low percentage of lung cancer (LC) cases are discovered at an early and treatable stage of the disease, leading to an abysmally low 5-year survival rate. This underscores the immediate necessity for improved diagnostic, prognostic, and predictive biomarkers for LC. Biopsied lung tissue, blood, and plasma are common sources used for LC diagnosis and monitoring of the disease. A growing number of studies have reported saliva to be a useful biological sample for early and noninvasive detection of oral and systemic diseases. Nevertheless, salivary biomarker discovery remains underresearched. Here, we have compiled the available literature to provide an overview of the current understanding of salivary markers for LC detection and provided perspectives for future clinical significance. Valuable markers with diagnostic and prognostic potentials in LC have been discovered in saliva, including metabolic (catalase activity, triene conjugates, and Schiff bases), inflammatory (interleukin 10, C-X-C motif chemokine ligand 10), proteomic (haptoglobin, zinc-α-2-glycoprotein, and calprotectin), genomic (epidermal growth factor receptor), and microbial candidates (Veillonella and Streptococcus). In combination, with each other and with other established screening methods, these salivary markers could be useful for improving early detection of the disease and ultimately improve the survival odds of LC patients. The existing literature suggests that saliva is a promising biological sample for identification and validation of biomarkers in LC, but how saliva can be utilized most effectively in a clinical setting for LC management is still under investigation.

Investigating the relationship between particulate matter and inflammatory biomarkers of exhaled breath condensate and blood in healthy young adults

Inflammatory biomarkers in exhaled breath condensate (EBC) are measured to estimate the effects of air pollution on humans. The present study was conducted to investigate the relationship between particulate matter and inflammatory biomarkers in blood plasma and exhaled air in young adults. The obtained results were compared in two periods; i.e., winter and summer. GRIMM Dust Monitors were used to measure PM₁₀, PM_2.5, and PM₁ in indoor and outdoor air. A total of 40 healthy young adults exhaling air condensate were collected. Then, biomarkers of interleukin-6 (IL-6), Nitrosothiols (RS-NOs), and Tumor necrosis factor-soluble receptor-II (sTNFRII) were measured by 96 wells method ELISA and commercial kits (HS600B R&D Kit and ALX-850–037-KI01) in EBC while interleukin-6 (IL-6), sTNFRII and White Blood Cell (WBC) were measured in blood plasma in two periods of February 2013 (winter) and May 2013 (summer). Significant association was found between particulate matter and the white blood cell count (p < 0.001), as well as plasma sTNFRII levels (p-value = 0.001). No significant relationship was found between particulate matter with RS-NOs (p = 0.128), EBC RSNOs (p-value = 0.128), and plasma IL-6 (p-value = 0.167). In addition, there was no significant relationship between interleukin-6 of exhaled air with interleukin-6 of plasma (p-value < 0.792 in the first period and < 0.890 in the second period). sTNFRII was not detected in EBC. Considering the direct effect between increasing some biomarkers in blood and EBC and particulate matter, it is concluded that air pollution causes this increasing.

Nitric oxide in occurrence, progress and therapy of lung Cancer: a systemic review and meta-analysis

Background

Nitric oxide (NO) plays an important role in lung cancer. However, the results of previous studies about NO in the occurrence, progress and therapy were not consistent. Therefore, we conducted a meta-analysis to evaluate the relationship between NO and lung cancer.

Method

We carried out comprehensive search in the databases, and collected related studies. The data of fraction of exhaled nitric oxide (FeNO) or blood NO in different populations (lung cancer patients and control subjects) and different time points (before therapy and after therapy) were extracted by two investigators. A random effect model was applied to analyze the differences of FeNO and blood NO in different populations and different time points. To further compare NO level of each subgroup with different pathological types and different stages, a network meta-analysis (NMA) was performed.

Results

Fifty studies including 2551 cases and 1691 controls were adopted in this meta-analysis. The FeNO (SMD 3.01, 95% CI 1.89–4.13, p < 0.00001) and blood NO (SMD 1.34, 95% CI 0.84–1.85, p < 0.00001) level in lung cancer patients was much higher than that in control subjects. NMA model indicated blood NO level in each cancer type except SCLC was higher than that in control patients. There was no significant difference of blood NO level among four kinds of lung cancer patients. Blood NO level in LCC patients (SUCRA = 83.5%) was the highest. Blood NO level in advanced stage but not early stage was higher than that in control subjects. Patients in advanced stage (SUCRA = 95.5%) had the highest blood NO level. No significant difference of FeNO (SMD -0.04, 95% CI -0.46-0.38, p > 0.05) and blood NO level (SMD -0.36, 95% CI -1.08-0.36, p > 0.05) was observed between pretreatment and posttreatment in all patients. However, FeNO level elevated (SMD 0.28, 95% CI 0.04–0.51, p = 0.02) and blood NO level decreased in NSCLC patients (SMD -0.95, 95% CI -1.89-0.00, p = 0.05) after therapy.

Conclusion

FeNO and blood NO level would contribute to diagnosis of lung cancer and evaluation of therapy effect, especially for NSCLC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08430-2.

Stimuli-responsive nanoparticles based on poly acrylic derivatives for tumor therapy

Serve side effects caused by discriminate damage of chemotherapeutic drugs to normal cell and cancer cells remain a main obstacle in clinic. Hence, continuous efforts have been made to find ways to effectively enhance drug delivery and reduce side effects. Recent decades have witnessed impressive progresses in fighting against cancer, with improved understanding of tumor microenvironment and rapid development in nanoscale drug delivery system (DDS). Nanocarriers based on biocompatible materials provide possibilities to improve antitumor efficiency and minimize off-target effects. Among all kinds of biocompatible materials applied in DDS, polymeric acrylic derivatives such as poly(acrylamide), poly(acrylic acid), poly(N-isopropylacrylamide) present inherent biocompatibility and stimuli-responsivity, and relatively easy to be functionalized. Furthermore, nanocarrier based on polymeric acrylic derivatives have demonstrated high drug encapsulation, improved uptake efficiency, prolonged circulation time and satisfactory therapeutic outcome in tumor. In this review, we aim to discuss recent progress in design and development of stimulus-responsive poly acrylic polymer based nanocarriers for tumor targeting drug delivery.

Current Advances of Nitric Oxide in Cancer and Anticancer Therapeutics

Nitric oxide (NO) is a short-lived, ubiquitous signaling molecule that affects numerous critical functions in the body. There are markedly conflicting findings in the literature regarding the bimodal effects of NO in carcinogenesis and tumor progression, which has important consequences for treatment. Several preclinical and clinical studies have suggested that both pro- and antitumorigenic effects of NO depend on multiple aspects, including, but not limited to, tissue of generation, the level of production, the oxidative/reductive (redox) environment in which this radical is generated, the presence or absence of NO transduction elements, and the tumor microenvironment. Generally, there are four major categories of NO-based anticancer therapies: NO donors, phosphodiesterase inhibitors (PDE-i), soluble guanylyl cyclase (sGC) activators, and immunomodulators. Of these, NO donors are well studied, well characterized, and also the most promising. In this study, we review the current knowledge in this area, with an emphasis placed on the role of NO as an anticancer therapy and dysregulated molecular interactions during the evolution of cancer, highlighting the strategies that may aid in the targeting of cancer.

Neutral Desorption Extractive Electrospray Ionization Mass Spectrometry Analysis Sputum for Non-Invasive Lung Adenocarcinoma Detection

Purpose

Increased use of low-dose spiral computed tomography (LDCT: low-dose computed tomography) screening has contributed to more frequent incidental detection of peripheral lung nodules, part of them were adenocarcinoma, which need to be further evaluated to establish a definitive diagnosis. Here, our primary objective was to evaluate the ambient mass spectrometry (AMS) sputum analysis as a non-invasive lung adenocarcinoma (LAC) diagnosis solution.

Patients and Methods

Neutral desorption extractive electrospray ionization mass spectrometry (ND-EESI-MS) and collision induced dissociation (CID) were used to detect sputum metabolites from 143 spontaneous sputum samples. Partial least squares-discriminant analysis (PLS-DA) was used to refine the biomarker panel, whereas orthogonal PLS-DA (OPLS-DA) was used to operationalize the enhanced biomarker panel for diagnosis.

Results

In this approach, 19 altered metabolites were detected by ND-EESI-MS from 76 cases of LAC and 67 cases of control. Significance testing and receiver operating characteristic (ROC) analysis identified 5 metabolites [hydroxyphenyllactic acid, phytosphingosine, N-nonanoylglycine, sphinganine, S-carboxymethyl-L-cysteine] with p <0.05 and AUC >0.75, respectively. Evaluation of model performance for prediction of LAC resulted in a cross-validation classification accuracy of 87.9%. Metabolic pathway analysis showed that sphingolipid metabolism, fatty acid metabolism, carnitine synthesis and Warburg effect were most impacted in response to disease.

Conclusion

This study indicates that the application of ND-EESI-MS to sputum analysis can be used as a non-invasive detection of peripheral lung nodules. The use of sputum metabolite biomarkers may aid in the development of a further evaluation program for lung adenocarcinoma.

Surface rheological properties alter aerosol formation from mucus mimetic surfaces

The effects of surface tension and surface viscoelastic properties on the formation of aerosol droplets generated from mucus-like viscoelastic gels (mucus mimetics) during shearing with a high velocity air stream were investigated. Mucus mimetic samples were formulated with similar composition (94% water and 6% dissolved solids, consisting of mucins, proteins, and ions), surface tension (via the addition of surfactant to the mimetic surface) and bulk viscoelastic properties (via crosslinking of mucin macromolecules in the mimetic) to that of native non-diseased tracheal mucus. The surface tension of the mucus mimetic was decreased by spreading one of two surfactants, dipalmitoyl phosphatidylcholine (DPPC) or calf lung surfactant (Infasurf®), on the mimetic surface. Aerosols were generated from the mimetic surfaces during simulated coughing using an enhanced simulated cough machine (ESCM) operating under controlled environmental conditions. The size distribution of aerosol droplets generated during simulated coughing from the surfactant-coated mimetic surfaces was multimodal, while no droplets were generated from the bare mimetic surface due to its high surface viscoelastic properties and high surface tension. The concentration of aerosols generated from the DPPC-coated mimetic was higher than that of the Infasurf®-coated mimetic, even though the surface tension of the two interfaces was the same. The experimental results suggest that a balance of surface elastic behavior and surface viscous behavior is required for the generation of aerosols from the viscoelastic surfaces.

Development of a Sensing Array for Human Breath Analysis Based on SWCNT Layers Functionalized with Semiconductor Organic Molecules

A sensor array based on heterojunctions between semiconducting organic layers and single walled carbon nanotube (SWCNT) films is produced to explore applications in breathomics, the molecular analysis of exhaled breath. The array is exposed to gas/volatiles relevant to specific diseases (ammonia, ethanol, acetone, 2-propanol, sodium hypochlorite, benzene, hydrogen sulfide, and nitrogen dioxide). Then, to evaluate its capability to operate with real relevant biological samples the array is exposed to human breath exhaled from healthy subjects. Finally, to provide a proof of concept of its diagnostic potential, the array is exposed to exhaled breath samples collected from subjects with chronic obstructive pulmonary disease (COPD), an airway chronic inflammatory disease not yet investigated with CNT-based sensor arrays, and breathprints are compared with those obtained from of healthy subjects. Principal component analysis shows that the sensor array is able to detect various target gas/volatiles with a clear fingerprint on a 2D subspace, is suitable for breath profiling in exhaled human breath, and is able to distinguish subjects with COPD from healthy subjects based on their breathprints. This classification ability is further improved by selecting the most responsive sensors to nitrogen dioxide, a potential biomarker of COPD.

Biochemical Markers of Saliva in Lung Cancer: Diagnostic and Prognostic Perspectives

The aim of the work is to study the metabolic characteristics of saliva in lung cancer for use in early diagnosis and determining the prognosis of the disease. The patient group included 425 lung cancer patients, 168 patients with non-cancerous lung diseases, and 550 healthy volunteers. Saliva samples were collected from all participants in the experiment before treatment and 34 biochemical saliva parameters were determined. Participants were monitored for six years to assess survival rates. The statistical analysis was performed by means of Statistica 10.0 (StatSoft) program and R package (version 3.2.3). To construct the classifier, the Random Forest method was used; the classification quality was assessed using the cross-validation method. Prognostic factors were analyzed by multivariate analysis using Cox's proportional hazard model in a backward step-wise fashion to adjust for potential confounding factors. A complex of metabolic changes occurring in saliva in lung cancer is described. Seven biochemical parameters were identified (catalase, triene conjugates, Schiff bases, pH, sialic acids, alkaline phosphatase, chlorides), which were used to construct the classifier. The sensitivity and specificity of the method were 69.5% and 87.5%, which is practically not inferior to the diagnostic characteristics of markers routinely used in the diagnosis of lung cancer. Significant independent factors in the poor prognosis of lung cancer are imidazole compounds (ICs) above 0.478 mmol/L and salivary lactate dehydrogenase activity below 545 U/L. Saliva has been shown to have great potential for the development of diagnostic and prognostic tests for lung cancer.

A Barcoded Polymer-Based Cross-Reactive Spectroscopic Sensor Array for Organic Volatiles

The development of cross-reactive sensor arrays for volatile organics (electronic noses, e-noses) is an active area of research. In this manuscript, we present a new format for barcoded polymer sensor arrays based on porous polymer beads. An array of nine self-encoded polymers was analyzed by Raman spectroscopy before and after exposure to a series of volatile organic compounds, and the changes in the vibrational fingerprints of their polymers was recorded before and after exposure. Our results show that the spectroscopic changes experienced by the porous spectroscopically encoded beads after exposure to an analyte can be used to identify and classify the target analytes. To expedite this analysis, analyte-specific changes induced in the sensor arrays were transformed into a response pattern using multivariate data analysis. These studies established the barcoded bead array format as a potentially effective sensing element in e-nose devices. Devices such as these have the potential to advance personalized medicine, providing a platform for non-invasive, real-time volatile metabolite detection.

Exhaled breath condensate biomarkers for lung cancer

Lung cancer is the main cause of cancer incidence and mortality worldwide and the identification of clinically useful biomarkers for lung cancer detection at both early and metastatic stage is a pressing medical need. Although many improvements have been made in the treatment and in the early screening of this cancer, most diagnosis are made at a late stage, when a lot of genetic and epigenetic changes have occurred. A promising source of biomarkers reflective of the pathogenesis of lung cancer is exhaled breath condensate (EBC), a biological fluid and a natural matrix of the respiratory tract. Molecules such as DNAs, RNAs, proteins, metabolites and volatile compounds are present in EBC, and their presence/absence or their variation in concentrations can be used as biomarkers. The aims of this review are to briefly describe exhaled breath composition, firstly, and then to document some of the EBC candidate biomarkers for lung cancer by dividing them according to their origin (genome, transcriptome, epigenome, metabolome, proteome and microbiota) in order to demonstrate the potential use of EBC as a helpful tool in cancer diagnostics, molecular profiling, therapy monitoring and screening of high risk individuals.

Does oral fluid contribute to exhaled breath samples collected by means of an electret membrane?

To date, blood (and serum) as well as urine samples are the most commonly collected specimens for routine doping controls, which allow for the analytical coverage of an extensive set of target analytes relevant to sports drug testing programs. In the course of studies to identify potential alternative matrices to complement current testing approaches, exhaled breath (EB) has been found to offer advantageous properties especially with regard to the sample collection procedure, which is less invasive, less intrusive, and less time‐consuming when compared to conventional blood and urine testing. A yet unaddressed question has been the potential contribution of oral fluid (OF) to EB samples. The current investigation focused on characterizing an electret membrane‐based EB collection device concerning a potential introduction of OF during the sampling procedure. For that purpose, EB and OF samples collected under varying conditions from a total of 14 healthy volunteers were tested for the presence of abundant salivary proteins using bottom‐up proteomics approaches such as SDS‐PAGE followed by tryptic digestion and chromatographic‐mass spectrometric analysis. The trapping baffles integrated into the mouthpiece of the EB collection device were found to effectively retain OF introduced into the unit during sample collection as no saliva breakthrough was detectable using the established analytical approach targeting predominantly the highly abundant salivary α‐amylase. Since α‐amylase was found unaffected by storage, smoking, food intake, and exercise, it appears to be a useful marker to reveal possible OF contaminations of EB collection devices.

Multimodal chemometric approach for the analysis of human exhaled breath in lung cancer patients by TD-GC × GC-TOFMS

Lung cancer is the deadliest cancer in developed countries. To reduce its mortality rate, it is important to enhance our capability to detect it at earlier stages by developing early diagnostic methods. In that context, the analysis of exhaled breath is an interesting approach because of the simplicity of the medical act and its non-invasiveness. Thermal desorption comprehensive two-dimensional gas chromatography time of flight mass spectrometry (TD-GC × GC-TOFMS) has been used to characterize and compare the volatile content of human breath of lung cancer patients and healthy volunteers. On the sampling side, the contaminations induced by the bags membrane and further environmental migration of VOCs during and after the sampling have also been investigated. Over a realistic period of 6 h, the concentration of contaminants inside the bag can increase from 2 to 3 folds based on simulated breath samples. On the data processing side, Fisher ratio (FR) and random forest (RF) approaches were applied and compared in regards to their ability to reduce the data dimensionality and to extract the significant information. Both approaches allow to efficiently smooth the background signal and extract significant features (27 for FR and 17 for RF). Principal component analysis (PCA) was used to evaluate the clustering capacity of the different models. For both approaches, a separation along PC-1 was obtained with a variance score around 35%. The combined model provides a partial separation with a PC-1 score of 52%. This proof-of-concept study further confirms the potential of breath analysis for cancer detection but also underlines the importance of quality control over the full analytical procedure, including the processing of the data.

Enhanced selectivity of target gas molecules through a minimal array of gas sensors based on nanoparticle-decorated SWCNTs

Layers of CNTs decorated with metal and metal–oxide nanoparticles can be used to develop highly selective gas sensor arrays.

Fluorometric gas-imaging system (sniff-cam), using the extinction of NADH with an ADH reverse reaction, for acetaldehyde in the gas phase

A gas-imaging system (sniff-cam) that allows fluorometric visualization of a two-dimensional (2-D) distribution of gaseous acetaldehyde (AcH) was developed. It employed a reverse reaction of a nicotinamide adenine dinucleotide (NADH) dependent enzyme that led to consumption of NADH in that reaction. The system was constructed with a highly sensitive camera, an ultraviolet light emitting diode array sheet, two band pass filters and an alcohol dehydrogenase (ADH)-immobilized mesh that was used for AcH detection. The reverse reaction of the ADH catalyzed the reduction of AcH to ethanol and the oxidation of NADH to NAD⁺, which occurred when gaseous AcH was applied to the ADH immobilized mesh that was wetted with a slightly acidic NADH solution. As NADH has an autofluorescence property [emission (λ_em) at 490 nm; excitation (λ_ex) at 340 nm], the presence of gaseous AcH was visualized by a decrease of fluorescence of the NADH at the ADH immobilized mesh. After constructing the gaseous AcH imaging system, optimizations of pH, and concentration of the NADH solution were performed. As a result of the optimizations (500 μM of NADH in 0.1 M of Tris hydrochloride (Tris-HCl) buffer at pH 6.5), the AcH sniff-cam showed a wide dynamic range (0.1-10 ppm) for gaseous AcH with a high correlation coefficient (R = 0.999). Furthermore, a fluorescence gradient with a rounded shape centered in a gas outlet was observed. These results demonstrated that the AcH sniff-cam utilizing the fluorescence decrease of NADH could be used to quantitatively evaluate the 2-D distribution of gaseous AcH.

Influence of Water Molecules on the Detection of Volatile Organic Compounds (VOC) Cancer Biomarkers by Nanocomposite Quantum Resistive Vapor Sensors vQRS

The anticipated diagnosis of various fatal diseases from the analysis of volatile organic compounds (VOC) biomarkers of the volatolome is the object of very dynamic research. Nanocomposite-based quantum resistive vapor sensors (vQRS) exhibit strong advantages in the detection of biomarkers, as they can operate at room temperature with low consumption and sub ppm (part per million) sensitivity. However, to meet this application they need to detect some ppm or less amounts of biomarkers in patients' breath, skin, or urine in complex blends of numerous VOC, most of the time hindered by a huge amount of water molecules. Therefore, it is crucial to analyze the effects of moisture on the chemo-resistive sensing behavior of carbon nanotubes based vQRS. We show that in the presence of water molecules, the sensors cannot detect the right amount of VOC molecules present in their environment. These perturbations of the detection mechanism are found to depend on the chemical interactions between water and other VOC molecules, but also on their competitive absorption on sensors receptive sites, located at the nanojunctions of the conductive architecture. This complex phenomenon studied with down to 12.5 ppm of acetone, ethanol, butanone, toluene, and cyclohexane mixed with 100 ppm of water was worth to investigate in the prospect of future developments of devices analysing real breath samples in which water can reach a concentration of 6%.

Assessing Lung Cancer Screening Programs under Uncertainty in a Heterogeneous Population

BACKGROUND

Lung cancer screening can reduce cancer mortality. Most implementation studies focus only on low-dose computed tomography (LDCT) and clinical attributes of screening and do not include preferences of potential participants. In this study we evaluated the perceived value of screening programs based on LDCT, breath analysis (BA), or blood biomarkers (BB) according to the perspective of the target population.

METHODS

A multi-criteria decision analysis framework was adopted. The weights of seven attributes of screening (sensitivity, specificity, radiation burden, duration of screening process, waiting time until results are communicated, location of screening, and mode of screening) were obtained from an earlier study that included a broad sample from the Netherlands. Performance data for the screening modalities was obtained from clinical trials and expert opinion. Parameter uncertainty about clinical performances was incorporated probabilistically, while heterogeneity in preferences was analyzed through subgroup analyses.

RESULTS

The mean overall values were 0.58 (CI: 0.57 to 0.59), 0.57 (CI: 0.56 to 0.59), and 0.44 (CI: 0.43 to 0.45) for BB, BA, and LDCT, respectively. Seventy-seven per cent of respondents preferred BB or BA. For most subgroups, the overall values were similar to those of the entire sample. BA had the highest value for respondents who would have been eligible for earlier screening trials.

DISCUSSION

BB and BA seem valuable to participants because they can be applied in a primary care setting. Although LDCT still seems preferable given its strong and positive evidence base, it is important to take non-clinical attributes into account to maximize attendance.

Automated in Vivo Nanosensing of Breath-Borne Protein Biomarkers

Toxicology and bedside medical condition monitoring is often desired to be both ultrasensitive and noninvasive. However, current biomarker analyses for these purposes are mostly offline and fail to detect low marker quantities. Here, we report a system called dLABer (detection of living animal's exhaled breath biomarker) that integrates living rats, breath sampling, microfluidics, and biosensors for the automated tracking of breath-borne biomarkers. Our data show that dLABer could selectively detect (online) and report differences (of up to 10³-fold) in the levels of inflammation agent interleukin-6 (IL-6) exhaled by rats injected with different ambient particulate matter (PM). The dLABer system was further shown to have an up to 10⁴ higher signal-to-noise ratio than that of the enzyme-linked immunosorbent assay (ELISA) when analyzing the same breath samples. In addition, both blood-borne IL-6 levels analyzed via ELISA in rats injected with different PM extracts and PM toxicity determined by a dithiothreitol (DTT) assay agreed well with those determined by the dLABer system. Video recordings further verified that rats exposed to PM with higher toxicity (according to a DTT assay and as revealed by dLABer) appeared to be less physically active. All the data presented here suggest that the dLABer system is capable of real-time, noninvasive monitoring of breath-borne biomarkers with ultrasensitivity. The dLABer system is expected to revolutionize pollutant health effect studies and bedside disease diagnosis as well as physiological condition monitoring at the single-protein level.

Quantifying hormones in exhaled breath for physiological assessment of large whales at sea

Exhaled breath analysis is a non-invasive assessment tool that has shown promise in human diagnostics, and could greatly benefit research, management, and conservation of large whales. However, hormone assessment of whale respiratory vapor (blow) has been challenged by variable water content and unknown total volume of collected samples. To advance this technique, we investigated urea (a compound present in narrow range in circulation) as a normalizing factor to correct for blow sample concentration. Normalized progesterone, testosterone, and cortisol concentrations of 100 blow samples from 46 photo-identified North Atlantic right whales (Eubalaena glacialis) were more biologically relevant compared to absolute estimates, varying by sex, age class, or individual. Progesterone was elevated in adult females compared with other cohorts and highest in one independently confirmed pregnant female. For both sexes, testosterone was two-fold higher in reproductively mature whales but studied adult females showed the widest variation. Cortisol was present in relatively low concentrations in blow and demonstrated variation between individual whales, suggesting potential for studies of individual differences in adrenal activity. Incorporation of methodologies that normalize sample concentration are essential for blow hormone analysis of free-swimming whales, and measurement of urea could be used to optimize non-invasive physiological assessment of whales.

Analysis of Cytokine Pattern in Exhaled Breath Condensate of Patients with Squamous Cell Lung Carcinoma

Exhaled breath condensate (EBC) analysis is a promising method for investigating airway pathology. In this study we compared the cytokine pattern of EBC of patients suffering from squamous cell lung carcinoma with that of healthy smokers. Breath condensates collected from 8 smoking lung cancer patients before receiving any anticancer treatment and 8 smokers without any clinical or radiological evidence of pulmonary tumors were used for antibody microarray analysis testing 120 cytokines simultaneously. Ninety-eight cytokines on the array gave a detectable signal in both groups. Cytokine levels were similar across the samples, and none of the cytokines exhibited a significant increase or decrease in cancer patients as compared to healthy subjects with similar smoking status, lung function, and airway inflammation. The results of this pilot study suggest that patients with squamous cell lung carcinoma cannot be distinguished from smokers with no pulmonary tumors based on EBC cytokine signals only.

ROS-Activated Ratiometric Fluorescent Polymeric Nanoparticles for Self-Reporting Drug Delivery

Reactive oxygen species (ROS)-responsive theranostic nanomedicines have attracted wide interest in recent years because ROS stress is implicated in some pathological disorders such as inflammatory diseases and cancers. In this article, we report a kind of innovative ROS-responsive theranostic polymeric nanoparticles that are able to load hydrophobic drugs and to fluorescently self-report the in vitro or intracellular drug release under ROS triggering. The fluorescent nanoparticles were formed by amphiphilic block copolymers consisting of a poly(ethylene glycol) (PEG) segment and an oxidation-responsive hydrophobic block. The copolymers with different hydrophobic block lengths were synthesized by the atom transfer radical polymerization of a phenylboronic ester-containing acrylic monomer with a small fraction of a ROS-activatable 1,8-naphthalimide-based fluorescent monomer, using PEG-Br as the macroinitiator. The copolymer nanoparticles were stable in neutral phosphate buffer but degraded upon H₂O₂ triggering, with the degradation rate depending on the hydrophobic block length and the concentration of H₂O₂. The degradation of nanoparticles was accompanied by a colorimetric change of the fluorophore from blue to green, which affords the nanoparticles the ability to detecting H₂O₂ by a ratiometric fluorescent approach. Moreover, the nanoparticles could encapsulate doxorubicin (DOX) and the H₂O₂-triggered DOX release was well associated with the change in ratiometric fluorescence. Confocal laser scanning microscope results reveal that the fluorescent nanoparticles were internalized into A549 cells through the endocytosis pathway. The ROS-stimulated degradation of the nanoparticles and intracellular DOX release and the fate of the degraded polymers could be monitored by ratiometric fluorescent imaging. Finally, the naked nanoparticles and the degradation products are cytocompatible, whereas the DOX-loaded ones exhibit concentration-dependent cytotoxicity. Of importance, the stimulation with exogenous H₂O₂ or lipopolysaccharide enhanced obviously the cell-killing capability of the DOX-loaded nanoparticles because of the ROS-enhanced intracellular DOX release.

Current and Prospective Protein Biomarkers of Lung Cancer

Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate.

Lung cancer screening

PURPOSE OF REVIEW

Lung cancer screening with low-dose chest computed tomography is now recommended for high-risk individuals by the US Preventive Services Task Force. This recommendation was informed by several randomized controlled trials, the largest of which, the National Lung Screening Trial, demonstrated a 20% relative reduction in lung cancer mortality with annual low-dose chest computed tomography compared with chest radiography.

RECENT FINDINGS

The benefit of lung cancer screening must be balanced against potential harms, including a high false-positive rate with consequent further evaluative studies and invasive testing. It is critical that harms be minimized as screening generalizes to the broad community. Informed decision making between providers and patients should include individualized risk assessment, a discussion of both potential benefit and harm, and tobacco treatment. Given the multiple components required for high quality, screening should ideally occur in the context of a multidisciplinary program.

SUMMARY

We are in the early days of lung cancer screening, still with much to learn. Ongoing studies are necessary to refine the definition of a positive screen and develop better methods of distinguishing between true positive and false-positive results. Novel approaches, including the development of multicomponent lung cancer biomarkers, will likely inform and improve our future screening practice.

Co-liquefaction with acetone and GC analysis of volatile compounds in exhaled breath as lung cancer biomarkers

Introduction: A simple, rapid and low cost method for enrichment of volatile organic compounds (VOCs) from exhaled breath (EB) is presented.

Methods: A 1000 mL home-made extraction device was filled with EB. The VOCs were extracted and condensed in 0.5 mL acetone. Recognition of volatiles in the real studied EB samples was performed by a GC-MS.

Results: The method displays an extraction efficiency of >86% with the enrichment factor of 1929 for octanal. Limits of detection and quantification, and linear dynamic range were 0.008, 0.026 and 0.026-400 ng/mL respectively. Analysis of real samples showed the existence of more than 100 compounds in EB of healthy volunteers and patients with lung cancer before and after treatment. Exhaled octanal concentration was significantly higher in lung cancer patient than in healthy volunteers and lung cancer patient after treatment.

Conclusion: Having used the proposed approach, high extraction recovery (up to 86%) was attained for the lung cancer marker, octanal, as an important biomarker. Our findings on smaples of EB of healthy controls and patients with lung cancer before and after treatment provide complelling evidence upon the effectiveness of the developed method.

Multi-resolution classification of exhaled aerosol images to detect obstructive lung diseases in small airways

Exhaled aerosol patterns have been used to detect obstructive respiratory diseases in the upper airways. Signals from small airway diseases are weak and may not manifest themselves in the exhaled aerosol patterns. Therefore, it will be more challenging to detect abnormalities in small airways. The objective of this study is to develop a simulation-based classification model that can accurately classify small airway diseases. The model performance was evaluated in five obstructed models that are located in lung bifurcations G7-9. The exhaled aerosol images were quantified using local fractal dimensions at different sampling resolutions (n × n). The datasets were classified using both the random forest (RF) and support vector machine (SVM) algorithms. Results show that RF performs slightly and persistently better than SVM. The sampling resolution of 12 × 12 gave the optimal classification for both algorithms. Based on the lung models with predefined obstructive levels, the optimal classification accuracy is 87.0% for 5-class classification, and is 92.5% for 4-class classification by regrouping the mislabeled samples. The proposed model with multi-resolution fractal feature extraction and RF algorithm appears to be sensitive enough to accurately distinguish airway abnormalities in small airways beyond G7 with healthy bronchiole diameter <4 mm. This aerosol-based breath test is promising to develop into an alternative or supplemental tool to the low-dose CT scanning for lung cancer screening.

Cytoplasmic Localization of RUNX3 via Histone Deacetylase-Mediated SRC Expression in Oxidative-Stressed Colon Cancer Cells

Runt domain transcription factor 3 (RUNX3) is a transcription factor that functions as a tumor suppressor. RUNX3 is frequently inactivated by epigenetic silencing or its protein mislocalization (cytoplasmic localization) in many cancer types. This study investigated whether oxidative stress induces redistribution of RUNX3 from the nucleus to the cytoplasm. The cytoplasmic localization of RUNX3 was associated with oxidative stress-induced RUNX3 phosphorylation at tyrosine residues via SRC activation. Moreover, oxidative stress increased expression of histone deacetylases (HDACs). RUNX3 phosphorylation and SRC expression induced by oxidative stress were inhibited by knockdown of HDAC1, restoring the nuclear localization of RUNX3 under oxidative stress. In conclusion, these results demonstrate that HDAC1- and SRC-mediated phosphorylation of RUNX3 induced by oxidative stress is associated with the cytoplasmic localization of RUNX3 and can lead to RUNX3 inactivation and carcinogenesis. J. Cell. Physiol. 232: 1914-1921, 2017. © 2016 Wiley Periodicals, Inc.

Canine scent detection for the diagnosis of lung cancer in a screening-like situation

The prognosis in lung cancer depends largely on early stage detection, and thus new screening methods are attracting increasing attention. Canine scent detection has shown promising results in lung cancer detection, but there has only been one previous study that reproduces a screening-like situation. Here breath samples were collected from 122 patients at risk for lung cancer (smokers and ex-smokers); 29 of the subjects had confirmed diagnosis of lung cancer but had not yet been treated and 93 subjects had no signs or symptoms of lung cancer at the time of inclusion. The breath samples were presented to a trained sniffer dog squadron in a double-blind manner. A rigid scientific protocol was used with respect to earlier canine scent detection studies, with one difference: instead of offering one in five positive samples to the dogs, we offered a random number of positive samples (zero to five). The final positive and negative predictive values of 30.9% and 84.0%, respectively, were rather low compared to other studies. The results differed from those of previous studies, indicating that canine scent detection might not be as powerful as is looked for in real screening situations. One main reason for the rather poor performance in our setting might be the higher stress from the lack of positive responses for dogs and handlers.

Elevated exhalation of hydrogen peroxide in patients with non-small cell lung cancer is not affected by chemotherapy

OBJECTIVES

Reactive oxygen species, which are implicated in the process of carcinogenesis, are also responsible for cell death during chemotherapy (CHT). Therefore, the aim of the study was to evaluate exhaled H₂O₂ levels in non-small cell lung cancer (NSCLC) patients before and after CHT.

METHODS

Thirty patients (age 61.3 ± 9.3 years) with advanced NSCLC (stage IIIB-IV) and 15 age-matched healthy cigarette smokers were enrolled into the study. Patients received four cycles of cisplatin or carboplatin with vinorelbine every three weeks. Before and after the first, second, and fourth cycle, the concentration of H₂O₂ in exhaled breath condensate was measured with respect to treatment response.

RESULTS

At the baseline, NSCLC patients exhaled 3.8 times more H₂O₂ than the control group (0.49 ± 0.14 vs. 0.13 ± 0.03 µmol/L, P < 0.05); this difference persisted throughout the study. CHT had no noticeable effect on exhaled H₂O₂ levels independent of the treatment response (partial remission vs. progressive disease). Pre- and post-CHT cycles of H₂O₂ levels generally correlated positively.

DISCUSSION

The study demonstrated the occurrence of oxidative stress in the airways of advanced NSCLC patients. Exhaled H₂O₂ level was not affected by CHT and independent of treatment results and changes in the number of circulating neutrophils.

Biomimetic Cross-Reactive Sensor Arrays: Prospects in Biodiagnostics

Biomimetic cross-reactive sensor arrays have been used to detect and analyze a wide variety of vapour and liquid components in applications such as food science, public health and safety, and diagnostics. As technology has advanced over the past three decades, these systems have become selective, sensitive, and affordable. Currently, the need for non-invasive and accurate devices for early disease diagnosis remains a challenge. This review provides an overview of the various types of Biomimetic cross-reactive sensor arrays (also referred to as electronic noses and tongues in the literature), their current use and future directions, and an outlook for future technological development.

Detection of cancer embryo antigen and endothelin-1 in exhaled breath condensate: A novel approach to investigate non-small cell lung cancer

The present study aimed to investigate the clinical significance of cancer embryo antigen (CEA) and endothelin-1 (ET-1) in the exhaled breath condensate (EBC) of patients with non-small cell lung cancer (NSCLC). EBC samples were collected from 143 patients with NSCLC and 119 healthy individuals by using an EBC collector. The CEA and ET-1 levels in the EBC and serum were detected. The levels of CEA and ET-1 in the serum and EBC of the NSCLC group were higher compared with those of the healthy group. The level of CEA in the EBC of the adenocarcinoma group was higher compared with that in the squamous cell carcinoma group. The levels of CEA and ET-1 in the serum and EBC in stages III and IV were higher compared with those in stages I and II. The levels of CEA and ET-1 in the EBC were positively correlated with those in the serum, and furthermore, they exhibited high specificity and sensitivity. Thus, these parameters may be used to diagnose lung cancer. The detection of CEA and ET-1 in EBC may help the process of diagnosing and monitoring the progression of NSCLC.

Cross-reactive, self-encoded polymer film arrays for sensor applications

Simple and versatile spectroscopically-encoded styrene-based polymers are the basis for advanced e-Nose sensor array technology.

Gasotransmitters in cancer: from pathophysiology to experimental therapy

The three endogenous gaseous transmitters - nitric oxide (NO), carbon monoxide (CO) and hydrogen sulfide (H2S) - regulate a number of key biological functions. Emerging data have revealed several new mechanisms for each of these three gasotransmitters in tumour biology. It is now appreciated that they show bimodal pharmacological character in cancer, in that not only the inhibition of their biosynthesis but also elevation of their concentration beyond a certain threshold can exert anticancer effects. This Review discusses the role of each gasotransmitter in cancer and the effects of pharmacological agents - some of which are in early-stage clinical studies - that modulate the levels of each gasotransmitter. A clearer understanding of the pharmacological character of these three gases and the mechanisms underlying their biological effects is expected to guide further clinical translation.

Detecting Lung Diseases from Exhaled Aerosols: Non-Invasive Lung Diagnosis Using Fractal Analysis and SVM Classification

Background

Each lung structure exhales a unique pattern of aerosols, which can be used to detect and monitor lung diseases non-invasively. The challenges are accurately interpreting the exhaled aerosol fingerprints and quantitatively correlating them to the lung diseases.

Objective and Methods

In this study, we presented a paradigm of an exhaled aerosol test that addresses the above two challenges and is promising to detect the site and severity of lung diseases. This paradigm consists of two steps: image feature extraction using sub-regional fractal analysis and data classification using a support vector machine (SVM). Numerical experiments were conducted to evaluate the feasibility of the breath test in four asthmatic lung models. A high-fidelity image-CFD approach was employed to compute the exhaled aerosol patterns under different disease conditions.

Findings

By employing the 10-fold cross-validation method, we achieved 100% classification accuracy among four asthmatic models using an ideal 108-sample dataset and 99.1% accuracy using a more realistic 324-sample dataset. The fractal-SVM classifier has been shown to be robust, highly sensitive to structural variations, and inherently suitable for investigating aerosol-disease correlations.

Conclusion

For the first time, this study quantitatively linked the exhaled aerosol patterns with their underlying diseases and set the stage for the development of a computer-aided diagnostic system for non-invasive detection of obstructive respiratory diseases.

Study of exhaled breath condensate sample preparation for metabolomics analysis by LC-MS/MS in high resolution mode

Metabolomic analysis of exhaled breath condensate (EBC) requires an unavoidable sample preparation step because of the low concentration of its components, and potential cleanup for possible interferents. Sample preparation based on protein precipitation (PP), solid-phase extraction (SPE) by hydrophilic and lipophilic sorbents or lyophilization has demonstrated that the analytical sample from the last is largely the best because lyophilization allows reconstitution in a volume as small as required (preconcentration factors up to 80-times with respect to the original sample), thus doubling the number of detected compounds as compared with the other alternatives (47 versus 25). In addition, PP and/or SPE cleanup are unnecessary as no effect from the EBC components removed by these steps appears in the chromatograms. The total 49 EBC compounds tentatively identified and confirmed by MS/MS in this research include amino acids, fatty acids, fatty amides, fatty aldehydes, sphingoid bases, oxoanionic compounds, imidazoles, hydroxy acids and aliphatic acyclic acids.

Analysis of p16 gene mutations and their expression using exhaled breath condensate in non-small-cell lung cancer

The aim of the present study was to investigate the mutational status of exons 1 and 2 of the p16 gene in the exhaled breath condensate (EBC) of patients with non-small-cell lung cancer (NSCLC) and determine the feasibility and clinical significance of applying EBC in the diagnosis of NSCLC. Polymerase chain reaction and DNA sequencing were applied to detect exon 1 and 2 alterations of the p16 gene in EBC by comparing 58 samples from NSCLC patients and 30 from healthy controls. Of the 58 EBC samples from NSCLC patients, 54 were successfully tested and 8 cases of mutations were identified, of which 3 were in exon 1 and 5 in exon 2. The mutation rate was 14.81% (8/54). There were no p16 gene mutations in the 30 samples obtained from healthy controls. EBC p16 gene mutations exhibited no statistically significant differences according to gender, smoking history, pathological type, degree of differentiation and presence or absence of lymph node metastasis. The p16 gene mutation rate was proportional to the tumor stage (P<0.05). Therefore, the detection of the p16 gene mutation in EBC may be used as a novel molecular marker to assist in the diagnosis of NSCLC.

Development of fabric-based chemical gas sensors for use as wearable electronic noses

Novel gas sensors embroidered into fabric substrates based on polymers/ SWNT-COOH nanocomposites were proposed in this paper, aiming for their use as a wearable electronic nose (e-nose). The fabric-based chemical gas sensors were fabricated by two main processes: drop coating and embroidery. Four potential polymers (PVC, cumene-PSMA, PSE and PVP)/functionalized-SWCNT sensing materials were deposited onto interdigitated electrodes previously prepared by embroidering conductive thread on a fabric substrate to make an optimal set of sensors. After preliminary trials of the obtained sensors, it was found that the sensors yielded a electrical resistance in the region of a few kilo-Ohms. The sensors were tested with various volatile compounds such as ammonium hydroxide, ethanol, pyridine, triethylamine, methanol and acetone, which are commonly found in the wastes released from the human body. These sensors were used to detect and discriminate between the body odors of different regions and exist in various forms such as the urine, armpit and exhaled breath odor. Based on a simple pattern recognition technique, we have shown that the proposed fabric-based chemical gas sensors can discriminate the human body odor from two persons.