Exhaled breath condensate biomarkers for lung cancer

Shikonin reactivates TSGs GADD45B and PPP3CC to block NSCLC cell proliferation and migration through JNK/P38/MAPK signaling pathways

BACKGROUND

Shikonin, a natural naphthoquinone compound extracted from the Chinese traditional herbal medicine "Lithospermum erythrorhizon", possesses antitumor activity against various cancer types. Tumor-suppressor genes (TSGs) negatively regulate cell growth, proliferation, and differentiation, thereby inhibiting tumor formation. However, the molecular mechanism of action of shikonin on TSGs in non-small-cell lung cancer (NSCLC) remains unclear.

METHODS

The inhibitory effect of shikonin on the proliferation and migration abilities of lung cancer cells were measured by Cell Counting Kit 8 (CCK8) and wound healing assays. The alteration of genes by shikonin treatment was detected by mRNA high-throughput sequencing and further confirmed by qPCR and western blotting experiments. The dominant functions of the upregulated genes were analyzed by GO and KEGG profiling.

RESULTS

Shikonin inhibited the proliferation and migration of A549 and H1299 NSCLC cells in a dose-dependent manner. mRNA high-throughput sequencing revealed a total of 1794 upregulated genes in shikonin-treated NSCLC cells. Moreover, bioinformatic analysis of GO and KEGG profiling revealed that the up-regulated genes were mostly involved in the JNK/P38/MAPK signaling pathway, among which the expression of GADD45B and PPP3CC was significantly enhanced. Finally, we confirmed that GADD45B and PPP3CC were indeed upregulated in JNK/P38/MAPK pathway.

CONCLUSIONS

Taken together, these results suggested that shikonin might affect the expression of GADD45B and PPP3CC through the JNK/P38/MAPK pathway, therefore exerting an inhibitory effect on the proliferation and migration of cancer cells. To our knowledge, this is the first study reporting the role of shikonin in upregulating TSGs to activate the JNK/P38/MAPK signaling pathways in NSCLC.

Roles of Inflammatory Biomarkers in Exhaled Breath Condensates in Respiratory Clinical Fields

BACKGROUND

Exhaled condensates contain inflammatory biomarkers; however, their roles in the clinical field have been under-investigated.

METHODS

We prospectively enrolled subjects admitted to pulmonology clinics. We collected exhaled breath condensates (EBC) and analysed the levels of six and 12 biomarkers using conventional and multiplex enzyme-linked immunosorbent assay, respectively.

RESULTS

Among the 123 subjects, healthy controls constituted the largest group (81 participants; 65.9%), followed by the preserved ratio impaired spirometry group (21 patients; 17.1%) and the chronic obstructive pulmonary disease (COPD) group (21 patients; 17.1%). In COPD patients, platelet derived growth factor-AA exhibited strong positive correlations with COPD assessment test (ρ=0.5926, p=0.0423) and COPD-specific version of St. George's Respiratory Questionnaire (SGRQ-C) score (total, ρ=0.6725, p=0.0166; activity, ρ=0.7176, p=0.0086; and impacts, ρ=0.6151, p=0.0333). Granzyme B showed strong positive correlations with SGRQ-C score (symptoms, ρ=0.6078, p=0.0360; and impacts, ρ=0.6007, p=0.0389). Interleukin 6 exhibited a strong positive correlation with SGRQ-C score (activity, ρ=0.4671, p=0.0378). The absolute serum eosinophil and basophil counts showed positive correlations with pro-collagen I alpha 1 (ρ=0.6735, p=0.0164 and ρ=0.6295, p=0.0283, respectively). In healthy subjects, forced expiratory volume in 1 second (FEV1)/forced vital capacity demonstrated significant correlation with CC chemokine ligand 3 (CCL3)/macrophage inflammatory protein 1 alpha (ρ=0.3897 and p=0.0068). FEV1 exhibited significant correlation with CCL11/eotaxin (ρ=0.4445 and p=0.0017).

CONCLUSION

Inflammatory biomarkers in EBC might be useful to predict quality of life concerning respiratory symptoms and serologic markers. Further studies are needed.

Phospholipid chlorohydrins as chlorine exposure biomarkers in a large animal model

Chlorine is a toxic industrial chemical that has been used as a chemical weapon in recent armed conflicts. Confirming human exposure to chlorine has proven challenging, and there is currently no established method for analyzing human biomedical samples to unambiguously verify chlorine exposure. In this study, two chlorine-specific biomarkers: palmitoyl-oleoyl phosphatidylglycerol chlorohydrin (POPG-HOCl) and the lipid derivative oleoyl ethanolamide chlorohydrin (OEA-HOCl) are shown in bronchoalveolar lavage fluid (BALF) samples from spontaneously breathing pigs after chlorine exposure. These biomarkers are formed by the chemical reaction of chlorine with unsaturated phospholipids found in the pulmonary surfactant, which is present at the gas-liquid interface within the lung alveoli. Our results strongly suggest that lipid chlorohydrins are promising candidate biomarkers in the development of a verification method for chlorine exposure. The establishment of verified methods capable of confirming the illicit use of toxic industrial chemicals is crucial for upholding the principles of the Chemical Weapons Convention (CWC) and enforcing the ban on chemical weapons. This study represents the first published dataset in BALF revealing chlorine biomarkers detected in a large animal. Furthermore, these biomarkers are distinct in that they originate from molecular chlorine rather than hypochlorous acid.

Detection technologies of volatile organic compounds in the breath for cancer diagnoses

Although there are new approaches in both cancer treatment and diagnosis, overall mortality is a major concern. New technologies have attempted to look at breath volatile organic compounds (VOCs) detection to diagnose cancer. Gas Chromatography and Mass Spectrometry (GC - MS) have remained the gold standard of VOC analysis for decades, but it has limitations in differentiating VOCs between cancer subtypes. To increase efficacy and accuracy, new methods to analyze these breath VOCs have been introduced, such as Solid Phase Microextraction/Gas Chromatography-Mass Spectrometry (SPME/GC-MS), Selected Ion Flow Tube - Mass Spectrometry (SIFT-MS), Proton Transfer Reaction - Mass Spectrometry (PRT-MS), Ion Mobility Spectrometry (IMS), and Colorimetric Sensors. This article highlights new technologies that have been studied and applied in the detection and quantification of breath VOCs for possible cancer diagnoses.

Water interference in the chromatographic analysis of exhaled breath samples: Challenges and mitigation strategies

This study demonstrates the adverse effects of water in exhaled breath samples on the accuracy of breath biomarker analysis when using gas chromatography. The presence of water in exhaled breath significantly modifies the retention times and peak areas of compounds, particularly for low-boiling, early eluting compounds. To tackle this issue, a two-step approach is introduced. The process begins with thorough desorption of the sorbent tube using a high split ratio and a short analysis duration, followed by a secondary analysis of the same tube. The efficacy of the new, straightforward approach was illustrated using humid breath samples and 57 compound standard mixture. This study highlights the importance of proper sample pretreatment and analysis to ensure reliable and accurate results in clinical research.

Diagnostic performance of respirators for collection and detection of SARS-CoV-2

Respirators, called as face mask, have been used to protect the wearer from the outside harmful air environment and prevent any virus from being released to neighbors from potentially infected exhaled breath. The antiviral effectiveness of respirators has not only been researched scientifically, but has also become a global issue due to society's obligation to wear respirators. In this paper, we report the results of a study on the collection and detection of viruses contained in exhaled breath using respirators. The inner electrostatic filter was carefully selected for virus collection because it does not come in direct contact with either human skin or the external environment. In the study of a healthy control group, it was confirmed that a large amount of DNA and biomolecules such as exosomes were collected from the respirator exposed to exhalation, and the amount of collection increased in proportion to the wearing time. We conducted experiments using a total of 72 paired samples with nasopharyngeal swabs and respirator samples. Out of these samples, fifty tested positive for SARS-CoV-2 and twenty-two tested negative. The PCR results of the NPS and respirator samples showed a high level of agreement, with a positive percent agreement of ≥ 90% and a negative percent agreement of ≥ 99%. Furthermore, there was a notable level of concordance between RCA-flow tests and PCR when examining the respirator samples. These results suggest that this is a non-invasive, quick and easy method of collecting samples from subjects using a respirator, which can significantly reduce the hassle of waiting at airports or public places and concerns about cross-contamination. Furthermore, we expect miniaturized technologies to integrate PCR detection into respirators in the near future.

Beta-Lactam Antibiotics Can Be Measured in the Exhaled Breath Condensate in Mechanically Ventilated Patients: A Pilot Study

Different techniques have been proposed to measure antibiotic levels within the lung parenchyma; however, their use is limited because they are invasive and associated with adverse effects. We explore whether beta-lactam antibiotics could be measured in exhaled breath condensate collected from heat and moisture exchange filters (HMEFs) and correlated with the concentration of antibiotics measured from bronchoalveolar lavage (BAL). We designed an observational study in patients undergoing mechanical ventilation, which required a BAL to confirm or discard the diagnosis of pneumonia. We measured and correlated the concentration of beta-lactam antibiotics in plasma, epithelial lining fluid (ELF), and exhaled breath condensate collected from HMEFs. We studied 12 patients, and we detected the presence of antibiotics in plasma, ELF, and HMEFs from every patient studied. The concentrations of antibiotics were very heterogeneous over the population studied. The mean antibiotic concentration was 293.5 (715) ng/mL in plasma, 12.3 (31) ng/mL in ELF, and 0.5 (0.9) ng/mL in HMEF. We found no significant correlation between the concentration of antibiotics in plasma and ELF (R² = 0.02, p = 0.64), between plasma and HMEF (R² = 0.02, p = 0.63), or between ELF and HMEF (R² = 0.02, p = 0.66). We conclude that beta-lactam antibiotics can be detected and measured from the exhaled breath condensate accumulated in the HMEF from mechanically ventilated patients. However, no correlations were observed between the antibiotic concentrations in HMEF with either plasma or ELF.

Sex-specific association of exposure to air pollutants and Nrf2 gene expression and inflammatory biomarkers in exhaled breath of healthy adolescents

Studies investigating the nuclear factor erythroid 2-related factor 2 (Nrf2) expression levels in the respiratory system of healthy subjects are scarce. Moreover, separate studies on the health-related outcomes of air pollution for each sex are limited. The current panel study investigated sex-specific Nrf2 expression levels and related oxidative stress and inflammatory responses among healthy adolescents exposed to PM2.5, PM10, O3, and PM2.5-bounded metals in a high traffic region. Forty-nine healthy nonsmoking subjects participated in the study for five consecutive months (Nov. 2019 to Feb. 2020). Each subject was asked to provide 1 mL of exhaled breath condensate (EBC). Data were analyzed using linear mixed-effects models. The results showed that PM10, PM2.5, O3, and PM2.5-bounded metals were negatively linked to Nrf2 expression level in EBC of females with -58.3% (95% CI: 79.5, -15.4), -32.1% (95% CI: -50.3, -7.1), -76.2% (95% CI: -92.6, -23.9), and -1.9 (95% CI: -3.4, -0.4), respectively. While our results presented no significant association between the studied pollutants and Nrf2 gene expression in males, significant associations were observed between the pollutants and total nitric oxide (NOx), interleukins 6 (IL-6), and tumor necrosis factor-alpha (TNF-α) in the EBC of females. In the case of males, only EBC cytokines showed a significant association with air pollutants. Overall, this study suggests that exposure to ambient air pollutants may affect the respiratory system with biologically different mechanisms in males and females. PM2.5 concentration had a positive correlation with exhaled TNF-α and IL6 values in females while positive correlation with TNF-α and negative correlation with IL6 values in males. O3 had a negative correlation with TNF-α in males.

Non-Invasive Disease Specific Biomarker Detection Using Infrared Spectroscopy: A Review

Many life-threatening diseases remain obscure in their early disease stages. Symptoms appear only at the advanced stage when the survival rate is poor. A non-invasive diagnostic tool may be able to identify disease even at the asymptotic stage and save lives. Volatile metabolites-based diagnostics hold a lot of promise to fulfil this demand. Many experimental techniques are being developed to establish a reliable non-invasive diagnostic tool; however, none of them are yet able to fulfil clinicians' demands. Infrared spectroscopy-based gaseous biofluid analysis demonstrated promising results to fulfil clinicians' expectations. The recent development of the standard operating procedure (SOP), sample measurement, and data analysis techniques for infrared spectroscopy are summarized in this review article. It has also outlined the applicability of infrared spectroscopy to identify the specific biomarkers for diseases such as diabetes, acute gastritis caused by bacterial infection, cerebral palsy, and prostate cancer.

Nonanal Gas Sensors Using Porous Glass as a Reaction Field for Ammonia-Catalyzed Aldol Condensation

Transmittance in porous-glass gas sensors, which use aldol condensation of vanillin and nonanal as the detection mechanism for nonanal, decreases because of the production of carbonates by the sodium hydroxide catalyst. In this study, the reasons for the decrease in transmittance and the measures to overcome this issue were investigated. Alkali-resistant porous glass with nanoscale porosity and light transparency was employed as a reaction field in a nonanal gas sensor using ammonia-catalyzed aldol condensation. In this sensor, the gas detection mechanism involves measuring the changes in light absorption of vanillin arising from aldol condensation with nonanal. Furthermore, the problem of carbonate precipitation was solved with the use of ammonia as the catalyst, which effectively resolves the issue of reduced transmittance that occurs when a strong base, such as sodium hydroxide, is used as a catalyst. Additionally, the alkali-resistant glass exhibited solid acidity because of the incorporated SiO₂ and ZrO₂ additives, which supported approximately 50 times more ammonia on the glass surface for a longer duration than a conventional sensor. Moreover, the detection limit obtained from multiple measurements was approximately 0.66 ppm. In summary, the developed sensor exhibits a high sensitivity to minute changes in the absorbance spectrum because of the reduction in the baseline noise of the matrix transmittance.

Lung cancer screening

Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access.

Non-Invasive Lung Cancer Diagnostics through Metabolites in Exhaled Breath: Influence of the Disease Variability and Comorbidities

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.

Remote Medical Scent Detection of Cancer and Infectious Diseases With Dogs and Rats: A Systematic Review

BACKGROUND

Remote medical scent detection of cancer and infectious diseases with dogs and rats has been an increasing field of research these last 20 years. If validated, the possibility of implementing such a technique in the clinic raises many hopes. This systematic review was performed to determine the evidence and performance of such methods and assess their potential relevance in the clinic.

METHODS

Pubmed and Web of Science databases were independently searched based on PRISMA standards between 01/01/2000 and 01/05/2021. We included studies aiming at detecting cancers and infectious diseases affecting humans with dogs or rats. We excluded studies using other animals, studies aiming to detect agricultural diseases, diseases affecting animals, and others such as diabetes and neurodegenerative diseases. Only original articles were included. Data about patients' selection, samples, animal characteristics, animal training, testing configurations, and performances were recorded.

RESULTS

A total of 62 studies were included. Sensitivity and specificity varied a lot among studies: While some publications report low sensitivities of 0.17 and specificities around 0.29, others achieve rates of 1 sensitivity and specificity. Only 6 studies were evaluated in a double-blind screening-like situation. In general, the risk of performance bias was high in most evaluated studies, and the quality of the evidence found was low.

CONCLUSIONS

Medical detection using animals' sense of smell lacks evidence and performances so far to be applied in the clinic. What odors the animals detect is not well understood. Further research should be conducted, focusing on patient selection, samples (choice of materials, standardization), and testing conditions. Interpolations of such results to free running detection (direct contact with humans) should be taken with extreme caution. Considering this synthesis, we discuss the challenges and highlight the excellent odor detection threshold exhibited by animals which represents a potential opportunity to develop an accessible and non-invasive method for disease detection.

Exhaled metabolic markers and relevant dysregulated pathways of lung cancer: a pilot study

INTRODUCTION

The clinical application of lung cancer detection based on breath test is still challenging due to lack of predictive molecular markers in exhaled breath. This study explored potential lung cancer biomarkers and their related pathways using a typical process for metabolomics investigation.

MATERIAL AND METHODS

Breath samples from 60 lung cancer patients and 176 healthy people were analyzed by GC-MS. The original data were GC-MS peak intensity removing background signal. Differential metabolites were selected after univariate statistical analysis and multivariate statistical analysis based on OPLS-DA and Spearman rank correlation analysis. A multivariate PLS-DA model was established based on differential metabolites for pattern recognition. Subsequently, pathway enrichment analysis was performed on differential metabolites.

RESULTS

The discriminant capability was assessed by ROC curve of whom the average AUC and average accuracy in 100-fold cross validations were 0.871 and 0.787, respectively. Eight potential biomarkers were involved in a total of 18 metabolic pathways. Among them, 11 metabolic pathways have p-value smaller than .1.

DISCUSSION

Some pathways among them are related to risk factors or therapies of lung cancer. However, more of them are dysregulated pathways of lung cancer reported in studies based on genome or transcriptome data.

CONCLUSION

We believe that it opens the possibility of using metabolomics methods to analyze data of exhaled breath and promotes involvement of knowledge dataset to cover more volatile metabolites.

CLINICAL SIGNIFICANCE

Although a series of related research reported diagnostic models with highly sensitive and specific prediction, the clinical application of lung cancer detection based on breath test is still challenging due to disease heterogeneity and lack of predictive molecular markers in exhaled breath. This study may promote the clinical application of this technique which is suitable for large-scale screening thanks to its low-cost and non-invasiveness. As a result, the mortality of lung cancer may be decreased in future.Key messagesIn the present study, 11 pathways involving 8 potential biomarkers were discovered to be dysregulated pathways of lung cancer.We found that it is possible to apply metabolomics methods in analysis of data from breath test, which is meaningful to discover convinced volatile markers with definite pathological and histological significance.

Collection and detection of SARS-CoV-2 in exhaled breath using face mask

Face masks are used to protect the wearer from harmful external air and to prevent transmission of viruses from air exhaled by potentially infected wearers to the surrounding people. In this study, we examined the potential utility of masks for collecting viruses contained in exhaled breath and detected the collected viruses via various molecular tests. Using KF94 masks, the inner electrostatic filter was selected for virus collection, and an RNA extraction protocol was developed for the face mask. Virus detection in worn mask samples was performed using PCR and rolling circle amplification (RCA) tests and four different target genes (N, E, RdRp, and ORF1ab genes). The present study confirmed that the mask sample tests showed positive SARS-CoV-2 results, similar to the PCR tests using nasopharyngeal swab samples. In addition, the quantity of nucleic acid collected in the masks linearly increased with wearing time. These results suggest that samples for SARS-CoV-2 tests can be collected in a noninvasive, quick, and easy method by simply submitting worn masks from subjects, which can significantly reduce the hassle of waiting at airports or public places and concerns about cross-infection. In addition, it is expected that miniaturization technology will integrate PCR assays on face masks in the near future, and mask-based self-diagnosis would play a significant role in resolving the pandemic situation.

Exhaled breath condensate efficacy to identify mutations in patients with lung cancer: A pilot study

Exhaled breath condensate (EBC) is used to investigate the efficacy of EBC to detect the genetic mutations in patients with lung cancer. Samples of 5 patients and 5 healthy volunteers were collected. DNA was extracted and used for amplification of hotspot regions of TP53 and KRAS genes by using PCR. We performed the mutation analysis by direct sequencing in all subjects. Detected mutations in EBC samples were compared with those of corresponding tumor tissues and there was complete agreement within the detected mutations in EBC and tumorous tissue. EBC can be used as an efficient and noninvasive source for the assessment of gene mutations in patients with lung cancer.

Metabolic Alterations in Sputum and Exhaled Breath Condensate of Early Stage Non-Small Cell Lung Cancer Patients After Surgical Resection: A Pilot Study

Every year, close to two million people world-wide are diagnosed with and die of lung cancer. Most patients present with advanced-stage cancer with limited curative options and poor prognosis. Diagnosis of lung cancer at an early stage provides the best chance for a cure. Low- dose CT screening of the chest in the high-risk population is the current standard of care for early detection of lung cancer. However, CT screening is invasive due to radiation exposure and carries the risk of unnecessary biopsies in non-cancerous tumors. In this pilot study, we present metabolic alterations observed in sputum and breath condensate of the same population of early- stage non-small cell lung cancer (NSCLC) patients cancer before and after surgical resection (SR), which could serve as noninvasive diagnostic tool. Exhaled breath condensate (EBC) (n=35) and sputum (n=15) were collected from early-stage non-small cell lung cancer (NSCLC) patients before and after SR. Median number of days for EBC and sputum collection before and after SR were 7 and 42; and 7 and 36 respectively Nuclear magnetic resonance (NMR) and liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) were used to analyze the metabolic profile of the collected samples. A total of 26 metabolites with significant alteration post SR were identified, of which 14 (54%) were lipids and 12 constituted nine different chemical metabolite classes. Eighteen metabolites (69%) were significantly upregulated and 8 (31%) were downregulated. Median fold change for all the up- and downregulated metabolites (LC-QTOF-MS) were 10 and 8, respectively. Median fold change (MFC) in concentration of all the up- and downregulated metabolites (NMR) were 0.04 and 0.27, respectively. Furthermore, glucose (median fold change, 0.01, p=0.037), adenosine monophosphate (13 log fold, p=0.0037) and N1, N12- diacetylspermine (8 log fold p=0.011) sputum levels were significantly increased post-SR. These identified sputa and EBC indices of altered metabolism could serve as basis for further exploration of biomarkers for early detection of lung cancer, treatment response, and targets for drug discovery. Validation of these promising results by larger clinical studies is warranted.

Identification of lung cancer breath biomarkers based on perioperative breathomics testing: A prospective observational study

BACKGROUND

Breathomics testing has been considered a promising method for detection and screening for lung cancer. This study aimed to identify breath biomarkers of lung cancer through perioperative dynamic breathomics testing.

METHODS

The discovery study was prospectively conducted between Sept 1, 2020 and Dec 31, 2020 in Peking University People's Hospital in China. High-pressure photon ionisation time-of-flight mass spectrometry was used for breathomics testing before surgery and 4 weeks after surgery. 28 volatile organic compounds (VOCs) were selected as candidates based on a literature review. VOCs that changed significantly postoperatively in patients with lung cancer were selected as potential breath biomarkers. An external validation was conducted to evaluate the performance of these VOCs for lung cancer diagnosis. Multivariable logistic regression was used to establish diagnostic models based on selected VOCs.

FINDINGS

In the discovery study of 84 patients with lung cancer, perioperative breathomics demonstrated 16 VOCs as lung cancer breath biomarkers. They were classified as aldehydes, hydrocarbons, ketones, carboxylic acids, and furan. In the external validation study including 157 patients with lung cancer and 368 healthy individuals, patients with lung cancer showed elevated spectrum peak intensity of the 16 VOCs after adjusting for age, sex, smoking, and comorbidities. The diagnostic model including 16 VOCs achieved an area under the curve (AUC) of 0.952, sensitivity of 89.2%, specificity of 89.1%, and accuracy of 89.1% in lung cancer diagnosis. The diagnostic model including the top eight VOCs achieved an AUC of 0.931, sensitivity of 86.0%, specificity of 87.2%, and accuracy of 86.9%.

INTERPRETATION

Perioperative dynamic breathomics is an effective approach for identifying lung cancer breath biomarkers. 16 lung cancer-related breath VOCs (aldehydes, hydrocarbons, ketones, carboxylic acids, and furan) were identified and validated. Further studies are warranted to investigate the underlying mechanisms of identified VOCs.

FUNDING

National Natural Science Foundation of China (82173386) and Peking University People's Hospital Scientific Research Development Founds (RDH2021-07).

Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review

Lung cancer has been studied for decades because of its high morbidity and high mortality. Traditional methods involving bronchoscopy and needle biopsy are invasive and expensive, which makes patients suffer more risks and costs. Various noninvasive lung cancer markers, such as medical imaging indices, volatile organic compounds (VOCs), and exhaled breath condensates (EBCs), have been discovered for application in screening, diagnosis, and prognosis. However, the detection of markers still relies on bulky and professional instruments, which are limited to training personnel or laboratories. This seriously hinders population screening for early diagnosis of lung cancer. Advanced smartphones integrated with powerful applications can provide easy operation and real-time monitoring for healthcare, which demonstrates tremendous application scenarios in the biomedical analysis region from medical institutions or laboratories to personalized medicine. In this review, we propose an overview of lung-cancer-related noninvasive markers from exhaled breath, focusing on the novel development of smartphone-based platforms for the detection of these biomarkers. Lastly, we discuss the current limitations and potential solutions.

Application of Artificial Intelligence in Lung Cancer

Simple Summary

Lung cancer is the leading cause of malignancy-related mortality worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and decision making to prognosis prediction. AI could reduce the labor work of LDCT, CXR, and pathology slides reading. AI as a second reader in LDCT and CXR reading reduces the effort of radiologists and increases the accuracy of nodule detection. Introducing AI to WSI in digital pathology increases the Kappa value of the pathologist and help to predict molecular phenotypes with radiomics and H&E staining. By extracting radiomics from image data and WSI from the histopathology field, clinicians could use AI to predict tumor properties such as gene mutation and PD-L1 expression. Furthermore, AI could help clinicians in decision-making by predicting treatment response, side effects, and prognosis prediction in medical treatment, surgery, and radiotherapy. Integrating AI in the future clinical workflow would be promising.

Abstract

Lung cancer is the leading cause of malignancy-related mortality worldwide due to its heterogeneous features and diagnosis at a late stage. Artificial intelligence (AI) is good at handling a large volume of computational and repeated labor work and is suitable for assisting doctors in analyzing image-dominant diseases like lung cancer. Scientists have shown long-standing efforts to apply AI in lung cancer screening via CXR and chest CT since the 1960s. Several grand challenges were held to find the best AI model. Currently, the FDA have approved several AI programs in CXR and chest CT reading, which enables AI systems to take part in lung cancer detection. Following the success of AI application in the radiology field, AI was applied to digitalized whole slide imaging (WSI) annotation. Integrating with more information, like demographics and clinical data, the AI systems could play a role in decision-making by classifying EGFR mutations and PD-L1 expression. AI systems also help clinicians to estimate the patient’s prognosis by predicting drug response, the tumor recurrence rate after surgery, radiotherapy response, and side effects. Though there are still some obstacles, deploying AI systems in the clinical workflow is vital for the foreseeable future.

Comparative proteomic analysis of exhaled breath condensate between lung adenocarcinoma and CT-detected benign pulmonary nodule patients

BACKGROUND

Lung cancer is the leading cause of cancer mortality worldwide. The collection of exhaled breath condensate (EBC) is a non-invasive method that may have enormous potential as a biomarker for the early detection of lung cancer.

OBJECTIVE

To investigate the proteomic differences of EBC between lung cancer and CT-detected benign nodule patients, and determine whether these proteins could be potential biomarkers.

METHODS

Proteomic analysis was performed on individual samples from 10 lung cancer patients and 10 CT-detected benign nodule patients using data-independent acquisition (DIA) mass spectrometry.

RESULTS

A total of 1,254 proteins were identified, and 21 proteins were differentially expressed in the lung adenocarcinoma group compared to the benign nodule group (p< 0.05). The GO analysis showed that most of these proteins were involved in neutrophil-related biological processes, and the KEGG analysis showed these proteins were mostly annotated to pyruvate and propanoate metabolism. Through protein-protein interactions (PPIs) analysis, ME1 and LDHB contributed most to the interaction-network of these proteins.

CONCLUSION

Significantly differentially expressed proteins were detected between lung cancer and the CT-detected benign nodule group from EBC samples, and these proteins might serve as potential novel biomarkers of EBC for early lung cancer detection.

Hypoxia in Lung Cancer Management: A Translational Approach

Simple Summary

Hypoxia is a common feature of lung cancers. Nonetheless, no guidelines have been established to integrate hypoxia-associated biomarkers in patient management. Here, we discuss the current knowledge and provide translational novel considerations regarding its clinical detection and targeting to improve the outcome of patients with non-small-cell lung carcinoma of all stages.

Abstract

Lung cancer represents the first cause of death by cancer worldwide and remains a challenging public health issue. Hypoxia, as a relevant biomarker, has raised high expectations for clinical practice. Here, we review clinical and pathological features related to hypoxic lung tumours. Secondly, we expound on the main current techniques to evaluate hypoxic status in NSCLC focusing on positive emission tomography. We present existing alternative experimental approaches such as the examination of circulating markers and highlight the interest in non-invasive markers. Finally, we evaluate the relevance of investigating hypoxia in lung cancer management as a companion biomarker at various lung cancer stages. Hypoxia could support the identification of patients with higher risks of NSCLC. Moreover, the presence of hypoxia in treated tumours could help clinicians predict a worse prognosis for patients with resected NSCLC and may help identify patients who would benefit potentially from adjuvant therapies. Globally, the large quantity of translational data incites experimental and clinical studies to implement the characterisation of hypoxia in clinical NSCLC management.

Females and Males Show Differences in Early-Stage Transcriptomic Biomarkers of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

The incidence and mortality rates of lung cancers are different between females and males. Therefore, sex information should be an important part of how to train and optimize a diagnostic model. However, most of the existing studies do not fully utilize this information. This study carried out a comparative investigation between sex-specific models and sex-independent models. Three feature selection algorithms and five classifiers were utilized to evaluate the contribution of the sex information to the detection of early-stage lung cancers. Both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) showed that the sex-specific models outperformed the sex-independent detection of early-stage lung cancers. The Venn plots suggested that females and males shared only a few transcriptomic biomarkers of early-stage lung cancers. Our experimental data suggested that sex information should be included in optimizing disease diagnosis models.

Exhaled breath analysis in disease detection

Investigating the use of exhaled breath analysis to diagnose and monitor different diseases has attracted much interest in recent years. This review introduces conventionally used methods and some emerging technologies aimed at breath analysis and their relevance to lung disease, airway inflammation, gastrointestinal disorders, metabolic disorders and kidney diseases. One section correlates breath components and specific diseases, whereas the other discusses some unique ideas, strategies, and devices to analyze exhaled breath for the diagnosis of some common diseases. This review aims to briefly introduce the potential application of exhaled breath analysis for the diagnosis and screening of various diseases, thereby providing a new avenue for the detection of non-invasive diseases.

Bringing Greater Accuracy to Europe's Healthcare Systems: The Unexploited Potential of Biomarker Testing in Oncology

Rapid and continuing advances in biomarker testing are not being matched by take-up in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. This paper sets out the potential of biomarker testing, the unfolding precision and range of possible diagnosis and prediction, and the many obstacles to adoption. It offers case studies of biomarker testing in breast, ovarian, prostate, lung, thyroid and colon cancers, and derives specific lessons as to the potential and actual use of each of them. It also draws lessons about how to improve access and alignment, and to remedy the data deficiencies that impede development. And it suggests solutions to outstanding issues - notably including funding and the tangled web of obtaining reimbursement or equivalent coverage that Europe's fragmented health system implies. It urges a European evolution towards an initial minimum testing scenario, which would guarantee universal access to a suite of biomarker tests for the currently most common conditions, and, further into the future, to an optimum testing scenario in which a much wider range of biomarker tests would be introduced and become part of a more sophisticated health system articulated around personalised medicine. For exploiting genomics to the full, it argues the need for a new policy framework for Europe. Biomarker testing is not an issue that can be treated in isolation, since the purpose of testing is to improve health. Its use is therefore always closely linked to specific health challenges and needs to be viewed in the broader policy context in the EU and more widely. The paper is the result of extensive engagement with experts and decision makers to develop the framework, and consequently represents a wide consensus of views on how healthcare systems should respond from push and pull factors at local, national and cross-border and EU level. It contains strong views and clear recommendations springing from the convictions of patients, clinicians, academics, medicines authorities, HTA bodies, payers, the diagnostic, pharmaceutical and ICT industries, and national policy makers.

Non-invasive cancer detection using volatile biomarkers: Is urine superior to breath?

In recent years numerous reports have highlighted the options of chemical breath analysis with regard to non-invasive cancer detection. Certain volatile organic compounds (VOC) supposedly present in higher amounts or in characteristic patterns have been suggested as potential biomarkers. However, so far no clinical application based on a specific set of compounds appears to exist. Numerous reports on the capability of sniffer dogs and sensor arrays or electronic noses to distinguish breath of cancer patients and healthy controls supports the concept of genuine cancer-related volatile profiles. However, the actual compounds responsible for the scent are completely unknown and there is no correlation with the potential biomarkers suggested on basis of chemical trace analysis. It is outlined that specific features connected with the VOC analysis in breath - namely small concentrations of volatiles, interfering background concentrations, considerable sampling effort and sample instability, impracticability regarding routine application - stand in the way of substantial progress. The underlying chemical-analytical challenge can only be met considering the severe susceptibility of VOC determination to these adverse conditions. Therefore, the attention is drawn to the needs for appropriate quality assurance/quality control as the most important feature for the reliable quantification of volatiles present in trace concentration. Consequently, the advantages of urine as an alternative matrix for volatile biomarker search in the context of diagnosing lung and other cancers are outlined with specific focus on quality assurance and practicability in clinical chemistry. The headspace over urine samples as the VOC source allows adapting gas chromatographical procedures well-established in water analysis. Foremost, the selection of urine over breath as non-invasive matrix should provide considerably more resilience to adverse effects during sampling and analysis. The most important advantage of urine over breath is seen in the option to partition, dispense, mix, spike, store, and thus to dispatch taylor-made urine samples on demand for quality control measures. Although it is still open at this point if cancer diagnosis supported by non-invasively sampled VOC profiles will ultimately reach clinical application the advantages of urine over breath should significantly facilitate urgently required steps beyond the current proof-of-concept stage and towards standardisation.

A review of breath analysis techniques in head and neck cancer

Cancers of the head and neck region are a severely disabling group of diseases with no method for early detection. Analysis of exhaled breath volatile organic compounds shows promise as biomarkers for early detection and disease monitoring. This article reviews breath analysis in the setting of head and neck cancer, with a practical focus on breath sampling techniques, detection technologies and valid data analysis methods. Title and abstract keyword searches were conducted on PubMed and Embase databases to identify English language studies without a time-period limitation. The main inclusion criteria were human studies comparing head and neck cancer patients to healthy controls using exhaled breath analysis. Multiple breath collection techniques, three major detection technologies and multiple data analysis methods were identified. However, the variability in techniques and lack of methodological standardization does not allow for adequate study replication or data pooling. Twenty-two volatile organic compounds identified in five studies have been reported to discriminate head and neck cancer patients from healthy controls. Breath analysis for detection of head and neck cancer shows promise as a non-invasive detection tool. However, methodological standardization is paramount for future research study design to provide the potential for translating these techniques into routine clinical use.