Detection of lung, breast, colorectal, and prostate cancers from exhaled breath using a single array of nanosensors

Precision detection of select human lung cancer biomarkers and cell lines using honeybee olfactory neural circuitry as a novel gas sensor

Human breath contains biomarkers (odorants) that can be targeted for early disease detection. It is well known that honeybees have a keen sense of smell and can detect a wide variety of odors at low concentrations. Here, we employ honeybee olfactory neuronal circuitry to classify human lung cancer volatile biomarkers at different concentrations and their mixtures at concentration ranges relevant to biomarkers in human breath from parts-per-billion to parts-per-trillion. We also validated this brain-based sensing technology by detecting human non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) cell lines using the 'smell' of the cell cultures. Different lung cancer biomarkers evoked distinct spiking response dynamics in the honeybee antennal lobe neurons indicating that those neurons encoded biomarker-specific information. By investigating lung cancer biomarker-evoked population neuronal responses from the honeybee antennal lobe, we classified individual human lung cancer biomarkers successfully (88% success rate). When we mixed six lung cancer biomarkers at different concentrations to create 'synthetic lung cancer' vs. 'synthetic healthy' human breath, honeybee population neuronal responses were able to classify those complex breath mixtures reliably with exceedingly high accuracy (93-100% success rate with a leave-one-trial-out classification method). Finally, we employed this sensor to detect human NSCLC and SCLC cell lines and we demonstrated that honeybee brain olfactory neurons could distinguish between lung cancer vs. healthy cell lines and could differentiate between different NSCLC and SCLC cell lines successfully (82% classification success rate). These results indicate that the honeybee olfactory system can be used as a sensitive biological gas sensor to detect human lung cancer.

Miniaturized Sniffing Device based on an Array of Fluorescent Carbon Quantum Dots and Metallic Nanoclusters Efficiently Identifies Hematologic Malignancy in Adults

The study demonstrates the potential of an optical nose made by depositing an array of fluorescent nanomaterials on a paper substrate for the early detection of leukemia in adults. This is based on the fact that blood volatile organic compounds (VOCs) are useful leukemia biomarkers. The integrated design was miniaturized and comprised both sensing zones and a sample holding zone, which were installed on a small sheet of paper within a miniature cubic reaction chamber fabricated by using 3D printing technology. The sensing device, comprising seven fluorescent sensing elements, namely, metal nanoclusters, quantum dots, and carbon dots was capable of detecting VOCs in the blood headspace and providing a colorimetric signature that could discriminate between blood samples from healthy and cancerous individuals. A total of 70 new leukemia cases and 51 healthy controls aged 20-50 years were studied. The device required a 60 μL portion of the blood sample and reacted to blood VOCs after 3 h when kept at 50 °C. The imaging data from the device was processed by linear discriminant analysis, and the results confirmed efficient identification of patient samples from healthy samples with 100% accuracy. Overall, the array system is noninvasive (or minimally invasive), portable, fast, inexpensive, and requires only a small amount of blood sample.

Identification potential biomarkers for diagnosis, and progress of breast cancer by using high-pressure photon ionization time-of-flight mass spectrometry

BACKGROUND

In this study, exhaled breath testing has been considered a promising method for the detection and monitoring of breast cancer (BC).

METHODS

A high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) platform was used to detect volatile organic compounds (VOCs) in breath samples. Then, machine learning (ML) models were constructed on VOCs for the diagnosis of BC and its progression monitoring. Ultimately, 1981 women with useable breath samples were included in the study, of whom 937 (47.3 %) had been diagnosed with BC. VOC panels were used for ML model construction for BC detection and progression monitoring.

RESULTS

On the blinded testing cohort, this VOC-based model successfully differentiated patients with and without BC with sensitivity, specificity, and area under receiver operator characteristic curve (AUC) values of 85.9 %, 90.4 %, and 0.946. The corresponding AUC values when differentiating between patients with and without lymph node metastasis (LNM) or between patients with tumor-node-metastasis (TNM) stage 0/I/II or III/IV disease were 0.840 and 0.708, respectively. While developed VOC-based models exhibited poor performance when attempting to differentiate between patients based on pathological patterns (Ductal carcinoma in situ (DCIS) vs Invasive BC (IBC)) or molecular subtypes (Luminal vs Human epidermal growth factor receptor 2 (HER2+) vs Triple-negative BC (TNBC)) of BC.

CONCLUSION

Collectively, the HPPI-TOFMS-based breathomics approaches may offer value for the detection and progression monitoring of BC. Additional research is necessary to explore the fundamental mechanisms of the identified VOCs.

Application of electronic nose technology in the diagnosis of gastrointestinal diseases: a review

Electronic noses (eNoses) are electronic bionic olfactory systems that use sensor arrays to produce response patterns to different odors, thereby enabling the identification of various scents. Gastrointestinal diseases have a high incidence rate and occur in 9 out of 10 people in China. Gastrointestinal diseases are characterized by a long course of symptoms and are associated with treatment difficulties and recurrence. This review offers a comprehensive overview of volatile organic compounds, with a specific emphasis on those detected via the eNose system. Furthermore, this review describes the application of bionic eNose technology in the diagnosis and screening of gastrointestinal diseases based on recent local and international research progress and advancements. Moreover, the prospects of bionic eNose technology in the field of gastrointestinal disease diagnostics are discussed.

Is the development of liquid biopsy for the early detection and the monitoring of breast cancers on its way of overtaking mammography?

Mammography, as of today, is used as a gold standard for screening, diagnosing, and monitoring breast cancer (BC). While overall beneficial, it presents several downsides, such as limitations in accuracy, relatively high costs, and dependence on heavy infrastructure, greatly limiting accessibility for the entire global target population. There is currently no established alternative to mammography, and overcoming this major challenge is a hot topic in research and technology. One avenue for tackling this issue is the development of highly sensitive and specific non-invasive blood tests for the early diagnosis and follow-up of breast cancer. This paper discusses the limitations of mammography and recapitulates the blood tests already available, those under development, and future developments in this field.

Unveiling Colorectal Cancer Biomarkers: Harnessing Biosensor Technology for Volatile Organic Compound Detection

Conventional screening options for colorectal cancer (CRC) detection are mainly direct visualization and invasive methods including colonoscopy and flexible sigmoidoscopy, which must be performed in a clinical setting and may be linked to adverse effects for some patients. Non-invasive CRC diagnostic tests such as computed tomography colonography and stool tests are either too costly or less reliable than invasive ones. On the other hand, volatile organic compounds (VOCs) are potentially ideal non-invasive biomarkers for CRC detection and monitoring. The present review is a comprehensive presentation of the current state-of-the-art VOC-based CRC diagnostics, with a specific focus on recent advancements in biosensor design and application. Among them, breath-based chromatography pattern analysis and sampling techniques are overviewed, along with nanoparticle-based optical and electrochemical biosensor approaches. Limitations of the currently available technologies are also discussed with an outlook for improvement in combination with big data analytics and advanced instrumentation, as well as expanding the scope and specificity of CRC-related volatile biomarkers.

Development of an organ-on-chip model for the detection of volatile organic compounds as potential biomarkers of tumour progression

Early detection of tumours remains a significant challenge due to their invasive nature and the limitations of current monitoring techniques. Liquid biopsies have emerged as a minimally invasive diagnostic approach, wherein volatile organic compounds (VOCs) show potential as compelling candidates. However, distinguishing tumour-specific VOCs is difficult due to the presence of gases from non-tumour tissues and environmental factors. Therefore, it is essential to develop preclinical models that accurately mimic the intricate tumour microenvironment to induce cellular metabolic changes and secretion of tumour-associated VOCs. In this study, a microfluidic device was used to recreate the ischaemic environment within solid tumours for the detection of tumour-derived VOCs. The system represents a significant advance in understanding the role of VOCs as biomarkers for early tumour detection and holds the potential to improve patient prognosis; particularly for inaccessible and rapidly progressing tumours such as glioblastoma.

Potentiality of phosphide-based nanotubes for breast cancer detection: A DFT investigation

Breast cancer is one of the most basilisk cancers for women due to its high mortality rate which can be prevented drastically with early-stage detection. In this work, the adsorption mechanism of two volatile organic compounds that are present in the breath of breast cancer patients, 2-Methyloctane and 3, 3-Dimethylpentane, has been investigated on aluminum phosphide nanotubes (AlPNT) and gallium phosphide nanotubes (GaPNT) in order to understand their feasibility as sensor materials to diagnosis breast cancer at early stage. We have used the quantum mechanical approach by employing density functional theory using B3LYP-D3 hybrid potential for noncovalent interaction along with the LanL2DZ basis in the Gaussian 09 software package. The adsorption properties analyses suggest that GaPNT exhibits better sensing behavior as well as proclaims 12.6% greater adsorption energy for 2-Methyloctane and 9.4% greater adsorption energy for 3, 3-Dimethylpentane than AlPNT. Other structural and electric properties analyses satisfy this conclusion and suggest that GaPNT exhibits higher stability than AlPNT and could possibly be a potential candidate for developing biosensors to detect breast cancer at the preliminary stages.

A multi-omics method for breast cancer diagnosis based on metabolites in exhaled breath, ultrasound imaging, and basic clinical information

Background and aims

Through a nested cohort study, we evaluated the diagnostic performance of breath-omics in differentiating between benign and malignant breast lesions, and assessed the diagnostic performance of a multi-omics approach that combines breath-omics, ultrasound radiomics, and clinic-omics in distinguishing between benign and malignant breast lesions.

Materials and methods

We recruited 1,723 consecutive patients who underwent an automated breast volume scanner (ABVS) examination. Breath samples were collected and analyzed by high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOF-MS) to obtain breath-omics features. 238 of 1,723 enrolled participants have received pathological confirmation of breast nodules finally. The breast lesions of the 238 participants were contoured manually based on ABVS images for ultrasound radiomics feature calculation. Then, single- and multi-omics models were constructed and evaluated for breast nodules diagnosis via five-fold cross-validation.

Results

The area under the curve (AUC) of the breath-omics model was 0.855. In comparison, the multi-omics model demonstrated superior diagnostic performance for breast cancer, with sensitivity, specificity, and AUC of 84.1 %, 89.9 %, and 0.946, respectively. The multi-omics performance was comparable to that of the Breast Imaging Reporting and Data System (BI-RADS) classification via senior ultrasound physician evaluation.

Conclusion

The multi-omics approach combining metabolites in exhaled breath, ultrasound imaging, and basic clinical information exhibits superior diagnostic performance and promises to be a non-invasive and reliable tool for breast cancer diagnosis.

Pilot study for bladder cancer detection with volatile organic compounds using ion mobility spectrometry: a novel urine-based approach

PURPOSE

Despite many efforts, no reliable urinary marker system has so far shown the potential to substitute cystoscopy. Measuring volatile organic compounds (VOCs) from urine is a promising alternative. VOCs are metabolic products which can be measured from the headspace of urine samples. Previous studies confirmed that the urine of bladder tumor patients has a different VOC profile than healthy controls. In this pilot study, the feasibility of discriminating VOCs from urine of bladder cancer patients from that of healthy control subjects was investigated. Aim of this study was to investigate whether VOC-based diagnosis of bladder cancer from urine samples is feasible using multicapillary column ion mobility spectrometry (MCC/IMS) and to identify potential molecular correlates to the relevant analytes.

METHODS

Headspace measurements of urine samples of 30 patients with confirmed transitional cell carcinoma (TCC) and 30 healthy controls were performed using MCC/IMS. In the results of the measurements, peaks showing significant differences between both groups were identified and implemented into a decision tree with respect to achieve group separation. Molecular correlates were predicted using a pre-defined dataset.

RESULTS

Eight peaks with significantly differing intensity were identified, 5 of which were highly significant. Using a six-step decision tree, MCC/IMS showed a sensitivity of 90% and specificity of 100% in group separation.

CONCLUSION

VOC-based detection of bladder cancer is feasible. MCC/IMS is a suitable method for urine-based diagnosis and should be further validated. The molecular characteristics and metabolic background of the analytes require further workup.

Exhaled volatile organic compounds in the detection of colorectal cancer: a systematic review and meta-analysis

There is an apparent need for novel non-invasive colorectal cancer (CRC) screening tests that are more acceptable to patients and can reliably detect CRC or reduce the number of unnecessary colonoscopies performed in cancer-free patients. An emerging number of studies demonstrate the potential value of exhaled volatile organic compounds (VOCs) as a diagnostic and triaging test for CRC. A systematic appraisal and meta-analysis of the published evidence was done to determine whether exhaled VOCs can be used in the detection and screening of CRC. Nine electronic databases were searched from inception of the databases until August 2020. Quantitative and descriptive data of CRC patients and healthy control (HC) participants who underwent VOCs breath analysis was extracted. In addition, where possible, sampling methods, analytical platforms, processors, and specific breath biomarkers found in each study were recorded. Fourteen articles were included in the systematic review with 491 colorectal patients and 754 HC participants (n=1245). Sub-group meta-analysis was conducted on nine of those articles and the pooled sensitivity was estimated to be 0.89 (95 % CI = 0.80-0.99) whereas specificity was 0.83 (95 % CI = 0.74-0.92). Heterogeneity of pooled sensitivity and specificity was estimated as I2=11.11 %. Although this study was limited by small sample size and different analytical platforms, the proposed future framework resolves such limitations and standardizes future research. It is reasonable to deduce that VOCs breath analysis is certainly a field of research that can progress to replace traditional methods within the framework of CRC screening and diagnosis.

Ammonia Detection by Electronic Noses for a Safer Work Environment

Providing employees with proper work conditions should be one of the main concerns of any employer. Even so, in many cases, work shifts chronically expose the workers to a wide range of potentially harmful compounds, such as ammonia. Ammonia has been present in the composition of products commonly used in a wide range of industries, namely production in lines, and also laboratories, schools, hospitals, and others. Chronic exposure to ammonia can yield several diseases, such as irritation and pruritus, as well as inflammation of ocular, cutaneous, and respiratory tissues. In more extreme cases, exposure to ammonia is also related to dyspnea, progressive cyanosis, and pulmonary edema. As such, the use of ammonia needs to be properly regulated and monitored to ensure safer work environments. The Occupational Safety and Health Administration and the European Agency for Safety and Health at Work have already commissioned regulations on the acceptable limits of exposure to ammonia. Nevertheless, the monitoring of ammonia gas is still not normalized because appropriate sensors can be difficult to find as commercially available products. To help promote promising methods of developing ammonia sensors, this work will compile and compare the results published so far.

Diagnostic performance of volatile organic compounds analysis and electronic noses for detecting colorectal cancer: a systematic review and meta-analysis

Introduction

The detection of Volatile Organic Compounds (VOCs) could provide a potential diagnostic modality for the early detection and surveillance of colorectal cancers. However, the overall diagnostic accuracy of the proposed tests remains uncertain.

Objective

This systematic review is to ascertain the diagnostic accuracy of using VOC analysis techniques and electronic noses (e-noses) as noninvasive diagnostic methods for colorectal cancer within the realm of clinical practice.

Methods

A systematic search was undertaken on PubMed, EMBASE, Web of Science, and the Cochrane Library to scrutinize pertinent studies published from their inception to September 1, 2023. Only studies conducted on human subjects were included. Meta-analysis was performed using a bivariate model to obtain summary estimates of sensitivity, specificity, and positive and negative likelihood ratios. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was deployed for quality assessment. The protocol for this systematic review was registered in PROSPERO, and PRISMA guidelines were used for the identification, screening, eligibility, and selection process.

Results

This review encompassed 32 studies, 22 studies for VOC analysis and 9 studies for e-nose, one for both, with a total of 4688 subjects in the analysis. The pooled sensitivity and specificity of VOC analysis for CRC detection were 0.88 (95% CI, 0.83-0.92) and 0.85 (95% CI, 0.78-0.90), respectively. In the case of e-nose, the pooled sensitivity was 0.87 (95% CI, 0.83-0.90), and the pooled specificity was 0.78 (95% CI, 0.62-0.88). The area under the receiver operating characteristic analysis (ROC) curve for VOC analysis and e-noses were 0.93 (95% CI, 0.90-0.95) and 0.90 (95% CI, 0.87-0.92), respectively.

Conclusion

The outcomes of this review substantiate the commendable accuracy of VOC analysis and e-nose technology in detecting CRC. VOC analysis has a higher specificity than e-nose for the diagnosis of CRC and a sensitivity comparable to that of e-nose. However, numerous limitations, including a modest sample size, absence of standardized collection methods, lack of external validation, and a notable risk of bias, were identified. Consequently, there exists an imperative need for expansive, multi-center clinical studies to elucidate the applicability and reproducibility of VOC analysis or e-nose in the noninvasive diagnosis of colorectal cancer.

Systematic review registration

https://www.crd.york.ac.uk/prospero/#recordDetails, identifier CRD42023398465.

VOC-based detection of prostate cancer using an electronic nose and ion mobility spectrometry: A novel urine-based approach

BACKGROUND

Many diseases leave behind specific metabolites which can be detected from breath and urine as volatile organic compounds (VOC). Our group previously described VOC-based methods for the detection of bladder cancer and urinary tract infections. This study investigated whether prostate cancer can be diagnosed from VOCs in urine headspace.

METHODS

For this pilot study, mid-stream urine samples were collected from 56 patients with histologically confirmed prostate cancer. A control group was formed with 53 healthy male volunteers matched for age who had recently undergone a negative screening by prostate-specific antigen (PSA) and digital rectal exam. Headspace measurements were performed with the electronic nose Cyranose 320TM . Statistical comparison was performed using principal component analysis, calculating Mahalanobis distance, and linear discriminant analysis. Further measurements were carried out with ion mobility spectrometry (IMS) to compare detection accuracy and to identify potential individual analytes. Bonferroni correction was applied for multiple testing.

RESULTS

The electronic nose yielded a sensitivity of 77% and specificity of 62%. Mahalanobis distance was 0.964, which is indicative of limited group separation. IMS identified a total of 38 individual analytical peaks, two of which showed significant differences between groups (p < 0.05). To discriminate between tumor and controls, a decision tree with nine steps was generated. This model led to a sensitivity of 98% and specificity of 100%.

CONCLUSIONS

VOC-based detection of prostate cancer seems feasible in principle. While the first results with an electronic nose show some limitations, the approach can compete with other urine-based marker systems. However, it seems less reliable than PSA testing. IMS is more accurate than the electronic nose with promising sensitivity and specificity, which warrants further research. The individual relevant metabolites identified by IMS should further be characterized using gas chromatography/mass spectrometry to facilitate potential targeted rapid testing.

Breath Fingerprint of Colorectal Cancer Patients Based on the Gas Chromatography-Mass Spectrometry Analysis

The human body emits a multitude of volatile organic compounds (VOCs) via tissues and various bodily fluids or exhaled breath. These compounds collectively create a distinctive chemical profile, which can potentially be employed to identify changes in human metabolism associated with colorectal cancer (CRC) and, consequently, facilitate the diagnosis of this disease. The main goal of this study was to investigate and characterize the VOCs' chemical patterns associated with the breath of CRC patients and controls and identify potential expiratory markers of this disease. For this purpose, gas chromatography-mass spectrometry was applied. Collectively, 1656 distinct compounds were identified in the breath samples provided by 152 subjects. Twenty-two statistically significant VOCs (p-xylene; hexanal; 2-methyl-1,3-dioxolane; 2,2,4-trimethyl-1,3-pentanediol diisobutyrate; hexadecane; nonane; ethylbenzene; cyclohexanone; diethyl phthalate; 6-methyl-5-hepten-2-one; tetrahydro-2H-pyran-2-one; 2-butanone; benzaldehyde; dodecanal; benzothiazole; tetradecane; 1-dodecanol; 1-benzene; 3-methylcyclopentyl acetate; 1-nonene; toluene) were observed at higher concentrations in the exhaled breath of the CRC group. The elevated levels of these VOCs in CRC patients' breath suggest the potential for these compounds to serve as biomarkers for CRC.

Prediction of positive pulmonary nodules based on machine learning algorithm combined with central carbon metabolism data

BACKGROUND

Lung cancer causes a huge disease burden, and early detection of positive pulmonary nodules (PPNs) as an early sign of lung cancer is extremely important for effective intervention. It is necessary to develop PPNs risk recognizer based on machine learning algorithm combined with central carbon metabolomics.

METHODS

The study included 2248 participants at high risk for lung cancer from the Ma'anshan Community Lung Cancer Screening cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to screen 18 central carbon-related metabolites in plasma, recursive feature elimination (RFE) was used to select all 42 features, followed by five machine learning algorithms for model development. The performance of the model was evaluated using area under the receiver operator characteristic curve (AUC), accuracy, precision, recall, and F1 scores. In addition, SHapley Additive exPlanations (SHAP) was performed to assess the interpretability of the final selected model and to gain insight into the impact of features on the predicted results.

RESULTS

Finally, the two prediction models based on the random forest (RF) algorithm performed best, with AUC values of 0.87 and 0.83, respectively, better than other models. We found that homogentisic acid, fumaric acid, maleic acid, hippuric acid, gluconic acid, and succinic acid played a significant role in both PPNs prediction model and NPNs vs PPNs model, while 2-oxadipic acid only played a role in the former model and phosphopyruvate only played a role in the NPNs vs PPNs model. This model demonstrates the potential of central carbon metabolism for PPNs risk prediction and identification.

CONCLUSION

We developed a series of predictive models for PPNs, which can help in the early detection of PPNs and thus reduce the risk of lung cancer.

Knowledge of Non-Invasive Biomarkers of Breast Cancer, Risk Factors, and BSE Practices Among Nursing Undergraduates in Farasan Island, KSA

Background of the Study

Mammograms are sometimes met with issues of overdiagnosis and underdiagnosis; therefore, they are less reliable in identifying cancer in women with dense breasts. As a result, it is critical to be aware of other sensitive screening techniques for the early diagnosis of breast cancer.

Aim

The ultimate objective of this study was to assess the knowledge of nursing undergraduates regarding non-invasive biomarkers, such as volatile organic compounds in breath, nipple aspirate fluid, sweat, urine, and tears, for the early detection of breast cancer to help improve patient care, determine the risk factors, and encourage practice of breast self-examination.

Methods

Cross-sectional research was done in the Department of Nursing at Farasan campus using a self-structured questionnaire as the study tool. A total of 260 students willingly participated. The study tool had evaluation questions focused on the non-invasive biomarkers of breast cancer, risk factors, and breast self-examination practices to collect data. The data were subjected to descriptive and inferential statistics. The statistical significance was calculated at P < .05. Data analyses were done using Microsoft Excel (2013).

Results

A significant knowledge gap existed among the study participants about the non-invasive biomarkers of breast cancer. A lesser percentage of students (25%) stated that they do breast self-examination on a monthly basis. The most common reasons for not doing the breast self-examination were "not knowing how to do the breast self-examination" (77.3%), fear of a positive diagnosis (53.9%), thinking that they are not at risk as all were in their teens and hence not required (44.7%), and lack of time (48.7%). Age and frequency of breast self-examination were significantly associated (P < .05) as those few students (22.7%) who were doing breast self-examination practices every 2-4 months belonged to a higher study year. Furthermore, knowledge regarding incidence rates and health care expenditure by the government on breast cancer was also significantly low (P < .05).

Conclusions

Outcomes would help prioritize actions to help future nurses better understand breast cancer, allowing them to extend patient care in the best way possible.

Advancing Colorectal Cancer Diagnosis with AI-Powered Breathomics: Navigating Challenges and Future Directions

Early detection of colorectal cancer is crucial for improving outcomes and reducing mortality. While there is strong evidence of effectiveness, currently adopted screening methods present several shortcomings which negatively impact the detection of early stage carcinogenesis, including low uptake due to patient discomfort. As a result, developing novel, non-invasive alternatives is an important research priority. Recent advancements in the field of breathomics, the study of breath composition and analysis, have paved the way for new avenues for non-invasive cancer detection and effective monitoring. Harnessing the utility of Volatile Organic Compounds in exhaled breath, breathomics has the potential to disrupt colorectal cancer screening practices. Our goal is to outline key research efforts in this area focusing on machine learning methods used for the analysis of breathomics data, highlight challenges involved in artificial intelligence application in this context, and suggest possible future directions which are currently considered within the framework of the European project ONCOSCREEN.

Breath Analysis for Lung Cancer Early Detection-A Clinical Study

This clinical study presents a comprehensive investigation into the utility of breath analysis as a non-invasive method for the early detection of lung cancer. The study enrolled 14 lung cancer patients, 14 non-lung cancer controls with diverse medical conditions, and 3 tuberculosis (TB) patients for biomarker discovery. Matching criteria including age, gender, smoking history, and comorbidities were strictly followed to ensure reliable comparisons. A systematic breath sampling protocol utilizing a BIO-VOC sampler was employed, followed by VOC analysis using Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC/MS). The resulting VOC profiles were subjected to stringent statistical analysis, including Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA), Kruskal-Wallis test, and Receiver Operating Characteristic (ROC) analysis. Notably, 13 VOCs exhibited statistically significant differences between lung cancer patients and controls. The combination of eight VOCs (hexanal, heptanal, octanal, benzaldehyde, undecane, phenylacetaldehyde, decanal, and benzoic acid) demonstrated substantial discriminatory power with an area under the curve (AUC) of 0.85, a sensitivity of 82%, and a specificity of 76% in the discovery set. Validation in an independent cohort yielded an AUC of 0.78, a sensitivity of 78%, and a specificity of 64%. Further analysis revealed that elevated aldehyde levels in lung cancer patients' breath could be attributed to overactivated Alcohol Dehydrogenase (ADH) pathways in cancerous tissues. Addressing methodological challenges, this study employed a matching of physiological and pathological confounders, controlled room air samples, and standardized breath sampling techniques. Despite the limitations, this study's findings emphasize the potential of breath analysis as a diagnostic tool for lung cancer and suggest its utility in differentiating tuberculosis from lung cancer. However, further research and validation are warranted for the translation of these findings into clinical practice.

The power of phages: revolutionizing cancer treatment

Cancer is a devastating disease with a high global mortality rate and is projected to increase further in the coming years. Current treatment options, such as chemotherapy and radiation therapy, have limitations including side effects, variable effectiveness, high costs, and limited availability. There is a growing need for alternative treatments that can target cancer cells specifically with fewer side effects. Phages, that infect bacteria but not eukaryotic cells, have emerged as promising cancer therapeutics due to their unique properties, including specificity and ease of genetic modification. Engineered phages can transform cancer treatment by targeting cancer cells while sparing healthy ones. Phages exhibit versatility as nanocarriers, capable of delivering therapeutic agents like gene therapy, immunotherapy, and vaccines. Phages are extensively used in vaccine development, with filamentous, tailed, and icosahedral phages explored for different antigen expression possibilities. Engineered filamentous phages bring benefits such as built in adjuvant properties, cost-effectiveness, versatility in multivalent formulations, feasibility of oral administration, and stability. Phage-based vaccines stimulate the innate immune system by engaging pattern recognition receptors on antigen-presenting cells, enhancing phage peptide antigen presentation to B-cells and T-cells. This review presents recent phage therapy advances and challenges in cancer therapy, exploring its versatile tools and vaccine potential.

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

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

A detection model for cognitive dysfunction based on volatile organic compounds from a large Chinese community cohort

INTRODUCTION

We explored whether volatile organic compound (VOC) detection can serve as a screening tool to distinguish cognitive dysfunction (CD) from cognitively normal (CN) individuals.

METHODS

The cognitive function of 1467 participants was assessed and their VOCs were detected. Six machine learning algorithms were conducted and the performance was determined. The plasma neurofilament light chain (NfL) was measured.

RESULTS

Distinguished VOC patterns existed between CD and CN groups. The CD detection model showed good accuracy with an area under the receiver-operating characteristic curve (AUC) of 0.876. In addition, we found that 10 VOC ions showed significant differences between CD and CN individuals (p < 0.05); three VOCs were significantly related to plasma NfL (p < 0.005). Moreover, a combination of VOCs with NfL showed the best discriminating power (AUC = 0.877).

DISCUSSION

Detection of VOCs from exhaled breath samples has the potential to provide a novel solution for the dilemma of CD screening.

Colorectal cancer diagnostic biomarkers: Beyond faecal haemoglobin

Colorectal cancer (CRC) is the third most common cancer worldwide, and the second commonest cause of cancer deaths worldwide. One of the most important prognostic factors, and thus a potential target for improving cancer care, is the stage of cancer at diagnosis. Earlier stage diagnosis is associated with better prognosis and longer survival times after treatment. At the same time, the use of targeted therapies and immunotherapy is improving CRC outcomes. Diagnostic biomarkers are key to both early detection and prediction of treatment responses. Currently faecal immunochemical testing for haemoglobin is perhaps the most widespread CRC diagnostic biomarker. However other biomarkers are approved for clinical use and others are in the validation stage of research prior to clinical use. This review focuses on these the evidence behind these biomarkers, their current and potential future use.

Recent Advances in Gas Detection Methodologies with a Special Focus on Environmental Sensing and Health Monitoring Applications─A Critical Review

With the expansion of the Internet-of-Things (IoT), the use of gas sensors in the field of wearable technology, smart devices, and smart homes has increased manifold. These gas sensors have two key applications─one is the detection of gases present in the environment and the other is the detection of Volatile Organic Compounds (VOCs) that are found in the breath. In this review, we focus systematically on the advancements in the field of various spectroscopic methods such as mass spectrometry-based analysis and point-of-care approach to detect VOCs and gases for environmental monitoring and disease diagnosis. Additionally, we highlight the development of smart sensors that work on the principle of electrochemical detection and provide examples of the same through an extensive literature review. At the end of this review, we highlight various challenges and future perspectives.

Species-Selective Detection of Volatile Organic Compounds by Ionic Liquid-Based Electrolyte Using Electrochemical Methods

The detection of volatile organic compounds (VOCs) is an important topic for environmental safety and public health. However, the current commercial VOC detectors suffer from cross-sensitivity and low reproducibility. In this work, we present species-selective detection for VOCs using an electrochemical cell based on ionic liquid (IL) electrolytes with features of high selectivity and reliability. The voltammograms measured with the IL-based electrolyte absorbing different VOCs exhibited species-selective features that were extracted and classified by linear discriminant analysis (LDA). The detection system could identify as many as four types of VOCs, including methanol, ethanol, acetone, formaldehyde, and additional water. A mixture of methanol and formaldehyde was detected as well. The sample required for the VOCs classification system was 50 μL, or 1.164 mmol, on average. The response time for each VOC measurement is as fast as 24 s. The volume of VOCs such as formaldehyde in solution could also be quantified by LDA and electrochemical impedance spectroscopy techniques, respectively. The system showed a tunable detection range for 1.6 and 16% (w/v) CH2O solution by adjusting the composition of the electrolyte. The limit of detection was as low as 1 μL. For the 1.6% CH2O solution, the linearity calibration range was determined to be from 5.30 to 53.00 μmol with a limit of detection at 0.53 μmol. The mechanisms for VOCs determination and quantification are also thoroughly discussed. It is expected that this work could provide a new insight into the concept of electrochemical detection of VOCs with machine learning analysis and be applied to both VOCs gas monitoring and fluid detection.

Pancreatic Cancer and Detection Methods

The pancreas is a vital organ with exocrine and endocrine functions. Pancreatitis is an inflammation of the pancreas caused by alcohol consumption and gallstones. This condition can heighten the risk of pancreatic cancer (PC), a challenging disease with a high mortality rate. Genetic and epigenetic factors contribute significantly to PC development, along with other risk factors. Early detection is crucial for improving PC outcomes. Diagnostic methods, including imagining modalities and tissue biopsy, aid in the detection and analysis of PC. In contrast, liquid biopsy (LB) shows promise in early tumor detection by assessing biomarkers in bodily fluids. Understanding the function of the pancreas, associated diseases, risk factors, and available diagnostic methods is essential for effective management and early PC detection. The current clinical examination of PC is challenging due to its asymptomatic early stages and limitations of highly precise diagnostics. Screening is recommended for high-risk populations and individuals with potential benign tumors. Among various PC screening methods, the N-NOSE plus pancreas test stands out with its high AUC of 0.865. Compared to other commercial products, the N-NOSE plus pancreas test offers a cost-effective solution for early detection. However, additional diagnostic tests are required for confirmation. Further research, validation, and the development of non-invasive screening methods and standardized scoring systems are crucial to enhance PC detection and improve patient outcomes. This review outlines the context of pancreatic cancer and the challenges for early detection.

Selectivity of Exhaled Breath Biomarkers of Lung Cancer in Relation to Cancer of Other Localizations

Lung cancer is a leading cause of death worldwide, mostly due to diagnostics in the advanced stage. Therefore, the development of a quick, simple, and non-invasive diagnostic tool to identify cancer is essential. However, the creation of a reliable diagnostic tool is possible only in case of selectivity to other diseases, particularly, cancer of other localizations. This paper is devoted to the study of the variability of exhaled breath samples among patients with lung cancer and cancer of other localizations, such as esophageal, breast, colorectal, kidney, stomach, prostate, cervix, and skin. For this, gas chromatography-mass spectrometry (GC-MS) was used. Two classification models were built. The first model separated patients with lung cancer and cancer of other localizations. The second model classified patients with lung, esophageal, breast, colorectal, and kidney cancer. Mann-Whitney U tests and Kruskal-Wallis H tests were applied to identify differences in investigated groups. Discriminant analysis (DA), gradient-boosted decision trees (GBDT), and artificial neural networks (ANN) were applied to create the models. In the case of classifying lung cancer and cancer of other localizations, average sensitivity and specificity were 68% and 69%, respectively. However, the accuracy of classifying groups of patients with lung, esophageal, breast, colorectal, and kidney cancer was poor.

Clinical Possibility of Caenorhabditis elegans as a Novel Evaluation Tool for Esophageal Cancer Patients Receiving Chemotherapy: A Prospective Study

BACKGROUND

The nematode Caenorhabditis elegans (C. elegans) possesses a sophisticated sense of smell and is used for a novel cancer screening test that utilizes the chemotaxis index. We designed a single-institution, prospective study to confirm the ability of Nematode Nose (N-NOSE) to determine preoperative chemotherapy's efficacy for esophageal cancer patients.

PATIENTS AND METHODS

We investigated the predictability of N-NOSE screening for the clinical effects of preoperative chemotherapy for esophageal cancer patients receiving radical surgery. The index reduction score (IRS) was calculated via the chemotaxis of C. elegans at three points: before treatment, before surgery, and after surgery, and its clinical relevance was examined.

RESULT

Thirty-nine patients with esophageal cancer were enrolled from August 2020 to December 2021, and 30 patients receiving radical surgery were examined. Complete response or partial response was achieved in 23 cases (76.7%). When the target of the treatment effect was complete response only, the prediction accuracies of the IRS calculated by area under the curve was 0.85 (95% Confidence interval: 0.62-1) in clinically achieving complete response group, and the sensitivity and specificity were 1 and 0.63, respectively.

CONCLUSION

Index reduction score using N-NOSE screening may reflect the efficacy of chemotherapy for esophageal cancer patients. A large-scale prospective study at multiple centers is desired in the future.

Breath Volatile Organic Compounds in Surveillance of Gastric Cancer Patients following Radical Surgical Management

As of today, there is a lack of a perfect non-invasive test for the surveillance of patients for potential relapse following curative treatment. Breath volatile organic compounds (VOCs) have been demonstrated to be an accurate diagnostic tool for gastric cancer (GC) detection; here, we aimed to prove the yield of the markers in surveillance, i.e., following curative surgical management. Patients were sampled in regular intervals before and within 3 years following curative surgery for GC; gas chromatography-mass spectrometry (GC-MS) and nanosensor technologies were used for the VOC assessment. GC-MS measurements revealed a single VOC (14b-Pregnane) that significantly decreased at 12 months, and three VOCs (Isochiapin B, Dotriacontane, Threitol, 2-O-octyl-) that decreased at 18 months following surgery. The nanomaterial-based sensors S9 and S14 revealed changes in the breath VOC content 9 months after surgery. Our study results confirm the cancer origin of the particular VOCs, as well as suggest the value of breath VOC testing for cancer patient surveillance, either during the treatment phase or thereafter, for potential relapse.

Smelling the Disease: Diagnostic Potential of Breath Analysis

Breath analysis is a relatively recent field of research with much promise in scientific and clinical studies. Breath contains endogenously produced volatile organic components (VOCs) resulting from metabolites of ingested precursors, gut and air-passage bacteria, environmental contacts, etc. Numerous recent studies have suggested changes in breath composition during the course of many diseases, and breath analysis may lead to the diagnosis of such diseases. Therefore, it is important to identify the disease-specific variations in the concentration of breath to diagnose the diseases. In this review, we explore methods that are used to detect VOCs in laboratory settings, VOC constituents in exhaled air and other body fluids (e.g., sweat, saliva, skin, urine, blood, fecal matter, vaginal secretions, etc.), VOC identification in various diseases, and recently developed electronic (E)-nose-based sensors to detect VOCs. Identifying such VOCs and applying them as disease-specific biomarkers to obtain accurate, reproducible, and fast disease diagnosis could serve as an alternative to traditional invasive diagnosis methods. However, the success of VOC-based identification of diseases is limited to laboratory settings. Large-scale clinical data are warranted for establishing the robustness of disease diagnosis. Also, to identify specific VOCs associated with illness states, extensive clinical trials must be performed using both analytical instruments and electronic noses equipped with stable and precise sensors.

Increasing the accuracy of colorectal cancer screening

INTRODUCTION

Colorectal cancer (CRC) is a major health issue, being responsible for nearly 10% of all cancer-related deaths. Since CRC is often an asymptomatic or paucisymptomatic disease until it reaches advanced stages, screening is crucial for the diagnosis of preneoplastic lesions or early CRC.

AREAS COVERED

The aim of this review is to summarize the literature evidence on currently available CRC screening tools, with their pros and cons, focusing on the level of accuracy reached by each test over time. We also provide an overview of novel technologies and scientific advances that are currently being investigated and that in the future may represent real game-changers in the field of CRC screening.

EXPERT OPINION

We suggest that best screening modalities are annual or biennial FIT and colonoscopy every 10 years. We believe that the introduction of artificial intelligence (AI)-tools in the CRC screening field could lead to a significant improvement of the screening efficacy in reducing CRC incidence and mortality in the future. More resources should be put into implementing CRC programmes and support research project to further increase accuracy of CRC screening tests and strategies.

A Systematic Review and Meta-Analysis: Volatile Organic Compound Analysis in the Detection of Hepatobiliary and Pancreatic Cancers

BACKGROUND

Hepatobiliary cancers are notoriously difficult to detect, frequently leading to diagnosis in later stages of disease when curative treatment is not an option. The currently used biomarkers such as AFP (alpha-fetoprotein) and CA19.9 lack sensitivity and specificity. Hence, there is an unmet need for an alternative biomarker.

AIM

To evaluate the diagnostic accuracy of volatile organic compounds (VOCs) for the detection of hepatobiliary and pancreatic cancers.

METHODS

A systematic review of VOCs' use in the detection of hepatobiliary and pancreatic cancers was performed. A meta-analysis was performed using the software R. Heterogeneity was explored through meta-regression analysis.

RESULTS

A total of 18 studies looking at 2296 patients were evaluated. Pooled sensitivity and specificity of VOCs for the detection of hepatobiliary and pancreatic cancer were 0.79 (95% CI, 0.72-0.85) and 0.81 (97.5% CI, 0.76-0.85), respectively. The area under the curve was 0.86. Meta-regression analysis showed that the sample media used contributed to heterogeneity. Bile-based VOCs showed the highest precision values, although urine and breath are preferred for their feasibility.

CONCLUSIONS

Volatile organic compounds have the potential to be used as an adjunct tool to aid in the early diagnosis of hepatobiliary cancers.

Chemiresistive Sensor Array with Nanostructured Interfaces for Detection of Human Breaths with Simulated Lung Cancer Breath VOCs

Timely screening of lung cancer represents a challenging task for early diagnosis and treatment, which calls for reliable, low-cost, and noninvasive detection tools. One type of promising tools for early-stage cancer detection is breath analyzers or sensors that detect breath volatile organic compounds (VOCs) as biomarkers in exhaled breaths. However, a major challenge is the lack of effective integration of the different sensor system components toward the desired portability, sensitivity, selectivity, and durability for many of the current breath sensors. In this report, we demonstrate herein a portable and wireless breath sensor testing system integrated with sensor electronics, breath sampling, data processing, and sensor arrays derived from nanoparticle-structured chemiresistive sensing interfaces for detection of VOCs relevant to lung cancer biomarkers in human breaths. In addition to showing the sensor viability for the targeted application by theoretical simulations of chemiresistive sensor array responses to the simulated VOCs in human breaths, the sensor system was tested experimentally with different combinations of VOCs and human breath samples spiked with lung cancer-specific VOCs. The sensor array exhibits high sensitivity to lung cancer VOC biomarkers and mixtures, with a limit of detection as low as 6 ppb. The results from testing the sensor array system in detecting breath samples with simulated lung cancer VOC constituents have demonstrated an excellent recognition rate in discriminating healthy human breath samples and those with lung cancer VOCs. The recognition statistics were analyzed, showing the potential viability and optimization toward achieving the desired sensitivity, selectivity, and accuracy in the breath screening of lung cancer.

Chemoresistive Nanosensors Employed to Detect Blood Tumor Markers in Patients Affected by Colorectal Cancer in a One-Year Follow Up

Colorectal cancer (CRC) represents 10% of the annual tumor diagnosis and deaths occurring worldwide. Given the lack of specific symptoms, which could determine a late diagnosis, the research for specific CRC biomarkers and for innovative low-invasive methods to detect them is crucial. Therefore, on the basis of previously published results, some volatile organic compounds (VOCs), detectable through gas sensors, resulted in particularly promising CRC biomarkers, making these sensors suitable candidates to be employed in CRC screening devices. A new device was employed here to analyze the exhalations of blood samples collected from CRC-affected patients at different stages of their pre- and post-surgery therapeutic path, in order to assess the sensor’s capability for discriminating among these samples. The stages considered were: the same day of the surgical treatment (T1); before the hospital discharge (T2); after one month and after 10–12 months from surgery (T3 and T4, respectively). This device, equipped with four different sensors based on different metal–oxide mixtures, enabled a distinction between T1 and T4 with a sensitivity and specificity of 93% and 82%, respectively, making it suitable for clinical follow-up protocols, patient health status monitoring and to detect possible post-treatment relapses.

Mir-153-3p Modulates the Breast Cancer Cells' Chemosensitivity to Doxorubicin by Targeting KIF20A

Breast cancer is considered the solid tumor most sensitive to chemotherapy. However, it can become resistant to various chemotherapeutic drugs, including doxorubicin, which triggers cell death by intercalation between DNA bases, free radical formation, and topoisomerase II inhibition. When drug resistance develops, several miRNAs are dysregulated, suggesting that miRNAs may play a significant role in resistance formation. In the current study, we investigated how doxorubicin sensitivity of breast cancer cells is affected by miR-153-3p and its target gene. The MTT method was used to determine the chemo-sensitizing effect of miR-153-3p on doxorubicin in MCF-7 and MDA-MB-231 cell lines. Results of Western blot and dual luciferase confirmed that miR-153-3p targets KIF20A and decreases its expression. Transwell and flow cytometry experiments showed that miR-153-3p and doxorubicin together had higher effects on MCF-7 and MDA-MB-231 cell proliferation, migration, and invasion, as well as increasing apoptosis and arresting cells in the G1 phase. Proteins related to apoptosis and the cell cycle exhibited the same tendency. Intracellular vesicle formation was inhibited and RAB26 was also downregulated by treatment with miR-153-3p alone or in combination with doxorubicin. Doxorubicin's ability to suppress tumors may be enhanced by miR-153-3p, according to in vivo studies. According to our findings, miR-153-3p has a direct effect on KIF20A and may regulate the formation of intracellular vesicles, which in turn makes breast cancer cells more susceptible to doxorubicin.

A novel non-invasive colorectal cancer diagnostic method: Volatile organic compounds as biomarkers

INTRODUCTION

Population-based fecal tests for colorectal cancer (CRC) screening have shown to reduce mortality thanks to the early detection of the disease. However, currently available fecal tests are limited in their sensitivity and specificity. Our aim is to look for volatile organic compounds in fecal samples as biomarkers for CRC detection.

MATERIAL AND METHODS

Eighty participants were included; 24 had adenocarcinoma, 24 had adenomatous polyps and 32 presented no neoplasms. Fecal samples were collected 48 h preceding the colonoscopy from all participants, except CRC patient samples that were collected after 3-4 weeks from the colonoscopy. Magnetic headspace adsorptive extraction (Mag-HSAE) followed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) was performed on stool samples to identify volatile organic compounds as biomarkers.

RESULTS

p-Cresol was significantly more abundant in the cancer samples (P < 0.001) with an area under the curve (AUC) of 0.85 (CI 95%; 0.737-0.953), having a sensitivity and specificity of 83% and 82%, respectively. In addition, 3(4H)-dibenzofuranone,4a,9b-dihydro-8,9b-dimethyl- (3(4H)-DBZ) was also more abundant in the cancer samples (P < 0.001) with an AUC of 0.77 (CI 95%; 0.635-0.905), sensitivity of 78% and specificity of 75%. When combined (p-cresol and 3(4H)-DBZ), the AUC was 0.86, sensitivity 87% and specificity 79%. p-Cresol also appeared to be promising as a biomarker for pre-malignant lesions with an AUC of 0.69 (CI 95%; 0.534-0.862), sensitivity 83% and specificity 63%, P = 0.045.

CONCLUSIONS

Volatile organic compounds emitted from feces and determined by a sensitive analytical methodology (Mag-HSAE-TD-GC-MS), employing a magnetic graphene oxide as extractant phase, could be used as a potential screening technology for CRC and pre-malignant lesions.

Noninvasive detection of soft tissue sarcoma using volatile organic compounds in exhaled breath: a pilot study

Aim: The aim of this pilot study was to assess whether an electronic nose can detect patients with soft tissue sarcoma (STS) based on volatile organic compound profiles in exhaled breath. Patients & methods: In this cross-sectional pilot study, patients with primary STS and healthy controls, matched on sex and age, were included for breath analysis. Machine learning techniques were used to develop the best-fitting model. Results: Fifty-nine breath samples were collected (29 STS and 30 control) from March 2018 to March 2022. The final model yielded a c-statistic of 0.85 with a sensitivity of 83% and specificity of 60%. Conclusion: This study suggests that exhaled volatile organic compound analysis could serve as a noninvasive diagnostic biomarker for the detection of STS with a good performance.

Volatile organic compounds as potential biomarkers of irritable bowel syndrome: A systematic review

BACKGROUND

Irritable bowel syndrome (IBS) is a prevalent gastrointestinal disease characterized by intermittent abdominal pain with altered bowel habits. Due to the condition's chronicity, patients suffer from poor quality of life, while the healthcare burden continues to grow. There is currently no reliable biomarker for the diagnosis of IBS, and the current approach depends on ruling-out organic diseases such as inflammatory bowel disease (IBD) and colorectal cancer by markers of inflammation like fecal calprotectin and C-reactive protein, or invasive procedures like a colonoscopy. Volatile organic compounds (VOCs) are growing in popularity as a biomarker due to its accuracy and ease of use.

PURPOSE

This systematic review of Medline and Cochrane's databases aimed to identify VOCs in the diagnosis of IBS. 57% of the studies proved that VOCs could identify IBS patients from healthy controls with AUC ranging from 0.83 to 0.99. Studies that distinguished IBS from IBD patients had slightly higher AUC of 0.87-0.98. Combining VOC into panels allowed the creation of discriminative algorithms. Though current research is limited by areas of heterogeneity in VOC sampling and small sample sizes, our review shows that VOC analysis has the potential to be a noninvasive point-of-care test that differentiates IBS from other organic gastrointestinal diseases.

The diagnostic breathprint of cancer; the past and the future

The main milestones in the exploration and validation of cancer breathprint for the advancement of personalised diagnosis and medicine are summarised here, with a special attention to the appraisal and translation of the accumulating knowledge from the laboratory to the Point-of-Care phase. An outlook into the opportunities of the use of breathprints and their wider availability for healthcare is offered.

Evaluation of a biosensor-based graphene oxide-DNA nanohybrid for lung cancer

Lung cancer is nowadays among the most prevalent diseases worldwide and features the highest mortality rate among various cancers, indicating that early diagnosis of the disease is of paramount importance. Given that the conventional methods of cancer detection are expensive and time-consuming, special attention has been paid to the provision of less expensive and faster techniques. In recent years, the dramatic advances in nanotechnology and the development of various nanomaterials have led to activities in this context. Recent studies indicate that the graphene oxide (GO) nanomaterial has high potential in the design of nano biosensors for lung cancer detection owing to its unique properties. In the current article, a nano biosensor based on a DNA-GO nanohybrid is introduced to detect deletion mutations causing lung cancer. In this method, mutations were detected using a FAM-labeled DNA probe with fluorescence spectrometry. GO was synthesized according to Hummers' method and examined and confirmed using Fourier Transform Infrared (FT-IR) Spectrometry and UV-vis spectrometry methods and Transmission Electron Microscopy (TEM) images.

The Versatility and Diagnostic Potential of VOC Profiling for Noninfectious Diseases

A variety of volatile organic compounds (VOCs) are produced and emitted by the human body every day. The identity and concentration of these VOCs reflect an individual's metabolic condition. Information regarding the production and origin of VOCs, however, has yet to be congruent among the scientific community. This review article focuses on the recent investigations of the source and detection of biological VOCs as a potential for noninvasive discrimination between healthy and diseased individuals. Analyzing the changes in the components of VOC profiles could provide information regarding the molecular mechanisms behind disease as well as presenting new approaches for personalized screening and diagnosis. VOC research has prioritized the study of cancer, resulting in many research articles and reviews being written on the topic. This review summarizes the information gained about VOC cancer studies over the past 10 years and looks at how this knowledge correlates with and can be expanded to new and upcoming fields of VOC research, including neurodegenerative and other noninfectious diseases. Recent advances in analytical techniques have allowed for the analysis of VOCs measured in breath, urine, blood, feces, and skin. New diagnostic approaches founded on sensor-based techniques allow for cheaper and quicker results, and we compare their diagnostic dependability with gas chromatography- and mass spectrometry-based techniques. The future of VOC analysis as a clinical practice and the challenges associated with this transition are also discussed and future research priorities are summarized.

Potential Role of Oxidative Stress in the Production of Volatile Organic Compounds in Obesity

Obesity is associated with numerous health issues such as sleep disorders, asthma, hepatic dysfunction, cancer, renal dysfunction, diabetes, cardiovascular complications, and infertility. Previous research has shown that the distribution of excess body fat, rather than excess body weight, determines obesity-related risk factors. It is widely accepted that abdominal fat is a serious risk factor for illnesses associated with obesity and the accumulation of visceral fat promotes the release of pro-oxidants, pro-inflammatory, and reactive oxygen species (ROS). The metabolic process in the human body produces several volatile organic compounds (VOCs) via urine, saliva, breath, blood, skin secretions, milk, and feces. Several studies have shown that VOCs are released by the interaction of ROS with underlying cellular components leading to increased protein oxidation, lipid peroxidation, or DNA damage. These VOCs released via oxidative stress in obese individuals may serves as a biomarker for obesity-related metabolic alterations and disease. In this review, we focus on the relationship between oxidative stress and VOCs in obesity.

Harnessing insect olfactory neural circuits for detecting and discriminating human cancers

There is overwhelming evidence that presence of cancer alters cellular metabolic processes, and these changes are manifested in emitted volatile organic compound (VOC) compositions of cancer cells. Here, we take a novel forward engineering approach by developing an insect olfactory neural circuit-based VOC sensor for cancer detection. We obtained oral cancer cell culture VOC-evoked extracellular neural responses from in vivo insect (locust) antennal lobe neurons. We employed biological neural computations of the antennal lobe circuitry for generating spatiotemporal neuronal response templates corresponding to each cell culture VOC mixture, and employed these neuronal templates to distinguish oral cancer cell lines (SAS, Ca9-22, and HSC-3) vs. a non-cancer cell line (HaCaT). Our results demonstrate that three different human oral cancers can be robustly distinguished from each other and from a non-cancer oral cell line. By using high-dimensional population neuronal response analysis and leave-one-trial-out methodology, our approach yielded high classification success for each cell line tested. Our analyses achieved 76-100% success in identifying cell lines by using the population neural response (n = 194) collected for the entire duration of the cell culture study. We also demonstrate this cancer detection technique can distinguish between different types of oral cancers and non-cancer at different time-matched points of growth. This brain-based cancer detection approach is fast as it can differentiate between VOC mixtures within 250 ms of stimulus onset. Our brain-based cancer detection system comprises a novel VOC sensing methodology that incorporates entire biological chemosensory arrays, biological signal transduction, and neuronal computations in a form of a forward-engineered technology for cancer VOC detection.

Systematic Review: Contribution of the Gut Microbiome to the Volatile Metabolic Fingerprint of Colorectal Neoplasia

Colorectal cancer (CRC) has been associated with changes in volatile metabolic profiles in several human biological matrices. This enables its non-invasive detection, but the origin of these volatile organic compounds (VOCs) and their relation to the gut microbiome are not yet fully understood. This systematic review provides an overview of the current understanding of this topic. A systematic search using PubMed, Embase, Medline, Cochrane Library, and the Web of Science according to PRISMA guidelines resulted in seventy-one included studies. In addition, a systematic search was conducted that identified five systematic reviews from which CRC-associated gut microbiota data were extracted. The included studies analyzed VOCs in feces, urine, breath, blood, tissue, and saliva. Eight studies performed microbiota analysis in addition to VOC analysis. The most frequently reported dysregulations over all matrices included short-chain fatty acids, amino acids, proteolytic fermentation products, and products related to the tricarboxylic acid cycle and Warburg metabolism. Many of these dysregulations could be related to the shifts in CRC-associated microbiota, and thus the gut microbiota presumably contributes to the metabolic fingerprint of VOC in CRC. Future research involving VOCs analysis should include simultaneous gut microbiota analysis.

Diagnosis by Volatile Organic Compounds in Exhaled Breath in Exhaled Breath from Patients with Gastric and Colorectal Cancers

One in three cancer deaths worldwide are caused by gastric and colorectal cancer malignancies. Although the incidence and fatality rates differ significantly from country to country, the rates of these cancers in East Asian nations such as South Korea and Japan have been increasing each year. Above all, the biggest danger of this disease is how challenging it is to recognize in its early stages. Moreover, most patients with these cancers do not present with any disease symptoms before receiving a definitive diagnosis. Currently, volatile organic compounds (VOCs) are being used for the early prediction of several other diseases, and research has been carried out on these applications. Exhaled VOCs from patients possess remarkable potential as novel biomarkers, and their analysis could be transformative in the prevention and early diagnosis of colon and stomach cancers. VOCs have been spotlighted in recent studies due to their ease of use. Diagnosis on the basis of patient VOC analysis takes less time than methods using gas chromatography, and results in the literature demonstrate that it is possible to determine whether a patient has certain diseases by using organic compounds in their breath as indicators. This study describes how VOCs can be used to precisely detect cancers; as more data are accumulated, the accuracy of this method will increase, and it can be applied in more fields.

Current Insights and Progress in the Clinical Management of Head and Neck Cancer

Head and neck cancer (HNC), also known as the cancer that can affect the structures between the dura mater and the pleura, is the 6th most common type of cancer. This heterogeneous group of malignancies is usually treated with a combination of surgery and radio- and chemotherapy, depending on if the disease is localized or at an advanced stage. However, most HNC patients are diagnosed at an advanced stage, resulting in the death of half of these patients. Thus, the prognosis of advanced or recurrent/metastatic HNC, especially HNC squamous cell carcinoma (HNSCC), is notably poorer than the prognosis of patients diagnosed with localized HNC. This review explores the epidemiology and etiologic factors of HNC, the histopathology of this heterogeneous cancer, and the diagnosis methods and treatment approaches currently available. Moreover, special interest is given to the novel therapies used to treat HNC subtypes with worse prognosis, exploring immunotherapies and targeted/multi-targeted drugs undergoing clinical trials, as well as light-based therapies (i.e., photodynamic and photothermal therapies).

Detecting Colorectal Adenomas and Cancer Using Volatile Organic Compounds in Exhaled Breath: A Proof-of-Principle Study to Improve Screening

INTRODUCTION

Early detection of colorectal cancer (CRC) by screening programs is crucial because survival rates worsen at advanced stages. However, the currently used screening method, the fecal immunochemical test (FIT), suffers from a high number of false-positives and is insensitive for detecting advanced adenomas (AAs), resulting in false-negatives for these premalignant lesions. Therefore, more accurate, noninvasive screening tools are needed. In this study, the utility of analyzing volatile organic compounds (VOCs) in exhaled breath in a FIT-positive population to detect the presence of colorectal neoplasia was studied.

METHODS

In this multicenter prospective study, breath samples were collected from 382 FIT-positive patients with subsequent colonoscopy participating in the national Dutch bowel screening program (n = 84 negative controls, n = 130 non-AAs, n = 138 AAs, and n = 30 CRCs). Precolonoscopy exhaled VOCs were analyzed using thermal desorption-gas chromatography-mass spectrometry, and the data were preprocessed and analyzed using machine learning techniques.

RESULTS

Using 10 discriminatory VOCs, AAs could be distinguished from negative controls with a sensitivity and specificity of 79% and 70%, respectively. Based on this biomarker profile, CRC and AA combined could be discriminated from controls with a sensitivity and specificity of 77% and 70%, respectively, and CRC alone could be discriminated from controls with a sensitivity and specificity of 80% and 70%, respectively. Moreover, the feasibility to discriminate non-AAs from controls and AAs was shown.

DISCUSSION

VOCs in exhaled breath can detect the presence of AAs and CRC in a CRC screening population and may improve CRC screening in the future.

The Use of Breath Analysis in the Management of Lung Cancer: Is It Ready for Primetime?

Breath analysis is a promising non-invasive method for the detection and management of lung cancer. Exhaled breath contains a complex mixture of volatile and non-volatile organic compounds that are produced as end-products of metabolism. Several studies have explored the patterns of these compounds and have postulated that a unique breath signature is emitted in the setting of lung cancer. Most studies have evaluated the use of gas chromatography and mass spectrometry to identify these unique breath signatures. With recent advances in the field of analytical chemistry and machine learning gaseous chemical sensing and identification devices have also been created to detect patterns of odorant molecules such as volatile organic compounds. These devices offer hope for a point-of-care test in the future. Several prospective studies have also explored the presence of specific genomic aberrations in the exhaled breath of patients with lung cancer as an alternative method for molecular analysis. Despite its potential, the use of breath analysis has largely been limited to translational research due to methodological issues, the lack of standardization or validation and the paucity of large multi-center studies. It is clear however that it offers a potentially non-invasive alternative to investigations such as tumor biopsy and blood sampling.