Identification of volatile organic compounds in the urine of patients with cervical cancer. Test concept for timely screening

A machine learning-based electronic nose for detecting neonatal sepsis: Analysis of volatile organic compound biomarkers in fecal samples

BACKGROUND

Neonatal sepsis is a global health threat, contributing to high morbidity and mortality rates among newborns. Recognizing the profound impact of neonatal sepsis on long-term health outcomes emphasizes the critical need for timely detection to mitigate its consequences and ensure optimal health for the affected newborns. Currently, various diagnostic approaches have been implemented, but they are limited by their invasiveness, high costs, centralized testing, frequent delays, inaccuracies in results, and the need for sophisticated laboratory equipment.

METHODS

We introduced a novel, non-invasive, cost-efficient, and easy-to-use technology that can provide rapid results at a point-of-care. The technology utilized a lab-built metal oxide semiconductor-based electronic nose (cNose) combined with volatile organic compound (VOC) biomarkers identified through gas chromatography-mass spectrometry (GC-MS) analysis. The system was evaluated using fecal profiling tests involving a total of 32 samples, including 17 positive and 15 negative sepsis, confirmed by blood culture. To assess the performance in discriminating patients from healthy controls, four machine learning algorithms were implemented.

RESULTS

Based on the cross-validation results, the MLPNN model provided the best results in distinguishing between neonates with positive and negative sepsis, achieving high-performance results of 90.63 % accuracy, 88.24 % sensitivity, and 93.33 % specificity at a 95 % confidence interval. Specific VOCs associated with neonatal sepsis, such as alcohols, acids, and esters, were successfully identified through GC-MS analysis, further validating the diagnostic capability of the cNose device.

CONCLUSION

The overall observations show the feasibility of using cNose system as a promising tool for real-time and bedside sepsis detection, potentially improving patient outcomes.

Exploring Components, Sensors, and Techniques for Cancer Detection via eNose Technology: A Systematic Review

This paper offers a systematic review of advancements in electronic nose technologies for early cancer detection with a particular focus on the detection and analysis of volatile organic compounds present in biomarkers such as breath, urine, saliva, and blood. Our objective is to comprehensively explore how these biomarkers can serve as early indicators of various cancers, enhancing diagnostic precision and reducing invasiveness. A total of 120 studies published between 2018 and 2023 were examined through systematic mapping and literature review methodologies, employing the PICOS (Population, Intervention, Comparison, Outcome, and Study design) methodology to guide the analysis. Of these studies, 65.83% were ranked in Q1 journals, illustrating the scientific rigor of the included research. Our review synthesizes both technical and clinical perspectives, evaluating sensor-based devices such as gas chromatography-mass spectrometry and selected ion flow tube-mass spectrometry with reported incidences of 30 and 8 studies, respectively. Key analytical techniques including Support Vector Machine, Principal Component Analysis, and Artificial Neural Networks were identified as the most prevalent, appearing in 22, 24, and 13 studies, respectively. While substantial improvements in detection accuracy and sensitivity are noted, significant challenges persist in sensor optimization, data integration, and adaptation into clinical settings. This comprehensive analysis bridges existing research gaps and lays a foundation for the development of non-invasive diagnostic devices. By refining detection technologies and advancing clinical applications, this work has the potential to transform cancer diagnostics, offering higher precision and reduced reliance on invasive procedures. Our aim is to provide a robust knowledge base for researchers at all experience levels, presenting insights on sensor capabilities, metrics, analytical methodologies, and the transformative impact of emerging electronic nose technologies in clinical practice.

Potential urinary volatile organic compounds as screening markers in cancer - a review

Early detection of cancer typically facilitates improved patient outcomes; however, many cancers are not easily diagnosed at an early stage. One potential route for developing new, non-invasive methods of cancer detection is by testing for cancer-related volatile organic compounds (VOCs) biomarkers in patients' urine. In this review, 44 studies covering the use and/or identification of cancer-related VOCs were examined, including studies which examined multiple types of cancer simultaneously, as well as diverse study designs. Among these studies the most studied cancers included prostate cancer (29% of papers), lung cancer (22%), breast cancer (20%), and bladder cancer (18%), with a smaller number of studies focused on colorectal cancer, cervical cancer, skin, liver cancer and others. Importantly, most studies which produced a VOC-based model of cancer detection observed a combined sensitivity and specificity above 150%, indicating that urine-based methods of cancer detection show considerable promise as a diagnostic tool. Mass spectrometry (MS) and electronic noses (eNose) were the most employed tools used in the detection of VOCs, while animal-based models were less common. In terms of VOCs of interest, 47 chemical species identified as correlated with various types of cancer in at least two unrelated papers, some of which were consistently up- or down-regulated in cancer patients, and which may represent useful targets for future studies investing urinary VOC biomarkers of cancer. Overall, it was concluded that research in this field has shown promising results, but more work may be needed before the widespread adoption of these techniques takes place.

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

BACKGROUND

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

AIM OF REVIEW

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

KEY SCIENTIFIC CONCEPTS OF REVIEW

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

Integration of Electrochemical Sensing and Machine Learning to Detect Tuberculosis via Methyl Nicotinate in Patient Breath

Tuberculosis (TB) remains a significant global health issue; making early, accurate, and inexpensive point-of-care detection critical for effective treatment. This paper presents a clinical demonstration of an electrochemical sensor that detects methyl-nicotinate (MN), a volatile organic biomarker associated with active pulmonary tuberculosis. The sensor was initially tested on a patient cohort comprised of 57 adults in Kampala, Uganda, of whom 42 were microbiologically confirmed TB-positive and 15 TB-negative. The sensor employed a copper(II) liquid metal salt solution with a square wave voltammetry method tailored for MN detection using commercially available screen-printed electrodes. An exploratory machine learning analysis was performed using XGBOOST. Utilizing this approach, the sensor was 78% accurate with 71% sensitivity and 100% specificity. These initial results suggest the sensing methodology is effective in identifying TB from complex breath samples, providing a promising tool for non-invasive and rapid TB detection in clinical settings.

Exhaled breath and urinary volatile organic compounds (VOCs) for cancer diagnoses, and microbial-related VOC metabolic pathway analysis: a systematic review and meta-analysis

BACKGROUND

The gradual evolution of the detection and quantification of volatile organic compounds (VOCs) has been instrumental in cancer diagnosis. The primary objective of this study was to assess the diagnostic potential of exhaled breath and urinary VOCs in cancer detection. As VOCs are indicative of tumor and human metabolism, our work also sought to investigate the metabolic pathways linked to the development of cancerous tumors.

MATERIALS AND METHODS

An electronic search was performed in the PubMed database. Original studies on VOCs within exhaled breath and urine for cancer detection with a control group were included. A meta-analysis was conducted using a bivariate model to assess the sensitivity and specificity of the VOCs for cancer detection. Fagan's nomogram was designed to leverage the findings from our diagnostic analysis for the purpose of estimating the likelihood of cancer in patients. Ultimately, MetOrigin was employed to conduct an analysis of the metabolic pathways associated with VOCs in relation to both human and/or microbiota.

RESULTS

The pooled sensitivity, specificity and the area under the curve for cancer screening utilizing exhaled breath and urinary VOCs were determined to be 0.89, 0.88, and 0.95, respectively. A pretest probability of 51% can be considered as the threshold for diagnosing cancers with VOCs. As the estimated pretest probability of cancer exceeds 51%, it becomes more appropriate to emphasize the 'ruling in' approach. Conversely, when the estimated pretest probability of cancer falls below 51%, it is more suitable to emphasize the 'ruling out' approach. A total of 14, 14, 6, and 7 microbiota-related VOCs were identified in relation to lung, colorectal, breast, and liver cancers, respectively. The enrichment analysis of volatile metabolites revealed a significant enrichment of butanoate metabolism in the aforementioned tumor types.

CONCLUSIONS

The analysis of exhaled breath and urinary VOCs showed promise for cancer screening. In addition, the enrichment analysis of volatile metabolites revealed a significant enrichment of butanoate metabolism in four tumor types, namely lung, colorectum, breast and liver. These findings hold significant implications for the prospective clinical application of multiomics correlation in disease management and the exploration of potential therapeutic targets.

The untargeted urine volatilome for biomedical applications: methodology and volatilome database

Chemically diverse in compounds, urine can give us an insight into metabolic breakdown products from foods, drinks, drugs, environmental contaminants, endogenous waste metabolites, and bacterial by-products. Hundreds of them are volatile compounds; however, their composition has never been provided in detail, nor has the methodology used for urine volatilome untargeted analysis. Here, we summarize key elements for the untargeted analysis of urine volatilome from a comprehensive compilation of literature, including the latest reports published. Current achievements and limitations on each process step are discussed and compared. 34 studies were found retrieving all information from the urine treatment to the final results obtained. In this report, we provide the first specific urine volatilome database, consisting of 841 compounds from 80 different chemical classes.

One-Drop Serum Screening Test for Anal Cancer in Men via Infrared Attenuated Total Reflection Spectroscopy

Rare cancers are a challenge for clinical practice, the treatment experience at major centers to which rare cancers are referred is limited and are the most difficult to diagnose. Research to identify causes or develop prevention and early detection strategies is extremely challenging. Anal cancer is an example of a rare cancer, with the human papillomavirus (HPV) infection being the most important risk factor associated. In the early stages, anal cancer does not exhibit evident symptoms. This disease is diagnosed by means of anoscopy, which diagnoses some cases of early cancer; nevertheless, sensitivity of this test ranges between 47 and 89%. Therefore, the development of new, effective, and evidence-based screening methodologies for the early detection of rare cancers is of great relevance. In this study, the potential of ATR-FTIR spectroscopy has been explored as a sensitive, nondestructive, and inexpensive analytical method for developing disease screening platforms in serum. Spectral differences were found in the regions of 1700-1100 and 1700-1400 cm^-1 between the control group and the anal cancer group related to the presence of proteins and nucleic acids. The chemometric analysis presented differences in the spectral fingerprints for both spectral regions with a high sensitivity ranging from 95.2 to 99.9% and a specificity ranging from 99.2 to 100%. This is the first step that we report for a methodology that is fast, nondestructive, and easy to perform, and the high sensitivity and specificity of the method are the basis for extensive research studies to implement these technologies in the clinical field.

The potential of urine for human papillomavirus-related cervical cancer prevention

Cervical cancer is one of the most preventable cancers. The introduction of human papillomavirus (HPV) vaccines and the adaptation of regular screening programs are key actions that need to be generalized globally to achieve the goal of cervical cancer elimination. However, it is still challenging to achieve satisfactory coverage rate, and many women are reluctant to participate in gynecologic examination. In this article, we review the research on the application of HPV detection in urine samples for cervical cancer screening and vaccine monitoring, as well as discuss the technical challenges and new technological advancements in urine-based tests. HPV detection in urine is an excellent noninvasive alternative that is widely accepted by women, relatively affordable, and provides the potential to reach women without the necessity for clinical visits. Thus, it is an attractive tool for both cervical cancer screening and vaccine monitoring.