Rapid recognition of volatile organic compounds with colorimetric sensor arrays for lung cancer screening

Considerations regarding the selection, sampling, extraction, analysis, and modelling of biomarkers in exhaled breath for early lung cancer screening

Lung cancer (LC) is the deadliest cancer due to the lack of efficient screening methods that detect the disease early. This review, covering the years 2011 - 2025, summarizes state-of-the-art LC screening through analysis of volatile organic compounds (VOCs) in exhaled breath. All fundamental parts of the methodology are covered, i.e., sampling, analysis, and multivariate data modelling. This review shows that breath is commonly collected in Tedlar® bags and subsequently analysed with solid phase micro-extraction gas chromatography mass spectrometry (SPME-GC-MS) or sensors. Data analysis has been made using multivariate methods like principal component analysis (PCA) or artificial neural networks (ANNs). The VOCs exhaled by LC patients and healthy subjects are in principle the same. However, concentration levels differ between the two groups. Therefore, LC patients are usually separated from healthy controls through multivariate modelling of a set of VOC biomarkers rather than by individual biomarkers. Although most exhaled VOCs are formed endogenously via metabolic processes and oxidative stress, some compounds also have exogenous origins, which must be taken into consideration. More than 200 different VOCs have been reported as potential biomarkers in the breath of LC patients, while the number of biomarkers per study were typically around 10-20 compounds. The 15 most common LC biomarkers were (from high to low frequency) acetone, isoprene, hexanal, benzene, butanone, styrene, ethylbenzene, 1-propanol, 2-propanol, toluene, pentanal, 2-pentanone, cyclohexane, nonanal and decane. Several methods showed, in combination with multivariate data analysis, potential to distinguish between LC patients and healthy controls.

A Comprehensive Review of Biomarker Sensors for a Breathalyzer Platform

Detecting volatile organic compounds (VOCs) is increasingly recognized as a pivotal tool in non-invasive disease diagnostics. VOCs are metabolic byproducts, mostly found in human breath, urine, feces, and sweat, whose profiles may shift significantly due to pathological conditions. This paper presents a thorough review of the latest advancements in sensor technologies for VOC detection, with a focus on their healthcare applications. It begins by introducing VOC detection principles, followed by a review of the rapidly evolving technologies in this area. Special emphasis is given to functionalized molecularly imprinted polymer-based biochemical sensors for detecting breath biomarkers, owing to their exceptional selectivity. The discussion examines SWaP-C considerations alongside the respective advantages and disadvantages of VOC sensing technologies. The paper also tackles the principal challenges facing the field and concludes by outlining the current status and proposing directions for future research.

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.

The Role of Nano-Sensors in Breath Analysis for Early and Non-Invasive Disease Diagnosis

Early-stage, precise disease diagnosis and treatment has been a crucial topic of scientific discussion since time immemorial. When these factors are combined with experience and scientific knowledge, they can benefit not only the patient, but also, by extension, the entire health system. The development of rapidly growing novel technologies allows for accurate diagnosis and treatment of disease. Nanomedicine can contribute to exhaled breath analysis (EBA) for disease diagnosis, providing nanomaterials and improving sensing performance and detection sensitivity. Through EBA, gas-based nano-sensors might be applied for the detection of various essential diseases, since some of their metabolic products are detectable and measurable in the exhaled breath. The design and development of innovative nanomaterial-based sensor devices for the detection of specific biomarkers in breath samples has emerged as a promising research field for the non-invasive accurate diagnosis of several diseases. EBA would be an inexpensive and widely available commercial tool that could also be used as a disease self-test kit. Thus, it could guide patients to the proper specialty, bypassing those expensive tests, resulting, hence, in earlier diagnosis, treatment, and thus a better quality of life. In this review, some of the most prevalent types of sensors used in breath-sample analysis are presented in parallel with the common diseases that might be diagnosed through EBA, highlighting the impact of incorporating new technological achievements in the clinical routine.

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.

Rapid quantification of acid value in frying oil using iron tetraphenylporphyrin fluorescent sensor coupled with density functional theory and multivariate analysis

Metalloporphyrin-based fluorescent sensor was developed for the acid value in frying oil. The electronic and structural performances of iron tetraphenylporphyrin (FeTPP) were theoretically investigated using time-dependent density functional theory (TD-DFT) and DFT at the B3LYP/LANL2DZ level. The quantified FeTPP-based fluorescent sensor results revealed its excellent performance in discriminating different analytes. In the present work, the acid value of palm olein was determined after every single frying cycle. A total of 10 frying cycles were conducted each day for 10 consecutive days. The FeTPP-based fluorescent sensor was used to quantify the acid value and the results were compared with the chemical data obtained by conventional titration method. The synchronous fluorescence spectrum for each sample was recorded. Parallel factor analysis (PARAFAC) was used to decompose the three-dimensional spectrum data. Then, the support vector regression (SVR), partial least squares (PLS), and back-propagation artificial neural network (BP-ANN) methods were applied to build the regression models. After the comparison of the constructed models, the SVR models exhibited the highest correlation coefficients among all models, with 0.9748 and 0.9276 for the training and test set, respectively. The findings suggested the potential of FeTPP-based fluorescent sensor in rapid monitoring of the used frying oil quality and perhaps also in other foods with higher oil content.

One metal-ion-regulated AgTNPs etching sensor array for visual discrimination of multiple organic acids

The detection and discrimination of organic acids (OAs) is of great importance in the early diagnosis of specific diseases. In this study, we established an effective visual sensor array for the identification of OA. This is the first time, to our best knowledge, that metal ions were used to regulate the etching of silver triangular nanoprisms (AgTNPs) in an OA discrimination sensor array. The sensor array was based on the oxidation etching of AgTNPs by three metal ions (Mn²⁺, Pb²⁺, and Cr³⁺) and accelerated etching of AgTNPs by OA. The introduction of metal ions alone led to a slight wavelength shift of the AgTNPs colloid solution, signifying the incomplete etching of the AgTNPs. Nevertheless, when metal ions and OA were introduced simultaneously to the solution, a significant blueshift of the localized surface plasmon resonance peak was detected, and a color change of the AgTNPs was observed, which were the consequences of morphological transitions of the AgTNPs. The addition of different OA accelerated AgTNPs etching in varying degrees, generating diverse colorimetric response patterns (i.e., RGB variations) as "fingerprints" associated with each specific organic acid. Pattern recognition algorithms and neural network simulation were employed to further data analysis, indicating the outstanding discrimination capability of the provided array for eight OA at the 33 µM level. Moreover, excellent results of selective experiments as well as real samples tests demonstrate that our proposed method possesses great potential for practical applications.

Sensors for Volatile Organic Compounds

This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.

Superwettable Biosensor for Disease Biomarker Detection

Bioinspired superwettable materials have aroused wide interests in recent years for their promising application fields from service life to industry. As one kind of emerging application, the superwettable surfaces used to fabricate biosensors for the detection of disease biomarkers, especially tumor biomarkers, have been extensively studied. In this mini review, we briefly summarized the sensing strategy for disease biomarker detection based on superwettable biosensors, including fluorescence, electrochemistry, surface-enhanced Raman scattering, and visual assays. Finally, the challenges and direction for future development of superwettable biosensors are also discussed.

Breath Analysis: A Promising Tool for Disease Diagnosis-The Role of Sensors

Early-stage disease diagnosis is of particular importance for effective patient identification as well as their treatment. Lack of patient compliance for the existing diagnostic methods, however, limits prompt diagnosis, rendering the development of non-invasive diagnostic tools mandatory. One of the most promising non-invasive diagnostic methods that has also attracted great research interest during the last years is breath analysis; the method detects gas-analytes such as exhaled volatile organic compounds (VOCs) and inorganic gases that are considered to be important biomarkers for various disease-types. The diagnostic ability of gas-pattern detection using analytical techniques and especially sensors has been widely discussed in the literature; however, the incorporation of novel nanomaterials in sensor-development has also proved to enhance sensor performance, for both selective and cross-reactive applications. The aim of the first part of this review is to provide an up-to-date overview of the main categories of sensors studied for disease diagnosis applications via the detection of exhaled gas-analytes and to highlight the role of nanomaterials. The second and most novel part of this review concentrates on the remarkable applicability of breath analysis in differential diagnosis, phenotyping, and the staging of several disease-types, which are currently amongst the most pressing challenges in the field.

Recent advancements in optical biosensors for cancer detection

Optical biosensors are rapid, real-time, and portable, have a low detection limit and a high sensitivity, and have a great potential for diagnosing various types of cancer. Optical biosensors can detect cancer in a few million malignant cells, in comparison to conventional diagnosis techniques that use 1 billion cells in tumor tissue with a diameter of 7 nm-10 nm. Current cancer detection methods are also costly, inconvenient, complex, time consuming, and require technical specialists. This review focuses on recent advances in optical biosensors for early detection of cancer. It is primarily concerned with advancements in the design of various biosensors using resonance, scattering, chemiluminescence, luminescence, interference, fluorescence, absorbance or reflectance, and various fiber types. The development of various two-dimensional materials with optical properties such as biocompatibility, field enhancement, and a higher surface-to-volume ratio, as well as advancements in microfabrication technologies, have accelerated the development of optical sensors for early detection of cancer and other diseases. Surface enhanced Raman spectroscopy technology has the potential to detect a single molecule with high specificity, and terahertz waves are a recently explored technology for cancer detection. Due to the low electromagnetic interference, small size, multiplexing, and remote sensing capabilities of optical fiber-based platforms, they may be a driving force behind the rapid development of biosensors. The advantages and disadvantages of existing and future optical biosensor designs for cancer detection are discussed in detail. Additionally, a prospect for future advancements in the development of optical biosensors for point-of-care and clinical applications is highlighted.

Volatolomics in healthcare and its advanced detection technology

Various diseases increasingly challenge the health status and life quality of human beings. Volatolome emitted from patients has been considered as a potential family of markers, volatolomics, for diagnosis/screening. There are two fundamental issues of volatolomics in healthcare. On one hand, the solid relationship between the volatolome and specific diseases needs to be clarified and verified. On the other hand, effective methods should be explored for the precise detection of volatolome. Several comprehensive review articles had been published in this field. However, a timely and systematical summary and elaboration is still desired. In this review article, the research methodology of volatolomics in healthcare is critically considered and given out, at first. Then, the sets of volatolome according to specific diseases through different body sources and the analytical instruments for their identifications are systematically summarized. Thirdly, the advanced electronic nose and photonic nose technologies for volatile organic compounds (VOCs) detection are well introduced. The existed obstacles and future perspectives are deeply thought and discussed. This article could give a good guidance to researchers in this interdisciplinary field, not only understanding the cutting-edge detection technologies for doctors (medicinal background), but also making reference to clarify the choice of aimed VOCs during the sensor research for chemists, materials scientists, electronics engineers, etc.

Detection of aldehydes by gold nanoparticle colorimetric array based on Tollens' reagent

Aldehydes are very common pollutants and many are possible human carcinogens. Herein, we report an easy-to-operate and low-cost method for discrimination of diverse aldehydes. Our colorimetric sensor array based on Tollens' reagent allows discrimination of ten kinds of aldehydes, showing a distinct color change from wine-red to deep yellow. In the presence of aldehydes, Ag shells are coated onto gold nanoparticles (GNPs) functionalized with diverse ligands (including bovine serum albumin, polyvinylpyrrolidone and L-cysteine), forming Au@Ag core-shell nanoparticles. The sensor array has great capacity for differentiating between ten kinds of aldehydes by color change, with accuracy and specificity of over 88%. Under optimal conditions, there is good linear correlation between Euclidean distance and formaldehyde concentrations ranging from 0.1 to 10 000 μM (R² = 0.9908). The sensor was successfully used to determine formaldehyde content in shrimp, with recovery of 85.8% to 114.82%. Our GNPs sensor shows good potential for fast, reliable identification of aldehydes in food.

MOS Sensors Array for the Discrimination of Lung Cancer and At-Risk Subjects with Exhaled Breath Analysis

Lung cancer is characterized by a tremendously high mortality rate and a low 5-year survival rate when diagnosed at a late stage. Early diagnosis of lung cancer drastically reduces its mortality rate and improves survival. Exhaled breath analysis could offer a tool to clinicians to improve the ability to detect lung cancer at an early stage, thus leading to a reduction in the associated survival rate. In this paper, we present an electronic nose for the automatic analysis of exhaled breath. A total of five a-specific gas sensors were embedded in the electronic nose, making it sensitive to different volatile organic compounds (VOCs) contained in exhaled breath. Nine features were extracted from each gas sensor response to exhaled breath, identifying the subject breathprint. We tested the electronic nose on a cohort of 80 subjects, equally split between lung cancer and at-risk control subjects. Including gas sensor features and clinical features in a classification model, recall, precision, and accuracy of 78%, 80%, and 77% were reached using a fourfold cross-validation approach. The addition of other a-specific gas sensors, or of sensors specific to certain compounds, could improve the classification accuracy, therefore allowing for the development of a clinical tool to be integrated in the clinical pipeline for exhaled breath analysis and lung cancer early diagnosis.

Mitigation of Humidity Interference in Colorimetric Sensing of Gases

Colorimetric sensing technologies have been widely used for both quantitative detection of specific analyte and recognition of a large set of analytes in gas phase, ranging from environmental chemicals to biomarkers in breath. However, the accuracy and reliability of the colorimetric gas sensors are threatened by the humidity interference in different application scenarios. Though substantial progress has been made toward new colorimetric sensors development, unless the humidity interference is well addressed, the colorimetric sensors cannot be deployed for real-world applications. Although there are comprehensive and insightful review articles about the colorimetric gas sensors, they have focused more on the progress in new sensing materials, new sensing systems, and new applications. There is a need for reviewing the works that have been done to solve the humidity issue, a challenge that the colorimetric gas sensors commonly face. In this review paper, we analyzed the mechanisms of the humidity interference and discussed the approaches that have been reported to mitigate the humidity interference in colorimetric sensing of environmental gases and breath biomarkers. Finally, the future perspectives of colorimetric sensing technologies are also discussed.

Early diagnosis of lung cancer: which is the optimal choice?

The prognosis of lung cancer patients with different clinical stages is significantly different. The 5-year survival of stage IA groups can exceed 90%, while patients with stage IV can be less than 10%. Therefore, early diagnosis is extremely important for lung cancer patients. This research focused on various diagnosis methods of early lung cancer, including imaging screening, bronchoscopy, and emerging potential liquid biopsies, as well as volatile organic compounds, autoantibodies, aiming to improve the early diagnosis rate and explore feasible and effective early diagnosis strategies.

Advancements in Microfabricated Gas Sensors and Microanalytical Tools for the Sensitive and Selective Detection of Odors

In recent years, advancements in micromachining techniques and nanomaterials have enabled the fabrication of highly sensitive devices for the detection of odorous species. Recent efforts done in the miniaturization of gas sensors have contributed to obtain increasingly compact and portable devices. Besides, the implementation of new nanomaterials in the active layer of these devices is helping to optimize their performance and increase their sensitivity close to humans' olfactory system. Nonetheless, a common concern of general-purpose gas sensors is their lack of selectivity towards multiple analytes. In recent years, advancements in microfabrication techniques and microfluidics have contributed to create new microanalytical tools, which represent a very good alternative to conventional analytical devices and sensor-array systems for the selective detection of odors. Hence, this paper presents a general overview of the recent advancements in microfabricated gas sensors and microanalytical devices for the sensitive and selective detection of volatile organic compounds (VOCs). The working principle of these devices, design requirements, implementation techniques, and the key parameters to optimize their performance are evaluated in this paper. The authors of this work intend to show the potential of combining both solutions in the creation of highly compact, low-cost, and easy-to-deploy platforms for odor monitoring.

Emerging non-invasive detection methodologies for lung cancer

The potential for non-invasive lung cancer (LC) diagnosis based on molecular, cellular and volatile biomarkers has been attracting increasing attention, with the development of advanced techniques and methodologies. It is standard practice to tailor the treatments of LC for certain specific genetic alterations, including the epidermal growth factor receptor, anaplastic lymphoma kinase and BRAF genes. Despite these advances, little is known about the internal mechanisms of different types of biomarkers and the involvement of their related biochemical pathways during the development of LC. The development of faster and more effective techniques is essential for the identification of different biomarkers. The present review summarizes some of the latest methods used for detecting molecular, cellular and volatile biomarkers in LC and their potential use in clinical diagnosis and targeted therapy.

Exploring potential biomarkers for lung adenocarcinoma using LC-MS/MS metabolomics

Background

The average 5-year survival rate of lung adenocarcinoma patients is only 15% to 17%, which is primarily due to late-stage diagnosis and a lack of specific prognostic evaluations that can recommend effective therapies. Additionally, there is no clinically recognized biomarker that is effective for early-stage diagnosis.

Methods

Tissue samples from 10 lung adenocarcinoma patients (both tumor and non-tumor tissues) and 10 benign lung tumor samples were collected. The significantly differentially represented metabolites from the three groups were analyzed by liquid chromatography and tandem mass spectrometry.

Results

Pathway analysis indicated that central carbon metabolism was the top altered pathway in lung adenocarcinoma, while protein digestion and absorption, and central carbon metabolism were the top altered pathways in benign lung tumors. Receiver operating characteristic curve analysis revealed that adenosine 3′-monophosphate, creatine, glycerol, and 14 other differential metabolites were potential sensitive and specific biomarkers for the diagnosis and prognosis of lung adenocarcinoma.

Conclusion

Our findings suggest that the metabolomics approach may be a useful method to detect potential biomarkers in lung adenocarcinoma patients.

Cerumenogram: a new frontier in cancer diagnosis in humans

Cancer is the deadliest human disease and the development of new diagnosis methods is important to increase the chances of a cure. In this work it was developed a new method, named here for the first time as cerumenogram, using cerumen (earwax) as a new biomatrix for diagnosis. Earwax samples collected from cancer patients (cancer group) and cancer-free patients (control group) were analyzed by Headspace/Gas Chromatography-Mass Spectrometry (HS/GC-MS), following with multivariate analysis steps to process the raw data generated. In total, 158 volatile organic metabolites (VOMs) were identified in the cerumen samples. The 27 selected as potential VOMs biomarkers for cancer provided 100% discrimination between the cancer and control groups. This new test can thus be routinely employed for cancer diagnoses that is non-invasive, fast, cheap, and highly accurate.

Sensitive detection of lung cancer biomarkers using an aptameric graphene-based nanosensor with enhanced stability

We present an electrolyte-gated graphene field effect transistor (GFET) nanosensor using aptamer for rapid, highly sensitive and specific detection of a lung cancer biomarker interleukin-6 (IL-6) with enhanced stability. The negatively charged aptamer folds into a compact secondary conformation upon binding with IL-6, thus altering the carrier concentration of graphene and yielding a detectable change in the drain-source current I_ds. Aptamer has smaller size than other receptors (e.g. antibodies), making it possible to bring the charged IL-6 more closely to the graphene surface upon affinity binding, thereby enhancing the sensitivity of the detection. Thanks to the higher stability of aptamer over antibodies, which degrade easily with increasing storage time, consistent sensing performance was obtained by our nanosensor over extended-time (>24 h) storage at 25 °C. Additionally, due to the GFET-enabled rapid transduction of the affinity recognition to IL-6, detection of IL-6 can be achieved in several minutes (<10 min). Experimental results indicate that this nanosensor can rapidly and specifically respond to the change in IL-6 levels with high consistency after extended-time storage and a detection limit (DL) down to 139 fM. Therefore, our nanosensor holds great potential for lung cancer diagnosis at its early stage.