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Angioli R, Santonico M, Pennazza G, Montera R, Luvero D, Gatti A, Zompanti A, Finamore P, Incalzi RA. Use of Sensor Array Analysis to Detect Ovarian Cancer through Breath, Urine, and Blood: A Case-Control Study. Diagnostics (Basel) 2024; 14:561. [PMID: 38473033 DOI: 10.3390/diagnostics14050561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 02/26/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
Ovarian cancer (OC) is the eighth most common cancer in women. Since screening programs do not exist, it is often diagnosed in advanced stages. Today, the detection of OC is based on clinical examination, transvaginal ultrasound (US), and serum biomarker (Carbohydrate Antigen 125 (CA 125) and Human Epididymis Protein 4 (HE4)) dosage, with a sensitivity of 88% and 95%, respectively, and a specificity of 84% for US and 76% for biomarkers. These methods are clearly not enough, and OC in its early stages is often missed. Many scientists have recently focused their attention on volatile organic compounds (VOCs). These are gaseous molecules, found in the breath, that could provide interesting information on several diseases, including solid tumors. To detect VOCs, an electronic nose was invented by a group of researchers. A similar device, the e-tongue, was later created to detect specific molecules in liquids. For the first time in the literature, we investigated the potential use of the electronic nose and the electronic tongue to detect ovarian cancer not just from breath but also from urine, blood, and plasma samples.
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Affiliation(s)
- Roberto Angioli
- Unit of Gynecology, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy
| | - Marco Santonico
- Unit of Electronics for Sensor Systems, Department of Science and Technology for Sustainable Development and One Health, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy
| | - Giorgio Pennazza
- Unit of Electronics for Sensor Systems, Department of Engineering, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy
| | - Roberto Montera
- Unit of Gynecology, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy
| | - Daniela Luvero
- Unit of Gynecology, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy
| | - Alessandra Gatti
- Unit of Gynecology, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy
| | - Alessandro Zompanti
- Unit of Electronics for Sensor Systems, Department of Engineering, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128 Rome, Italy
| | - Panaiotis Finamore
- Unit of Geriatrics, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy
| | - Raffaele Antonelli Incalzi
- Unit of Geriatrics, University Campus Bio-Medico of Rome, Via Alvaro del Portillo 200, 00128 Rome, Italy
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Zniber M, Vahdatiyekta P, Huynh TP. Analysis of urine using electronic tongue towards non-invasive cancer diagnosis. Biosens Bioelectron 2023; 219:114810. [PMID: 36272349 DOI: 10.1016/j.bios.2022.114810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 04/27/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022]
Abstract
Electronic tongues (e-tongues) have been broadly employed in monitoring the quality of food, beverage, cosmetics, and pharmaceutical products, and in diagnosis of diseases, as the e-tongues can discriminate samples of high complexity, reduce interference of the matrix, offer rapid response. Compared to other analytical approaches using expensive and complex instrumentation as well as required sample preparation, the e-tongue is non-destructive, miniaturizable and on-site method with little or no preparation of samples. Even though e-tongues are successfully commercialized, their application in cancer diagnosis from urine samples is underestimated. In this review, we would like to highlight the various analytical techniques such as Raman spectroscopy, infrared spectroscopy, fluorescence spectroscopy, and electrochemical methods (potentiometry and voltammetry) used as e-tongues for urine analysis towards non-invasive cancer diagnosis. Besides, different machine learning approaches, for instance, supervised and unsupervised learning algorithms are introduced to analyze extracted chemical data. Finally, capabilities of e-tongues in distinguishing between patients diagnosed with cancer and healthy controls are highlighted.
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Affiliation(s)
- Mohammed Zniber
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, 20500, Turku, Finland
| | - Parastoo Vahdatiyekta
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, 20500, Turku, Finland
| | - Tan-Phat Huynh
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, 20500, Turku, Finland.
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Monreal-Trigo J, Alcañiz M, Martínez-Bisbal MC, Loras A, Pascual L, Ruiz-Cerdá JL, Ferrer A, Martínez-Máñez R. New bladder cancer non-invasive surveillance method based on voltammetric electronic tongue measurement of urine. iScience 2022; 25:104829. [PMID: 36034216 PMCID: PMC9399275 DOI: 10.1016/j.isci.2022.104829] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 06/14/2022] [Accepted: 07/20/2022] [Indexed: 11/08/2022] Open
Abstract
Bladder cancer (BC) is the sixth leading cause of death by cancer. Depending on the invasiveness of tumors, patients with BC will undergo surgery and surveillance lifelong, owing the high rate of recurrence and progression. In this context, the development of strategies to support non-invasive BC diagnosis is focusing attention. Voltammetric electronic tongue (VET) has been demonstrated to be of use in the analysis of biofluids. Here, we present the implementation of a VET to study 207 urines to discriminate BC and non-BC for diagnosis and surveillance to detect recurrences. Special attention has been paid to the experimental setup to improve reproducibility in the measurements. PLSDA analysis together with variable selection provided a model with high sensitivity, specificity, and area under the ROC curve AUC (0.844, 0.882, and 0.917, respectively). These results pave the way for the development of non-invasive low-cost and easy-to-use strategies to support BC diagnosis and follow-up. Bladder cancer (BC) and control urines were studied by voltammetric electronic tongue A PLSDA model was obtained with high sensitivity, specificity, and accuracy (84/88/86) 103/122 BC urines and 7⅝5 control urines were predicted correctly The electronic tongue has the potential for non-invasive BC diagnostics and follow-up
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Using machine learning and an electronic tongue for discriminating saliva samples from oral cavity cancer patients and healthy individuals. Talanta 2022; 243:123327. [DOI: 10.1016/j.talanta.2022.123327] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 02/14/2022] [Accepted: 02/16/2022] [Indexed: 11/20/2022]
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Leong SX, Leong YX, Koh CSL, Tan EX, Nguyen LBT, Chen JRT, Chong C, Pang DWC, Sim HYF, Liang X, Tan NS, Ling XY. Emerging nanosensor platforms and machine learning strategies toward rapid, point-of-need small-molecule metabolite detection and monitoring. Chem Sci 2022; 13:11009-11029. [PMID: 36320477 PMCID: PMC9516957 DOI: 10.1039/d2sc02981b] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Accepted: 09/05/2022] [Indexed: 11/25/2022] Open
Abstract
Speedy, point-of-need detection and monitoring of small-molecule metabolites are vital across diverse applications ranging from biomedicine to agri-food and environmental surveillance. Nanomaterial-based sensor (nanosensor) platforms are rapidly emerging as excellent candidates for versatile and ultrasensitive detection owing to their highly configurable optical, electrical and electrochemical properties, fast readout, as well as portability and ease of use. To translate nanosensor technologies for real-world applications, key challenges to overcome include ultralow analyte concentration down to ppb or nM levels, complex sample matrices with numerous interfering species, difficulty in differentiating isomers and structural analogues, as well as complex, multidimensional datasets of high sample variability. In this Perspective, we focus on contemporary and emerging strategies to address the aforementioned challenges and enhance nanosensor detection performance in terms of sensitivity, selectivity and multiplexing capability. We outline 3 main concepts: (1) customization of designer nanosensor platform configurations via chemical- and physical-based modification strategies, (2) development of hybrid techniques including multimodal and hyphenated techniques, and (3) synergistic use of machine learning such as clustering, classification and regression algorithms for data exploration and predictions. These concepts can be further integrated as multifaceted strategies to further boost nanosensor performances. Finally, we present a critical outlook that explores future opportunities toward the design of next-generation nanosensor platforms for rapid, point-of-need detection of various small-molecule metabolites. Overview of the current status on emerging, multi-faceted nanosensor platform designs and data analysis strategies for rapid, point-of-need detection and monitoring of small-molecule metabolites.![]()
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Affiliation(s)
- Shi Xuan Leong
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
| | - Yong Xiang Leong
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
| | - Charlynn Sher Lin Koh
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
| | - Emily Xi Tan
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
| | - Lam Bang Thanh Nguyen
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
| | - Jaslyn Ru Ting Chen
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
| | - Carice Chong
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
| | - Desmond Wei Cheng Pang
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
| | - Howard Yi Fan Sim
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
| | - Xiaochen Liang
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
| | - Nguan Soon Tan
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore
| | - Xing Yi Ling
- Division of Chemistry and Biological Chemistry, School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
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Novel Prostate Cancer Biomarkers: Aetiology, Clinical Performance and Sensing Applications. CHEMOSENSORS 2021. [DOI: 10.3390/chemosensors9080205] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The review initially provides a short introduction to prostate cancer (PCa) incidence, mortality, and diagnostics. Next, the need for novel biomarkers for PCa diagnostics is briefly discussed. The core of the review provides details about PCa aetiology, alternative biomarkers available for PCa diagnostics besides prostate specific antigen and their biosensing. In particular, low molecular mass biomolecules (ions and metabolites) and high molecular mass biomolecules (proteins, RNA, DNA, glycoproteins, enzymes) are discussed, along with clinical performance parameters.
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Integration of voltammetric analysis, protein electrophoresis and pH measurement for diagnosis of pleural effusions: a non-conventional diagnostic approach. Sci Rep 2020; 10:15222. [PMID: 32938981 PMCID: PMC7495467 DOI: 10.1038/s41598-020-71542-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 07/29/2020] [Indexed: 12/03/2022] Open
Abstract
Pleural effusion is very common, but an etiologic diagnosis is often difficult. We used three unconventional diagnostic techniques (voltammetric analysis, protein electrophoresis and pH measurement) performed on pleural effusion to do a preliminary distinction between a neoplastic and a non-neoplastic origin. Pleural fluid samples were collected through thoracentesis, thoracoscopy, or post-surgery pleural drainage of 116 patients admitted to acute care wards. Samples were analyzed with the three unconventional techniques: voltammetric analysis using the BIONOTE system, capillary electrophoresis and pH measurement using a potentiometric method. The BIONOTE system is an innovative system that performs a cyclic voltammetric analysis of a biological liquid sample. The final output of the electrochemical analysis is an electrical pattern that represents a fingerprint of the analyzed sample and each sample has a different fingerprint. Data from the three unconventional diagnostic techniques were analyzed using partial least squares discriminant analysis to discriminate neoplastic from non-neoplastic effusions; we also evaluated sensitivity, specificity and percentage of correct classification. The mean age was 68 years (SD: 12); 78 (67.24%) participants were men. Results obtained from all the unconventional techniques employed showed that neoplastic and non-neoplastic pleural effusions were correctly classified in 80.2% of cases, with a sensitivity of 77% and specificity of 83%. The combined use of voltammetric analysis, protein electrophoresis and pH measurement of pleural fluid can easily and quickly distinguish a neoplastic from a non-neoplastic pleural effusion with reliable accuracy and represents an innovative diagnostic approach. In fact, this protocol can be executed in just few minutes directly in the patient's bed and it holds great promise to improve the prognosis and therapeutic chances.
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Electronic Tongues for Inedible Media. SENSORS 2019; 19:s19235113. [PMID: 31766686 PMCID: PMC6928786 DOI: 10.3390/s19235113] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 11/12/2019] [Accepted: 11/20/2019] [Indexed: 12/16/2022]
Abstract
“Electronic tongues”, “taste sensors”, and similar devices (further named as “multisensor systems”, or MSS) have been studied and applied mostly for the analysis of edible analytes. This is not surprising, since the MSS development was sometimes inspired by the mainstream idea that they could substitute human gustatory tests. However, the basic principle behind multisensor systems—a combination of an array of cross-sensitive chemical sensors for liquid analysis and a machine learning engine for multivariate data processing—does not imply any limitations on the application of such systems for the analysis of inedible media. This review deals with the numerous MSS applications for the analysis of inedible analytes, among other things, for agricultural and medical purposes.
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Wei Z, Yang Y, Wang J, Zhang W, Ren Q. The measurement principles, working parameters and configurations of voltammetric electronic tongues and its applications for foodstuff analysis. J FOOD ENG 2018. [DOI: 10.1016/j.jfoodeng.2017.08.005] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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