| Title: | Liquid Biopsy-Based Volatile Organic Compounds from Blood and Urine and Their Combined Data Sets for Highly Accurate Detection of Cancer |
| Author(s): | Einoch Amor R; Levy J; Broza YY; Vangravs R; Rapoport S; Zhang M; Wu W; Leja M; Behar JA; Haick H; |
| Address: | "Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa 3200003, Israel. The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering and Faculty of Biomedical Engineering, Technion-Israel Institute of Technology, Haifa 3200003, Israel. Institute of Clinical and Preventive Medicine & Faculty of Medicine, University of Latvia, Riga LV-1004, Latvia. Department of Research, Riga East University Hospital, Digestive Diseases Centre GASTRO, Riga 1586, Latvia. School of Chemistry and Molecular Engineering, Shanghai Key Laboratory for Urban Ecological Processes and Eco-Restoration, East China Normal University, Shanghai 200241, China. School of Advanced Materials and Nanotechnology, Interdisciplinary Research Center of Smart Sensors, Xidian University, Shaanxi 710126, P.R. China" |
| DOI: | 10.1021/acssensors.2c02422 |
| ISSN/ISBN: | 2379-3694 (Electronic) 2379-3694 (Linking) |
| Abstract: | "Liquid biopsy is seen as a prospective tool for cancer screening and tracking. However, the difficulty lies in effectively sieving, isolating, and overseeing cancer biomarkers from the backdrop of multiple disrupting cells and substances. The current study reports on the ability to perform liquid biopsy without the need to physically filter and/or isolate the cancer cells per se. This has been achieved through the detection and classification of volatile organic compounds (VOCs) emitted from the cancer cells found in the headspace of blood or urine samples or a combined data set of both. Spectrometric analysis shows that blood and urine contain complementary or overlapping VOC information on kidney cancer, gastric cancer, lung cancer, and fibrogastroscopy subjects. Based on this information, a nanomaterial-based chemical sensor array in conjugation with machine learning as well as data fusion of the signals achieved was carried out on various body fluids to assess the VOC profiles of cancer. The detection of VOC patterns by either Gas Chromatography-Mass Spectrometry (GC-MS) analysis or our sensor array achieved >90% accuracy, >80% sensitivity, and >80% specificity in different binary classification tasks. The hybrid approach, namely, analyzing the VOC datasets of blood and urine together, contributes an additional discrimination ability to the improvement (>3%) of the model's accuracy. The contribution of the hybrid approach for an additional discrimination ability to the improvement of the model's accuracy is examined and reported" |
| Keywords: | "Humans *Volatile Organic Compounds/analysis Biomarkers, Tumor/analysis *Lung Neoplasms/diagnosis *Body Fluids/chemistry Liquid Biopsy cancer diagnosis hybrid machine learning volatile organic compound;" |
| Notes: | "MedlineEinoch Amor, Reef Levy, Jeremy Broza, Yoav Y Vangravs, Reinis Rapoport, Shelley Zhang, Min Wu, Weiwei Leja, Marcis Behar, Joachim A Haick, Hossam eng Research Support, Non-U.S. Gov't 2023/03/18 ACS Sens. 2023 Apr 28; 8(4):1450-1461. doi: 10.1021/acssensors.2c02422. Epub 2023 Mar 16" |
