| Autor: |
Nicholas Kybert, Katharine Prokop-Prigge, Cynthia M. Otto, Lorenzo Ramirez, EmmaRose Joffe, Janos Tanyi, Jody Piltz-Seymour, A. T. Charlie Johnson, George Preti |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
AIP Advances, Vol 10, Iss 3, Pp 035213-035213-11 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2158-3226 |
| DOI: |
10.1063/1.5144532 |
| Popis: |
All cells release low molecular weight organic compounds that possess finite vapor pressures at body and/or ambient temperatures. These volatile organic compounds (VOCs) may possess an odor and can be found emanating from all body fluids. As cells turn malignant, analysis of changes in these VOCs can provide insight into cancer onset and diagnosis. Previous studies have demonstrated that dogs can be trained to distinguish ovarian cancer tissues of various stages and grades from normal ovarian tissue and other gynecological malignancies with sensitivity and specificity over 95%. When trained on biopsied tissue, dogs were able to detect the VOC disturbances in peripheral blood samples with the same accuracy. Building on these earlier studies, we examined the VOCs emanating from plasma samples from primary ovarian cancer patients, patients with benign reproductive tract growths, and healthy controls. We used a three-pronged sensor approach to analyze the VOCs from plasma: canines trained on tissue and plasma samples, analysis using solid phase microextraction gas chromatography–mass spectrometry, and novel single stranded DNA-coated carbon nanotube sensor field effect transistors. Each of the three experimental approaches used in this study provided preliminary evidence that plasma from ovarian cancer patients emits a volatile odor signature that can be distinguished from the VOCs of patients with benign ovarian tumors and controls. Our results provide optimism that a diagnostic approach based on the analysis of the VOC odor signature of ovarian cancer is achievable. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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