A novel approach utilizing rapid thin-film microextraction method for salivary metabolomics studies in lung cancer diagnosis

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dc.authorid0000-0003-0551-664X
dc.authorid0000-0001-8090-703X
dc.authorid0000-0002-6089-1840
dc.authorid0000-0003-1121-9967
dc.contributor.authorPelit, Fusun
dc.contributor.authorErbas, Ilknur
dc.contributor.authorOzupek, Nazli Mert
dc.contributor.authorGul, Merve
dc.contributor.authorSakrak, Esra
dc.contributor.authorOcakoglu, Kasim
dc.contributor.authorGoksel, Ozlem
dc.contributor.authorPelit, Levent
dc.contributor.authorGoksel, Tuncay
dc.date.accessioned2025-03-25T08:24:20Z
dc.date.available2025-03-25T08:24:20Z
dc.date.issued2024
dc.departmentEge Üniversitesi, Fen Fakültesi, Kimya Bölümü
dc.description.abstractThis study investigated the potential of targeted salivary metabolomics as a convenient diagnostic tool for lung cancer (LC), utilizing a rapid TFME-based method. It specifically examines TFME blades modified with SiO2 nanoparticles, which were produced using a custom-made coating system. Validation of the metabolite biomarker analysis was performed by these blades using liquid chromatography-tandem mass spectroscopy (LCMS/MS). The extraction efficiencies of SiO2 nanoparticle/polyacrylonitrile (PAN) composite-coated blades were compared for 18 metabolites. Response surface methodology (RSM) was used to optimize the analysis conditions. Linear calibration plots were obtained for all metabolites at concentrations between 0.025 to 4.0 mu g/mL in the presence of internal standard, with correlation coefficients (R-2) ranging from 0.9975 to 0.9841. The limit of detection (LOD) and limit of quantitation (LOQ) were in the range of 0.014 to 0.97 mu g mL(-1) and 0.046 to 3.20 mu gmL(-1), respectively. The %RSD values for all analytes were within the acceptable range (less than 20 %) for the proposed method. The method was applied to the saliva samples of 40 patients with LC and 38 healthy controls. The efficacy of metabolites for LC diagnosis was determined by in silico methods and the results reveal that phenylalanine and purine metabolism metabolites (e.g., hypoxanthine) are of great importance for LC diagnosis. Furthermore, potentially significant biomarker analysis results from the ROC curve data reveal that proline, hypoxanthine, and phenylalanine were identified as potential biomarkers for LC diagnosis.
dc.identifier.citationPelit, F., Erbas, I., Mert Ozupek, N., Gul, M., Sakrak, E., Ocakoglu, K., Pelit, L., Ozdemir, D., Goksel, T., Basbinar, Y., & Goksel, O. (2024). A novel approach utilizing rapid thin-film microextraction method for salivary metabolomics studies in lung cancer diagnosis. Microchemical Journal, 207, 112069.
dc.identifier.doi10.1016/j.microc.2024.112069
dc.identifier.endpage12
dc.identifier.issn0026265X
dc.identifier.issueDec
dc.identifier.scopus2-s2.0-85207899081
dc.identifier.scopusqualityQ1
dc.identifier.startpage1
dc.identifier.urihttps://doi.org/10.1016/j.microc.2024.112069
dc.identifier.urihttps://hdl.handle.net/11454/116914
dc.identifier.volume207
dc.identifier.wosWOS:001350472900001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorPelit, Fusun
dc.institutionauthorErbas, Ilknur
dc.institutionauthorGul, Merve
dc.institutionauthorSakrak, Esra
dc.institutionauthorGoksel, Ozlem
dc.institutionauthorPelit, Levent
dc.institutionauthorGoksel, Tuncay
dc.institutionauthorid0000-0003-0551-664X
dc.institutionauthorid0000-0001-8090-703X
dc.institutionauthorid0000-0002-6089-1840
dc.institutionauthorid0000-0003-1121-9967
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofMicrochemical Journal
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBiomarker
dc.subjectLiquid Chromatography-Tandem Mass Spectrometry
dc.subjectMetabolomics
dc.subjectSaliva
dc.subjectThin Film Microextraction
dc.titleA novel approach utilizing rapid thin-film microextraction method for salivary metabolomics studies in lung cancer diagnosis
dc.typeArticle

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