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Diagnostic potential of nanoparticle aided assays for MUC16 and MUC1 glycovariants in ovarian cancer
Department of Life Technologies and FICAN West Cancer Centre, University of Turku, Finland.
Department of Life Technologies and FICAN West Cancer Centre, University of Turku, Finland.
University of Skövde, School of Bioscience. University of Skövde, Systems Biology Research Environment. (Translationell bioinformatik, Translational Bioinformatics)ORCID iD: 0000-0001-9242-4852
Department of Life Technologies and FICAN West Cancer Centre, University of Turku, Finland.
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2022 (English)In: International Journal of Cancer, ISSN 0020-7136, E-ISSN 1097-0215, Vol. 151, no 7, p. 1175-1184Article in journal (Refereed) Published
Abstract [en]

This study reports the discovery and evaluation of nanoparticle aided sensitive assays for glycovariants of MUC16 and MUC1 in a unique collection of paired ovarian cyst fluids and serum samples obtained at or prior to surgery for ovarian carcinoma suspicion. Selected glycovariants and the immunoassays for CA125, CA15-3 and HE4 were compared and validated in 347 cyst fluid and serum samples. Whereas CA125 and CA15-3 performed poorly in cyst fluid to separate carcinoma and controls, four glycovariants including MUC16MGL , MUC16STn , MUC1STn and MUC1Tn provided highly improved separations. In serum, the two STn glycovariants outperformed conventional CA125, CA15-3 and HE4 assays in all sub-categories analysed with main benefits obtained at high specificities and at postmenopausal and early-stage disease. Serum MUC16STn performed best at high specificity (90-99%), but sensitivity was also improved by the other glycovariants and CA15-3. The highly improved specificity, excellent analytical sensitivity, and robustness of the nanoparticle assisted glycovariant assays carry great promise for improved identification and early detection of ovarian carcinoma in routine differential diagnostics. This article is protected by copyright. All rights reserved.

Place, publisher, year, edition, pages
John Wiley & Sons, 2022. Vol. 151, no 7, p. 1175-1184
Keywords [en]
STn, diagnosis, epithelial ovarian cancer, europium nanoparticle, mucins
National Category
Cancer and Oncology
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:his:diva-21135DOI: 10.1002/ijc.34111ISI: 000799910200001PubMedID: 35531590Scopus ID: 2-s2.0-85130972083OAI: oai:DiVA.org:his-21135DiVA, id: diva2:1657745
Funder
Swedish Cancer Society, CAN-2018/834Region Västra Götaland, ALFGBG-721051Region Västra Götaland, ALFGBG-932583
Note

CC BY-NC 4.0

Attribution-NonCommercial 4.0 International

First published: 09 May 2022

Corresponding author: Kamlesh Gidwani (kamlesh.gidwani@utu.fi), Karin Sundfeldt (karin.sundfeldt@obgyn.gu.se)

Funding:

Swedish Cancer Foundation CAN-2018/834

ALF-VGR Region, Sweden ALFGBG-721051, ALFGBG-932583

Jane and Aatos Erkko Foundation, Finland 2018-2021

Nordic Cancer Union, Denmark 194914

Available from: 2022-05-12 Created: 2022-05-12 Last updated: 2022-08-16Bibliographically approved

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