期刊
ANALYTICA CHIMICA ACTA
卷 1184, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.aca.2021.338892
关键词
N-linked glycans; Prostate cancer; Serum biomarkers; Urinary biomarkers; sdAb
资金
- National Research, Development and Innovation Office [2018-2.1.17-TET-KR-2018-00010]
- Hungarian Government
- New National Excellence Program Hungarian Ministry of Human Capacities and the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences [UNKP-20-5]
- Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences
- National Research, Development and Innovation Fund of Hungary [TKP2020-IKA-07, 2020-4.1.1-TKP2020]
This paper describes the development and implementation of a high-throughput capillary electrophoresis-based glycan analysis workflow for urinary PSA, which shows excellent selectivity and high resolution, making it a valuable tool for distinguishing different forms of prostate cancer.
Prostate cancer represents the second highest malignancy rate in men in all cancer diagnoses worldwide. The development and progression of prostate cancer is not completely understood yet at molecular level, but it has been reported that changes in the N-glycosylation of prostate-specific antigen (PSA) occur during tumor genesis. In this paper we report on the development and implementation of a highthroughput capillary electrophoresis based glycan analysis workflow for urinary PSA analysis. The technology utilizes selective, high yield single domain antibody based PSA capture, followed by preconcentration and capillary electrophoresis coupled with laser-induced fluorescence detection, resulting in high resolution N-glycan profiles. Urinary PSA glycan profiles were compared to a commercially available PSA standard revealing differences in their a2,3-and a2,6-sialylated isomers, proving the excellent selectivity of the suggested workflow. This is important as sialylation classification plays an important role in the differentiation between indolent, significant and aggressive forms of prostate cancer. (c) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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