Literature DB >> 25358590

Urinary prostate protein glycosylation profiling as a diagnostic biomarker for prostate cancer.

Tijl Vermassen1, Charles Van Praet, Nicolaas Lumen, Karel Decaestecker, Dieter Vanderschaeghe, Nico Callewaert, Geert Villeirs, Piet Hoebeke, Simon Van Belle, Sylvie Rottey, Joris Delanghe.   

Abstract

BACKGROUND: Serum prostate-specific antigen (sPSA) measurement is widely used as opportunistic screening tool for prostate cancer (PCa). sPSA suffers from considerable sensitivity and specificity problems, particularly in the diagnostic gray zone (sPSA 4-10 µg/L). Furthermore, sPSA is not able to discriminate between poorly-, moderately-, and well-differentiated PCa. We investigated prostatic protein glycosylation profiles as a potential PCa biomarker.
METHODS: Differences in total urine N-glycosylation profile of prostatic proteins were determined between healthy volunteers (n = 54), patients with benign prostate hyperplasia (BPH; n = 93) and newly diagnosed PCa patients (n = 74). Variations in N-glycosylation profile and prostate volume were combined into one urinary glycoprofile marker (UGM). Additionally, differences in N-glycosylation were identified between Gleason <7, =7, and >7.
RESULTS: The UGM was able to discriminate BPH from PCa, overall and in the diagnostic gray zone (P < 0.001). The UGM showed comparable diagnostic accuracy to sPSA, but gave an additive diagnostic value to sPSA (P < 0.001). In the diagnostic gray zone the UGM performed significantly better than sPSA (P < 0.001). A significant difference was found in core-fucosylation of biantennary structures and overall core-fucosylation of multiantennary structures between Gleason < 7 and Gleason > 7 (P = 0.010 and P = 0.020, respectively) and between Gleason = 7 and Gleason > 7 (P = 0.011 and P = 0.025, respectively).
CONCLUSIONS: The UGM shows high potential as PCa biomarker, particularly in the diagnostic gray zone. Further research is needed to validate these findings.
© 2014 Wiley Periodicals, Inc.

Entities:  

Keywords:  Gleason score; benign prostate hyperplasia; diagnostic marker; prostate cancer; urinary asparagine-linked glycosylation

Mesh:

Substances:

Year:  2014        PMID: 25358590     DOI: 10.1002/pros.22918

Source DB:  PubMed          Journal:  Prostate        ISSN: 0270-4137            Impact factor:   4.104


  9 in total

1.  Prostate cancer: urinary glycoprofile identifies presence and grade of cancer.

Authors:  Robert Phillips
Journal:  Nat Rev Urol       Date:  2014-11-18       Impact factor: 14.432

2.  Site-Specific Fucosylation Analysis Identifying Glycoproteins Associated with Aggressive Prostate Cancer Cell Lines Using Tandem Affinity Enrichments of Intact Glycopeptides Followed by Mass Spectrometry.

Authors:  Jianliang Zhou; Weiming Yang; Yingwei Hu; Naseruddin Höti; Yang Liu; Punit Shah; Shisheng Sun; David Clark; Stefani Thomas; Hui Zhang
Journal:  Anal Chem       Date:  2017-07-03       Impact factor: 6.986

Review 3.  Narrative review of urinary glycan biomarkers in prostate cancer.

Authors:  Shingo Hatakeyama; Tohru Yoneyama; Yuki Tobisawa; Hayato Yamamoto; Chikara Ohyama
Journal:  Transl Androl Urol       Date:  2021-04

Review 4.  Approaches to the discovery of non-invasive urinary biomarkers of prostate cancer.

Authors:  Andrej Jedinak; Kevin R Loughlin; Marsha A Moses
Journal:  Oncotarget       Date:  2018-08-21

5.  Distinct urinary glycoprotein signatures in prostate cancer patients.

Authors:  Rebeca Kawahara; Fabio Ortega; Livia Rosa-Fernandes; Vanessa Guimarães; Daniel Quina; Willian Nahas; Veit Schwämmle; Miguel Srougi; Katia R M Leite; Morten Thaysen-Andersen; Martin R Larsen; Giuseppe Palmisano
Journal:  Oncotarget       Date:  2018-09-04

6.  One-Step Preparation of Phenyl Boron-Modified Magnetic Mesoporous Silica for Selective Enrichment of cis-Diol-Containing Substances.

Authors:  Hua Fu; Jing Hu; Min Zhang; Yuerong Wang; Hongyang Zhang; Ping Hu
Journal:  Molecules       Date:  2018-03-07       Impact factor: 4.411

7.  HILIC-MRM-MS for Linkage-Specific Separation of Sialylated Glycopeptides to Quantify Prostate-Specific Antigen Proteoforms.

Authors:  Yuri E M van der Burgt; Kasper M Siliakus; Christa M Cobbaert; L Renee Ruhaak
Journal:  J Proteome Res       Date:  2020-03-18       Impact factor: 4.466

8.  Diagnostic accuracy of urinary prostate protein glycosylation profiling in prostatitis diagnosis.

Authors:  Tijl Vermassen; Charles Van Praet; Filip Poelaert; Nicolaas Lumen; Karel Decaestecker; Piet Hoebeke; Simon Van Belle; Sylvie Rottey; Joris Delanghe
Journal:  Biochem Med (Zagreb)       Date:  2015-10-15       Impact factor: 2.313

9.  High-throughput analysis of N-glycans using AutoTip via glycoprotein immobilization.

Authors:  Shuang Yang; David Clark; Yang Liu; Shuwei Li; Hui Zhang
Journal:  Sci Rep       Date:  2017-08-31       Impact factor: 4.379

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.