Literature DB >> 34354152

Alterations in protein expression and site-specific N-glycosylation of prostate cancer tissues.

Simon Sugár1,2, Gábor Tóth1,3, Fanni Bugyi1,4, Károly Vékey1, Katalin Karászi5, László Drahos1, Lilla Turiák6,7.   

Abstract

Identifying molecular alterations occurring during cancer progression is essential for a deeper understanding of the underlying biological processes. Here we have analyzed cancerous and healthy prostate biopsies using nanoLC-MS(MS) to detect proteins with altered expression and N-glycosylation. We have identified 75 proteins with significantly changing expression during disease progression. The biological processes involved were assigned based on protein-protein interaction networks. These include cellular component organization, metabolic and localization processes. Multiple glycoproteins were identified with aberrant glycosylation in prostate cancer, where differences in glycosite-specific sialylation, fucosylation, and galactosylation were the most substantial. Many of the glycoproteins with altered N-glycosylation were extracellular matrix constituents, and are heavily involved in the establishment of the tumor microenvironment.
© 2021. The Author(s).

Entities:  

Year:  2021        PMID: 34354152     DOI: 10.1038/s41598-021-95417-5

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  44 in total

1.  Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study.

Authors:  Peter Ström; Kimmo Kartasalo; Henrik Olsson; Leslie Solorzano; Brett Delahunt; Daniel M Berney; David G Bostwick; Andrew J Evans; David J Grignon; Peter A Humphrey; Kenneth A Iczkowski; James G Kench; Glen Kristiansen; Theodorus H van der Kwast; Katia R M Leite; Jesse K McKenney; Jon Oxley; Chin-Chen Pan; Hemamali Samaratunga; John R Srigley; Hiroyuki Takahashi; Toyonori Tsuzuki; Murali Varma; Ming Zhou; Johan Lindberg; Cecilia Lindskog; Pekka Ruusuvuori; Carolina Wählby; Henrik Grönberg; Mattias Rantalainen; Lars Egevad; Martin Eklund
Journal:  Lancet Oncol       Date:  2020-01-08       Impact factor: 41.316

2.  Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study.

Authors:  Wouter Bulten; Hans Pinckaers; Hester van Boven; Robert Vink; Thomas de Bel; Bram van Ginneken; Jeroen van der Laak; Christina Hulsbergen-van de Kaa; Geert Litjens
Journal:  Lancet Oncol       Date:  2020-01-08       Impact factor: 41.316

3.  Advantages of replacing the total PSA assay with the assay for PSA-alpha 1-antichymotrypsin complex for the screening and management of prostate cancer.

Authors:  J T Wu; G H Liu
Journal:  J Clin Lab Anal       Date:  1998       Impact factor: 2.352

4.  Overdiagnosis of prostate cancer.

Authors:  Gurdarshan S Sandhu; Gerald L Andriole
Journal:  J Natl Cancer Inst Monogr       Date:  2012-12

Review 5.  Recent advances in image-guided targeted prostate biopsy.

Authors:  Anna M Brown; Osama Elbuluk; Francesca Mertan; Sandeep Sankineni; Daniel J Margolis; Bradford J Wood; Peter A Pinto; Peter L Choyke; Baris Turkbey
Journal:  Abdom Imaging       Date:  2015-08

6.  Underestimation of Gleason score at prostate biopsy reflects sampling error in lower volume tumours.

Authors:  Niall M Corcoran; Chris M Hovens; Matthew K H Hong; John Pedersen; Rowan G Casey; Stephen Connolly; Justin Peters; Laurence Harewood; Martin E Gleave; S Larry Goldenberg; Anthony J Costello
Journal:  BJU Int       Date:  2011-09-02       Impact factor: 5.588

7.  EAU-ESTRO-SIOG Guidelines on Prostate Cancer. Part 1: Screening, Diagnosis, and Local Treatment with Curative Intent.

Authors:  Nicolas Mottet; Joaquim Bellmunt; Michel Bolla; Erik Briers; Marcus G Cumberbatch; Maria De Santis; Nicola Fossati; Tobias Gross; Ann M Henry; Steven Joniau; Thomas B Lam; Malcolm D Mason; Vsevolod B Matveev; Paul C Moldovan; Roderick C N van den Bergh; Thomas Van den Broeck; Henk G van der Poel; Theo H van der Kwast; Olivier Rouvière; Ivo G Schoots; Thomas Wiegel; Philip Cornford
Journal:  Eur Urol       Date:  2016-08-25       Impact factor: 20.096

8.  MRI-Targeted, Systematic, and Combined Biopsy for Prostate Cancer Diagnosis.

Authors:  Michael Ahdoot; Andrew R Wilbur; Sarah E Reese; Amir H Lebastchi; Sherif Mehralivand; Patrick T Gomella; Jonathan Bloom; Sandeep Gurram; Minhaj Siddiqui; Paul Pinsky; Howard Parnes; W Marston Linehan; Maria Merino; Peter L Choyke; Joanna H Shih; Baris Turkbey; Bradford J Wood; Peter A Pinto
Journal:  N Engl J Med       Date:  2020-03-05       Impact factor: 91.245

9.  Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists.

Authors:  Wouter Bulten; Maschenka Balkenhol; Jean-Joël Awoumou Belinga; Américo Brilhante; Aslı Çakır; Lars Egevad; Martin Eklund; Xavier Farré; Katerina Geronatsiou; Vincent Molinié; Guilherme Pereira; Paromita Roy; Günter Saile; Paulo Salles; Ewout Schaafsma; Joëlle Tschui; Anne-Marie Vos; Hester van Boven; Robert Vink; Jeroen van der Laak; Christina Hulsbergen-van der Kaa; Geert Litjens
Journal:  Mod Pathol       Date:  2020-08-05       Impact factor: 7.842

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  3 in total

1.  Proteomic Analysis of Lung Cancer Types-A Pilot Study.

Authors:  Simon Sugár; Fanni Bugyi; Gábor Tóth; Judit Pápay; Ilona Kovalszky; Tamás Tornóczky; László Drahos; Lilla Turiák
Journal:  Cancers (Basel)       Date:  2022-05-26       Impact factor: 6.575

Review 2.  From Omics to Multi-Omics Approaches for In-Depth Analysis of the Molecular Mechanisms of Prostate Cancer.

Authors:  Ekaterina Nevedomskaya; Bernard Haendler
Journal:  Int J Mol Sci       Date:  2022-06-03       Impact factor: 6.208

3.  An analytical study on the identification of N-linked glycosylation sites using machine learning model.

Authors:  Muhammad Aizaz Akmal; Muhammad Awais Hassan; Shoaib Muhammad; Khaldoon S Khurshid; Abdullah Mohamed
Journal:  PeerJ Comput Sci       Date:  2022-09-21
  3 in total

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