Literature DB >> 27184840

Glycosaminoglycan Profiling in Patients' Plasma and Urine Predicts the Occurrence of Metastatic Clear Cell Renal Cell Carcinoma.

Francesco Gatto1, Nicola Volpi2, Helén Nilsson3, Intawat Nookaew1, Marco Maruzzo4, Anna Roma4, Martin E Johansson3, Ulrika Stierner5, Sven Lundstam6, Umberto Basso4, Jens Nielsen7.   

Abstract

Metabolic reprogramming is a hallmark of clear cell renal cell carcinoma (ccRCC) progression. Here, we used genome-scale metabolic modeling to elucidate metabolic reprogramming in 481 ccRCC samples and discovered strongly coordinated regulation of glycosaminoglycan (GAG) biosynthesis at the transcript and protein levels. Extracellular GAGs are implicated in metastasis, so we speculated that such regulation might translate into a non-invasive biomarker for metastatic ccRCC (mccRCC). We measured 18 GAG properties in 34 mccRCC samples versus 16 healthy plasma and/or urine samples. The GAG profiles were distinctively altered in mccRCC. We derived three GAG scores that distinguished mccRCC patients with 93.1%-100% accuracy. We validated the score accuracies in an independent cohort (up to 18 mccRCC versus nine healthy) and verified that the scores normalized in eight patients with no evidence of disease. In conclusion, coordinated regulation of GAG biosynthesis occurs in ccRCC, and non-invasive GAG profiling is suitable for mccRCC diagnosis.
Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

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Year:  2016        PMID: 27184840     DOI: 10.1016/j.celrep.2016.04.056

Source DB:  PubMed          Journal:  Cell Rep            Impact factor:   9.423


  14 in total

1.  One-pot analysis of sulfated glycosaminoglycans.

Authors:  C B Shrikanth; J Sanjana; Nandini D Chilkunda
Journal:  Glycoconj J       Date:  2017-12-05       Impact factor: 2.916

2.  IDENTIFYING CANCER SPECIFIC METABOLIC SIGNATURES USING CONSTRAINT-BASED MODELS.

Authors:  A Schultz; S Mehta; C W Hu; F W Hoff; T M Horton; S M Kornblau; A A Qutub
Journal:  Pac Symp Biocomput       Date:  2017

3.  Genome-Scale Metabolic Modeling from Yeast to Human Cell Models of Complex Diseases: Latest Advances and Challenges.

Authors:  Yu Chen; Gang Li; Jens Nielsen
Journal:  Methods Mol Biol       Date:  2019

4.  Structural characterization of a clinically described heparin-like substance in plasma causing bleeding.

Authors:  Yanlei Yu; Karen Bruzdoski; Vadim Kostousov; Lisa Hensch; Shiu-Ki Hui; Fakiha Siddiqui; Amber Farooqui; Ahmed Kouta; Fuming Zhang; Jawed Fareed; Jun Teruya; Robert J Linhardt
Journal:  Carbohydr Polym       Date:  2020-05-19       Impact factor: 9.381

Review 5.  Roles of Proteoglycans and Glycosaminoglycans in Cancer Development and Progression.

Authors:  Jinfen Wei; Meiling Hu; Kaitang Huang; Shudai Lin; Hongli Du
Journal:  Int J Mol Sci       Date:  2020-08-20       Impact factor: 5.923

Review 6.  Enzymatic Synthesis of Glycans and Glycoconjugates.

Authors:  Thomas Rexer; Dominic Laaf; Johannes Gottschalk; Hannes Frohnmeyer; Erdmann Rapp; Lothar Elling
Journal:  Adv Biochem Eng Biotechnol       Date:  2021       Impact factor: 2.635

7.  Prognostic Value of Plasma and Urine Glycosaminoglycan Scores in Clear Cell Renal Cell Carcinoma.

Authors:  Francesco Gatto; Marco Maruzzo; Cristina Magro; Umberto Basso; Jens Nielsen
Journal:  Front Oncol       Date:  2016-11-24       Impact factor: 6.244

8.  A simple method for detecting oncofetal chondroitin sulfate glycosaminoglycans in bladder cancer urine.

Authors:  Thomas Mandel Clausen; Gunjan Kumar; Emilie K Ibsen; Maj S Ørum-Madsen; Antonio Hurtado-Coll; Tobias Gustavsson; Mette Ø Agerbæk; Francesco Gatto; Tilman Todenhöfer; Umberto Basso; Margaret A Knowles; Marta Sanchez-Carbayo; Ali Salanti; Peter C Black; Mads Daugaard
Journal:  Cell Death Discov       Date:  2020-07-27

Review 9.  Glycosaminoglycan-Inspired Biomaterials for the Development of Bioactive Hydrogel Networks.

Authors:  Mariana I Neves; Marco Araújo; Lorenzo Moroni; Ricardo M P da Silva; Cristina C Barrias
Journal:  Molecules       Date:  2020-02-21       Impact factor: 4.411

10.  A Three-Metabolic-Genes Risk Score Model Predicts Overall Survival in Clear Cell Renal Cell Carcinoma Patients.

Authors:  Yiqiao Zhao; Zijia Tao; Xiaonan Chen
Journal:  Front Oncol       Date:  2020-10-22       Impact factor: 6.244

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