Literature DB >> 21137047

Banking of clinical samples for proteomic biomarker studies: a consideration of logistical issues with a focus on pre-analytical variation.

David H Jackson1, Rosamonde E Banks.   

Abstract

Biobanks with their collections of clinical samples and data are essential resources for the success of clinical proteomics in delivering and validating candidate biomarkers. Samples must be banked in a manner that allows maximum subsequent compatibility with analytical techniques and additionally many critical factors must be taken into account when establishing a biobank or selecting samples from a biobank. These include logistical, ethical, legal and security issues and, very importantly, steps to minimise any pre-analytical variability introduced through sample processing and handling (technical effects). The inherent variation present within the samples must also be taken into account. In this review, we examine the impact of these factors and issues to be faced when banking samples with a particular focus on sources of pre-analytical variation, which must be rigorously controlled and recorded. It is encouraging that several initiatives are now addressing such key issues and these are also discussed.
Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2010        PMID: 21137047     DOI: 10.1002/prca.200900220

Source DB:  PubMed          Journal:  Proteomics Clin Appl        ISSN: 1862-8346            Impact factor:   3.494


  22 in total

Review 1.  Proteomics and diabetic nephropathy: what have we learned from a decade of clinical proteomics studies?

Authors:  Massimo Papale; Salvatore Di Paolo; Grazia Vocino; Maria Teresa Rocchetti; Loreto Gesualdo
Journal:  J Nephrol       Date:  2014-02-25       Impact factor: 3.902

Review 2.  Proteomic studies of urinary biomarkers for prostate, bladder and kidney cancers.

Authors:  Steven L Wood; Margaret A Knowles; Douglas Thompson; Peter J Selby; Rosamonde E Banks
Journal:  Nat Rev Urol       Date:  2013-02-26       Impact factor: 14.432

Review 3.  Proteomic Approaches to Decipher Mechanisms Underlying Pathogenesis in Multiple Sclerosis Patients.

Authors:  Vaibhav Singh; Ajai Tripathi; Ranjan Dutta
Journal:  Proteomics       Date:  2019-06-21       Impact factor: 3.984

4.  Elevating sampling.

Authors:  Joseph M Labuz; Shuichi Takayama
Journal:  Lab Chip       Date:  2014-09-07       Impact factor: 6.799

Review 5.  Before you analyze a human specimen, think quality, variability, and bias.

Authors:  Mark David Lim; Anthony Dickherber; Carolyn C Compton
Journal:  Anal Chem       Date:  2010-11-29       Impact factor: 6.986

6.  On Comprehensive Mass Spectrometry Data Analysis for Proteome Profiling of Human Blood Samples.

Authors:  Sameer Manchanda; Mikaela Meyer; Qianqian Li; Kai Liang; Yan Li; Nan Kong
Journal:  J Healthc Inform Res       Date:  2018-05-22

Review 7.  Biomarker discovery in mass spectrometry-based urinary proteomics.

Authors:  Samuel Thomas; Ling Hao; William A Ricke; Lingjun Li
Journal:  Proteomics Clin Appl       Date:  2016-02-11       Impact factor: 3.494

Review 8.  Taking a new biomarker into routine use--a perspective from the routine clinical biochemistry laboratory.

Authors:  Catharine Sturgeon; Robert Hill; Glen L Hortin; Douglas Thompson
Journal:  Proteomics Clin Appl       Date:  2010-11-22       Impact factor: 3.494

Review 9.  Variation in parathyroid hormone immunoassay results--a critical governance issue in the management of chronic kidney disease.

Authors:  Catharine M Sturgeon; Stuart M Sprague; Wendy Metcalfe
Journal:  Nephrol Dial Transplant       Date:  2011-11       Impact factor: 5.992

10.  Predicting response to bevacizumab in ovarian cancer: a panel of potential biomarkers informing treatment selection.

Authors:  Fiona Collinson; Michelle Hutchinson; Rachel A Craven; David A Cairns; Alexandre Zougman; Tobias C Wind; Narinder Gahir; Michael P Messenger; Sharon Jackson; Douglas Thompson; Cybil Adusei; Jonathan A Ledermann; Geoffrey Hall; Gordon C Jayson; Peter J Selby; Rosamonde E Banks
Journal:  Clin Cancer Res       Date:  2013-08-09       Impact factor: 12.531

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