Literature DB >> 15814023

The importance of experimental design in proteomic mass spectrometry experiments: some cautionary tales.

Jianhua Hu1, Kevin R Coombes, Jeffrey S Morris, Keith A Baggerly.   

Abstract

Proteomic expression patterns derived from mass spectrometry have been put forward as potential biomarkers for the early diagnosis of cancer and other diseases. This approach has generated much excitement and has led to a large number of new experiments and vast amounts of new data. The data, derived at great expense, can have very little value if careful attention is not paid to the experimental design and analysis. Using examples from surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) and matrix-assisted laser desorption-ionisation/time-of-flight (MALDI-TOF) experiments, we describe several experimental design issues that can corrupt a dataset. Fortunately, the problems we identify can be avoided if attention is paid to potential sources of bias before the experiment is run. With an appropriate experimental design, proteomics technology can be a useful tool for discovering important information relating protein expression to disease.

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Year:  2005        PMID: 15814023     DOI: 10.1093/bfgp/3.4.322

Source DB:  PubMed          Journal:  Brief Funct Genomic Proteomic        ISSN: 1473-9550


  40 in total

1.  Proteomic profiling of cerebrospinal fluid identifies prostaglandin D2 synthase as a putative biomarker for pediatric medulloblastoma: A pediatric brain tumor consortium study.

Authors:  Meena U Rajagopal; Yetrib Hathout; Tobey J MacDonald; Mark W Kieran; Sri Gururangan; Susan M Blaney; Peter Phillips; Roger Packer; Heather Gordish-Dressman; Brian R Rood
Journal:  Proteomics       Date:  2011-01-27       Impact factor: 3.984

2.  Statistical contributions to proteomic research.

Authors:  Jeffrey S Morris; Keith A Baggerly; Howard B Gutstein; Kevin R Coombes
Journal:  Methods Mol Biol       Date:  2010

Review 3.  Multiplexed protein measurement: technologies and applications of protein and antibody arrays.

Authors:  Stephen F Kingsmore
Journal:  Nat Rev Drug Discov       Date:  2006-04       Impact factor: 84.694

Review 4.  Laser capture sampling and analytical issues in proteomics.

Authors:  Howard B Gutstein; Jeffrey S Morris
Journal:  Expert Rev Proteomics       Date:  2007-10       Impact factor: 3.940

5.  Bayesian analysis of mass spectrometry proteomic data using wavelet-based functional mixed models.

Authors:  Jeffrey S Morris; Philip J Brown; Richard C Herrick; Keith A Baggerly; Kevin R Coombes
Journal:  Biometrics       Date:  2007-09-20       Impact factor: 2.571

6.  An insight into high-resolution mass-spectrometry data.

Authors:  J E Eckel-Passow; A L Oberg; T M Therneau; H R Bergen
Journal:  Biostatistics       Date:  2009-03-26       Impact factor: 5.899

7.  Development and evaluation of normalization methods for label-free relative quantification of endogenous peptides.

Authors:  Kim Kultima; Anna Nilsson; Birger Scholz; Uwe L Rossbach; Maria Fälth; Per E Andrén
Journal:  Mol Cell Proteomics       Date:  2009-07-12       Impact factor: 5.911

Review 8.  Challenges for biomarker discovery in body fluids using SELDI-TOF-MS.

Authors:  Muriel De Bock; Dominique de Seny; Marie-Alice Meuwis; Jean-Paul Chapelle; Edouard Louis; Michel Malaise; Marie-Paule Merville; Marianne Fillet
Journal:  J Biomed Biotechnol       Date:  2009-12-06

Review 9.  Current status and prospects of clinical proteomics studies on detection of colorectal cancer: hopes and fears.

Authors:  M E de Noo; R A E M Tollenaar; A M Deelder; L H Bouwman
Journal:  World J Gastroenterol       Date:  2006-11-07       Impact factor: 5.742

10.  Proteomic classification of acute leukemias by alignment-based quantitation of LC-MS/MS data sets.

Authors:  Eric J Foss; Dragan Radulovic; Derek L Stirewalt; Jerald Radich; Olga Sala-Torra; Era L Pogosova-Agadjanyan; Shawna M Hengel; Keith R Loeb; H Joachim Deeg; Soheil Meshinchi; David R Goodlett; Antonio Bedalov
Journal:  J Proteome Res       Date:  2012-09-11       Impact factor: 4.466

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