Literature DB >> 15283891

Clinical proteomics: Applications for prostate cancer biomarker discovery and detection.

Emanuel F Petricoin1, David K Ornstein, Lance A Liotta.   

Abstract

The science of proteomics comprises much more than simply generating lists of proteins that change in expression as a cause of or consequence of pathophysiology. The goal of proteomics should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. Serum proteomic pattern diagnostics is a new type of proteomic concept in which patterns of ion signatures generated from high dimensional mass spectrometry data are used as diagnostic classifiers. This recent approach has exciting potential for clinical utility of diagnostic patterns because low molecular weight metabolites, peptides, and protein fragments may have higher accuracy than traditional biomarkers of cancer detection. Intriguingly, we now have discovered that this diagnostic information exists in a bound state, complexed with circulating highly abundant carrier proteins. These diagnostic fragments may one day be harvested by circulating nanoparticles, designed to absorb, enrich, and amplify the repertoire of diagnostic biomarkers generated-even at the critical, initial stages of carcinogenesis. Copyright 2004 Elsevier Inc.

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Year:  2004        PMID: 15283891     DOI: 10.1016/j.urolonc.2004.04.011

Source DB:  PubMed          Journal:  Urol Oncol        ISSN: 1078-1439            Impact factor:   3.498


  9 in total

Review 1.  Proteomic technology for biomarker profiling in cancer: an update.

Authors:  Moulay A Alaoui-Jamali; Ying-jie Xu
Journal:  J Zhejiang Univ Sci B       Date:  2006-06       Impact factor: 3.066

2.  Detection of pre-neoplastic and neoplastic prostate disease by MALDI profiling of urine.

Authors:  Amosy E M'Koma; David L Blum; Jeremy L Norris; Tatsuki Koyama; Dean Billheimer; Saundra Motley; Mayshan Ghiassi; Nika Ferdowsi; Indrani Bhowmick; Sam S Chang; Jay H Fowke; Richard M Caprioli; Neil A Bhowmick
Journal:  Biochem Biophys Res Commun       Date:  2006-12-22       Impact factor: 3.575

3.  Estimating the AUC with a Graphical Lasso Method for High-dimensional Biomarkers with LOD.

Authors:  Jirui Wang; Yunpeng Zhao; Liansheng Larry Tang
Journal:  Biostat Epidemiol       Date:  2021-03-17

4.  A proteomic workflow for discovery of serum carrier protein-bound biomarker candidates of alcohol abuse using LC-MS/MS.

Authors:  Xianyin Lai; Suthat Liangpunsakul; David W Crabb; Heather N Ringham; Frank A Witzmann
Journal:  Electrophoresis       Date:  2009-06       Impact factor: 3.535

5.  Combining markers with and without the limit of detection.

Authors:  Ting Dong; Catherine Chunling Liu; Emanuel F Petricoin; Liansheng Larry Tang
Journal:  Stat Med       Date:  2013-10-17       Impact factor: 2.373

6.  A protein profile study to discriminate CIN lesions from normal cervical epithelium.

Authors:  Kai-Erik Uleberg; Ane Cecilie Munk; Ivar Skaland; Cristina Furlan; Bianca van Diermen; Einar Gudlaugsson; Emiel A M Janssen; Anais Malpica; Weiwei Feng; Anne Hjelle; Jan P A Baak
Journal:  Cell Oncol (Dordr)       Date:  2011-05-15       Impact factor: 6.730

Review 7.  Personalized exposure assessment: promising approaches for human environmental health research.

Authors:  Brenda K Weis; David Balshaw; John R Barr; David Brown; Mark Ellisman; Paul Lioy; Gilbert Omenn; John D Potter; Martyn T Smith; Lydia Sohn; William A Suk; Susan Sumner; James Swenberg; David R Walt; Simon Watkins; Claudia Thompson; Samuel H Wilson
Journal:  Environ Health Perspect       Date:  2005-07       Impact factor: 9.031

8.  A novel blood-based biomarker for detection of autism spectrum disorders.

Authors:  N Momeni; J Bergquist; L Brudin; F Behnia; B Sivberg; M T Joghataei; B L Persson
Journal:  Transl Psychiatry       Date:  2012-03-13       Impact factor: 6.222

9.  Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles.

Authors:  Guangtao Ge; G William Wong
Journal:  BMC Bioinformatics       Date:  2008-06-11       Impact factor: 3.169

  9 in total

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