Literature DB >> 11146442

Correlation of clinical data with proteomics profiles in 24 patients with B-cell chronic lymphocytic leukemia.

T Voss1, H Ahorn, P Haberl, H Döhner, K Wilgenbus.   

Abstract

The development of human cancer is caused by complex molecular perturbations leading to variable clinical behavior often even in single disease entities. To prove that expression profiling on the protein level can be correlated with clinical data we systematically compared in a pilot study the protein expression patterns obtained by 2-dimensional gel electrophoresis with clinical features in human B-cell chronic lymphocytic leukemia (B-CLL), a disease characterized by broad clinical variability. Statistical methods were devised to analyze the spot pattern from 24 patient samples. This analysis allowed the identification of proteins that clearly discriminated between the patient groups with defined chromosomal characteristics or whose expression levels did correlate with clinical parameters such as patient survival. This report demonstrates that the correlation of large-scale protein expression profiles with clinical data can be used to gain new insights into molecular aspects of a disease. The data described here show that B-CLL patient populations with shorter survival times exhibit changed levels of redox enzymes, heat shock protein 27 and protein disulfide isomerase. These molecules may be potentially involved in drug resistance. Copyright 2001 Wiley-Liss, Inc.

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Year:  2001        PMID: 11146442     DOI: 10.1002/1097-0215(200002)9999:9999<::aid-ijc1037>3.0.co;2-j

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  9 in total

Review 1.  Current perspectives in cancer proteomics.

Authors:  Miriam V Dwek; Sarah L Rawlings
Journal:  Mol Biotechnol       Date:  2002-10       Impact factor: 2.695

2.  Quantitative protein expression analysis of CLL B cells from mutated and unmutated IgV(H) subgroups using acid-cleavable isotope-coded affinity tag reagents.

Authors:  David R Barnidge; Diane F Jelinek; David C Muddiman; Neil E Kay
Journal:  J Proteome Res       Date:  2005 Jul-Aug       Impact factor: 4.466

3.  Clinical proteomics: present and future prospects.

Authors:  Nicole M Verrills
Journal:  Clin Biochem Rev       Date:  2006-05

4.  A unique proteomic profile on surface IgM ligation in unmutated chronic lymphocytic leukemia.

Authors:  Aurore Perrot; Cédric Pionneau; Sophie Nadaud; Frédéric Davi; Véronique Leblond; Frédéric Jacob; Hélène Merle-Béral; Raoul Herbrecht; Marie-Christine Béné; John G Gribben; Seiamak Bahram; Laurent Vallat
Journal:  Blood       Date:  2011-05-20       Impact factor: 22.113

5.  Construction of protein profile classification model and screening of proteomic signature of acute leukemia.

Authors:  Yun Xu; Jiacai Zhuo; Yonggang Duan; Benhang Shi; Xuhong Chen; Xiaoli Zhang; Liang Xiao; Jin Lou; Ruihong Huang; Qiongli Zhang; Xin Du; Ming Li; Daping Wang; Dunyun Shi
Journal:  Int J Clin Exp Pathol       Date:  2014-08-15

6.  Change in serum proteome during allogeneic hematopoietic stem cell transplantation and clinical significance of serum C-reactive protein and haptoglobin.

Authors:  Joohyun Ryu; Se Ryeon Lee; Sung Goo Park; Sunghyun Kang; Hyeoung-Joon Kim; Byoung Chul Park
Journal:  Exp Mol Med       Date:  2010-09-30       Impact factor: 8.718

Review 7.  Use of comparative proteomics to identify potential resistance mechanisms in cancer treatment.

Authors:  Jian-Ting Zhang; Yang Liu
Journal:  Cancer Treat Rev       Date:  2007-09-12       Impact factor: 12.111

Review 8.  Contribution of oncoproteomics to cancer biomarker discovery.

Authors:  William C S Cho
Journal:  Mol Cancer       Date:  2007-04-02       Impact factor: 27.401

9.  High correlation of the proteome patterns in bone marrow and peripheral blood blast cells in patients with acute myeloid leukemia.

Authors:  Gero Hütter; Anne Letsch; Daniel Nowak; Julia Poland; Pranav Sinha; Eckhard Thiel; Wolf-K Hofmann
Journal:  J Transl Med       Date:  2009-01-15       Impact factor: 5.531

  9 in total

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