Literature DB >> 9150955

A protein expression database for the molecular pharmacology of cancer.

T G Myers1, N L Anderson, M Waltham, G Li, J K Buolamwini, D A Scudiero, K D Paull, E A Sausville, J N Weinstein.   

Abstract

In the last six years, the Developmental Therapeutics Program (DTP) of the US National Cancer Institute (NCI) has screened over 60,000 chemical compounds and a larger number of natural product extracts for their ability to inhibit growth of 60 different cancer cell lines representing different organs of origin. Whereas inhibition of the growth of one cancer cell type gives no information on drug specificity, the relative growth inhibitory activities against 60 different cells constitute patterns that encode detailed information on mechanisms of action and resistance (as reviewed in Boyd and Paull, Drug Devel. Res. 1995, 34, 19-109 and Weinstein et al., Science 1997, 275, 343-349). In order to correlate the patterns of activity with properties of the cells, we and other laboratories are characterizing the cells with respect to a large number of factors at the DNA, mRNA, and protein levels. As part of that effort, we have developed a two-dimensional gel electrophoresis (2-DE) protein expression database covering all 60 cell types (Buolamwini et al., submitted). Here we present analyses of the correlations among protein spots (i) in terms of their patterns of expression and (ii) in terms of their apparent relationships to the pharmacology of a set of 3989 screened compounds. The correlations tend to be stronger for the latter than for the former, suggesting that the spots have more robust signatures in terms of the pharmacology than in terms of expression levels. Links to pertinent databases and tools of analysis will be updated progressively at http:@www.nci.nih.gov/intra/lmp/jnwbio.htm and http:@epnwsl.ncifcrf.gov:2345/dis3d/dtp.++ +html.

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Year:  1997        PMID: 9150955     DOI: 10.1002/elps.1150180351

Source DB:  PubMed          Journal:  Electrophoresis        ISSN: 0173-0835            Impact factor:   3.535


  13 in total

Review 1.  The complexity of radiation stress responses: analysis by informatics and functional genomics approaches.

Authors:  A J Fornace; S A Amundson; M Bittner; T G Myers; P Meltzer; J N Weinsten; J Trent
Journal:  Gene Expr       Date:  1999

2.  Common origins of MDA-MB-435 cells from various sources with those shown to have melanoma properties.

Authors:  James M Rae; Susan J Ramus; Mark Waltham; Jane E Armes; Ian G Campbell; Robert Clarke; Robert J Barndt; Michael D Johnson; Erik W Thompson
Journal:  Clin Exp Metastasis       Date:  2004       Impact factor: 5.150

3.  Clinical proteomics: present and future prospects.

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

4.  Integrating data on DNA copy number with gene expression levels and drug sensitivities in the NCI-60 cell line panel.

Authors:  Kimberly J Bussey; Koei Chin; Samir Lababidi; Mark Reimers; William C Reinhold; Wen-Lin Kuo; Fuad Gwadry; Hosein Kouros-Mehr; Jane Fridlyand; Ajay Jain; Colin Collins; Satoshi Nishizuka; Giovanni Tonon; Anna Roschke; Kristen Gehlhaus; Ilan Kirsch; Dominic A Scudiero; Joe W Gray; John N Weinstein
Journal:  Mol Cancer Ther       Date:  2006-04       Impact factor: 6.261

5.  A Galaxy Implementation of Next-Generation Clustered Heatmaps for Interactive Exploration of Molecular Profiling Data.

Authors:  Bradley M Broom; Michael C Ryan; Robert E Brown; Futa Ikeda; Mark Stucky; David W Kane; James Melott; Chris Wakefield; Tod D Casasent; Rehan Akbani; John N Weinstein
Journal:  Cancer Res       Date:  2017-11-01       Impact factor: 12.701

6.  Compression wood-responsive proteins in developing xylem of maritime pine (Pinus pinaster ait.).

Authors:  C Plomion; C Pionneau; J Brach; P Costa; H Baillères
Journal:  Plant Physiol       Date:  2000-07       Impact factor: 8.340

7.  Comparing cDNA and oligonucleotide array data: concordance of gene expression across platforms for the NCI-60 cancer cells.

Authors:  Jae K Lee; Kimberly J Bussey; Fuad G Gwadry; William Reinhold; Gregory Riddick; Sandra L Pelletier; Satoshi Nishizuka; Gergely Szakacs; Jean-Phillipe Annereau; Uma Shankavaram; Samir Lababidi; Lawrence H Smith; Michael M Gottesman; John N Weinstein
Journal:  Genome Biol       Date:  2003-11-25       Impact factor: 13.583

8.  In vitro differential sensitivity of melanomas to phenothiazines is based on the presence of codon 600 BRAF mutation.

Authors:  Ogechi N Ikediobi; Mark Reimers; Steffen Durinck; Paul E Blower; Andrew P Futreal; Michael R Stratton; John N Weinstein
Journal:  Mol Cancer Ther       Date:  2008-06-04       Impact factor: 6.261

9.  Proteomic profiling of the NCI-60 cancer cell lines using new high-density reverse-phase lysate microarrays.

Authors:  Satoshi Nishizuka; Lu Charboneau; Lynn Young; Sylvia Major; William C Reinhold; Mark Waltham; Hosein Kouros-Mehr; Kimberly J Bussey; Jae K Lee; Virginia Espina; Peter J Munson; Emanuel Petricoin; Lance A Liotta; John N Weinstein
Journal:  Proc Natl Acad Sci U S A       Date:  2003-11-17       Impact factor: 11.205

10.  AbMiner: a bioinformatic resource on available monoclonal antibodies and corresponding gene identifiers for genomic, proteomic, and immunologic studies.

Authors:  Sylvia M Major; Satoshi Nishizuka; Daisaku Morita; Rick Rowland; Margot Sunshine; Uma Shankavaram; Frank Washburn; Daniel Asin; Hosein Kouros-Mehr; David Kane; John N Weinstein
Journal:  BMC Bioinformatics       Date:  2006-04-06       Impact factor: 3.169

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