A Protein Expression Database for the Molecular Pharmacology of Cancer

(Web page under construction)

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In the last six years, the Developmental Therapeutics Program (DTP) of the U.S. 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 cancer cell lines representing different organs of origin. Included are leukemias and lymphomas, as well as cancers of breast, prostate, ovary, lung, colon, kidney, and central nervous system 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 encode rich, detailed information on mechanisms of action and resistance [1-4 (see references below)]. 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 2-dimensional gel electrophoresis (2-DE) protein expression database covering all 60 cell types [5,6].

Over the next months, this web site will be fleshed out with gel images, databaseses, and links to other pertinent sites. Included will be analyses of the correlations among protein spots (i) in terms of their patterns of expression and (ii) in terms of their apparent relationships to drug activity for a set of approximately 4,000 tested compounds.

For methods, see refs. [5,6] below as well as the Large Scale Biology web site.

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2-D Gel Images

1,014 spots have been indexed, and 151 spots have been incorporated into a quality-controlled database for analysis. The indexing was done on a master gel obtained by electrophoresing a mixture of cell types. A central portion of the master gel image is shown below.

Computer-Processed Image of 2-D Gel Master. (546 x 508 pixels). Red peudo-color indicates a spot in the quality-controlled database of 151; blue pseudo-color indicates one of the other spots. Labels indicate spots presumptively identified to date.

Click on image for larger version (536 x 408 pixels).

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Comparing 2-D Gels (The Flicker Program)

Peter Lemkin (Image Processing Section, Laboratory of Mathematical Biology, National Cancer Institute) has developed a program called Flicker [7,8] for cross-comparing gel images on the web. This program is demonstrated for the above master image and 2-D gels from MCF7 breast cancer cells. Additional gels from the database will be added over the next months, along with comparison gels run on the same cell lines but in different laboratories. More information on this program, including a reference manual, can be found through the Flicker home page.

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A Clickable Gel Image Database

Peter Lemkin (Image Processing Section, Laboratory of Mathematical Biology, National Cancer Institute) has developed a program for clicking on a 2-D gel spot to (i) access information on that spot (protein) in a database and (ii) link to information on the protein in other databases (e.g., SWISS-PROT). The basis is Peter's search engine program dbENGINE. A demonstration is currently operational for plasma protein 2-D gels, but the master gel shown above, along with others from the NCI drug discovery cell set, will be available soon.

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Identification of Spots by MALDI-Mass Spec.

This page is under construction, but see Li, et al. [9] in reference section below.

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  1. Paull, K.D., Hamel, E., and Malspeis, L. Display and analysis of patterns of differntial activity of drugs against human tumor cell lines: Development of mean graph and COMPARE algorithm. J. Natl. Cancer Inst. 81: 1088-1092, 1989.
  2. Boyd, M.R. and Paull, K.D. Some practical considerations and applications of the National Cancer Institute in vitro anticancer drug discovery screen. Drug Devel. Res. 34: 91, 1995.
  3. Weinstein, J.N., Kohn, K.W., Grever, M.R., Viswanadhan, V.N., Rubinstein, L.V., Monks, A., Scudiero, D.A., Welch, L., Koutsoukos, A., Chiausa, A.J., and Paull, K.D. Neural computing in cancer drug development: Predicting mechanism of action. Science 258: 447-451, 1992. (Abstract)
  4. Weinstein, J.N., Myers, T.G., O'Connor, P.M., Friend, S.H., Fornace, A.J., Kohn, K.W., Fojo, T., Bates, S.E., Rubinstein, L.V., Anderson, N.L., Buolamwini, J.K., van Osdol, W.W., Monks, A.P., Scudiero, D.A., Sausville, E.A., Zaharevitz, D.W., Viswanadhan, V., Bunow, B., Johnson, G.S., Wittes, R.E., and Paull, K.D. An information-intensive approach to the molecular pharmacology of cancer. Science 275: 343-349 (1997) (January 17 issue). (Abstract)
  5. Myers, T.G., Waltham, M., Li, G., Buolamwini, J.K., Scudiero, D.A., Rubinstein, L.V., Paull, K.D., Sausville, E.A., Anderson, N.L., and Weinstein, J.N., A protein expression database for the molecular pharmacology of cancer. Electrophoresis , in press. (Abstract)
  6. Buolamwini, J.K., Myers, T.G., Anderson, N.L., Waltham, M., Li, G., Scudiero, D.A., Paull, K.D., Peterfy, M., Sausville, E.A., Kohn, K.W., and Weinstein, J.N. Patterns of protein expression in cells of the NCI cancer drug discovery program, submitted. (Abstract)
  7. Lemkin, P.F., Chipperfield, M., Merril, C., and Zullo, S. A world wide web (WWW) server database engine for an organelle database, MitoDat. Electrophoresis 17: 566-572, 1996.
  8. Lemkin, P.F. Comparing two-dimensional electrophoretic gel images across the internet. Electrophoresis, in press.
  9. Li, G., Waltham, M., Unsworth, E., Treston, A., Anderson, N.L., and Weinstein, J.N. Rapid protein identification from two-dimensional polyacrylamide gels by MALDI mass spectrometry. Electrophoresis , in press.

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Last updated: January 25, 1997. John N. Weinstein (weinstein@dtpax2.ncifcrf.gov).