Prostate Proteome Information

Introduction and Discussion.

While transcript profiling offers tremendous opportunities to identify and understand gene expression correlates of biological processes, the approach has limitations. One significant shortcoming is that cellular functions are generally carried out by proteins, not by their precursor DNA and RNA molecules. Transcript abundance levels do not always correlate with protein abundance levels, and one cannot always determine from the genomic sequence if a transcript is destined for translation or, instead, functions as an RNA. The comprehensive study of cellular proteins and protein systems, termed proteomics, offers an approach complementary to gene expression studies at the transcript level. However, proteomics has many unique difficulties that distinguish it from studies of genes and transcripts. The detection of low abundance proteins poses a particular challenge, especially since the dynamic ranges of proteins in biological systems extends from one copy per cell to = 1 million copies per cell-a dynamic range of >106. An amplification system analogous to the polymerase chain reaction has yet to be developed for protein studies. Despite this disadvantage, the field of proteomics has made great strides, brought about primarily by technological advances in mass spectrometry and computational biology. Several approaches have been developed for 'comprehensively' assessing the proteome of cells or tissues. Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE)(31) has been widely used, but suffers from a lack of sensitivity, and is laborious and poorly reproducible(32). Mass Spectrometry (MS) has emerged as the method of choice for characterizing complex protein mixtures, such as those found in tissues or body fluids(33). Surface Enhanced Laser Desorption Ionization (SELDI) MS has been used to analyze serum in order to generate profiles of proteins or protein fragments that associate with disease states such as prostate carcinoma(34, 35). While potentially quite powerful, major drawbacks center on the limited mass range, poor quantitation, and difficulties identifying specific proteins of interest.

A technique has been developed by our collaborator, Dr. Ruedi Aebersold, to quantitate differences in the patterns of protein expression between two cellular states. This technique employs Isotope Coded Affinity Tags (ICAT) that contain three components: a biotin affinity tag, a linker with either eight hydrogen or eight deuterium atoms (generating light and heavy forms of the molecule) and a SH-reactive group capable of covalent linkage to cysteine residues. The proteins of one cell state (e.g. secretory epithelium) are labeled with the light reagent and those of a second cell state (e.g. carcinoma) with the heavy reagent. Equal quantities of labeled cells are mixed, proteolyzed, and passed over an avidin column to isolate cysteine-labeled peptides (about 90% of proteins have cysteine residues), followed by microcapillary liquid chromatography tandem mass spectrometry (µLC-MS/MS). The first MS analysis gives the areas under the curves of the paired isotopic peptides (hence, their relative abundances); the second MS analysis provides the fingerprint of the peptides. Thus, the ICAT method increases throughput by reducing sample redundancy, -only cysteine-containing peptides are assessed---and retains sample complexity while allowing for accurate relative protein quantification.

Note: proteome data in the form of mass spectrometer datasets will be accessible through this site in the future. This section is currently in development.

Reviews and studies published by our group and collaborators that assess alterations in the prostate proteome:

Comprehensive analyses of prostate gene expression: convergence of expressed sequence tag databases, transcript profiling and proteomics.
Nelson PS, Han D, Rochon Y, Corthals GL, Lin B, Monson A, Nguyen V, Franza BR, Plymate SR, Aebersold R, Hood L.
Electrophoresis. 2000 May;21(9):1823-31.
Abstract | PDF
Large-scale proteomics and its future impact on medicine.
Corthals G, and Nelson PS.
Pharmacogenomics J. 2001;1(1):15-9. Review.
Abstract | PDF
From genomics to proteomics: techniques and applications in cancer research.
Martin DB, Nelson PS.
Trends in Cell Biology 2001 Nov; 11(11):S60-5. Review.
Abstract | PDF
Quantitative proteomic analysis of proteins released by neoplastic prostate epithelium.
Martin DB, Gifford DR, Wright ME, Keller A, Yi E, Goodlett DR, Aebersold R, Nelson PS.
Cancer Res. 2004 Jan 1;64(1):347-55.
Abstract | PDF
Identification of androgen-coregulated protein networks from the microsomes of human prostate cancer cells.
Wright ME, Eng J, Sherman J, Hockenbery DM, Nelson PS, Galitski T, Aebersold R.
Genome Biol. 2003;5(1):R4.
Abstract | PDF