Abstract
Prostate cancer is initially responsive to androgen ablation therapy and progresses to androgen-unresponsive states that are refractory to treatment. The mechanism of this transition is unknown. A systems approach to disease begins with the quantitative delineation of the informational elements (mRNAs and proteins) in various disease states. We employed two recently developed high-throughput technologies, massively parallel signature sequencing (MPSS) and isotope-coded affinity tag, to gain a comprehensive picture of the changes in mRNA levels and more restricted analysis of protein levels, respectively, during the transition from androgen-dependent LNCaP (model for early-stage prostate cancer) to androgen-independent CL1 cells (model for late-stage prostate cancer). We sequenced >5 million MPSS signatures, obtained >142,000 tandem mass spectra, and built comprehensive MPSS and proteomic databases. The integrated mRNA and protein expression data revealed underlying functional differences between androgen-dependent and androgen-independent prostate cancer cells. The high sensitivity of MPSS enabled us to identify virtually all of the expressed transcripts and to quantify the changes in gene expression between these two cell states, including functionally important low-abundance mRNAs, such as those encoding transcription factors and signal transduction molecules. These data enable us to map the differences onto extant physiologic networks, creating perturbation networks that reflect prostate cancer progression. We found 37 BioCarta and 14 Kyoto Encyclopedia of Genes and Genomes pathways that are up-regulated and 23 BioCarta and 22 Kyoto Encyclopedia of Genes and Genomes pathways that are down-regulated in LNCaP cells versus CL1 cells. Our efforts represent a significant step toward a systems approach to understanding prostate cancer progression.
Highlights
Prostate cancer is the most common nondermatologic cancer in the United States [1]
The signatures were classified into three major categories: 1,093 signatures matched repeat sequences, 15,541 signatures matched unique cDNAs or expressed sequence tag (EST), and 2,961 signatures had no matches to any cDNA or EST sequences
The systems approach to disease is predicated on the idea that the disease process is reflected in disease-perturbed protein and gene regulatory networks
Summary
Such therapies produce tumor regression, they eventually fail because most prostate carcinomas become androgen independent [2]. To improve the efficacy of prostate cancer therapy, it is necessary to understand the molecular mechanisms underlying the transition from androgen dependence to androgen independence. The transition from androgen-dependent to androgen-independent status likely results from multiple processes, including activation of oncogenes, inactivation of tumor suppressor genes, and changes in key components of signal transduction pathways and gene regulatory networks. Normal protein and gene regulatory networks may be perturbed by disease, through genetic and/or environmental perturbations, and understanding these differences lies at the heart of systems approaches to disease. Disease-perturbed networks initiate altered responses that bring about pathologic phenotypes, such as the invasiveness of cancer cells
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