Purpose: After an initial response to androgen ablation, most prostate tumors recur, ultimately progressing to highly aggressive androgen-independent cancer. The molecular mechanisms underlying progression are not well known in part due to the rarity of androgen-independent samples from primary and metastatic sites. Experimental Design: We compared the gene expression profiles of 10 androgen-independent primary prostate tumor biopsies with 10 primary, untreated androgen-dependent tumors. Samples were laser capture microdissected, the RNA was amplified, and gene expression was assessed using Affymetrix Human Genome U133A GeneChip. Differential expression was examined with principal component analysis, hierarchical clustering, and Student's t testing. Analysis of gene ontology was done with Expression Analysis Systematic Explorer and gene expression data were integrated with genomic alterations with Differential Gene Locus Mapping. Results: Unsupervised principal component analysis showed that the androgen-dependent and androgen-independent tumors segregated from one another. After filtering the data, 239 differentially expressed genes were identified. Two main gene ontologies were found discordant between androgen-independent and androgen-dependent tumors: macromolecule biosynthesis was down-regulated and cell adhesion was up-regulated in androgen-independent tumors. Other differentially expressed genes were related to interleukin-6 signaling as well as angiogenesis, cell adhesion, apoptosis, oxidative stress, and hormone response. The Differential Gene Locus Mapping analysis identified nine regions of potential chromosomal deletion in the androgen-independent tumors, including 1p36, 3p21, 6p21, 8p21, 11p15, 11q12, 12q23, 16q12, and 16q21. Conclusions: Taken together, these data identify several unique characteristics of androgen-independent prostate cancer that may hold potential for the development of targeted therapeutic intervention.
Frozen tissue specimens are the gold standard for molecular analysis. However, snap freezing presents several challenges regarding collection and storage of tissue, and preservation of histological detail. We evaluate an alternative preservation method, ethanol fixation followed by paraffin embedding, by analyzing expression profiles of microdissected cells on Affymetrix oligonucleotide arrays of three matched benign prostatic hyperplasia (BPH) and tumor samples processed with each preservation method. Frozen samples generated an average present call of 26% of the probe sets, compared to 4.5% in ethanol-paraffin samples. Eighty-eight percent of the probe sets called present in the ethanol-paraffin samples were also present in the frozen specimens. Comparing ethanolparaffin BPH to tumor, 52 probe sets showed a twofold differential expression or higher in at least two cases, 23 of which were also differentially expressed in at least one frozen case. Despite a significant drop in the number of transcripts detectable, the data suggests that the obtainable information in ethanol-fixed samples may be useful for molecular profiling where frozen tissue is not available. However, ethanol fixation and paraffin embedding of tissue specimens is not optimal for high-throughput mRNA expression analysis. Improved methods for transcript profiling of archival samples, and/or tissue processing are still required. Formalin fixation and paraffin embedding is the standard tissue processing method used in histopathology laboratories. This protocol allows for permanent preservation of the tissues, easy storage, and optimal histological quality. Unfortunately, formalin fixation severely compromises analysis of biomolecules, in particular mRNA and proteins. We have recently demonstrated the utility of an alternative fixation method, 70% ethanol followed by paraffin embedding. 1
Gene expression measurement techniques such as quantitative reverse transcriptase (qRT)-PCR require a normalization strategy to allow meaningful comparisons across biological samples. Typically, this is accomplished through the use of an endogenous housekeeping gene that is presumed to show stable expression levels in the samples under study. There is concern regarding how precisely specific genes can be measured in limited amounts of mRNA such as those from microdissected (MD) tissues. To address this issue, we evaluated three different approaches for qRT-PCR normalization of dissected samples; cell count during microdissection, total RNA measurement, and endogenous control genes. The data indicate that both cell count and total RNA are useful in calibrating input amounts at the outset of a study, but do not provide enough precision to serve as normalization standards. However, endogenous control genes can accurately determine the relative abundance of a target gene relative to the entire cellular transcriptome. Taken together, these results suggest that precise gene expression measurements can be made from MD samples if the appropriate normalization strategy is employed.
Characterization of gene expression profiles in tumor cells and the tumor microenvironment is an important step in understanding neoplastic progression. To date, there are limited data available on expression changes that occur in the tumor-associated stroma as either a cause or consequence of cancer. In the present study, we employed a 54,000 target oligonucleotide microarray to compare expression profiles in the 4 major components of the microenvironment: tumor epithelium, tumor-associated stroma, normal epithelium, and normal stroma. Cells from 5 human, whole-mount prostatectomy specimens were microdissected and the extracted and amplified mRNA was hybridized to an Affymetrix Human Genome U133 Plus 2.0 GeneChip. Using the intersection of 2 analysis methods, we identified sets of differentially expressed genes among the 4 components. Forty-four genes were found to be consistently differentially expressed in the tumor-associated stroma; 35 were found in the tumor epithelium. Interestingly, the tumor-associated stroma showed a predominant up-regulation of transcripts compared with normal stroma, in sharp contrast to the overall down-regulation seen in the tumor epithelium relative to normal epithelium. These data provide insight into the molecular changes occurring in tumor-associated stromal cells and suggest new potential targets for future diagnostic, imaging, or therapeutic intervention.
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