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Transgenic expression of activated AKT1 in the murine prostate induces prostatic intraepithelial neoplasia (PIN) that does not progress to invasive prostate cancer (CaP). In luminal epithelial cells of Akt-driven PIN, we show the concomitant induction of p27(Kip1) and senescence. Genetic ablation of p27(Kip1) led to downregulation of senescence markers and progression to cancer. In humans, p27(Kip1) and senescence markers were elevated in PIN not associated with CaP but were decreased or absent, respectively, in cancer-associated PIN and in CaP. Importantly, p27(Kip1) upregulation in mouse and human in situ lesions did not depend upon mTOR or Akt activation but was instead specifically associated with alterations in cell polarity, architecture, and adhesion molecules. These data suggest that a p27(Kip1)-driven checkpoint limits progression of PIN to CaP.

Inherited genetic risk factors play an important role in cancer. However, other than the Mendelian fashion cancer susceptibility genes found in familial cancer syndromes, little is known about risk modifiers that control individual susceptibility. Here we developed a strategy, parental strain expression mapping, that utilizes the homogeneity of inbred mice and genome-wide mRNA expression analyses to directly identify candidate germ-line modifier genes and pathways underlying phenotypic differences among murine strains exposed to transgenic activation of AKT1. We identified multiple candidate modifier pathways and, specifically, the glycolysis pathway as a candidate negative modulator of AKT1-induced proliferation. In keeping with the findings in the murine models, in multiple human prostate expression data set, we found that enrichment of glycolysis pathways in normal tissues was associated with decreased rates of cancer recurrence after prostatectomy. Together, these data suggest that parental strain expression mapping can directly identify germ-line modifier pathways of relevance to human disease.

Prostate cancer is a common and clinically heterogeneous disease with marked variability in progression. The recent identification of gene fusions of the 5'-untranslated region of TMPRSS2 (21q22.3) with the ETS transcription factor family members, either ERG (21q22.2), ETV1 (7p21.2), or ETV4 (17q21), suggests a mechanism for overexpression of the ETS genes in the majority of prostate cancers. In the current study using fluorescence in situ hybridization (FISH), we identified the TMPRSS2:ERG rearrangements in 49.2% of 118 primary prostate cancers and 41.2% of 18 hormone-naive lymph node metastases. The FISH assay detected intronic deletions between ERG and TMPRSS2 resulting in TMPRSS2:ERG fusion in 60.3% (35 of 58) of the primary TMPRSS2:ERG prostate cancers and 42.9% (3 of 7) of the TMPRSS2:ERG hormone-naive lymph node metastases. A significant association was observed between TMPRSS2:ERG rearranged tumors through deletions and higher tumor stage and the presence of metastatic disease involving pelvic lymph nodes. Using 100K oligonucleotide single nucleotide polymorphism arrays, a homogeneous deletion site between ERG and TMPRSS2 on chromosome 21q22.2-3 was identified with two distinct subclasses distinguished by the start point of the deletion at either 38.765 or 38.911 Mb. This study confirms that TMPRSS2:ERG is fused in approximately half of the prostate cancers through deletion of genomic DNA between ERG and TMPRSS2. The deletion as cause of TMPRSS2:ERG fusion is associated with clinical features for prostate cancer progression compared with tumors that lack the TMPRSS2:ERG rearrangement.

Background: In this article, we describe the design and implementation of a comprehensive prostate cancer database developed to collect, store, and access clinical, treatment, and outcomes data for research and clinical care., Patients and Methods: The Prostate Cancer Clinical Research Information System is a relational database. Data are entered from multiple sources, including medical records, institutional laboratory, patient registration, pharmacy systems, and clinician forms. The history, design, and operational characteristics of the database are described. Issues regarding necessary staffing and funding of databases are reviewed., Results: Four thousand two hundred forty-six patients have information in the Prostate Cancer Clinical Research Information System. Mean age of patients is 62 years, and 89% are white. Seventy-one percent of patients presented at diagnosis with T1 or T2 disease, and 78% had biopsy Gleason scores of

Loss of heterozygosity (LOH) of chromosomal regions bearing tumor suppressors is a key event in the evolution of epithelial and mesenchymal tumors. Identification of these regions usually relies on genotyping tumor and counterpart normal DNA and noting regions where heterozygous alleles in the normal DNA become homozygous in the tumor. However, paired normal samples for tumors and cell lines are often not available. With the advent of oligonucleotide arrays that simultaneously assay thousands of single-nucleotide polymorphism (SNP) markers, genotyping can now be done at high enough resolution to allow identification of LOH events by the absence of heterozygous loci, without comparison to normal controls. Here we describe a hidden Markov model-based method to identify LOH from unpaired tumor samples, taking into account SNP intermarker distances, SNP-specific heterozygosity rates, and the haplotype structure of the human genome. When we applied the method to data genotyped on 100 K arrays, we correctly identified 99% of SNP markers as either retention or loss. We also correctly identified 81% of the regions of LOH, including 98% of regions greater than 3 megabases. By integrating copy number analysis into the method, we were able to distinguish LOH from allelic imbalance. Application of this method to data from a set of prostate samples without paired normals identified known regions of prevalent LOH. We have developed a method for analyzing high-density oligonucleotide SNP array data to accurately identify of regions of LOH and retention in tumors without the need for paired normal samples.

We identified prosaposin (PSAP) as a secreted protein expressed in androgen-independent (AI) prostate cancer cells by cloning/sequencing, after probing a PC-3 cDNA library expressed in the lambdaTriplEx phagemid expression vector with a polyclonal rabbit antibody generated against pooled human seminal plasma. PSAP is a neurotrophic molecule; its deficiency or inactivation has proved to be lethal in man and mice, and in mice, it leads to abnormal development and atrophy of the prostate gland, despite normal testosterone levels. We used Southern hybridization, quantitative real-time polymerase chain reaction, and/or single nucleotide polymorphism (SNP) array analysis, and we now report the genomic amplification of PSAP in the metastatic AI prostate cancer cell lines, PC-3, DU-145, MDA-PCa 2b, M-12, and NCI-H660. In addition, by using SNP arrays and a set of 25 punch biopsy samples of human prostate cancer xenografts (LAPC3, LuCaP 23.1, 35, 49, 58, 73, 77, 81, 86.2, 92.1, 93, 96, 105, and 115), lymph nodes, and visceral-organ metastases, we detected amplification of the PSAP locus (10q22.1) in LuCaP 58 and 96 xenografts and two lymph node metastases. In addition, AI metastatic prostate cancer cell lines C4-2B and IA8-ARCaP over-expressed PSAP mRNA without evidence of genomic amplification. Taken together with prior data that demonstrated the growth-, migration-, and invasion-promoting activities, the activation of multiple signal transduction pathways, and the antiapoptotic effect of PSAP (or one of its active domains, saposin C) in prostate cancer cells, our current observation of PSAP amplification or overexpression in prostate cancer suggests, for the first time, a role for this molecule in the process of carcinogenesis or cancer progression in the prostate., ((c) 2005 Wiley-Liss, Inc.)

Prostate cancer remains a major cause of cancer-related mortality. Genetic clues to the molecular pathways driving the most aggressive forms of prostate cancer have been limited. Genetic inactivation of PTEN through either gene deletion or point mutation is reasonably common in metastatic prostate cancer and the resulting activation of phosphoinostide 3-kinase, AKT and mTOR provides a major therapeutic opportunity in this disease as mTOR inhibitors, HSP90 inhibitors and PI3K inhibitors begin to enter clinical development.

Androgen ablation is the primary treatment modality for patients with metastatic prostate cancer; however, the role of androgen receptor signaling in prostate cancer development remains enigmatic. Using a series of genetically defined immortalized and tumorigenic human prostate epithelial cells, we found that introduction of the androgen receptor induced differentiation of transformed prostate epithelial cells to a luminal phenotype reminiscent of organ-confined prostate cancer when placed in the prostate microenvironment. Moreover, androgen receptor expression converted previously androgen-independent, tumorigenic prostate epithelial cells into cells dependent on testosterone for tumor formation. These observations indicate that androgen receptor expression is oncogenic and addictive for the human prostate epithelium.

Purpose: NKX3.1 is an androgen regulated gene that is largely specific to the prostate for expression and it is predicted to encode a homeobox protein. Null alleles of NKX3.1 in mice results in impaired prostate development as well as hyperplasia and dysplasia of the prostate. In addition, the NKX3.1 gene maps to a region of high loss of heterozygosity in prostate cancer in humans, suggesting that NKX3.1 might have a direct role in prostate carcinogenesis, possibly functioning as a tumor suppressor protein. Previous studies of the levels of NKX3.1 mRNA or protein in prostate cancer specimens have resulted in conflicting findings., Materials and Methods: To resolve this issue we assessed NKX3.1 expression by mRNA in situ analysis and immunohistochemistry on the same prostate cancer tissue arrays., Results: Data showed that NKX3.1 mRNA and protein levels in prostate cancer specimens are correlated, suggesting that most regulation is at the transcriptional level. There was no correlation of NKX3.1 expression levels with tumor grade or clinical stage. In general there was a suggestion that worse clinical features at surgery were associated with lower IHC stain scores. In particular, extracapsular extension but not seminal vesicle invasion inversely correlated with NKX3.1 expression., Conclusions: Together these data suggest that NKX3.1 does not function as a typical tumor suppressor protein in prostate cancer but it may still have important regulatory roles during prostate cancer progression.

Loss of PTEN function leads to activation of phosphoinositide 3-kinase (PI3K) signaling and Akt. Clinical trials are now testing whether mammalian target of rapamycin (mTOR) inhibition is useful in treating PTEN-null cancers. Here, we report that mTOR inhibition induced apoptosis of epithelial cells and the complete reversal of a neoplastic phenotype in the prostate of mice expressing human AKT1 in the ventral prostate. Induction of cell death required the mitochondrial pathway, as prostate-specific coexpression of BCL2 blocked apoptosis. Thus, there is an mTOR-dependent survival signal required downstream of Akt. Bcl2 expression, however, only partially restored intraluminal cell growth in the setting of mTOR inhibition. Expression profiling showed that Hif-1 alpha targets, including genes encoding most glycolytic enzymes, constituted the dominant transcriptional response to AKT activation and mTOR inhibition. These data suggest that the expansion of AKT-driven prostate epithelial cells requires mTOR-dependent survival signaling and activation of HIF-1 alpha, and that clinical resistance to mTOR inhibitors may emerge through BCL2 expression and/or upregulation of HIF-1 alpha activity.

Gains in the long arm of chromosome 8 (8q) are believed to be associated with poor outcome and the development of hormone-refractory prostate cancer. Based on a meta-analysis of gene expression microarray data from multiple prostate cancer studies (D. R. Rhodes et al., Cancer Res 2002;62:4427-33), a candidate oncogene, Tumor Protein D52 (TPD52), was identified in the 8q21 amplicon. TPD52 is a coiled-coil motif-bearing protein, potentially involved in vesicle trafficking. Both mRNA and protein levels of TPD52 were highly elevated in prostate cancer tissues. Array comparative genomic hybridization and amplification analysis using single nucleotide polymorphism arrays demonstrated increased DNA copy number in the region encompassing TPD52. Fluorescence in situ hybridization on tissue microarrays confirmed TPD52 amplification in prostate cancer epithelia. Furthermore, our studies suggest that TPD52 protein levels may be regulated by androgens, consistent with the presence of androgen response elements in the upstream promoter of TPD52. In summary, these findings suggest that dysregulation of TPD52 by genomic amplification and androgen induction may play a role in prostate cancer progression.

Purpose: We summarize and discuss our recent work exploring the use of gene expression analysis for the prediction of histopathological features of prostate cancer and patient outcome following radical prostatectomy., Materials and Methods: Using "gene chips" capable of analyzing expression of greater than 10,000 genes simultaneously, expression data were collected from prostate tumors and adjacent normal tissue taken from patients undergoing radical prostatectomy between 1995 and 1997 at our hospital. Differentially expressed genes were analyzed using a signal-to-noise metric and by Pearson correlation, while predictive models were built and tested using nearest-neighbor prediction and leave-one-out cross validation. Patient outcome data were analyzed using Kaplan-Meier plots., Results: Robust expression differences were readily detected between tumor and normal tissue, and computer models were built that could predict the identity of tumor or normal differences with 92% accuracy. We were able to find gene expression correlates of Gleason score and, more importantly, a preliminary 5-gene model was found that could separate cases into recurrent and nonrecurrent groups based on the expression patterns found in the primary tumors., Conclusions: These data suggest that it may be possible to predict prostate tumor behavior based on expression signatures present at the time of surgery. A critical next step will be to try and validate such findings in larger independent datasets.

Oligonucleotide arrays that detect single nucleotide polymorphisms were used to generate genome-wide loss of heterozygosity (LOH) maps from laser capture microdissected paraffin-embedded samples using as little as 5 ng of DNA. The allele detection rate from such samples was comparable with that obtained with standard amounts of DNA prepared from frozen tissues. A novel informatics platform, dChipSNP, was used to automate the definition of statistically valid regions of LOH, assign LOH genotypes to prostate cancer samples, and organize by hierarchical clustering prostate cancers based on the pattern of LOH. This organizational strategy revealed apparently distinct genetic subsets of prostate cancer.

We analyzed a prostate cancer xenograft derived from a locally advanced tumor using combined cytogenetic, array-based comparative genomic hybridization and expression analyses. This analysis revealed that genes in the 20q13 chromosomal region, CSE1L, ZNF217, MYBL2, and STK15, were significantly overexpressed in this tumor. The expression pattern of these genes was then confirmed in two large human prostate cancer microarray databases. Furthermore, the MYBL2 and STK15 have been significantly overexpressed in prostate metastases, allowing a clear distinction between localized tumors and metastases. Our data suggest these genes to be involved in advanced stages of prostate tumorigenesis and as such, they may serve as markers for tumor progression.

The recent finding of overexpression of the polycomb group transcriptional repressor EZH2 in prostate cancer raises the possibility that transcriptional regulation at the chromatin level may play a role in the development of the metastatic phenotype and suggests new avenues of exploration with respect to patient stratification and therapeutics.

Prostate tumors are among the most heterogeneous of cancers, both histologically and clinically. Microarray expression analysis was used to determine whether global biological differences underlie common pathological features of prostate cancer and to identify genes that might anticipate the clinical behavior of this disease. While no expression correlates of age, serum prostate specific antigen (PSA), and measures of local invasion were found, a set of genes was identified that strongly correlated with the state of tumor differentiation as measured by Gleason score. Moreover, a model using gene expression data alone accurately predicted patient outcome following prostatectomy. These results support the notion that the clinical behavior of prostate cancer is linked to underlying gene expression differences that are detectable at the time of diagnosis.