Identification of differentially expressed genes in organ-confined prostate cancer by gene expression array

Comprehensive analysis of the glutathione S-transferase Mu (GSTM) gene family in ovarian cancer identifies prognostic and expression significance

Background

Ovarian cancer (OC) is one of the most common types of gynecologic tumor over the world. The Glutathione S-transferase Mu (GSTM) has five members, including GSTM1-5. These GSTMs is involved in cell metabolism and detoxification, but their role in OC remains unknown.

Methods

Data from multiple public databases associated with OC and GSTMs were collected. Expression, prognosis, function enrichment, immune infiltration, stemness index, and drug sensitivity analysis was utilized to identify the roles of GSTMs in OC progression. RT-qPCR analysis confirmed the effect of AICAR, AT-7519, PHA-793887 and PI-103 on the mRNA levels of GSTM3/4.

Results

GSTM1-5 were decreased in OC samples compared to normal ovary samples. GSTM1/5 were positively correlated with OC prognosis, but GSTM3 was negatively correlated with OC prognosis. Function enrichment analysis indicated GSTMs were involved in glutathione metabolism, drug metabolism, and drug resistance. Immune infiltration analysis indicated GSTM2/3/4 promoted immune escape in OC. GSTM5 was significantly correlated with OC stemness index. GSTM3/4 were remarkedly associated with OC chemoresistance, especially in AICAR, AT-7519, PHA-793887 and PI-103.

Conclusion

GSTM3 was negatively correlated with OC prognosis, and associated with OC chemoresistance and immune escape. This gene may serve as potential prognostic biomarkers and therapeutic target for OC patients.

GSTM1 gene expression and copy number variation in prostate cancer patients-Effect of chemical exposures and physical activity

BACKGROUND

Many etiological factors have been related to prostate cancer (CaP) development, progression, and survival, such as age, population origin, geographic area, occupational exposures, and nutrition and lifestyle factors. However, physical activity affords health benefits to cancer patients, including those with CaP. Glutathione S-Transferases enzymes have been linked to CaP because of their role in the detoxification of a wide variety of potential carcinogens, steroid hormones and xenobiotics. Among the different glutathione S-transferases isoforms, null genotype for GSTM1 has been associated with an increased risk of CaP, although data are controversial. As the relationship between copy number variation and gene expression of GSTM1 in CaP remains unexplored, this study analyzed GSTM1 gene expression and/or dosage effect on CaP risk and aggressiveness. The potential protective role of physical activity was also explored.

METHODS

Three hundred and seventeen patients (159 non-CaP and 158 CaP) were recruited from the Service of Urology (Hospital Virgen de las Nieves, Granada, Spain) over the period 2012 to 2014 and were followed-up until January 2018 to ensure a correct classification of control and patients. Individuals were classified in each group based on histological analysis of tissue biopsy, along with data on PSA level, Gleason score and T stage in patients with biopsies positive for CaP. Individuals with a negative biopsy were considered as controls. All controls underwent a systematic 20-core ultrasound guided biopsy in order to limit the false negative rate. Genomic DNA was extracted from peripheral blood to determine the exact copy numbers of GSTM1, and RNA was extracted from prostate tissue samples to determine GSTM1 gene expression. Both analyses were performed using the qPCR method. A questionnaire was administered to all patients to assess environmental exposures, lifestyle, and physical activity. The association of GSTM1 copy number variation and expression with the rest of variables was assessed by chi-square test and the Mann-Whitney test. Multiple logistic regression was used to assess which factors were associated with the risk of CaP.

RESULTS

The presence of 1 or 2 copies of the GSTM1 gene was not less prevalent in CaP compared to non-CaP patients; however, a significant decreased GSTM1 gene expression was observed in CaP tissue relative to non-CaP tissue (P = 0.003). CaP patients with environmental exposure to dust and smoke, and smoking habit had a significantly decreased GSTM1 gene expression (and near-significantly decreased for living in urban areas) as compared to non-CaP patients with the same exposures. In addition, physical activity was significantly associated with a lower risk of CaP (P = 0.006) and with increased GSTM1 gene expression (P = 0.002).

CONCLUSIONS

A reduced GSTM1 gene expression in prostate tissue was observed in CaP patients with some environmental chemical exposures. Intriguingly, physical activity might play a protective role against CaP development, possibly as a result of increasing GSTM1 gene expression in prostate tissue. However, this observation warrants further confirmation.

Differentially Expressed Genes and Signature Pathways of Human Prostate Cancer

Genomic technologies including microarrays and next-generation sequencing have enabled the generation of molecular signatures of prostate cancer. Lists of differentially expressed genes between malignant and non-malignant states are thought to be fertile sources of putative prostate cancer biomarkers. However such lists of differentially expressed genes can be highly variable for multiple reasons. As such, looking at differential expression in the context of gene sets and pathways has been more robust. Using next-generation genome sequencing data from The Cancer Genome Atlas, differential gene expression between age- and stage- matched human prostate tumors and non-malignant samples was assessed and used to craft a pathway signature of prostate cancer. Up- and down-regulated genes were assigned to pathways composed of curated groups of related genes from multiple databases. The significance of these pathways was then evaluated according to the number of differentially expressed genes found in the pathway and their position within the pathway using Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis. The “transforming growth factor-beta signaling” and “Ran regulation of mitotic spindle formation” pathways were strongly associated with prostate cancer. Several other significant pathways confirm reported findings from microarray data that suggest actin cytoskeleton regulation, cell cycle, mitogen-activated protein kinase signaling, and calcium signaling are also altered in prostate cancer. Thus we have demonstrated feasibility of pathway analysis and identified an underexplored area (Ran) for investigation in prostate cancer pathogenesis.

Genetic variants of chemokine CCL2 and chemokine receptor CCR2 genes and risk of prostate cancer

Chemokines and their receptors acts as mediators of migration of immune cells to the site of inflammation and deregulated inflammatory response is associated with increased risk of cancer. We performed a case-control study to analyze the frequencies of CCL2 (I/D, rs3917887), -2518 (A > G, rs1024611), and CCR2 (G > A, rs1799864) polymorphisms for prostate cancer (PCa) risk. In this hospital-based case-control study, histologically confirmed 195 PCa patients and 250 unrelated healthy controls of similar ethnicity were genotyped by PCR-RFLP. The result showed that heterozygous ID (odds ratio (OR) = 1.71; p = 0.010) carrier genotype of CCL2 gene were at increased risk for developing PCa. Variant allele D carriers (ID + DD) demonstrated a 1.67-fold increased risk (OR = 1.67; p = 0.010), suggesting a dominant effect model involved in PCa risk. Similarly, variant allele D of CCL2 gene also had a higher risk (OR = 1.53; p = 0.040) for developing PCa. High risk to PCa was also observed with respect to diplotypes, I-G (OR = 1.83; Bonferroni corrected p value (P c) = 0.004) and D-A (OR = 2.11; P c = 0.004) of CCL2 I/D and -2518 (A > G). In association of genotypes with clinic-pathological grade of tumor, homozygous DD (OR = 7.40; P c = 0.042) and variant allele carrier ID + DD (OR = 2.42; P c = 0.036) genotypes of CCL2 gene conferred risk in high Gleason grade tumor of PCa. We observed a significantly enhanced risk for PCa due to interaction between CCL2 I/D, -2518 (A > G), and CCR2 (G > A) genotypes. However, -2518 (A > G) and CCR2 V64I (G > A) gene polymorphisms were not significantly associated with PCa risk. Our results supported that CCL2 I/D gene variant contribute to the susceptibility and clinic-pathological characteristic of PCa and could be considered as an important risk factor for this malignancy in North Indian men.

Computational identification of surrogate genes for prostate cancer phases using machine learning and molecular network analysis

BACKGROUND

Prostate cancer is one of the most common malignant diseases and is characterized by heterogeneity in the clinical course. To date, there are no efficient morphologic features or genomic biomarkers that can characterize the phenotypes of the cancer, especially with regard to metastasis--the most adverse outcome. Searching for effective surrogate genes out of large quantities of gene expression data is a key to cancer phenotyping and/or understanding molecular mechanisms underlying prostate cancer development.

RESULTS

Using the maximum relevance minimum redundancy (mRMR) method on microarray data from normal tissues, primary tumors and metastatic tumors, we identifed four genes that can optimally classify samples of different prostate cancer phases. Moreover, we constructed a molecular interaction network with existing bioinformatic resources and co-identifed eight genes on the shortest-paths among the mRMR-identified genes, which are potential co-acting factors of prostate cancer. Functional analyses show that molecular functions involved in cell communication, hormone-receptor mediated signaling, and transcription regulation play important roles in the development of prostate cancer.

CONCLUSION

We conclude that the surrogate genes we have selected compose an effective classifier of prostate cancer phases, which corresponds to a minimum characterization of cancer phenotypes on the molecular level. Along with their molecular interaction partners, it is fairly to assume that these genes may have important roles in prostate cancer development; particularly, the un-reported genes may bring new insights for the understanding of the molecular mechanisms. Thus our results may serve as a candidate gene set for further functional studies.

Integrative genomic analysis for the discovery of biomarkers in prostate cancer

Genome-wide association studies (GWAS) have achieved great success in identifying single nucleotide polymorphisms (SNPs, herein called genetic variants) and genes associated with risk of developing prostate cancer. However, GWAS do not typically link the genetic variants to the disease state or inform the broader context in which the genetic variants operate. Here, we present a novel integrative genomics approach that combines GWAS information with gene expression data to infer the causal association between gene expression and the disease and to identify the network states and biological pathways enriched for genetic variants. We identified gene regulatory networks and biological pathways enriched for genetic variants, including the prostate cancer, IGF-1, JAK2, androgen, and prolactin signaling pathways. The integration of GWAS information with gene expression data provides insights about the broader context in which genetic variants associated with an increased risk of developing prostate cancer operate.

A 12-gene expression signature is associated with aggressive histological in prostate cancer: SEC14L1 and TCEB1 genes are potential markers of progression

The main challenge for clinical management of prostate cancer is to distinguish tumors that will progress faster and will show a higher tendency to recur from the more indolent ones. We have compared expression profiles of 18 prostate cancer samples (seven with a Gleason score of 6, eight with a Gleason score of 7, and three with a Gleason score of ≥8) and five nonneoplastic prostate samples, using the Affymetrix Human Array GeneChip Exon 1.0 ST. Microarray analysis revealed 99 genes showing statistically significant differences among tumors with Gleason scores of 6, 7, and ≥8. In addition, mRNA expression of 29 selected genes was analyzed by real-time quantitative RT-PCR with microfluidic cards in an extended series of 30 prostate tumors. Of the 29 genes, 18 (62%) were independently confirmed in the extended series by quantitative RT-PCR: 14 were up-regulated and 4 were down-regulated in tumors with a higher Gleason score. Twelve of these genes were differentially expressed in tumors with a Gleason score of 6 to 7 versus ≥8. Finally, IHC validation of the protein levels of two genes from the 12-gene signature (SEC14L1 and TCEB1) showed strong protein expression levels of both genes, which were statistically associated with a high combined Gleason score, advanced stage, and prostate-specific antigen progression. This set of genes may contribute to a better understanding of the molecular basis of prostate cancer. TCEB1 and SELC14L1 are good candidate markers for predicting prognosis and progression of prostate cancer.

Id1 and Id3 expression is associated with increasing grade of prostate cancer: Id3 preferentially regulates CDKN1B

As transcriptional regulators of basic helix-oop-helix (bHLH) transcription and non-bHLH factors, the inhibitor of differentiation (Id1, Id2, Id3, and Id4) proteins play a critical role in coordinated regulation of cell growth, differentiation, tumorigenesis, and angiogenesis. Id1 regulates prostate cancer (PCa) cell proliferation, apoptosis, and androgen independence, but its clinical significance in PCa remains controversial. Moreover, there is lack of evidence on the expression of Id2 and Id3 in PCa progression. In this study we investigated the expression of Id2 and Id3 and reevaluated the expression of Id1 in PCa. We show that increased Id1 and Id3 protein expression is strongly associated with increasing grade of PCa. At the molecular level, we report that silencing either Id1 or Id3 attenuates cell cycle. Although structurally and mechanistically similar, our results show that both these proteins are noncompensatory at least in PCa progression. Moreover, through gene silencing approaches we show that Id1 and Id3 primarily attenuates CDKN1A (p21) and CDKN1B (p27), respectively. We also demonstrate that silencing Id3 alone significantly attenuates proliferation of PCa cells as compared with Id1. We propose that increased Id1 and Id3 expression attenuates all three cyclin-dependent kinase inhibitors (CDKN2B, -1A, and -1B) resulting in a more aggressive PCa phenotype.

Identification of markers of prostate cancer progression using candidate gene expression

BACKGROUND

Metastatic prostate cancer (PCa) has no curative treatment options. Some forms of PCa are indolent and slow growing, while others metastasise quickly and may prove fatal within a very short time. The basis of this variable prognosis is poorly understood, despite considerable research. The aim of this study was to identify markers associated with the progression of PCa.

METHODS

Artificial neuronal network analysis combined with data from literature and previous work produced a panel of putative PCa progression markers, which were used in a transcriptomic analysis of 29 radical prostatectomy samples and correlated with clinical outcome.

RESULTS

Statistical analysis yielded seven putative markers of PCa progression, ANPEP, ABL1, PSCA, EFNA1, HSPB1, INMT and TRIP13. Two data transformation methods were utilised with only markers that were significant in both selected for further analysis. ANPEP and EFNA1 were significantly correlated with Gleason score. Models of progression co-utilising markers ANPEP and ABL1 or ANPEP and PSCA had the ability to correctly predict indolent or aggressive disease, based on Gleason score, in 89.7% and 86.2% of cases, respectively. Another model of TRIP13 expression in combination with preoperative PSA level and Gleason score was able to correctly predict recurrence in 85.7% of cases.

CONCLUSION

This proof of principle study demonstrates a novel association of carcinogenic and tumourigenic gene expression with PCa stage and prognosis.

LNCaP Atlas: gene expression associated with in vivo progression to castration-recurrent prostate cancer

Background

There is no cure for castration-recurrent prostate cancer (CRPC) and the mechanisms underlying this stage of the disease are unknown.

Methods

We analyzed the transcriptome of human LNCaP prostate cancer cells as they progress to CRPC in vivo using replicate LongSAGE libraries. We refer to these libraries as the LNCaP atlas and compared these gene expression profiles with current suggested models of CRPC.

Results

Three million tags were sequenced using in vivo samples at various stages of hormonal progression to reveal 96 novel genes differentially expressed in CRPC. Thirty-one genes encode proteins that are either secreted or are located at the plasma membrane, 21 genes changed levels of expression in response to androgen, and 8 genes have enriched expression in the prostate. Expression of 26, 6, 12, and 15 genes have previously been linked to prostate cancer, Gleason grade, progression, and metastasis, respectively. Expression profiles of genes in CRPC support a role for the transcriptional activity of the androgen receptor (CCNH, CUEDC2, FLNA, PSMA7), steroid synthesis and metabolism (DHCR24, DHRS7, ELOVL5, HSD17B4, OPRK1), neuroendocrine (ENO2, MAOA, OPRK1, S100A10, TRPM8), and proliferation (GAS5, GNB2L1, MT-ND3, NKX3-1, PCGEM1, PTGFR, STEAP1, TMEM30A), but neither supported nor discounted a role for cell survival genes.

Conclusions

The in vivo gene expression atlas for LNCaP was sequenced and support a role for the androgen receptor in CRPC.

Cancer biomarker discovery: the entropic hallmark

Background

It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods.

Methodology/Principal Findings

Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer.

Conclusions/Significance

We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-througput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases.

The helix-loop-helix Id-1 inhibits PSA expression in prostate cancer cells

The inhibitor of basic helix-loop-helix transcription factors, Id-1, is an important gene whose expression increases during prostate cancer progression and that upregulates proliferation, migration and invasion. We used microarray analysis to identify the downstream genes whose transcriptional expression is modulated by Id-1 protein. We compared gene expression in control LNCaP cells and Id-1-transduced LNCaP cells, which become significantly more aggressive after Id-1 overexpression, thus mimicking the high levels of Id-1 detected in metastatic cell lines. We used the Affy HTA U133A Expression Arrays with 45,000 probe sets representing more than 39,000 transcripts. We found that one of the most significantly downregulated genes on Id-1 expression was kallikrein 3 [also called prostate specific antigen (PSA)], the most commonly used biomarker of prostate cancer. Here, we show that the reduction in PSA mRNA and protein expression associated with high-grade prostate cancers, which generally express high levels of Id-1, could be the consequence of Id-1 overexpression.

Monocyte chemotactic protein-1 (MCP-1/CCL2) is associated with prostatic growth dysregulation and benign prostatic hyperplasia

BACKGROUND

Chronic inflammation is commonly observed in benign prostate hyperplasia (BPH), and prostate tissue often contains increased inflammatory infiltrates, including T cells and macrophages. Cytokines are not only key mediators of inflammation but may also play important roles in the initiation and progression of BPH.

METHODS

In order to determine what cytokines might be involved in prostatic enlargement, expressed prostatic secretions (EPS) from ex vivo prostates were analyzed by human cytokine antibody microarray and ELISA. Prostate epithelial cells (PrEC) and prostate stromal cells (PrSC) were used for ELISA, proliferation, and Western blot assays.

RESULTS

Monocyte chemotactic protein-1 (MCP-1/CCL2) was one of the most elevated proteins in secretions from large prostate glands. PrSC were found to secrete MCP-1; Western blotting showed that both PrSC and PrEC express the MCP-1 receptor CCR2 which by RT-PCR was the CCR2b isoform. Proliferation assays showed that MCP-1 stimulates the proliferation of PrEC, but not PrSC, and that a specific MCP-1 antagonist (RS102895) suppressed this effect. Conditioned medium from PrSC stimulated the proliferation of PrEC as well, an effect completely inhibited by both RS102895 and a neutralizing anti-MCP-1 monoclonal antibody. The inflammatory cytokines interleukin (IL)-1 beta, interferon-gamma, and IL-2 enhanced the secretion of MCP-1 from PrEC and PrSC. In addition, MCP-1 levels in EPS correlated with mRNA levels of the macrophage marker CD68 in the same secretions.

CONCLUSIONS

The cytokine MCP-1, of apparent prostatic stromal cell origin, may play an important role in prostatic enlargement and BPH, and is a candidate biomarker for these pathologic processes.

Targeting chemokine (C-C motif) ligand 2 (CCL2) as an example of translation of cancer molecular biology to the clinic

Chemokines are a family of small and secreted proteins that play pleiotropic roles in inflammation-related pathological diseases, including cancer. Among the identified 50 human chemokines, chemokine (C-C motif) ligand 2 (CCL2) is of particular importance in cancer development since it serves as one of the key mediators of interactions between tumor and host cells. CCL2 is produced by cancer cells and multiple different host cells within the tumor microenvironment. CCL2 mediates tumorigenesis in many different cancer types. For example, CCL2 has been reported to promote prostate cancer cell proliferation, migration, invasion, and survival, via binding to its functional receptor CCR2. Furthermore, CCL2 induces the recruitment of macrophages and induces angiogenesis and matrix remodeling. Targeting CCL2 has been demonstrated as an effective therapeutic approach in preclinical prostate cancer models, and currently, neutralizing monoclonal antibody against CCL2 has entered into clinical trials in prostate cancer. In this chapter, targeting CCL2 in prostate cancer will be used as an example to show translation of laboratory findings from cancer molecular biology to the clinic.

TGF-beta3 and cancer: a review

With the development of growth factors and growth factor modulators as therapeutics for a range of disorders, it is prudent to consider whether modulating the growth factor profile in a tissue can influence tumour initiation or progression. As recombinant human TGF-beta3 (avotermin) is being developed for the improvement of scarring in the skin it is important to understand the role, if any, of this cytokine in tumour progression. Elevated levels of TGF-beta3 expression detected in late-stage tumours have linked this cytokine with tumourigenesis, although functional data to support a causative role are lacking. While it has proved tempting for researchers to interpret a 'correlation' as a 'cause' of disease, what has often been overlooked is the normal biological role of TGF-beta3 in processes that are often subverted in tumourigenesis. Clarifying the role of this cytokine is complicated by inappropriate extrapolation of the data relating to TGF-beta1 in tumourigenesis, despite marked differences in biology between the TGF-beta isoforms. Indeed, published studies have indicated that TGF-beta3 may actually play a protective role against tumourigenesis in a range of tissues including the skin, breast, oral and gastric mucosa. Based on currently available data it is reasonable to hypothesize that administration of acute low doses of exogenous TGF-beta3 is unlikely to influence tumour initiation or progression.

Inhibitor of DNA binding-1 overexpression in prostate cancer: relevance to tumor differentiation

Inhibitor of DNA binding-1 (Id1) is a dominant-negative regulator of basic helix-loop-helix transcription factor, which control malignant cell behaviors in several types of carcinomas. This study aimed to find the relationship between Id1 expression and some clinical parameters. Paraffin-embedded tissue specimens from two normal human prostates, 12 benign prostatic hyperplasia (BPH), 43 prostate cancers(PCa) were detected by immunofluorescence assay. Prostatectomy samples from 11 BPH and 28 PCa were used for real time RT-PCR. The relationship between Id1 staining and several patient's clinical parameters, including Gleason grade, PSA, clinical stage, and size of tumor, was further analyzed. Significant up-regulated Id1 protein was shown in prostate cancer specimens, while only weak expression in some BPH samples (5/12). Analyzed by image software, the mean proportion of Id1 positive staining remarkably increased with the increasing of Gleason grade in prostate cancer specimens (r = 0.9967, P < 0.01). Id1 expression was not significantly associated with PSA, TNM stage or tumor size. Furthermore, the average mRNA of prostate cancer was 3.09 times of BPH. This study confirms that Id1 protein and mRNA are over expressed in prostate cancer tissues. Overexpression of Id1 protein correlates with tumor tissue differentiation. We propose that Id1 over expression can be used in the analysis of the progression of prostate cancer.

Application of transcript profiling in formalin-fixed paraffin-embedded diagnostic prostate cancer needle biopsies

OBJECTIVE

To investigate the feasibility of transcript profiling in diagnostic formalin-fixed and paraffin-embedded (FFPE) biopsies for prostate cancer.

MATERIALS AND METHODS

Laser-capture microdissection (LCM) was used to microdissect glandular epithelium as well as stromal tissue in archival prostate needle biopsies. Optimized RNA extraction, reverse transcription and real-time PCR (QPCR) protocols were used to detect transcript expression. RNA degradation effects were assessed using hydrolysed cell line RNA and matched xenograft FFPE and frozen tumours.

RESULTS

LCM and RNA extraction was achieved in all biopsies from a pilot cohort of five patients. cDNA produced was successfully used to detect expression of glyceraldehyde-3-phosphate dehydrogenase, RPL13, prostate-specific antigen, vimentin, inhibitor of differentiation/DNA binding 1 (Id-1) and polycomb group protein enhancer of zeste homolog 2 (EZH2) transcripts. In the cell line and xenograft models, we investigated the effect of RNA degradation on transcript quantification by QPCR. In both models normalization of transcript quantity with a housekeeping gene resulted in restored expression in all degraded samples to within a 50% difference of control samples. Using an extended cohort of 29 biopsies, we tested application in detecting differences in EZH2 and Id-1 expression between malignant and benign epithelium. The results confirmed that our technique was capable of quantifying significant differences in expression between malignant and benign epithelium consistent with the reported trends.

CONCLUSION

This study reports the use of standard FFPE needle biopsies for transcript profiling and supports the concept of molecular prognostic studies in tissue acquired at diagnosis in prostate cancer.

Associations between smoking, polymorphisms in polycyclic aromatic hydrocarbon (PAH) metabolism and conjugation genes and PAH-DNA adducts in prostate tumors differ by race

Polycyclic aromatic hydrocarbon (PAH)-DNA adducts may induce mutations that contribute to carcinogenesis. We evaluated potential associations between smoking and polymorphisms in PAH metabolism [CYP1A1 Ile 462Val, CYP1B1 Ala 119Ser and Leu 432Val, microsomal epoxide hydrolase (mEH) Tyr 113His and His139Arg, CYP3A4 A(-392)G] and conjugation [glutathione S-transferase (GST) M1 null deletion, GSTP1 Ile 105Val] genes and PAH-DNA adduct levels (measured by immunohistochemistry) in tumor and nontumor prostate cells in 400 prostate cancer cases. Although no statistically significant associations were observed in the total sample, stratification by ethnicity revealed that Caucasian ever smokers compared with nonsmokers had higher adduct levels in tumor cells (mean staining intensity in absorbance units +/- SE, 0.1748 +/- 0.0052 versus 0.1507 +/- 0.0070; P = 0.006), and Caucasians carrying two mEH 139Arg compared with two 139His alleles had lower adducts in tumor (0.1320 +/- 0.0129 versus 0.1714 +/- 0.0059; P = 0.006) and nontumor (0.1856 +/- 0.0184 versus 0.2291 +/- 0.0085; P = 0.03) cells. African Americans with two CYP1B1 432Val compared with two 432Ile alleles had lower adducts in tumor cells (0.1600 +/- 0.0060 versus 0.1970 +/- 0.0153; P = 0.03). After adjusting for smoking status, carrying the putative "high-risk" genotype combination, the faster metabolism of PAH-epoxides to PAH-diol-epoxides (CYP1B1 432Val/Val and mEH 139Arg/Arg) with lower PAH-diol-epoxide conjugation (GSTP1 (105)Ile/Ile), was associated with increased adducts only in Caucasian nontumor cells (0.2363 +/- 0.0132 versus 0.1920 +/- 0.0157; P= 0.05). We present evidence, for the first time in human prostate that the association between smoking and PAH-DNA adducts differs by race and is modified by common genetic variants.

In silico mining identifies IGFBP3 as a novel target of methylation in prostate cancer

Promoter hypermethylation is central in deregulating gene expression in cancer. Identification of novel methylation targets in specific cancers provides a basis for their use as biomarkers of disease occurrence and progression. We developed an in silico strategy to globally identify potential targets of promoter hypermethylation in prostate cancer by screening for 5′ CpG islands in 631 genes that were reported as downregulated in prostate cancer. A virtual archive of 338 potential targets of methylation was produced. One candidate, IGFBP3, was selected for investigation, along with glutathione-S-transferase pi (GSTP1), a well-known methylation target in prostate cancer. Methylation of IGFBP3 was detected by quantitative methylation-specific PCR in 49/79 primary prostate adenocarcinoma and 7/14 adjacent preinvasive high-grade prostatic intraepithelial neoplasia, but in only 5/37 benign prostatic hyperplasia (P<0.0001) and in 0/39 histologically normal adjacent prostate tissue, which implies that methylation of IGFBP3 may be involved in the early stages of prostate cancer development. Hypermethylation of IGFBP3 was only detected in samples that also demonstrated methylation of GSTP1 and was also correlated with Gleason score ⩾7 (P=0.01), indicating that it has potential as a prognostic marker. In addition, pharmacological demethylation induced strong expression of IGFBP3 in LNCaP prostate cancer cells. Our concept of a methylation candidate gene bank was successful in identifying a novel target of frequent hypermethylation in early-stage prostate cancer. Evaluation of further relevant genes could contribute towards a methylation signature of this disease.

Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process

Background

Prostate cancer is characterized by heterogeneity in the clinical course that often does not correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets.

Methods

Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors.

Results

The metastatic samples are highly heterogenous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodelling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1).

Conclusion

We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.

Identification of genes potentially involved in the acquisition of androgen-independent and metastatic tumor growth in an autochthonous genetically engineered mouse prostate cancer model

BACKGROUND

A major focus of prostate cancer research has been to identify genes that are deregulated during tumor progression, potentially providing diagnostic markers and therapeutic targets.

METHODS

We have employed serial analysis of gene expression (SAGE) and microarray hybridization to identify alterations that occur during malignant transformation in the Transgenic Adenocarcinoma of the Mouse Prostate (TRAMP) model. Many of these alterations were validated by real-time PCR (rtPCR).

RESULTS

We identified several hundred mRNAs that were deregulated. Cluster analysis of microarray profiles with samples from various stages of the disease demonstrated that androgen-independent (AI) primary tumors are similar to metastases; 180 transcripts have expression patterns suggesting an involvement in the genesis of late-stage tumors, and our data support a role for phospholipase A2 group IIA in the acquisition of their highly aggressive characteristics.

CONCLUSIONS

Our analyses identified well-characterized genes that were previously known to be involved in prostate cancer, validating our study, and also uncovered transcripts that had not previously been implicated in prostate cancer progression.

Polymorphisms in polycyclic aromatic hydrocarbon metabolism and conjugation genes, interactions with smoking and prostate cancer risk

The relationship between cigarette smoking and prostate cancer remains unclear. Any potential association may depend on the individuals' ability to metabolize and detoxify cigarette carcinogens--such as polycyclic aromatic hydrocarbons. To investigate this, we studied the association between prostate cancer and smoking, as well as the main and modifying effects of functional polymorphisms in genes that metabolize polycyclic aromatic hydrocarbons (CYP1A1 Ile(462)Val, microsomal epoxide hydrolase His(139)Arg) and detoxify reactive derivatives (GSTM1 null deletion, GSTT1 null deletion, GSTP1 Ile(105)Val and Ala(114)Val) using a family-based case-control design (439 prostate cancer cases and 479 brother controls). Within the entire study population, there were no main effects for smoking or any of the polymorphisms. However, the nondeleted GSTM1 allele was inversely associated with prostate cancer [odds ratio (OR), 0.50; 95% confidence interval (95% CI), 0.26-0.94] among men with less aggressive disease (Gleason score < 7 and clinical tumor stage < T2c) and positively associated (OR, 1.68; 95% CI, 1.01-2.79) with prostate cancer in men with more aggressive disease (Gleason score > or = 7 or clinical tumor stage > or = T2c). We also found a statistically significant negative multiplicative interaction between the GSTM1 nondeleted allele and heavy smoking (> 20 pack-years) in the total study population (P = 0.01) and in Caucasians (P = 0.01). Among Caucasians, heavy smoking increased prostate cancer risk nearly 2-fold in those with the GSTM1 null genotype (OR, 1.73; 95% CI, 0.99-3.05) but this increased risk was not observed in heavy smokers who carried the GSTM1 nondeleted allele (OR, 0.95; 95% CI, 0.53-1.71). Our results highlight the importance of considering genetic modifiers of carcinogens when evaluating smoking in prostate cancer.

Monocyte chemotactic protein-1 (MCP-1) acts as a paracrine and autocrine factor for prostate cancer growth and invasion

BACKGROUND

Monocyte chemotactic protein-1 (MCP-1) plays a key role in the recruitment and activation of monocytes during inflammation. Increased MCP-1 serum levels in patients with various cancers were correlated with advanced stage. Here, we evaluated the role of MCP-1 on prostate cancer (CaP) cell proliferation and invasion.

METHODS

Expression of MCP-1 in tissue specimens was analyzed by immunohistochemical staining. MCP-1 production was determined by ELISA in conditioned media collected from primary prostate epithelia (PrEC), LNCaP, C4-2B, PC3 cells, and hFOB. Cell proliferation and invasion were assayed by MTS assay and invasion chambers.

RESULTS

All CaP cells, as well as hFOB, produced high amount of MCP-1 compared to PrEC cells. MCP-1 expression levels were associated with advanced pathologic stage. MCP-1 induced proliferation and invasion of CaP cells and this was abolished partially either by CCR2 antagonist or PI3 Kinase inhibitor.

CONCLUSION

MCP-1 acts as a paracrine and autocrine factor for CaP growth and invasion.

Increasing expression of GST-pi MIF, and ID1 genes in chemoresistant prostate cancer cells

The differential expression of genes and related proteins of multidrug resistance in chemoresistant prostate cancer cell lines were elucidated in this study. RNA extracted from doxorubicin-resistant rat prostate cancer (PCa) cells (AT3/ADR1000) and native PCa cells was hybridized to expression arrays containing cDNAs from 588 known genes. Differential expression of selected genes was confirmed by quantitative reverse-transcription polymerase chain reaction (RT-PCR) analysis. Protein contents were measured by fluorescent flow cytometry and immunoblotting. Localization of selected proteins in cells was observed by immunocytochemical staining. Up-regulation of eleven genes and down-regulation of one single gene were displayed in the chemoresistant prostate cancer cells. Overexpression of mRNAs in macrophage migration inhibitory factor (MIF), DNA binding protein inhibitor 1 (ID1), and glutathione S-transferase-pi (GST-pi) were confirmed by gene-specific RT-PCR. Protein over-expression of GST-pi, MIF, and ID1 in resistant cells were 3.3-, 1.5-, and 1.5-fold to native cells, respectively. Immunocytochemistry revealed that GST-pi, MIF, and ID1 were present primarily in the cytoplasm of tumor cells, but ID1 also could be found in the nucleus. AT3/ADR1000 drug-resistant PCa cells displayed significantly increased expression of GST-pi, MIF, and ID1 proteins when compared with native PCa cells. It indicates these genes may play a role in drug resistance of prostate cancer.

Integration of gene expression profiling and clinical variables to predict prostate carcinoma recurrence after radical prostatectomy

BACKGROUND

Gene expression profiling of prostate carcinoma offers an alternative means to distinguish aggressive tumor biology and may improve the accuracy of outcome prediction for patients with prostate carcinoma treated by radical prostatectomy.

METHODS

Gene expression differences between 37 recurrent and 42 nonrecurrent primary prostate tumor specimens were analyzed by oligonucleotide microarrays. Two logistic regression modeling approaches were used to predict prostate carcinoma recurrence after radical prostatectomy. One approach was based exclusively on gene expression differences between the two classes. The second approach integrated prognostic gene variables with a validated postoperative predictive model based on standard variables (nomogram). The predictive accuracy of these modeling approaches was evaluated by leave-one-out cross-validation (LOOCV) and compared with the nomogram.

RESULTS

The modeling approach using gene variables alone accurately classified 59 (75%) tissue samples in LOOCV, a classification rate substantially higher than expected by chance. However, this predictive accuracy was inferior to the nomogram (concordance index, 0.75 vs. 0.84, P = 0.01). Models combining clinical and gene variables accurately classified 70 (89%) tissue samples and the predictive accuracy using this approach (concordance index, 0.89) was superior to the nomogram (P = 0.009) and models based on gene variables alone (P < 0.001). Importantly, the combined approach provided a marked improvement for patients whose nomogram-predicted likelihood of disease recurrence was in the indeterminate range (7-year disease progression-free probability, 30-70%; concordance index, 0.83 vs. 0.59, P = 0.01).

CONCLUSIONS

Integration of gene expression signatures and clinical variables produced predictive models for prostate carcinoma recurrence that perform significantly better than those based on either clinical variables or gene expression information alone.

Functional epigenomics identifies genes frequently silenced in prostate cancer

In many cases, silencing of gene expression by CpG methylation is causally involved in carcinogenesis. Furthermore, cancer-specific CpG methylation may serve as a tumor marker. In order to identify candidate genes for inactivation by CpG methylation in prostate cancer, the prostate cancer cell lines LNCaP, PC3, and Du-145 were treated with 5-aza-2' deoxycytidine and trichostatin A, which leads to reversion of epigenetic silencing. By microarray analysis of 18,400 individual transcripts, several hundred genes were found to be induced when compared with cells treated with trichostatin A. Fifty re-expressed genes were selected for further analysis based on their known function, which implied a possible involvement in tumor suppression. Twelve of these genes showed a significant degree of CpG methylation in their promoters. Six genes were silenced by CpG methylation in the majority of five analyzed prostate cancer cell lines, although they displayed robust mRNA expression in normal prostate epithelial cells obtained from four different donors. In primary prostate cancer samples derived from 41 patients, the frequencies of CpG methylation detected in the promoter regions of these genes were: GPX3, 93%; SFRP1, 83%; COX2, 78%; DKK3, 68%; GSTM1, 58%; and KIP2/p57, 56%. Ectopic expression of SFRP1 or DKK3 resulted in decreased proliferation. The expression of DKK3 was accompanied by attenuation of the mitogen-activated protein kinase pathway. The high frequency of CpG methylation detected in the promoters of the identified genes suggests a potential causal involvement in prostate cancer and may prove useful for diagnostic purposes.

Differences in gene expression in prostate cancer, normal appearing prostate tissue adjacent to cancer and prostate tissue from cancer free organ donors

Background

Typical high throughput microarrays experiments compare gene expression across two specimen classes – an experimental class and baseline (or comparison) class. The choice of specimen classes is a major factor in the differential gene expression patterns revealed by these experiments. In most studies of prostate cancer, histologically malignant tissue is chosen as the experimental class while normal appearing prostate tissue adjacent to the tumor (adjacent normal) is chosen as the baseline against which comparison is made. However, normal appearing prostate tissue from tumor free organ donors represents an alterative source of baseline tissue for differential expression studies.

Methods

To examine the effect of using donor normal tissue as opposed to adjacent normal tissue as a baseline for prostate cancer expression studies, we compared, using oligonucleotide microarrays, the expression profiles of primary prostate cancer (tumor), adjacent normal tissue and normal tissue from tumor free donors.

Results

Statistical analysis using Significance Analysis of Microarrays (SAM) demonstrates the presence of unique gene expression profiles for each of these specimen classes. The tumor v donor expression profile was more extensive that the tumor v adjacent normal profile. The differentially expressed gene lists from tumor v donor, tumor v adjacent normal and adjacent normal v donor comparisons were examined to identify regulated genes. When donors were used as the baseline, similar genes are highly regulated in both tumor and adjacent normal tissue. Significantly, both tumor and adjacent normal tissue exhibit significant up regulation of proliferation related genes including transcription factors, signal transducers and growth regulators compared to donor tissue. These genes were not picked up in a direct comparison of tumor and adjacent normal tissues.

Conclusions

The up-regulation of these gene types in both tissue types is an unexpected finding and suggests that normal appearing prostate tissue can undergo genetic changes in response to or in expectation of morphologic cancer. A possible field effect surrounding prostate cancers and the implications of these findings for characterizing gene expression changes in prostate tumors are discussed.

Effect of one-step 100% ethanol fixation and modified manual microdissection on high-quality RNA recovery from esophageal carcinoma specimen

This paper attempts to determine an optimal fixation protocol for stabilizing RNA during microdissection so as to obtain high-quality RNA from specific cell populations procured from esophageal carcinoma specimens, and to develop a manual microdissection that can facilitate the procurement. The special features of our protocol include one-step dehydration of tissue sections in 100% ethanol immediately after cryosectioning, a self-made T-shape plate (T plate) and "exclusion microdissection" procedure. The quality of RNA isolated from dissected cells was analyzed by neutral agarose gel electrophoresis and reverse transcription-polymerase chain reaction (RT-PCR) to detect genes of different abundance levels. One-step 100% ethanol fixation of cryosections effectively stabilized RNA integrity for agelong period of time while maintaining histological morphology comparable to that using the conventional procedure, indicating that it is a valid protocol for preservation of RNA in microdissected samples. In conjunction with the application of the T plate and 'exclusion microdissection' procedure, which efficiently simplifies manual microdissection procedure, allowing maximal procurement of target cells from complex primary tissues, full use of every single specimen for maximal procurement of target cells from the sections was allowed. The RNA isolated from 5 different stage-specific cell populations of an esophageal carcinoma specimen was of high quality and sufficient in quantity for various downstream molecular analyses. Our method is suitable for a wide spectrum of expression analysis in diverse clinical settings.

Id-1 and Id-2 proteins as molecular markers for human prostate cancer progression

PURPOSE

Id proteins are dominant-negative regulators of basic helix-loop-helix transcription factors that control malignant cell behavior in many different tissues. This study aimed to identify the potential role of Id-1 and Id-2 proteins as molecular makers for prostate cancer progression.

EXPERIMENTAL DESIGN

Using the technique of immunohistochemistry, we determined Id-1 and Id-2 expression in a panel of 67 human prostate biopsies. We also manipulated Id-1 and Id-2 expression in LNCaP and PC3 prostate cancer cell lines and determined the effects on invasion in vitro, matrix metalloproteinase secretion, and proliferation.

RESULTS

Both Id-1 and Id-2 proteins were up-regulated during human prostate cancer progression in vivo and were overexpressed in highly aggressive prostate cancer cells. In vitro, constitutive expression of Id-1, and to a lesser extent Id-2, converted nonaggressive LNCaP prostate cancer cells into more proliferative and invasive cells and increased their secretion of matrix metalloproteinases. Conversely, the down-regulation of Id-2 expression in highly metastatic PC3 cells reduced their growth potential and invasiveness.

CONCLUSIONS

We propose that both Id-1 and Id-2 proteins control prostate cancer cell phenotypes and could serve as molecular markers of aggressive human prostate cancer.

Predicting prostate cancer behavior using transcript profiles

PURPOSE

Prostate cancer represents a disease with diverse clinical outcomes. Treatment strategies that optimize benefit and minimize morbidities depend on accurate estimates of disease status and likelihood of progression. Emerging technologies capable of qualitatively and quantitatively profiling genes expressed by neoplastic tissues may provide insights into tumor behavior. This review discusses the use of microarray based transcript expression profiling to stratify human cancers into risk categories.

MATERIALS AND METHODS

MEDLINE was used to perform a comprehensive literature review of reports describing the assessment of gene expression profiles in malignant diseases. Particular emphasis was placed on studies developing models using individual genes or gene cohorts as predictors of prostate cancer outcome.

RESULTS

Alterations in the expression of individual genes identified by microarray analyses have been used in studies of outcome in cancers of the prostate and other tissue types. Profiles of expressed genes have been used to develop prediction models that stratify cancers into prognostic categories based on relapse rates or responses to therapy.

CONCLUSIONS

Gene expression profiles offer an opportunity for acquiring molecular determinants correlating with clinical outcome. With rare exceptions these profiles have yet to be validated or used in prospective studies. Future research will benefit from assessments of intratumor heterogeneity and host factors such as the immune response and hormonal milieu. The prospective validation of predictive models will serve to prove usefulness in the clinical arena.

Feature genes of hepatitis B virus-positive hepatocellular carcinoma, established by its molecular discrimination approach using prediction analysis of microarray

Recent introduction of a learning algorithm for cDNA microarray analysis has permitted to select feature set to accurately distinguish human cancers according to their pathological judgments. Here, we demonstrate that hepatitis B virus-positive hepatocellular carcinoma (HCC) could successfully be identified from non-tumor liver tissues by supervised learning analysis of gene expression profiling. Through learning and cross-validating HCC sample set, we could identify an optimized set of 44 genes to discriminate the status of HCC from non-tumor liver tissues. In an analysis of other blind-tested HCC sample sets, this feature set was found to be statistically significant, indicating the reproducibility of our molecular discrimination approach with the defined genes. One prominent finding was an asymmetrical distribution pattern of expression profiling in HCC, in which the number of down-regulated genes was greater than that of up-regulated genes. In conclusion, the present findings indicate that application of learning algorithm to HCC may establish a reliable feature set of genes to be useful for therapeutic target of HCC, and that the asymmetric expression pattern may emphasize the importance of suppressed genes in HCC.

Oncogenic action of secreted phospholipase A2 in prostate cancer

Mortality from prostate cancer is associated with progression of tumors to androgen-independent growth and metastasis. Eicosanoid products of both the cyclooxygenase (COX) and lipoxygenase (LOX) pathways are important mediators of the proliferation of prostate cancer cells in culture and regulate tumor vascularization and metastasis in animal models. Pharmacologic agents that block either COX or LOX products effectively reduce the size of prostate cancer xenografts. Phospholipase A(2) (PLA(2)) enzymes regulate the provision of arachidonic acid to both COX- and LOX-derived eicosanoids, and a secreted form of the enzyme (sPLA(2)-IIA) is elevated in prostate cancer tissues. Here, we show by immunohistochemistry, in patients receiving androgen ablation therapy, that sPLA(2)-IIA remains elevated in remaining cancer cells relative to benign glands after treatment. Furthermore, sPLA(2)-IIA expression seen in benign glands is substantially decreased after androgen depletion, whereas cytosolic PLA(2)-alpha (cPLA(2)-alpha) levels are unchanged. sPLA(2)-IIA mRNA expression is detectable and inducible by androgen (0.01-10 nmol/L) in the androgen-sensitive cell line LNCaP, and exogenous addition of sPLA(2)-IIA (1-100 nmol/L), but not an inactive sPLA(2)-IIA mutant (H(48)Q), results in a dose-dependent increase in cell numbers or the fraction of cells in G(2)-M phase, which is inhibited by sPLA(2)-IIA-selective inhibitors. The effect of exogenous sPLA(2)-IIA can also be blocked by inhibition of cPLA(2)-alpha, suggesting a role for cPLA(2)-alpha in mediating sPLA(2)-IIAlpha action. sPLA(2)-IIA inhibitors suppressed basal proliferation in LNCaP cells and in the androgen-independent, sPLA(2)-positive cell line PC3 but not in the sPLA(2)-IIA-negative androgen-independent cell line DU145. Established PC3 xenograft tumors grew more slowly in mice treated with sPLA(2)-IIA inhibitors than those treated with saline only. The PLA(2) enzymes, and sPLA(2)-IIA in particular, thus represent important targets for the treatment of sPLA(2)-IIA-positive androgen-independent prostate cancer.

Bone morphogenetic protein (BMP)-6 signaling and BMP antagonist noggin in prostate cancer

It has been proposed that the osteoblastic nature of prostate cancer skeletal metastases is due in part to elevated activity of bone morphogenetic proteins (BMPs). BMPs are osteoinductive morphogens, and elevated expression of BMP-6 correlates with skeletal metastases of prostate cancer. In this study, we investigated the expression levels of BMPs and their modulators in prostate, using microarray analysis of cell cultures and gene expression. Addition of exogenous BMP-6 to DU-145 prostate cancer cell cultures inhibited their growth by up-regulation of several cyclin-dependent kinase inhibitors such as p21/CIP, p18, and p19. Expression of noggin, a BMP antagonist, was significantly up-regulated by BMP-6 by microarray analysis and was confirmed by quantitative reverse transcription-polymerase chain reaction and at the protein level. Noggin protein was present in prostate biopsies and localized to the epithelial components of prostate by immunohistochemistry. Recombinant noggin inhibited the function of BMP-6, suggesting a negative feedback regulation of BMP activity and indicating a strategy for the development of a novel therapeutic target in the treatment of painful osteosclerotic bone metastases of prostate cancer.

Gene expression alterations in prostate cancer predicting tumor aggression and preceding development of malignancy

PURPOSE

The incidence of prostate cancer is frequent, occurring in almost one-third of men older than 45 years. Only a fraction of the cases reach the stages displaying clinical significance. Despite the advances in our understanding of prostate carcinogenesis and disease progression, our knowledge of this disease is still fragmented. Identification of the genes and patterns of gene expression will provide a more cohesive picture of prostate cancer biology.

PATIENTS AND METHODS

In this study, we performed a comprehensive gene expression analysis on 152 human samples including prostate cancer tissues, prostate tissues adjacent to tumor, and organ donor prostate tissues, obtained from men of various ages, using the Affymetrix (Santa Clara, CA) U95a, U95b, and U95c chip sets (37,777 genes and expression sequence tags).

RESULTS

Our results confirm an alteration of gene expression in prostate cancer when comparing with nontumor adjacent prostate tissues. However, our study also indicates that the gene expression pattern in tissues adjacent to cancer is so substantially altered that it resembles a cancer field effect.

CONCLUSION

We also found that gene expression patterns can be used to predict the aggressiveness of prostate cancer using a novel model.

Mechanisms regulating the recruitment of macrophages into hypoxic areas of tumors and other ischemic tissues

The mechanisms responsible for recruiting monocytes from the bloodstream into solid tumors are now well characterized. However, recent evidence has shown that these cells then differentiate into macrophages and accumulate in large numbers in avascular and necrotic areas where they are exposed to hypoxia. This parallels their tendency to congregate in ischemic areas of other diseased tissues such as atherosclerotic plaques and arthritic joints. In tumors, macrophages appear to undergo marked phenotypic changes when exposed to hypoxia and to switch on their expression of a number of mitogenic and proangiogenic cytokines and enzymes. This then promotes tumor growth, angiogenesis, and metastasis. Here, we compare the various mechanisms responsible for monocyte recruitment into tumors with those regulating the accumulation of macrophages in hypoxic/necrotic areas. Because the latter are best characterized in human tumors, we focus mainly on these but also discuss their relevance to macrophage migration in ischemic areas of other diseased tissues. Finally, we discuss the relevance of these mechanisms to the development of novel cancer therapies, both in providing targets to reduce the proangiogenic contribution made by hypoxic macrophages in tumors and in developing the use of macrophages to deliver therapeutic gene constructs to hypoxic areas of diseased tissues.

Human prostate cancer risk factors

Prostate cancer has the highest prevalence of any nonskin cancer in the human body, with similar likelihood of neoplastic foci found within the prostates of men around the world regardless of diet, occupation, lifestyle, or other factors. Essentially all men with circulating androgens will develop microscopic prostate cancer if they live long enough. This review is a contemporary and comprehensive, literature-based analysis of the putative risk factors for human prostate cancer, and the results were presented at a multidisciplinary consensus conference held in Crystal City, Virginia, in the fall of 2002. The objectives were to evaluate known environmental factors and mechanisms of prostatic carcinogenesis and to identify existing data gaps and future research needs. The review is divided into four sections, including 1) epidemiology (endogenous factors [family history, hormones, race, aging and oxidative stress] and exogenous factors [diet, environmental agents, occupation and other factors, including lifestyle factors]); 2) animal and cell culture models for prediction of human risk (rodent models, transgenic models, mouse reconstitution models, severe combined immunodeficiency syndrome mouse models, canine models, xenograft models, and cell culture models); 3) biomarkers in prostate cancer, most of which have been tested only as predictive factors for patient outcome after treatment rather than as risk factors; and 4) genotoxic and nongenotoxic mechanisms of carcinogenesis. The authors conclude that most of the data regarding risk relies, of necessity, on epidemiologic studies, but animal and cell culture models offer promise in confirming some important findings. The current understanding of biomarkers of disease and risk factors is limited. An understanding of the risk factors for prostate cancer has practical importance for public health research and policy, genetic and nutritional education and chemoprevention, and prevention strategies.

Molecular profiling of prostate cancer

The ability to distinguish between aggressive and nonaggressive tumors has not changed despite vast improvements in the detection of prostate cancer (PCA). To improve predictive accuracy, additional PCA-specific biomarkers must be identified and it is the emerging microarray technology and gene expression profiling that appear to be capable of achieving this goal. Through comparisons of a number of published microarray studies of PCA, several potential biomarkers appear on the horizon, including the serine protease Hepsin, a-methylacyl CoA racemase, and the human homologue of the Drosophila protein Enhancer of Zeste. Although these markers will move toward validation by eventual protein expression studies, another aspect of microarray expression, global signature expression patterns through multidimensional scaling, appears to be promising in distinguishing between aggressive and nonaggressive forms of PCA or in distinguishing PCA from benign prostatic hyperplasia or normal prostate tissue.

Transcriptional profiling of medulloblastoma in children

OBJECT

Although medulloblastoma is the most common malignant brain tumor found in children, little is known about its molecular pathogenesis. The authors have attempted to compare patterns of gene expression in medulloblastoma samples with those in the healthy cerebellum.

METHODS

The authors used complementary (c)DNA microarray analysis to compare the expression of genes in samples of medulloblastoma and normal cerebellum. The expression levels of a subset of genes were then verified by immunohistochemical analysis. Six genes were identified that were expressed at a much higher level in at least five of six medulloblastomas: ezrin, cyclin D2, high mobility group protein 2, MAPRE1, histone deacetylase 2, and ornithine decarboxylase 1. A number of potentially important genes whose expression was much lower in medulloblastomas than in control cerebellum were also identified: tenascin R, TRK-B, FGF receptor, and death receptor 3. The expression levels of a subset of the identified genes were confirmed by immunohistochemical analysis, which was performed on fetal cerebellum and medulloblastoma samples.

CONCLUSIONS

The authors demonstrate that cDNA microarray analysis is an effective method of increasing understanding of the molecular biology of medulloblastomas found in children. A comparison between gene expression patterns in medulloblastoma and those observed in healthy cerebellum may provide clues as to the origin of these tumors and may lead to the identification of new genes or pathways to be targeted for future therapies.

Id proteins in epithelial cells

Id helix-loop-helix (Id HLH) proteins are negative regulators of basic HLH transcription factors. They are expressed during embryonic development and are important for the regulation of cell phenotypes in adults. They participate in the molecular networks controlling cell growth, differentiation, and carcinogenesis, through specific basic HLH and non-basic HLH protein interactions. Recent in vitro and in vivo data implicate Id HLH as important orchestrating proteins of homeostasis in glandular and protective epithelia. In particular, Id proteins have been reported to be involved in cell behavior in epidermis, respiratory system, digestive tract, pancreas, liver, thyroid, urinary system, prostate, testis, endometrium, cervix, ovary, and mammary gland. The purpose of this review is to summarize the evidence implicating Id proteins in the regulation of mammalian epithelial cell phenotypes.

PTOV-1, a novel protein overexpressed in prostate cancer, shuttles between the cytoplasm and the nucleus and promotes entry into the S phase of the cell division cycle

PTOV1 was recently identified as a novel gene and protein during a differential display screening for genes overexpressed in prostate cancer. The PTOV1 protein consists of two novel protein domains arranged in tandem, without significant similarities to known protein motifs. By immunohistochemical analysis, we have found that PTOV1 is overexpressed in 71% of 38 prostate carcinomas and in 80% of samples with prostate intraepithelial neoplasia. High levels of PTOV1 in tumors correlated significantly with proliferative index, as assessed by Ki67 immunoreactivity, and associated with a nuclear localization of the protein, suggesting a functional relationship between PTOV1 overexpression, proliferative status, and nuclear localization. In quiescent cultured prostate tumor cells, PTOV1 localized to the cytoplasm, being excluded from nuclei. After serum stimulation, PTOV1 partially translocated to the nucleus at the beginning of the S phase. At the end of mitosis, PTOV1 exited the nucleus. Transient transfection of chimeric green fluorescent protein-PTOV1 forced the entry of cells into the S phase of the cell cycle, as shown by double fluorescent imaging for green fluorescent protein and for Ki67, and also by flow cytometry. This was accompanied by greatly increased levels of cyclin D1 protein in the transfected cells. These observations suggest that overexpression of PTOV1 can contribute to the proliferative status of prostate tumor cells and thus to their biological behavior.

Selective reduction of AKR1C2 in prostate cancer and its role in DHT metabolism

BACKGROUND

As androgens play an essential role in prostate cancer, we sought to develop a real-time PCR to characterize mRNA expression profiles of human members of the Aldo-Keto Reductase (AKR) 1C gene family, as well as of 5 alpha-steroid reductase Type II (SRD5A2) in prostate cancer samples. Functional activity and regulation of AKR1C2, a 3 alpha-hydroxysteroid dehydrogenase (HSD) type III, was also assessed in prostate cancer cell lines.

METHODS

Gene specific PCR primers were established and relative gene expression of human AKR1C family members was determined in paired samples of cancerous and surrounding unaffected prostate tissue.

RESULTS

AKR1C2 preferentially reduces DHT to the weak metabolite 5 alpha-androstane-3 alpha,17 beta-diol (3 alpha-diol) without conversion of 3 alpha-diol to DHT in the PC-3 cell line, and its expression was increased by DHT treatment in LNCaP cells. Selectively reduced expression of AKR1C2 mRNA, but not AKR1C1 (97% sequence identity), was found in approximately half of the pairs whereas AKR1C3 relative expression was not significantly altered. No aberrant expression of AKR1C4 expression or significant differences in SRD5A2 gene expression were found.

CONCLUSIONS

AKR1C2 functions as a DHT reductase in prostate-derived cells lines and is regulated by DHT. Additional studies are needed to further define the significance of reduced AKR1C2 expression in prostate cancer and its potential role in modulating local availability of DHT.

Current status of the molecular genetics of human prostatic adenocarcinomas

Molecular genetic mechanisms involved in the progression of prostate cancer are not well understood due to extensive tumor heterogeneity and lack of suitable models. New methods such as fluorescence in-situ hybridization (FISH), comparative genomic hybridization (CGH) and microsatellite analysis have documented losses or gains on various chromosomes. Altered chromosomal regions have been associated with the activation of oncogenes and the inactivation of tumor suppressor genes or defects in mismatch repair (MMR) genes. It is suggested that increased genomic instability is associated with decreased androgen-responsive and progressive behavior of human prostate tumors, but it remains unclear whether this genomic instability is causing the progression of cancer or is the consequence of cancer. Extended studies on hereditary prostate cancer have identified 7 prostate cancer susceptibility loci on several chromosomes, but no specific gene has been confined for a large proportion of susceptibility. In this review we summarize the ongoing molecular genetic events associated with the sporadic and hereditary prostate cancer development and progression.

Microarray analysis in prostate cancer research

PURPOSE OF REVIEW

Microarray technologies are now being used to analyse prostate tumors and to gain insights into prostate cancer biology. This review provides a background on microarray technology, reviews recent applications of these techniques in prostate cancer research, and discusses the potential application of this technology to patient care.

RECENT FINDINGS

An analysis of genome-wide changes in expression has identified several hundred genes differentially expressed by normal and malignant prostate tissues. Some, such as hepsin, not only show increased expression in cancer, but can also provide prognostic information on prostate tumors based on their level of expression. Microarrays have also been used to characterize gene expression changes associated with androgen stimulation, the activation of EGR1 pathways, and prostate epithelial cellular senescence.

SUMMARY

Microarray analysis of gene expression in prostate cancer is in its infancy. Future work will probably yield new diagnostic and prognostic markers, provide insight into prostate cancer biology, and aid in identifying new therapeutic strategies.

Potential role for Id myogenic repressors in apoptosis and attenuation of hypertrophy in muscles of aged rats

Aging attenuates the overload-induced increase in myogenic regulatory transcription factor (MRF) expression and the extent of muscle enlargement. To identify whether mRNA levels of repressors of the MRFs are greater in overloaded muscles from aged animals, overload was achieved in plantaris muscle of aged (33 mo; n = 14) and adult (9 mo; n = 17) rats. After 14 days, plantaris muscles in the overloaded limb were ~25% and 6% larger in adult and aged rats, respectively, compared with the contralateral limb. Hypertrophied muscles of adult rats had significantly greater levels of mRNA and protein levels for myogenin and MyoD compared with control muscles, but neither MRF increased with overload in muscles of aged rats. Muscles of aged rats had greater Id mRNA (150-700%) and protein repressor (200-6,000%) levels compared with adult rats. BAX and caspase 9 protein levels were 9,500% and 300% greater, respectively, in both control and hypertrophied muscles of aged rats compared with young adult rats. These data are consistent with the hypothesis that aging increases Id transcripts that activate apoptotic pathways involving BAX. This may contribute to sarcopenia by attenuating MRF protein levels in muscles of old animals.

Expression profile of differentially-regulated genes during progression of androgen-independent growth in human prostate cancer cells

Because of the heterogeneous nature of prostate cancer, identifying the molecular mechanisms involved during the transition from an androgen-sensitive to an androgen-independent phenotype is very complex. An LNCaP cell model that recapitulates prostate cancer progression, comprising early passage androgen-sensitive (LNCaP-C33) and late passage androgen-independent (LNCaP-C81) phenotypes, would help to provide a better understanding of such molecular events. In this study, we examined the genes expressed by LNCaP-C33 and LNCaP-C81 cells using cDNA microarrays containing 1176 known genes. This analysis demonstrated that 34 genes are up-regulated and eight genes are down-regulated in androgen-independent cells. Northern blot analysis confirmed the differences identified by microarrays on several candidate genes, including c-MYC, c-MYC purine-binding transcription factor (PuF), macrophage migration inhibitory factor (MIF), macrophage inhibitory cytokine-1 (MIC-1), lactate dehydrogenase-A (LDH-A), guanine nucleotide-binding protein Gi, alpha-1 subunit (NBP), cyclin dependent kinase-2 (CDK-2), prostate-specific membrane antigen (PSM), cyclin H (CCNH), 60S ribosomal protein L10 (RPL10), 60S ribosomal protein L32 (RPL32), and 40S ribosomal protein S16 (RPS16). These differentially-regulated genes are correlated with progression of human prostate cancer and may be of therapeutic relevance as well as an aid in understanding the molecular genetic events involved in the development of this disease's hormone-refractory behavior.

Osteoblasts produce soluble factors that induce a gene expression pattern in non-metastatic prostate cancer cells, similar to that found in bone metastatic prostate cancer cells

BACKGROUND

Progressive prostate cancer typically metastasizes to bone where prostate cancer cells gain an osteoblast-like phenotype and induce osteoblastic metastases through unknown mechanisms. To investigate the biology of prostate cancer skeletal metastases, we compared gene expression between the non-metastatic LNCaP cell line and its derivative cell line C4-2B that metastasizes to bone.

METHODS

Total RNA from LNCaP and C4-2B cell lines was isolated and used to probe membrane-based gene arrays (Comparison 1). Additionally, LNCaP cells were incubated in the absence or presence of conditioned media (CM) from a human osteoblast-like cell line (HOBIT) and total RNA from these cells was used to probe gene arrays (Comparison 2). Differential expression of genes was confirmed by RT-PCR.

RESULTS

Of the 1,176 genes screened, 35 were differentially expressed between LNCaP and C4-2B cells (Comparison 1). HOBIT-CM induced differential expression of 30 genes in LNCaP cells (Comparison 2). Interestingly, 19 genes that were differentially expressed in C4-2B vs. LNCaP also displayed a similar expression pattern in LNCaPs grown in HOBIT-CM. These genes are primarily involved in motility, metabolism, signal transduction, tumorigenesis, and apoptosis.

CONCLUSIONS

These results suggest that osteoblasts produce soluble factors that contribute to the progression of prostate cancer skeletal metastases, including their transition to an osteoblast-like phenotype. Additionally, these data provide targets to explore for further investigations towards defining the biology of skeletal metastases.

Gene expression correlates of clinical prostate cancer behavior

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.