Abberant methylation of p16, HIC1, N33 and GSTP1 genes in tumor epitelium and tumor-associated stromal cells of prostate cancer

The methylation status of four genes significant in prostate carcinogenesis p16, HIC1, N33 and GSTP1, were evaluated using quantitative methylationsensitive polymerase chain reaction. Tumor epithelia, tumor-associated stroma, normal epithelia, foci of PIN and benign prostate hyperplasia, and stroma adjacent to tumor tissues were isolated from whole-mount prostatectomy specimens of patients with localized prostate cancer by using laser capture microdissection. We found high levels of gene methylation in the tumor epithelium and tumor-associated stromal cells and some methylation in both hyperplastic epithelium and stromal cells in normal-appearing tissues located adjacent to tumors. Promoter methylation in the non-neoplastic cells of the prostate tumor microenvironment may play an important role in cancer development and progression. We examined the promoter methylation status of pl6, HIC1, N33 and GSTP1 in prostate biopsy fragments and prostate tissues after radical prostatectomy from patients with adenocarcinoma without laser capture microdissection. Methylation frequencies of all genes in tumor samples were considerably lower than frequencies in microdissected tumour samples (HIC1, 71 versus 89%; p16, 22 versus 78%; GSTP1, 32 versus 100%; N33, 20 versus 33%). The laser capture microdissection is required procedure in methylation studies taking into account multifocality and heterogenity of prostate cancer tissue.     

Expression signatures that correlated with Gleason score and relapse in prostate cancer

Predicting prognosis in prostate carcinoma remains a challenge when using clinical and pathologic criteria only. We used an array-based DASL assay to identify molecular signatures for predicting prostate cancer relapse in formalin-fixed, paraffin-embedded (FFPE) prostate cancers, through gene expression profiling of 512 prioritized genes. Of the 71 patients that we analyzed, all but 3 had no evidence of residual tumor (defined as negative surgical margins) following radical prostatectomy and no patient received adjuvant therapy following surgery. All of the 71 patients had an undetectable serum PSA following radical prostatectomy. Follow-up period was 44+/-15 months. Highly reproducible gene expression patterns were obtained with these samples (average R(2)=0.99). We identified a panel of 11 genes that correlated positively and 5 genes that correlated negatively with Gleason grade. A gene expression score (GEX) was derived from the expression levels of the 16 genes. We assessed the prognostic value of these genes and found the GEX significantly correlated with disease relapse (p=0.007). These results suggest that the approach we used is effective for expression profiling in heterogeneous FFPE tissues for cancer diagnosis/prognosis biomarker discovery and validation.     

Discovery and Validation of a Prostate Cancer Genomic Classifier that Predicts Early Metastasis Following Radical Prostatectomy

Purpose

Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis.

Methods

A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry who underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 who experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set.

Results

Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67–0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression.

Conclusion

A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.     

An Accurate Prostate Cancer Prognosticator Using a Seven-Gene Signature Plus Gleason Score and Taking Cell Type Heterogeneity into Account

One of the major challenges in the development of prostate cancer prognostic biomarkers is the cellular heterogeneity in tissue samples. We developed an objective Cluster-Correlation (CC) analysis to identify gene expression changes in various cell types that are associated with progression. In the Cluster step, samples were clustered (unsupervised) based on the expression values of each gene through a mixture model combined with a multiple linear regression model in which cell-type percent data were used for decomposition. In the Correlation step, a Chi-square test was used to select potential prognostic genes. With CC analysis, we identified 324 significantly expressed genes (68 tumor and 256 stroma cell expressed genes) which were strongly associated with the observed biochemical relapse status. Significance Analysis of Microarray (SAM) was then utilized to develop a seven-gene classifier. The Classifier has been validated using two independent Data Sets. The overall prediction accuracy and sensitivity is 71% and 76%, respectively. The inclusion of the Gleason sum to the seven-gene classifier raised the prediction accuracy and sensitivity to 83% and 76% respectively based on independent testing. These results indicated that our prognostic model that includes cell type adjustments and using Gleason score and the seven-gene signature has some utility for predicting outcomes for prostate cancer for individual patients at the time of prognosis. The strategy could have applications for improving marker performance in other cancers and other diseases.     

Differential vitamin D 24-hydroxylase/CYP24A1 gene promoter methylation in endothelium from benign and malignant human prostate

Epigenetic alterations occur in tumor-associated vessels in the tumor microenvironment. Methylation of the CYP24A1 gene promoter differs in endothelial cells isolated from tumors and non-tumor microenvironments in mice. The epigenetic makeup of endothelial cells of human tumor-associated vasculature is unknown due to difficulty of isolating endothelial cells populations from a heterogeneous tissue microenvironment. To ascertain CYP24A1 promoter methylation in tumor-associated endothelium, we utilized laser microdissection guided by CD31 immunohistochemistry to procure endothelial cells from human prostate tumor specimens. Prostate tissues were obtained following robotic radical prostatectomy from men with clinically localized prostate cancer. Adjacent histologically benign prostate tissues were used to compare endothelium from benign versus tumor microenvironments. Sodium bisulfite sequencing of CYP24A1 promoter region showed that the average CYP24A1 promoter methylation in the endothelium was 20% from the tumor microenvironment compared with 8.2% in the benign microenvironment (p < 0.05). A 2-fold to 17-fold increase in CYP24A1 promoter methylation was observed in the prostate tumor endothelium compared with the matched benign prostate endothelium in four patient samples, while CYP24A1 promoter methylation remained unchanged in two patient samples. In addition, there is no correlation of the level of CYP24A1 promoter methylation in prostate tumor-associated endothelium with that of epithelium/stroma. This study demonstrates that the CYP24A1 promoter is methylated in tumor-associated endothelium, indicating that epigenetic alterations in CYP24A1 may play a role in determining the phenotype of tumor-associated vasculature in the prostate tumor microenvironment.Key words: CYP24A1, DNA methylation, human prostate cancer, tumor endothelium, laser microdissection     

Differential vitamin D 24-hydroxylase/CYP24A1 gene promoter methylation in endothelium from benign and malignant human prostate

Epigenetic alterations occur in tumor-associated vessels in the tumor microenvironment. Methylation of the CYP24A1 gene promoter differs in endothelial cells isolated from tumors and non-tumor microenvironments in mice. The epigenetic makeup of endothelial cells of human tumor-associated vasculature is unknown due to difficulty of isolating endothelial cells populations from a heterogeneous tissue microenvironment. To ascertain CYP24A1 promoter methylation in tumor-associated endothelium, we utilized laser microdissection guided by CD31 immunohistochemistry to procure endothelial cells from human prostate tumor specimens. Prostate tissues were obtained following robotic radical prostatectomy from men with clinically localized prostate cancer. Adjacent histologically benign prostate tissues were used to compare endothelium from benign versus tumor microenvironments. Sodium bisulfite sequencing of CYP24A1 promoter region showed that the average CYP24A1 promoter methylation in the endothelium was 20% from the tumor microenvironment compared with 8.2% in the benign microenvironment (p&lt;0.05). A 2-fold to 17-fold increase in CYP24A1 promoter methylation was observed in the prostate tumor endothelium compared with the matched benign prostate endothelium in four patient samples, while CYP24A1 remained unchanged in two patient sample. In addition, there is no correlation of the level of CYP24A1 promoter methylation in prostate tumor-associated endothelium with that of epithelium/stroma. This study demonstrates that the CYP24A1 promoter is methylated in tumor-associated endothelium, indicating that epigenetic alterations in CYP24A1 may play a role in determining the phenotype of tumor-associated vasculature in the prostate tumor microenvironment.     

Gene Expression in Uninvolved Oral Mucosa of OSCC Patients Facilitates Identification of Markers Predictive of OSCC Outcomes

Oral and oropharyngeal squamous cell carcinomas (OSCC) are among the most common cancers worldwide, with approximately 60% 5-yr survival rate. To identify potential markers for disease progression, we used Affymetrix U133 plus 2.0 arrays to examine the gene expression profiles of 167 primary tumor samples from OSCC patients, 58 uninvolved oral mucosae from OSCC patients and 45 normal oral mucosae from patients without oral cancer, all enrolled at one of the three University of Washington-affiliated medical centers between 2003 to 2008. We found 2,596 probe sets differentially expressed between 167 tumor samples and 45 normal samples. Among 2,596 probe sets, 71 were significantly and consistently up- or down-regulated in the comparison between normal samples and uninvolved oral samples and between uninvolved oral samples and tumor samples. Cox regression analyses showed that 20 of the 71 probe sets were significantly associated with progression-free survival. The risk score for each patient was calculated from coefficients of a Cox model incorporating these 20 probe sets. The hazard ratio (HR) associated with each unit change in the risk score adjusting for age, gender, tumor stage, and high-risk HPV status was 2.7 (95% CI: 2.0–3.8, p = 8.8E-10). The risk scores in an independent dataset of 74 OSCC patients from the MD Anderson Cancer Center was also significantly associated with progression-free survival independent of age, gender, and tumor stage (HR 1.6, 95% CI: 1.1–2.2, p = 0.008). Gene Set Enrichment Analysis showed that the most prominent biological pathway represented by the 71 probe sets was the Integrin cell surface interactions pathway. In conclusion, we identified 71 probe sets in which dysregulation occurred in both uninvolved oral mucosal and cancer samples. Dysregulation of 20 of the 71 probe sets was associated with progression-free survival and was validated in an independent dataset.     

High Lysyl Oxidase (LOX) in the Non-Malignant Prostate Epithelium Predicts a Poor Outcome in Prostate Cancer Patient Managed by Watchful Waiting

Lysyl oxidase (LOX) has been shown to both promote and suppress tumor progression, but its role in prostate cancer is largely unknown. LOX immunoreactivity was scored in prostate tumor epithelium, tumor stroma and in the tumor-adjacent non-malignant prostate epithelium and stroma. LOX scores in tumor and non-malignant prostate tissues were then examined for possible associations with clinical characteristics and survival in a historical cohort of men that were diagnosed with prostate cancer at transurethral resection and followed by watchful waiting. Men with a low LOX score in the non-malignant prostate epithelium had significantly longer cancer specific survival than men with a high score. Furthermore, LOX score in non-malignant prostate epithelium remained prognostic in a multivariable analysis including Gleason score. LOX score in prostate tumor epithelium positively correlated to Gleason score and metastases but was not associated with cancer survival. LOX score in tumor and non-malignant prostate stroma appeared unrelated to these tumor characteristics. In radical prostatectomy specimens, LOX immune-staining corresponded to LOX in-situ hybridization and LOX mRNA levels were found to be similar between tumor and adjacent non-malignant areas, but significantly increased in bone metastases samples. LOX levels both in tumors and in the surrounding tumor-bearing organ are apparently related to prostate cancer aggressiveness.     

Prostate cancer progression and surrounding microenvironment

Bidirectional cellular interactions between prostate cancer and prostate or bone stroma are needed for local tumor growth and distant metastasis. The genetics of cancer cells is affected by the host microenvironment and, reciprocally, permanent gene expression changes occur in the stroma surrounding epithelial cancer cells. The immune-mediated micromilieu also affects the progression of prostate cancer; the role of the immune system in controlling the growth of prostate cancer cells is complex, with immune escape mechanisms prevailing over effective antitumor response. Moreover, tumor stem cell models to explain the origin and progression of prostate cancer require appropriate environmental conditions. On the basis of a review of the literature, this article aims to outline the recent advances in the elucidation of the molecular mechanisms underlying the interactions between prostate cancer and its microenvironment.     

Integration of Molecular Profiling and Chemical Imaging to Elucidate Fibroblast-Microenvironment Impact on Cancer Cell Phenotype and Endocrine Resistance in Breast Cancer

The tumor microenvironment is known to play a key role in altering the properties and behavior of nearby cancer cells. Its influence on resistance to endocrine therapy and cancer relapse, however, is poorly understood. Here we investigate the interaction of mammary fibroblasts and estrogen receptor-positive breast cancer cells in three-dimensional culture models in order to characterize gene expression, cellular changes, and the secreted protein factors involved in the cellular cross-talk. We show that fibroblasts, which are the predominant cell type found in the stroma adjacent to the cancer cells in a tumor, induce an epithelial-to-mesenchymal transition in the cancer cells, leading to hormone-independent growth, a more invasive phenotype, and resistance to endocrine therapy. Here, we applied a label-free chemical imaging modality, Fourier transform infrared (FT-IR) spectroscopic imaging, to identify cells that had transitioned to hormone-independent growth. Both the molecular and chemical profiles identified here were translated from cell culture to patient samples: a secreted protein signature was used to stratify patient populations based on gene expression and FT-IR was used to characterize breast tumor patient biopsies. Our findings underscore the role of mammary fibroblasts in promoting aggressiveness and endocrine therapy resistance in ER-positive breast cancers and highlight the utility of FT-IR for the further characterization of breast cancer samples.     

Frequent allelic losses in tumor-associated stromal cells and tumor epitelium of prostate cancer

It has become increasingly clear that tumor microenvironment plays a critical role in carcinogenesis. Accumulation of genetic alterations is typical not only for cancer epithelial cells but tumor-associated fibroblasts as well. Tumor epithelia, tumor-associated stroma from prostatectomy specimens of patients with prostate cancer and cells from prostatic intraepithelial neoplasia (PIN) and adjacent stroma from males with PIN were isolated by using laser capture microdissection. Microsatellite allelotyping was evaluated using 4 highly polymorphic markers for chromosomal regions 8p22, 16q23-24 and 13q14. Incidences of alterations (loss of heterozygosity or allelic imbalance) were 48% for region 8p22, 72% for 16q23 and 37% for 13q14. The LOH frequencies in tumor-associated stroma cells were very similar. Alterations at chromosome 13q were significantly associated with advanced tumor stage, whereas AI at 16q was also associated with high Gleason score and lymph node metastasis. We find some incidences of allelic imbalance in premalignant lesions in epithelial (16-27%) and stromal (7-22%) components. Our results show that the frequencies of genetic aberrations are as high in stromal cells as in tumor cells.     

Prostate tumor-stroma interaction: molecular mechanisms and opportunities for therapeutic targeting

Maintenance of cell and tissue homeostasis is dependent upon the dynamic balance of cell proliferation, differentiation, and apoptosis through interactions between cells and their microenvironment. The unique prostatic cellular phenotypes are induced and maintained by interaction between epithelium and adjacent stroma through intimate intercellular signaling pathways. In this article, we summarize current advances in the tumor-stroma interaction and its biologic and therapeutic implications. We specifically emphasize current studies of the possible factors driving the "vicious cycle" between stroma and emerging prostate tumor epithelial cells that may be responsible for carcinogenesis and metastasis to bone. Stroma responds both genotypically and phenotypically to tumor epithelium upon co-culture under 3-D conditions. Likewise, the emerging carcinoma responds to stromal signals that drive progression to malignancy. A vicious cycle mediated by soluble and insoluble molecules secreted by tumor cells and stroma appear be the critical factors supporting and sustaining tumor colonization in bone. Co-targeting tumor and stroma with therapeutic agents has yielded promising results both in pre-clinical models of prostate cancer and bony metastasis and in clinical trials of patients treated with a dual tumor and stroma targeting strategies. In conclusion, understanding and targeting the interaction of the tumor and its stromal microenvironmant may improve the prognosis, reduce the suffering and increase the survival of patients with advanced cancer metastasis.     

ICGA-PSO-ELM approach for accurate multiclass cancer classification resulting in reduced gene sets in which genes encoding secreted proteins are highly represented

A combination of Integer-Coded Genetic Algorithm (ICGA) and Particle Swarm Optimization (PSO), coupled with the neural-network-based Extreme Learning Machine (ELM), is used for gene selection and cancer classification. ICGA is used with PSO-ELM to select an optimal set of genes, which is then used to build a classifier to develop an algorithm (ICGA_PSO_ELM) that can handle sparse data and sample imbalance. We evaluate the performance of ICGA-PSO-ELM and compare our results with existing methods in the literature. An investigation into the functions of the selected genes, using a systems biology approach, revealed that many of the identified genes are involved in cell signaling and proliferation. An analysis of these gene sets shows a larger representation of genes that encode secreted proteins than found in randomly selected gene sets. Secreted proteins constitute a major means by which cells interact with their surroundings. Mounting biological evidence has identified the tumor microenvironment as a critical factor that determines tumor survival and growth. Thus, the genes identified by this study that encode secreted proteins might provide important insights to the nature of the critical biological features in the microenvironment of each tumor type that allow these cells to thrive and proliferate.     

Correlation of protein expression, Gleason score and DNA ploidy in prostate cancer

The prognosis of prostate cancer correlates with tumor differentiation. Gleason score and DNA ploidy are two prognostic factors that correlate with prognosis. We analyzed differences in protein expression in prostate cancer of high and low aggressiveness according to these measures. From 35 prostatectomy specimens, 29 cancer samples and 10 benign samples were harvested by scraping cells from cut surfaces. DNA ploidy was assessed by image cytometry. Protein preparations from cell suspensions were examined by 2-DE. Protein spots that differed quantitatively between sample groups were identified by MS fingerprinting of tryptic fragments and MS/MS sequence analysis. We found 39 protein spots with expression levels that were raised or lowered in correlation with Gleason score and/or DNA ploidy pattern (31 overexpressed in high-malignant cancer, 8 underexpressed). Of these, 30 were identified by MS. Among overexpressed proteins were heat-shock, structural and membrane proteins and enzymes involved in gene silencing, protein synthesis/degradation, mitochondrial protein import (metaxin 2), detoxification (GST-pi) and energy metabolism. Stroma-associated proteins were generally underexpressed. The protein expression of prostate cancer correlates with tumor differentiation. Potential prognostic markers may be found among proteins that are differentially expressed and the clinical value of these should be validated.     

Clinical experience with gene therapy for the treatment of prostate cancer

Localized prostate cancer can be treated effectively with radical prostatectomy or radiation therapy. The treatment options for metastatic prostate cancer are limited to hormonal therapy; hormone-refractory cancer is treated with taxane-based chemotherapy, which provides only a modest survival benefit. New treatments are needed. The gene for the initiation of prostate cancer has not been identified; however, gene therapy can involve tumor injection of a gene to kill cells, systemic gene delivery to target and kill metastases, or local gene expression intended to generate a systemic response. This review will provide an overview of the various strategies of cancer gene therapy, focusing on those that have gone to clinical trial, detailing clinical experience in prostate cancer patients.