Comparison of the Gene Expression Profiles of Human Primary Prostate Epithelial Cells and DU145 Prostate Cancer Cells

Comparison of the Gene Expression Profiles of Human Primary Prostate Epithelial Cells and Cells. HPrEC: Human Primary Prostate Epithelial Cells; DEGs: Differentially Expressed Genes; PSA: Prostate Specific Antigen; DMEM: Dulbecco’s Modified Eagle Medium; RMA: Robust Multi-Chip Analysis; MCODE: Molecular Complex Detection; DRE: Digital Rectal Examination; KEGG: Kyoto Encyclopedia of Genes and Genomes cancer is a debilitating disease that kills thousands of men worldwide each year. Investigating the biology of prostate cancer remains a high priority on the global scientific landscape. The current study utilized microarray techniques (Affymetrix Human Genome U133 Plus 2.0 Arrays) and bioinformatics analysis to compare the gene expression profiles of human primary prostate epithelial cells (HPrEC) and DU145 human prostate cancer cells. Microarray analysis yielded 6310 differentially expressed genes (DEGs) with a two-fold change and 1322 DEGs with a five-fold change. Metascape was used to characterize differentially expressed genes to specific molecular networks and canonical signaling pathways. Several signal transduction pathways and relevant prostate cancer-related genes (e.g., CSF1, CTSL, CYP3A5, DPYSL3, EGFR, FYN, LAMB3, ITGB4, PYGB) were identified which are consistent with previous studies as potential targets to prostate cancer progression. Future research publications using the current microarray dataset will explore the biological functions of select differentially expressed genes and protein products to better resolve the molecular basis of prostate cancer development and progression and may elucidate biomarkers and novel therapeutic strategies designed to effectively target prostate cancer.


Introduction
Prostate cancer remains the second leading cause of cancer-associated deaths of men in the United States [1,2]. The prostate gland is a component of the male reproductive system in mammals roughly the size of a walnut. The prostate gland is below the urinary bladder and is responsible for the secretion of an alkaline fluid that provides nourishment and protection for spermatozoa. Prostate cancer is the result of genetic and epigenetic factors that lead to the unregulated growth of prostate cells [3]. The use of the Gleason score, Prostate Specific Antigen (PSA) levels, and the TNM system are often used to characterize prostate cancer and to determine the appropriate medical response. Disease surveillance data suggests that incidence and mortality of prostate cancer overwhelmingly occurs in men over 50 years old with family history as a major predisposition factor. Reports also suggest that early detection sig nificantly leads to higher survival rates. Prostate cancer treatments in recent years include a combination of hormone therapy, surgical procedures, and chemotherapy [4,5]. The elucidation of underlying molecular mechanisms of prostate cancer can improve the detection, diagnosis, and disease staging. The identification of potential biomarkers and therapeutic solutions may lead to the reduction of global prostate cancer cases and deaths.
The development of biomolecular microarrays over 30 years ago has exponentially improved our comprehension of the molecular events that underlie biological processes in prokaryotes and eukaryotes [6]. The utilization of DNA microarrays and bioinformatics to evaluate gene expression of human carcinomas is a widely used technique to gain insights into disease development, progression, biomarkers, diagnosis, and prognosis [7][8][9][10][11]. One of the more exciting applications of microarrays is to utilize DNA chips to explore gene expression profiles specific to various therapeutic treatments [11][12][13][14][15][16]. Ren  Recently, researchers identified the DEGs involved in adipogenesis and used the drug screening approach (connectivity map) to determine that the drug Pyrvinium, an existing anti-helmintic drug, would serve as a potent anti-adipogenic agent based on inverse DEGs [17].
The purpose of the current study was to identify specific molecular components and biological pathways associated with prostate cancer using microarray technology and bioinformatics analysis. Human cells were cultured for 72 hrs at 37°C in a 5% CO2 atmosphere and harvested as previously described [24].
Prostate cells were analyzed using an Olympus IX70 Microscope to determine cell morphology and stringency of culture conditions.

RNA Sample Preparation and Microarray Procedures
Total RNA was extracted from HPrECs and DU145 cells using

Differentially Expressed Genes
Following analysis of RMA normalized microarray data, it was determined that a total of 6310 DEGs with a two-fold change or greater (p-value of <0.05) and 1322 DEGs with a five-fold change or greater (p-value of <0.01) were generated ( Figure 2). The gene expression profile of HPrECs provided the baseline in this experiment.

Gene Ontology Enrichment Analysis of DEGs
In the remainder of the Results section only the 1322 DEGs that demonstrated a five-fold change or greater were analyzed. Figure 3 illustrates a heat map based on gene ontology analysis that displays the major biological processes associated with the selected DEGs.

Discussion
Prostate cancer will account for the highest number of new cancer cases in men in the United States according to a recent report [29].  The VEGF signaling pathway has been implicated in pro-tumorigenic processes such as angiogenesis and metastasis. Binding of the VEGF to the vascular endothelial growth factor receptor results in gene expression that promotes the production of blood vessels, cell migration, and cell survival. The development of new blood vessels is necessary for tumor development and a major requirement for tumor invasivity. Figure 6 was obtained from KEGG and displays the VEGF canonical signal transduction pathway. Targeting the VEGF signaling pathway has been successfully applied to human cancers such as breast cancer, non-small cell lung cancer, and prostate cancer. Specifically, Bevacizumab, a monoclonal antibody that targets VEGF along with docetaxel inhibited cell proliferation processes in prostate cancer. Proteins identified in this study could be used as therapeutic targets to suppress cellular growth. Figure 6 displays additional potential downstream targets of VEGF signaling that may produce anti-tumor effects on prostate cancer cells. This seminal study was designed to present global gene expression data to identify specific biomarkers and therapeutic targets.
These types of studies are important and have the potential to convey meaningful insights regarding neoplastic transformations.
Cell culture-based gene expression profile studies, however, should be followed with microarray procedures involving primary tissue from patients to more accurately evaluate endogenous biological conditions. Comparing the molecular profiles (e.g., gene, protein) of healthy and diseased tissue from patients will lead to more robust data regarding the innerworkings of malignant neoplastic diseases.
Future research studies in the Microbial Signal Transduction Pathway Research Lab at Livingstone College will focus on select DEGs that were highly upregulated or downregulated in DU145 cells compared to human primary prostate epithelial cells. Additionally, subsequent investigations will involve the treatment of DU145 cells with existing drugs in a dose-dependent manner coupled with gene expression profiling (e.g., microarray and PCR array). These studies will be designed to evaluate the therapeutic value of synthetic and natural drugs in treating prostate cancer and may implicate new target molecules and biological processes of interest and expand our understanding of the development and progression of prostate cancer.