Excluding skin cancers, prostate cancer is the most frequently diagnosed cancer in American men. The American Cancer Society estimated 220,800 new prostate cancer cases would be diagnosed in 2015. Prostate cancer is also the second leading cause of cancer-specific mortality at 27,540 deaths estimated in 2015. Of particular concern are the increased incidence, mortality, and aggressive features of prostate cancer seen in African American men. These health disparities are not fully explained by non-biological factors such as socioeconomics, access to care, or treatment. Prostate cancer presents a compelling case for the clinical usefulness of biomarkers. The lack of an assured prostate cancer susceptibility gene necessitates other molecular markers are required for screening. Because of its slow-growing nature, early prostate cancer is asymptomatic so biomarkers that accurately diagnose asymptomatic prostate cancer would be of great value. Additionally, prognostic markers to discriminate indolent and aggressive disease would be highly prized. The racial differences in prostate cancer also suggest that biomarkers could be particularly useful in heavily burdened populations such as African American men. For a myriad of reasons, however, biomarker discovery has not been as fruitful as anticipated in the wake of advances in high-throughput genomic and proteomic technologies. Pathway analysis has emerged as a strategy for identifying molecular changes in prostate cancer and uncovering molecular targets for biomarkers and therapy. The thread uniting the studies presented herein is the application of pathway analysis to human prostate cancer to identify altered mechanisms of prostate cancer tumors development and progression. Study 1 used comprehensive genomic patient data obtained from The Cancer Genome Atlas to identify differentially expressed genes and pathway signatures in prostate cancer. This analysis highlighted the strong association of the "TGF-β signaling" and "Ran regulation of mitotic spindle formation" with prostate cancer and confirmed reported findings from microarray data that suggest "Actin Cytoskeleton Regulation", "Cell Cycle", "MAPK Signaling", and "Calcium Signaling" are also altered in prostate cancer. Study 2 incorporated a similar methodological approach to study paired RC-77 human prostate cancer cell lines. This cell model is one of few models derived from an African American patient. This work completed the first comprehensive proteomic analysis of RC-77 cell lines and found 63 differentially expressed proteins between the malignant RC-77T/E cell line and the non-malignant RC-77N/E, with 18 proteins uniquely detected in RC-77T/E and 2 proteins uniquely detected in RC-77N/E. Many of these differentially expressed proteins fall into the category of structural proteins or have a structural role. A pathway approach was used to provide a context for these differences and revealed correlation of the "Tight Junction", "Cell Adhesion Molecules", "Adherens Junction", "ECM-Receptor interaction", "Focal Adhesion", and "Proteoglycans in Cancer" pathways with either RC-77T/E or RC-77N/E cells. Study 3 applied the pathway analysis to race-, age-, and stage-matched malignant and non-malignant prostate tissues to examine pathway dysregulation in the context of racial health disparities. While this small case study was not able to show racial differences in the expression of individual genes, pathways were differentially associated with African American prostate cancer. Three supplementary files containing the expression data and full analysis results for each project are included with this dissertation: Supplementary File 1 (MyersJS_SuppInfo_GenomicData_TCGA.xlsx), Supplementary File 2 (MyersJS_SuppInfo_ProteomicData_RC77.xlsx), and Supplementary File 3 (MyersJS_SuppInfo_ProteomicData_Tissues.xlsx).