Investigation of Signaling Pathways of Human Cancers of Breast and Prostrate

Over 232,000 women will be diagnosed with breast cancer in 2014 in the United States, and approximately 40,000 women will die from this disease. Similarly, it is estimated that 230,000 men will be diagnosed with prostate cancer in the United States, and over 29,000 men will die from this disease. These figures make breast cancer and prostate cancer the two most diagnosed cancers in women and men, respectively, and they are both the second leading cause of cancer mortality in their respective genders. These alarming numbers show that we have a long way to go before finding a cure for cancer. Because cancer is a multifaceted disease, systems biology approaches provide excellent ways to fully appreciate and understand its complexity. The overall theme of this dissertation is the application of data analysis and bioinformatic techniques in order to gain insight to the signaling pathways involved in breast and prostate cancer. High-throughput genomics and proteomics allow for an unprecedented glimpse into the inner workings of biology, particularly in the case of cancer. These relatively inexpensive, high-throughput experiments have given rise to a glut of data that has not been thoroughly analyzed. This means that data analysis and bioinformatics techniques can be applied to large data sets in order to answer questions and unlock new directions in cancer research. Here, a comprehensive differential gene expression analysis and pathway analysis was performed using the breast cancer data from The Cancer Genome Atlas in order to understand health disparity in African American breast cancer. Furthermore, proteomics and phosphoproteomics experimental techniques were applied to better understand the protein expression differences and signaling pathways of an advanced metastatic prostate cancer cell model. Finally, data analysis of patient models for aggressive prostate cancer was performed in order to compare and contrast the differences with the advanced metastatic prostate cancer cell model. Attached to this manuscript is a zipped file containing supplementary tables. These supplementary tables support results presented in Chapters 2, 3, and 4. There are 13 supplementary tables in total.