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. / A Dissertation submitted to the Department of Chemistry and Biochemistry in partial fulfillment of the requirements for the degree of Doctor of
Philosophy. / Fall Semester, 2014. / September 15, 2014. / bioinformatics, breast cancer, pathway analysis, prostate cancer, signaling networks, signaling pathways / Includes bibliographical references. / Qing-Xiang Sang, Professor Directing Thesis; Richard Bertram, University Representative; Oliver Steinbock, Committee Member; Wei Yang, Committee
Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_253412 |
| Contributors | Stewart, Paul (authoraut), Sang, Qing-Xiang Amy (professor directing thesis), Bertram, R. (Richard) (university representative), Steinbock, Oliver (committee member), Yang, Wei (committee member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Chemistry and Biochemistry (degree granting department) |
| Publisher | Florida State University, Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource (117 pages), computer, application/pdf |
| Rights | This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them. |
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