Date of Award

Spring 1998

Document Type

Thesis

Department

Mathematics, Engineering & Computer Science

First Advisor

Marie Vanisko

Second Advisor

Murphy Fox

Third Advisor

Marilyn Schendel

Abstract

This paper stems from research information accumulated over the summer of 1997 on the topic of ovarian cancer. My role in this was statistical accumulation, computation, and initial analysis. The study appealed to me due to the intertwined usage of math and biology it entailed. Specifically, a background in biology aided in comprehending the affliction of ovarian cancer and the underlying genetics that control it. The original purpose of this study involved compiling statistics on the symptoms, pathology reports, and flow cytometry data accumulated over the past few years from ovarian cancer patients at the Women’s Cancer Center of Northern California. From this, a new method of classifying the extent of the disease in new patients would be developed. The results of analyzing this data could improve upon the current method of diagnosis, which involves stages and grades. This would allow the treating physician a better chance at informing the patient as to the severity of the disease from which she suffers. It would also allow the patient to be more informed as to the chances of survival, the complications, and the realism of reoccurrence. The specific genes that maintain cell cycles and their division, possible mutations, and how all of it is regulated through the expression of certain genetic elements are explained in this paper. The possible benefits of this study include more thorough examinations, better treatments, and informed prognoses. These ideas are experimental, yet their implications could bring about major changes in the treatments of ovarian cancer.