Using Computational Modeling Techniques to Analyze Cancer Cell/Tumor Growth, and Identifying Best Methods of Analyzing Data from Tools like Mass Spectrometry When Studying Tumor Growth

Public project summary

Despite extensive efforts to analyze cancer cells, no property has yet been found that can be applied to cure all types of cancer. As a result, doctors and pationes often must resort to using chemotherapy or radiotherapy to treat this deadly disease. This problem has negatively impacted cancer patients because it only provides a possibility of short term remission, and it does not contribute to an actual cure for cancer. It is commonly remarked that when one is stuck, it is best to change perspective and use a different strategy to attack the issue. In this case, the specific problem is how certain chemicals transform cancer cells. One possible approach is to study the use of recently developed tools like mass spectrometry and computational modeling to perform quantitative analyses on cancer data. This project will conduct a study that investigates the effects of certain chemicals on lipogenesis in cancer cells using computational modeling through mass spectrometry analyses, with the intent of identifying properties that apply to all cancer cells.