Flow cytometry in evaluation of tumor cells using Drosophila cancer model
Presenter(s)
Michael M Gilbert, Kirti Snigdha
Files
Description
Cancer is characterized by rapid uncontrolled division of mutated tumor cells. These cells arise amidst the normal cells and differ from them in the DNA content, rate of cell division and proliferation. The presence of DNA aneuploidy and a high proportion of S-phase tumor cells have been associated with tumor malignancy and a poor prognosis. Our lab focuses on understanding how the tumor cells and normal cells interact in vivo using Drosophila melanogaster to drive the tumor survival and progression. Given to its well-studied genetics, low redundancy in genome, ease of maintenance and similarities in gene architecture, they have served as an excellent model system for many diseases including cancer. We hypothesize that the tumor and normal cell interact among each other through molecular signals and this aids in tumor progression. Identifying the key differences between normal and tumor cell will help us in better understanding the interactions happening between them. A flow cytometer is exceptionally useful with these observations including the detection of tumor cell DNA aneuploidy and the analysis of tumor cell proliferation. In this sophisticated technique we will be able to identify the changes in the cell cycle, and the amount of DNA content present in both the tumor cells and normal cells. It will also help in understanding the molecular basis of cell proliferation, and cell signaling. We have established epithelial tumor model in Drosophila wing imaginal disc in which the tumor cells are marked by green fluorescent protein and are surrounded by normal cells. We propose to use flow cytometry to identify the tumor cells from the normal cells based on the GFP expression. We intend to evaluate the changes in the tumor cell population, DNA content and cell cycle due to blocking of key signaling pathways between tumor cell and normal cell. Here we present our findings by using flow cytometry.
Publication Date
4-5-2017
Project Designation
Independent Research - Graduate
Primary Advisor
Madhuri Kango-Singh
Primary Advisor's Department
Biology
Keywords
Stander Symposium project
Recommended Citation
"Flow cytometry in evaluation of tumor cells using Drosophila cancer model" (2017). Stander Symposium Projects. 1091.
https://ecommons.udayton.edu/stander_posters/1091