These past few weeks, we have finished recording our final three videos and plan to upload them within the next two weeks! We wanted to give a HUGE thank you to everyone who supported our project. First, our on and off campus mentors, Dr. Aegina Martin and Dr. Stuart Martin. We couldn't have completed our project without the awesome experience of being able to go into the lab and learn research techniques. Thank you to Julia and Megan for taking time out of your research to help us!!! We are so grateful for all your expertise :). In addition, thank you to Ms. Das for coordinating everything in the fellows program. It has been an amazing experience!

Also... we have some 3D models coming in!

We will investigate the role of five genes on breast cancer survival rates via immunofluorescent staining and bioinformatic databases. Collecting our data from an RNA sequence file of all expressed genes in patient cell lines, we identified gene candidates with the highest read count differences between MCF10As—non tumorigenic cells—and MDA-MB-436s—triple negative, aggressive breast cancer cells. With great changes in expression between cancerous and normal cells, we will investigate the likelihood of these genes as potential oncogenes by (a) analyzing the functions and behavior of each gene through previous literature and experiments (b) staining the cells with immunofluorescent antibodies to compare the location and presence of each gene in MCF10As versus MDA-MB-436s (c). performing western blots on each gene so we may see the experimental expression difference of each gene between the two cell lines, with the MCF10As serving as a control group. In particular, we are curious to see if any of the genes are expressed in microtentacles (McTNs)—tubulin-based protrusions from cancer cells which help them attach to blood vessels and other cells. If a gene is present within the McTNs, it could aid cancer in metastasizing. After viewing the immunofluorescent stained genes and completing western blots, bioinformatic databases like KMPlotter and cBioPortal will help us investigate the survival rate of patients with triple negative breast cancer when one of five genes is over or under expressed in patient samples.
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