MDA-MB-231 Breast Cancer Cell Line
and
Curcuma longa with Wild Type p53 Plasmid
Research of 2017
Due to consumption of food & water, breathing, metabolism, sun radiation, pollution, etc., free radicals are created in our body. Such radicals are molecules that need an electron to be stable. In order to do so, they grab an electron from the neighbouring molecule. This chain reaction is known as oxidative stress, which is controlled by reactive oxygen species (ROS).
Fortunately, we have something called antioxidants. They counteract the effects of oxidative stress. Thus their balance is essential for various cellular activities such as transcription of proteins, cell replication, apoptosis, signaling, etc.
Due to reasons mentioned in the figure (on the right), cancer cells have elevated levels of oxidative stress. They use high levels of ROS to transcribe certain proteins. For instance, NF-kB protein is activated which allows them to keep on proliferating infinitely. On the other hand, such high levels of oxidative stress deactivate p53 protein which is responisble for apoptosis. Hence ROS allows them to keep dividing while avoiding apoptosis .
Since antioxidants can counteract the effects of oxidative stress, they can be used to cure cancer. When antoxidants are added to the cancer cells, they reduce levels of ROS hence NF-kB is deactivated and p53 protein becomes active again. Due to this, cancer cells can't proliferate further and apoptosis starts killing them.
Wild Type p53 plasmid was obtained from Addgene which was later minipreped, and the cells were transfected with that DNA. The figure on the left shows the layout used in the experiment. Red plasmid was used for fluorescence. DMSO was the solvent for the antioxidant, Curcuma longa. After three days of incubation, the percentage of dead cells was calculated for each variable using Trypsin, Trypan blue, and cell counter.
The bar graph shows average cell death by experimental groups and controls of three trials. Untreated cells resulted in 0% cell death in all trials. (Thus, the last bar has no height: 0% cell death.) Error bars represent the appropriate standard deviation of each variable.
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