Annel Andrea Leon Tenorio
Andrea, a junior majoring in Bioengineering at Stanford University, studied the repurposing of pharmaceutical drugs for use as potential cancer therapeutics.
Developing a drug can be both a long and expensive process. The average time and cost to develop a drug are 9-16 years and 460 million dollars. But this timeline can be accelerated and the process’s overall cost reduced through drug repurposing: where you take a drug that has been through the drug discovery process, and you use it to treat an illness different from its original purpose.
I am honored to have been a part of the Broad Summer Research Program 2021 cohort! For me, not only was the summer of 2021 a period of great growth and learning, but also of excitement and inspiration. It has been a privilege to get to know my cohort and learn about their passions and drive to make the world a better place. I am excited to see us continue to grow as scientists and accomplish our own individual missions to make positive change.My team aimed to identify inhibitors as candidates for drug repurposing by utilizing three Broad datasets, Prism, Achilles, and CCLE. PRISM is a dataframe where different individual drugs were used on different cell lines, resulting in drug sensitivity data. Achilles is a dataframe where individual genes were knocked out in different cell lines, resulting in gene dependency data. We correlated the resulting cell line effect of both dataframes to produce a correlation table with the combined cell line effect. We then utilized this correlation table alongside our third dataframe, the cancer cell line encyclopedia, CCLE. The CCLE dataframe gives us information about the different cell lines, such as mutation and expression data. Finally, empowered with the knowledge from our correlation table and CCLE, we were able to identify promising drug and gene targets for drug repurposing. One example of these promising drug and gene target combinations includes Aripiprazole and the TGM1 gene, which have a positive correlation that may impact cancer cell death. After identifying this combination, I explored what cancer cell line types Aripiprazole causes the most cell death in. I found that Aripiprazole may have a more significant effect on endometrial and uterine cancer cell lines. I wanted to investigate this further, so I subsetted my data to only include endometrial and uterine cancer cell lines. I observed an even more positive correlation between Aripiprazole sensitivity and TGM1 dependency, prompting further investigation on this drug and gene target combination for the treatment of endometrial and uterine cancer.
Project: Investigating the Repurposing of Aripiprazole as a Potential Cancer Therapeutic
Mentors: Andrew Boghossian, Cancer Program, PRISM, Dr. Julian Avila-Pacheco, Metabolomics Platform