EXPLOITATION OF SMALL INTERFERING RNA METHODOLOGY TO IDENTIFY NOVEL ANTICANCER TREATMENTS

The majority of current pharmacological treatments for cancer target rapidly dividing cells, a characteristic of most cancer cells. Unfortunately, these treatments also affect cells that normally divide at a rapid rate, such as cells of the digestive tract, hair follicles, and bone marrow, which limits the efficacy of chemotherapy due to toxic side effects. Reducing the drug dose to evade these side effects, however, often impairs efficacy and encourages drug resistance. Therefore, new unbiased approaches are required to identify new drug combinations with existing effective cancer chemotherapeutics. I therefore exploited data from a short interfering RNA (siRNA) high throughput screen targeting 5,520 unique druggable genes, which comprises gene products that are theoretically good targets for drug development. I used the siRNA screening methodology to identify novel combination chemotherapies for the treatment of glioblastoma multiforme (GBM), the most common and aggressive form of human primary brain tumors. My hypothesis is that unrecognized chemosensitivity nodes exist for the microtubule destabilizing agent vinblastine. GBM cells were treated with a sub-lethal concentration of vinblastine and identified gene products that sensitized cells to vinblastine. Using a series of statistical methods, followed by target identification assays, I found gene products that sensitized GBM cells to vinblastine, implicating siRNA screening technology as an efficient, unbiased method for identifying potentially novel anticancer treatments