Identification of Novel Drug Targets and Lead Compounds for Advanced Prostate Cancer through Genomic and Cheminformatic Analyses

Prostate cancer is one of the most common cancers for males in the United States and Canada, with 260,000 estimated cases and 32,000 deaths per year. When diagnosed early, prostate cancer can be treated with high rate of success by surgery or radiation therapy. However, in advanced cases, the remaining treatment option is hormone therapy that relies on drugs to target a key protein, androgen receptor (AR), in prostate cancer cells. Unfortunately, the effectiveness of hormone therapy is temporary due to drug resistance in cancer cells. Therefore in most patients, the cancer reoccurs and progresses into a very deadly form after 2 to 3 years. Furthermore, new experimental results indicated that despite the fact that AR has a normal function in normal prostate cells, its function is hijacked and altered by other proteins in cancer cells through mutations.

It is very challenging to identify those 'bad proteins' because of the biological complexity of cancer cells; moreover, it is equally challenging to develop drugs that can counter the action of those proteins. Fortunately, there are two recent technological advancements that, when combined together, can create a very powerful tool to address those obstacles. The first is the accumulation of 'big data' from many large-scale experiments that investigated different aspects of mutations in prostate cancer cells. To analyze and integrate such big datasets demands heavy computation and powerful algorithms. The second is the advancement on protein modeling and simulation that enables a much more efficient search than conventional approaches for best drug candidates from millions of chemical structures. Thus, the proposed project is aimed to combine the power of big data analyses, protein modeling and simulation, computer-aided drug design, and biological validation to develop the next generation of drugs, targeting those malicious proteins in prostate cancer.

Having received my training from a diverse background on molecular biology, computer science, and statistical analysis, my goal is to apply those skills to this challenging and crucial field of prostate cancer research. Working alongside with the top scientists in the field at Vancouver Prostate Centre (VPC), one of the best cancer research centers in the world with state-of-the-art biological and computational facilities, helps me further my training and career goal. Under the guidance of a world-renowned prostate cancer researcher, Dr. Paul Rennie, the project will successfully generate a number of drug candidates against three new protein targets. Although it is a lengthy and costly process to take a drug from a laboratory to a patient (with an average time of 10-15 years and a cost up to billions of dollars), the time and cost will be significantly reduced by the computational approaches proposed by the project and the unique integration at VPC, combining drug discovery, preclinical development, and clinical research under a single research organization. We anticipate that results from this project will lead to new drugs that can be used alternatively or synergistically with current hormone therapy to benefit patients with the most deadly forms of prostate cancer.