A major bottleneck in devising effective targeted therapies for cancer treatment lies at the identification of relevant drug targets. Genetic screens that measure the outcome of inhibiting individual genes in cancer cells and in normal cells on a genome-scale are powerful experiments that could identify such drug targets. Until recently these screens could not be performed in human cells. To perform such screens, my laboratory has developed new methods, based on the principle of RNA interference (RNAi), to individually inactivate every gene in the human genome, approximately 32,000 genes, one at a time. Furthermore, we have developed technologies to carry out these screens in high throughput fashion. Through this funding opportunity, I aim to further develop our RNAi technology platform to enhance its throughput and fidelity. I will use lung cancer cell lines as a discovery paradigm for this technology development effort. The ultimate goal is to enable the genome-wide interrogation of large numbers of cancer cell lines to comprehensively identify the dependencies and vulnerabilities specific to cancer cells but not normal cells. This approach should uncover many previously unrecognized targets for drug discovery and has the potential to provide additional, more effective treatment options for cancer patients.
Our proposal aims to develop and mature a ultra-high throughput RNA interference (RNAi) screening platform for the identification of cancer-lethal genes. Based on the RNAi technology that my lab has developed, this proposed screening platform will enable the rapid, genome-wide screening of large numbers of cancer and normal cell lines to identify genes that are selectively required for cancer cell viability and therefore might serve as potential cancer drug targets. We will use lung cancer cell lines as a discovery paradigm for the development and validation of this technology platform.
| Luo, Ji; Solimini, Nicole L; Elledge, Stephen J (2009) Principles of cancer therapy: oncogene and non-oncogene addiction. Cell 136:823-37 |
