Genomic Approaches for Detection and Treatment of Breast Cancer
Abstract
A key part of our research plan has been the development and use of retroviral vectors expressing RNA interference RNAs to identify human genes involved in causing or restraining cancer. In our first progress report we described our efforts to develop shRNA libraries and showed they could be used to identify tumor suppressors. Ultimately our goal is to screen of complex pools of shRNA expressing retroviruses each marked with a bar code that allows the results of the screen to be read out by microarray hybridization. We demonstrated this could be accomplished in enrichment screens for shRNAs that caused cellular transformation and growth in soft agar. However, a key goal has been to identify shRNAs that debilitate or kill cancer cells. In order for this to be possible in complex pools, it is imperative that each vector knock down its target with high penetrance. We have successfully achieved this level of knockdown and can now see particular shRNA expressing viruses drop out of complex pools. We are also developing bar code hybridization methods that allow us to detect over 80% of the viruses in pool. We hope to push this to over 90% using double bar codes. Together the high knockdown vectors together with the bar code hybridization has allowed us to achieve the central goal of this Award. We have taken advantage of our improvements to perform a variety of screens relevant to cancer. These include lethality screens to identify genes that cancer cell lines rely upon to proliferate and survive. We also are performing screens that are identifying genes whose loss gives rise to resistance to tyrosine kinase inhibitors. Finally we are continuing our efforts to identify tumor suppressors in human mammary epithelial cells. We have expanded this to identify oncogenes in the same system. In parallel we are attempting to generate a system through which we can explore the autoimmune phenotype of breast cancer patients. We have generated the peptide display libraries required fo
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 2006
- Accession Number
- ADA468017
Entities
People
- Stephen Elledge
Organizations
- Brigham and Women's Hospital