The central hypothesis for the proposed research is that genome wide RNAi inhibition of specific gene targets will identify previously unrecognized critical molecular pathways which modulate the growth of Myeloma cells in either direction and that such information can be positively exploited clinically. While newer agents such as bortezomib, thalidomide and lenalidomide have profound clinical activity in myeloma the exact point of molecular action is unknown. Furthermore, none of these drugs is curative and the identification of novel vulnerability targets which can be exploited, together with the identification of existing pharmaceutical agents which may have unrecognized activity in MM is a critical goal for future progress. Since the critical targets of MM cells remain elusive further genomic scale analysis and the creation of a vulnerability map of MM, is in our opinion, required to further our global understanding of this disease and how treatments may be both personalized and optimized. Our objective in this proposal is therefore to apply advanced functional genomic strategies to identify and rapidly validate the critical role of candidate genes in MM growth and survival and advance this information clinically. In that light we have recently conducted high throughput, kinome wide, RNAi lethality screening in MM cell lines to identify kinases essential to the survival of human MM. In addition, we have identified kinase targets that sensitize tumor cells to bortezomib therapy by RNAi screening in the presence of this drug. Finally, we have now completed a preliminary screen of the druggable genome (7000 genes) in a single MM cell line with and without bortezomib and lenalidomide. Through other previous efforts we have an extensive panel of 60 MM cell lines, a large database of both gene expression and comparative genomic hybridization in cell lines and primary patient samples and ready access to patient tissues. We propose here to extend these findings to explore a more globally representative 17,000 gene high throughput, synthetic lethal RNAi screen in MM cell lines and to validate these findings using secondary screening, target validation in primary patient cells, and bioinformatic processing which brings together our disparate genomic datasets. Specifically, we will determine the extent to which silencing gene expression, by parallel RNAi, will modify cytotoxic sensitivity in either direction in cultured Myeloma cell lines. We will then apply pharmacogenomics and classical molecular biology to cell lines, animal models and patient samples to validate the clinical relevance of these putative drug targets and determine the extent to which they can be used as biomarkers of therapeutic response.

Public Health Relevance

Multiple Myeloma affects 50,000 people in the United States at any given time. Major advances have been made in the treatment and newer agents such as bortezomib, thalidomide and lenalidomide have profound clinical activity. However, none of these drugs is curative and the means by which they work opaque. Thus identification of novel vulnerability targets which can be exploited, together with the identification of existing pharmaceutical agents which may have unrecognized activity in MM is a critical goal for future progress. To achieve this we will screen 17,000 genes for there ability to control myeloma cell growth. This genomic scale analysis and the creation of a vulnerability map of Myeloma, is a prerequisite to further our global understanding of this disease and how treatments may be both personalized and optimized.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA133115-03
Application #
7894623
Study Section
Drug Discovery and Molecular Pharmacology Study Section (DMP)
Program Officer
Arya, Suresh
Project Start
2008-09-15
Project End
2013-07-31
Budget Start
2010-08-01
Budget End
2011-07-31
Support Year
3
Fiscal Year
2010
Total Cost
$254,967
Indirect Cost
Name
Mayo Clinic, Arizona
Department
Type
DUNS #
153665211
City
Scottsdale
State
AZ
Country
United States
Zip Code
85259
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Egan, Jan B; Shi, Chang-Xin; Tembe, Waibhav et al. (2012) Whole-genome sequencing of multiple myeloma from diagnosis to plasma cell leukemia reveals genomic initiating events, evolution, and clonal tides. Blood 120:1060-6
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