Title |
Drug response in a genetically engineered mouse model of multiple myeloma is predictive of clinical efficacy
|
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Published in |
Blood, March 2012
|
DOI | 10.1182/blood-2012-02-412783 |
Pubmed ID | |
Authors |
Marta Chesi, Geoffrey M. Matthews, Victoria M. Garbitt, Stephen E. Palmer, Jake Shortt, Marcus Lefebure, A. Keith Stewart, Ricky W. Johnstone, P. Leif Bergsagel |
Abstract |
The attrition rate for anticancer drugs entering clinical trials is unacceptably high. For multiple myeloma (MM), we postulate that this is because of preclinical models that overemphasize the antiproliferative activity of drugs, and clinical trials performed in refractory end-stage patients. We validate the Vk*MYC transgenic mouse as a faithful model to predict single-agent drug activity in MM with a positive predictive value of 67% (4 of 6) for clinical activity, and a negative predictive value of 86% (6 of 7) for clinical inactivity. We identify 4 novel agents that should be prioritized for evaluation in clinical trials. Transplantation of Vk*MYC tumor cells into congenic mice selected for a more aggressive disease that models end-stage drug-resistant MM and responds only to combinations of drugs with single-agent activity in untreated Vk*MYC MM. We predict that combinations of standard agents, histone deacetylase inhibitors, bromodomain inhibitors, and hypoxia-activated prodrugs will demonstrate efficacy in the treatment of relapsed MM. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 67% |
Unknown | 2 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 67% |
Scientists | 1 | 17% |
Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | <1% |
Turkey | 1 | <1% |
Belgium | 1 | <1% |
Australia | 1 | <1% |
Unknown | 121 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 31 | 25% |
Student > Ph. D. Student | 30 | 24% |
Student > Master | 12 | 10% |
Student > Bachelor | 11 | 9% |
Other | 9 | 7% |
Other | 13 | 10% |
Unknown | 19 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 29 | 23% |
Medicine and Dentistry | 28 | 22% |
Biochemistry, Genetics and Molecular Biology | 15 | 12% |
Immunology and Microbiology | 8 | 6% |
Chemistry | 6 | 5% |
Other | 14 | 11% |
Unknown | 25 | 20% |