| Title |
A Hyperactive Signalosome in Acute Myeloid Leukemia Drives Addiction to a Tumor-Specific Hsp90 Species
|
|---|---|
| Published in |
Cell Reports, November 2015
|
| DOI | 10.1016/j.celrep.2015.10.073 |
| Pubmed ID | |
| Authors |
Hongliang Zong, Alexander Gozman, Eloisi Caldas-Lopes, Tony Taldone, Eric Sturgill, Sarah Brennan, Stefan O. Ochiana, Erica M. Gomes-DaGama, Siddhartha Sen, Anna Rodina, John Koren, Michael W. Becker, Charles M. Rudin, Ari Melnick, Ross L. Levine, Gail J. Roboz, Stephen D. Nimer, Gabriela Chiosis, Monica L. Guzman |
| Abstract |
Acute myeloid leukemia (AML) is a heterogeneous and fatal disease with an urgent need for improved therapeutic regimens given that most patients die from relapsed disease. Irrespective of mutation status, the development of aggressive leukemias is enabled by increasing dependence on signaling networks. We demonstrate that a hyperactive signalosome drives addiction of AML cells to a tumor-specific Hsp90 species (teHsp90). Through genetic, environmental, and pharmacologic perturbations, we demonstrate a direct and quantitative link between hyperactivated signaling pathways and apoptotic sensitivity of AML to teHsp90 inhibition. Specifically, we find that hyperactive JAK-STAT and PI3K-AKT signaling networks are maintained by teHsp90 and, in fact, gradual activation of these networks drives tumors increasingly dependent on teHsp90. Thus, although clinically aggressive AML survives via signalosome activation, this addiction creates a vulnerability that can be exploited with Hsp90-directed therapy. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 2% |
| Unknown | 60 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 26% |
| Student > Ph. D. Student | 12 | 20% |
| Student > Master | 8 | 13% |
| Other | 3 | 5% |
| Professor | 3 | 5% |
| Other | 4 | 7% |
| Unknown | 15 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 19 | 31% |
| Agricultural and Biological Sciences | 12 | 20% |
| Medicine and Dentistry | 4 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 3% |
| Immunology and Microbiology | 2 | 3% |
| Other | 4 | 7% |
| Unknown | 18 | 30% |