| Title |
Affinity-based proteomics reveal cancer-specific networks coordinated by Hsp90
|
|---|---|
| Published in |
Nature Chemical Biology, September 2011
|
| DOI | 10.1038/nchembio.670 |
| Pubmed ID | |
| Authors |
Kamalika Moulick, James H Ahn, Hongliang Zong, Anna Rodina, Leandro Cerchietti, Erica M Gomes DaGama, Eloisi Caldas-Lopes, Kristin Beebe, Fabiana Perna, Katerina Hatzi, Ly P Vu, Xinyang Zhao, Danuta Zatorska, Tony Taldone, Peter Smith-Jones, Mary Alpaugh, Steven S Gross, Nagavarakishore Pillarsetty, Thomas Ku, Jason S Lewis, Steven M Larson, Ross Levine, Hediye Erdjument-Bromage, Monica L Guzman, Stephen D Nimer, Ari Melnick, Len Neckers, Gabriela Chiosis |
| Abstract |
Most cancers are characterized by multiple molecular alterations, but identification of the key proteins involved in these signaling pathways is currently beyond reach. We show that the inhibitor PU-H71 preferentially targets tumor-enriched Hsp90 complexes and affinity captures Hsp90-dependent oncogenic client proteins. We have used PU-H71 affinity capture to design a proteomic approach that, when combined with bioinformatic pathway analysis, identifies dysregulated signaling networks and key oncoproteins in chronic myeloid leukemia. The identified interactome overlaps with the well-characterized altered proteome in this cancer, indicating that this method can provide global insights into the biology of individual tumors, including primary patient specimens. In addition, we show that this approach can be used to identify previously uncharacterized oncoproteins and mechanisms, potentially leading to new targeted therapies. We further show that the abundance of the PU-H71-enriched Hsp90 species, which is not dictated by Hsp90 expression alone, is predictive of the cell's sensitivity to Hsp90 inhibition. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 3% |
| United Kingdom | 3 | 2% |
| Canada | 2 | 1% |
| Singapore | 1 | <1% |
| Japan | 1 | <1% |
| Germany | 1 | <1% |
| Colombia | 1 | <1% |
| Austria | 1 | <1% |
| Unknown | 156 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 45 | 26% |
| Researcher | 37 | 22% |
| Student > Bachelor | 13 | 8% |
| Student > Master | 12 | 7% |
| Professor > Associate Professor | 12 | 7% |
| Other | 24 | 14% |
| Unknown | 28 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 46 | 27% |
| Biochemistry, Genetics and Molecular Biology | 40 | 23% |
| Chemistry | 26 | 15% |
| Medicine and Dentistry | 16 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 1% |
| Other | 8 | 5% |
| Unknown | 33 | 19% |