| Title |
Prospective Molecular Profiling of Canine Cancers Provides a Clinically Relevant Comparative Model for Evaluating Personalized Medicine (PMed) Trials
|
|---|---|
| Published in |
PLOS ONE, March 2014
|
| DOI | 10.1371/journal.pone.0090028 |
| Pubmed ID | |
| Authors |
Melissa Paoloni, Craig Webb, Christina Mazcko, David Cherba, William Hendricks, Susan Lana, E. J. Ehrhart, Brad Charles, Heather Fehling, Leena Kumar, David Vail, Michael Henson, Michael Childress, Barbara Kitchell, Christopher Kingsley, Seungchan Kim, Mark Neff, Barbara Davis, Chand Khanna, Jeffrey Trent |
| Abstract |
Molecularly-guided trials (i.e. PMed) now seek to aid clinical decision-making by matching cancer targets with therapeutic options. Progress has been hampered by the lack of cancer models that account for individual-to-individual heterogeneity within and across cancer types. Naturally occurring cancers in pet animals are heterogeneous and thus provide an opportunity to answer questions about these PMed strategies and optimize translation to human patients. In order to realize this opportunity, it is now necessary to demonstrate the feasibility of conducting molecularly-guided analysis of tumors from dogs with naturally occurring cancer in a clinically relevant setting. |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 44% |
| Argentina | 1 | 11% |
| Unknown | 4 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 89% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Finland | 1 | 1% |
| India | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 81 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 19% |
| Student > Ph. D. Student | 13 | 15% |
| Other | 10 | 12% |
| Student > Bachelor | 9 | 11% |
| Student > Master | 7 | 8% |
| Other | 16 | 19% |
| Unknown | 13 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Veterinary Science and Veterinary Medicine | 17 | 20% |
| Biochemistry, Genetics and Molecular Biology | 16 | 19% |
| Medicine and Dentistry | 11 | 13% |
| Agricultural and Biological Sciences | 10 | 12% |
| Neuroscience | 3 | 4% |
| Other | 11 | 13% |
| Unknown | 16 | 19% |