| Title |
Discovery Analysis of TCGA Data Reveals Association between Germline Genotype and Survival in Ovarian Cancer Patients
|
|---|---|
| Published in |
PLOS ONE, March 2013
|
| DOI | 10.1371/journal.pone.0055037 |
| Pubmed ID | |
| Authors |
Rosemary Braun, Richard Finney, Chunhua Yan, Qing-Rong Chen, Ying Hu, Michael Edmonson, Daoud Meerzaman, Kenneth Buetow |
| Abstract |
Ovarian cancer remains a significant public health burden, with the highest mortality rate of all the gynecological cancers. This is attributable to the late stage at which the majority of ovarian cancers are diagnosed, coupled with the low and variable response of advanced tumors to standard chemotherapies. To date, clinically useful predictors of treatment response remain lacking. Identifying the genetic determinants of ovarian cancer survival and treatment response is crucial to the development of prognostic biomarkers and personalized therapies that may improve outcomes for the late-stage patients who comprise the majority of cases. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Mexico | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 55 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 26% |
| Researcher | 13 | 22% |
| Student > Bachelor | 6 | 10% |
| Student > Master | 5 | 9% |
| Other | 4 | 7% |
| Other | 7 | 12% |
| Unknown | 8 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 21 | 36% |
| Biochemistry, Genetics and Molecular Biology | 9 | 16% |
| Medicine and Dentistry | 6 | 10% |
| Mathematics | 4 | 7% |
| Computer Science | 3 | 5% |
| Other | 7 | 12% |
| Unknown | 8 | 14% |