Title |
Molecular cytogenetics as a clinical test for prognostic and predictive biomarkers in newly diagnosed ovarian cancer
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Published in |
Journal of Ovarian Research, January 2013
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DOI | 10.1186/1757-2215-6-2 |
Pubmed ID | |
Authors |
Shelly Gunn, Xavier Reveles, Korrie Weldon, Andres Barrera, Mariam Ishaque, Dale Taylor, Chris McCaskill, Jaeweon Kim, Rashmi Shah, Mansoor Mohammed, Todd Barry, Brianne Kaiser, Amita Patnaik, Anthony Tolcher |
Abstract |
There is a clinical need for routinely available genomic biomarker testing in newly diagnosed ovarian cancer. In the current study we performed molecular cytogenetics using a validated array based comparative genomic hybridization (array CGH) assay to screen for the presence of predictive and prognostic biomarkers in archival diagnostic tissue from ovarian cancer patients. We hypothesized that biomarkers of high-risk disease would be detectable in tumor samples from patients with treatment refractory, advanced disease, and would be detected less frequently in tumor samples from patients with more favorable outcomes. In addition, we predicted that the use of a genome-wide copy number analysis (CNA) testing platform would enable us to identify novel potentially targetable chromosomal alterations of therapeutic significance in a percentage of cases. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 25 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 8 | 32% |
Researcher | 5 | 20% |
Student > Master | 3 | 12% |
Student > Bachelor | 3 | 12% |
Student > Postgraduate | 2 | 8% |
Other | 3 | 12% |
Unknown | 1 | 4% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 7 | 28% |
Agricultural and Biological Sciences | 7 | 28% |
Computer Science | 3 | 12% |
Biochemistry, Genetics and Molecular Biology | 2 | 8% |
Nursing and Health Professions | 1 | 4% |
Other | 4 | 16% |
Unknown | 1 | 4% |