Title |
A target based approach identifies genomic predictors of breast cancer patient response to chemotherapy
|
---|---|
Published in |
BMC Medical Genomics, May 2012
|
DOI | 10.1186/1755-8794-5-16 |
Pubmed ID | |
Authors |
Robin M Hallett, Gregory Pond, John A Hassell |
Abstract |
The efficacy of chemotherapy regimens in breast cancer patients is variable and unpredictable. Whether individual patients either achieve long-term remission or suffer recurrence after therapy may be dictated by intrinsic properties of their breast tumors including genetic lesions and consequent aberrant transcriptional programs. Global gene expression profiling provides a powerful tool to identify such tumor-intrinsic transcriptional programs, whose analyses provide insight into the underlying biology of individual patient tumors. For example, multi-gene expression signatures have been identified that can predict the likelihood of disease reccurrence, and thus guide patient prognosis. Whereas such prognostic signatures are being introduced in the clinical setting, similar signatures that predict sensitivity or resistance to chemotherapy are not currently clinically available. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 40% |
United States | 1 | 20% |
Unknown | 2 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 80% |
Scientists | 1 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Mexico | 1 | 3% |
United States | 1 | 3% |
Unknown | 31 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 11 | 33% |
Student > Ph. D. Student | 6 | 18% |
Student > Master | 4 | 12% |
Student > Bachelor | 3 | 9% |
Other | 3 | 9% |
Other | 6 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 11 | 33% |
Biochemistry, Genetics and Molecular Biology | 7 | 21% |
Medicine and Dentistry | 6 | 18% |
Computer Science | 5 | 15% |
Psychology | 2 | 6% |
Other | 0 | 0% |
Unknown | 2 | 6% |