| Title |
Molecular targeted therapies in metastatic melanoma
|
|---|---|
| Published in |
Pharmacogenomics and Personalized Medicine, June 2013
|
| DOI | 10.2147/pgpm.s44800 |
| Pubmed ID | |
| Authors |
Rima Chakraborty, Carilyn N Wieland, Nneka I Comfere |
| Abstract |
The advent of personalized medicine has ushered in a new era for cancer therapy with a significant impact on the management of advanced melanoma. Molecular targeted therapies have shown promise in the management of various malignancies, including melanoma, with lower toxicity profiles and better overall survival as compared with conventional therapy. The discovery of BRAF mutations in melanoma led to the development of BRAF inhibitors for the treatment of advanced melanoma. However, growing concerns over drug resistance to molecular targeted therapies including BRAF inhibitors, have spurred efforts to elucidate additional molecular targets for the treatment of advanced melanoma. In this review, we discuss the known molecular aberrations in melanoma, current and novel targeted approaches in its treatment, and drug resistance patterns. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 2% |
| Unknown | 51 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 25% |
| Researcher | 8 | 15% |
| Student > Master | 8 | 15% |
| Student > Bachelor | 7 | 13% |
| Other | 4 | 8% |
| Other | 7 | 13% |
| Unknown | 5 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 31% |
| Medicine and Dentistry | 11 | 21% |
| Biochemistry, Genetics and Molecular Biology | 9 | 17% |
| Unspecified | 2 | 4% |
| Economics, Econometrics and Finance | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 8 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 July 2013.
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#20,964,263
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Outputs from Pharmacogenomics and Personalized Medicine
#1
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#157,771
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Outputs of similar age from Pharmacogenomics and Personalized Medicine
#1
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