| Title |
Molecular Markers in Sex Hormone Pathway Genes Associated with the Efficacy of Androgen-Deprivation Therapy for Prostate Cancer
|
|---|---|
| Published in |
PLOS ONE, January 2013
|
| DOI | 10.1371/journal.pone.0054627 |
| Pubmed ID | |
| Authors |
Chia-Cheng Yu, Shu-Pin Huang, Yung-Chin Lee, Chao-Yuan Huang, Chia-Chu Liu, Tzyh-Chyuan Hour, Chun-Nung Huang, Bang-Jau You, Ta-Yuan Chang, Chun-Hsiung Huang, Bo-Ying Bao |
| Abstract |
Although most advanced prostate cancer patients respond to androgen-deprivation therapy (ADT), the efficacy is widely variable. We investigated whether the host genetic variations in sex hormone pathway genes are associated with the efficacy of ADT. A cohort of 645 patients with advanced prostate cancer treated with ADT was genotyped for 18 polymorphisms across 12 key genes involved in androgen and estrogen metabolism. We found that after adjusting for known risk factors in multivariate Cox regression models, AKR1C3 rs12529 and AR-CAG repeat length remained significantly associated with prostate cancer-specific mortality (PCSM) after ADT (P ≤ 0.041). Furthermore, individuals carrying two unfavorable genotypes at these loci presented a 13.7-fold increased risk of PCSM compared with individuals carrying zero (P<0.001). Our results identify two candidate molecular markers in key genes of androgen and estrogen pathways associated with PCSM after ADT, establishing the role of pharmacogenomics in this therapy. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Lithuania | 1 | 7% |
| Portugal | 1 | 7% |
| Unknown | 12 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 21% |
| Student > Bachelor | 3 | 21% |
| Professor > Associate Professor | 2 | 14% |
| Professor | 1 | 7% |
| Other | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 4 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 29% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 14% |
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Environmental Science | 1 | 7% |
| Computer Science | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 4 | 29% |