Genetic variations in TP53 binding sites are predictors of clinical outcomes in prostate cancer patients
Journal
Archives of Toxicology
Journal Volume
88
Journal Issue
4
Pages
901-911
Date Issued
2014
Author(s)
Abstract
Since the tumor protein p53 (TP53), a transcription factor, plays a crucial role in prostate cancer development and progression, we hypothesized that sequence variants in TP53 binding sites might affect clinical outcomes in patients with prostate cancer. We systematically evaluated 41 single nucleotide polymorphisms (SNPs) within genome-wide predicted TP53 binding sites in a cohort of 1,024 prostate cancer patients. The associations of these SNPs with prostate cancer characteristics and clinical outcomes after radical prostatectomy for localized disease and after androgen-deprivation therapy (ADT) for advanced disease were assessed by Kaplan-Meier analysis and Cox regression model. ARAP2 rs1444377 and TRPS1 rs722740 were associated with advanced stage prostate cancer. FRK rs171866 remained as a significant predictor for disease progression; DAB2 rs268091 and EXOC4 rs1149558 remained as significant predictors for prostate cancer-specific mortality (PCSM); and EXOC4 rs1149558 remained as a significant predictor for all-cause mortality after ADT in multivariate models that included clinicopathologic predictors. In addition, the numbers of protective genotypes at DAB2 rs268091 and EXOC4 rs1149558 showed a cumulative effect on PCSM (P for trend = 0.002). Our results suggested that SNPs within TP53 binding sites might be valuable biomarkers for prostate cancer outcome prediction. ? 2014 Springer-Verlag.
Subjects
Mortality; Prognosis; Prostate cancer; Single nucleotide polymorphism (SNP); TP53; Transcription factor binding sites
SDGs
Other Subjects
antiandrogen; protein p53; protein p53; TP53 protein, human; tumor marker; advanced cancer; aged; androgen deprivation therapy; article; binding site; cancer mortality; cancer surgery; disease course; genetic association; genetic variability; human; Kaplan Meier method; major clinical study; male; outcomes research; prediction; predictor variable; priority journal; proportional hazards model; prostate cancer; prostatectomy; single nucleotide polymorphism; disease free survival; genetic predisposition; genetics; genome-wide association study; metabolism; mortality; odds ratio; phenotype; prospective study; prostatectomy; Prostatic Neoplasms; protection; risk factor; single nucleotide polymorphism; statistical model; treatment outcome; tumor cell line; Androgen Antagonists; Binding Sites; Biomarkers, Tumor; Cell Line, Tumor; Disease Progression; Disease-Free Survival; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Kaplan-Meier Estimate; Logistic Models; Male; Odds Ratio; Phenotype; Polymorphism, Single Nucleotide; Proportional Hazards Models; Prospective Studies; Prostatectomy; Prostatic Neoplasms; Protective Factors; Risk Factors; Treatment Outcome; Tumor Suppressor Protein p53
Publisher
Springer Verlag
Type
journal article