Program in Cancer Biology and Genetics, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
Eur Urol. 2012 Mar;61(3):471-7. doi: 10.1016/j.eururo.2011.10.047. Epub 2011 Nov 7.
Although case-control studies have identified numerous single nucleotide polymorphisms (SNPs) associated with prostate cancer, the clinical role of these SNPs remains unclear.
Evaluate previously identified SNPs for association with prostate cancer and accuracy in predicting prostate cancer in a large prospective population-based cohort of unscreened men.
DESIGN, SETTING, AND PARTICIPANTS: This study used a nested case-control design based on the Malmö Diet and Cancer cohort with 943 men diagnosed with prostate cancer and 2829 matched controls. Blood samples were collected between 1991 and 1996, and follow-up lasted through 2005.
We genotyped 50 SNPs, analyzed prostate-specific antigen (PSA) in blood from baseline, and tested for association with prostate cancer using the Cochran-Mantel-Haenszel test. We further developed a predictive model using SNPs nominally significant in univariate analysis and determined its accuracy to predict prostate cancer.
Eighteen SNPs at 10 independent loci were associated with prostate cancer. Four independent SNPs at four independent loci remained significant after multiple test correction (p<0.001). Seven SNPs at five independent loci were associated with advanced prostate cancer defined as clinical stage≥T3 or evidence of metastasis at diagnosis. Four independent SNPs were associated with advanced or aggressive cancer defined as stage≥T3, metastasis, Gleason score≥8, or World Health Organization grade 3 at diagnosis. Prostate cancer risk prediction with SNPs alone was less accurate than with PSA at baseline (area under the curve of 0.57 vs 0.79), with no benefit from combining SNPs with PSA. This study is limited by our reliance on clinical diagnosis of prostate cancer; there are likely undiagnosed cases among our control group.
Only a few previously reported SNPs were associated with prostate cancer risk in the large prospective Diet and Cancer cohort in Malmö, Sweden. SNPs were less useful in predicting prostate cancer risk than PSA at baseline.
尽管病例对照研究已经确定了许多与前列腺癌相关的单核苷酸多态性（SNP），但这些 SNP 的临床作用仍不清楚。
在一个大型、前瞻性、基于人群的未筛查男性队列中，评估先前确定的与前列腺癌相关的 SNP 以及预测前列腺癌的准确性。
设计、地点和参与者：本研究采用基于马尔默饮食与癌症队列的巢式病例对照设计，共纳入 943 例前列腺癌患者和 2829 名匹配对照。血液样本采集于 1991 年至 1996 年之间，随访时间截至 2005 年。
我们对 50 个 SNP 进行了基因分型，分析了基线时血液中的前列腺特异性抗原（PSA），并使用 Cochran-Mantel-Haenszel 检验检测与前列腺癌的相关性。我们进一步使用单变量分析中名义显著的 SNP 构建了预测模型，并确定了其预测前列腺癌的准确性。
在 10 个独立位点的 18 个 SNP 与前列腺癌相关。经过多重检验校正后，4 个独立的 SNP 在 4 个独立的位点仍然显著（p<0.001）。在诊断时定义为临床分期≥T3 或有转移证据的 7 个 SNP 与晚期前列腺癌相关。在诊断时定义为分期≥T3、转移、Gleason 评分≥8 或世界卫生组织分级 3 的 4 个独立 SNP 与晚期或侵袭性癌症相关。仅使用 SNP 进行前列腺癌风险预测的准确性低于基线时的 PSA（曲线下面积为 0.57 对 0.79），并且将 SNP 与 PSA 结合使用没有获益。本研究的局限性在于我们依赖于前列腺癌的临床诊断；我们的对照组中可能存在未诊断的病例。
在瑞典马尔默的大型前瞻性饮食与癌症队列中，只有少数先前报道的 SNP 与前列腺癌风险相关。SNP 在预测前列腺癌风险方面的作用不如基线时的 PSA。
