Department of Pathology and Laboratory Medicine, University of Calgary, Cumming School of Medicine, Calgary, AB, Canada.
Calgary Laboratory Services, Calgary, AB, Canada.
J Cancer Res Clin Oncol. 2018 May;144(5):883-891. doi: 10.1007/s00432-018-2615-7. Epub 2018 Mar 6.
To validate a previously characterized 10-gene signature in prostate cancer with implication to distinguish aggressive and indolent disease within low and intermediate patients' risk groups.
A case-control study design used to select 545 patients from the Mayo clinic tumor registry who underwent radical prostatectomy. A training set from this cohort (n = 359) was used to build a 10-gene model, based on high-dimensional discriminant analysis (HDDA10) to predict several endpoints of clinical patients' outcome. An independent set (n = 219) from the same institution was used as validation set.
HDDA10 showed significant performance for predicting metastasis (Mets) (AUC 0.68, p = 6.4E - 6) and biochemical recurrence (BCR) (AUC = 0.65, p = 0.003) in the validation set outperforming Gleason grade grouping (GG) for BCR (AUC 0.57, p = 0.03) and with comparable performance for Mets endpoint (GG AUC 0.66, p = 8.1E - 5). HDDA10 prognostic significance was superior to any clinical-pathological parameter within GG2 + 3 (GS7) patients achieving an AUC of 0.74 (p = 0.0037) for BCR compared to Gleason pattern 4 (AUC 0.64) (p = 0.015) and AUC for Mets of 0.68 versus AUC of 0.65 for Gleason pattern 4 (p = 0.01). HDDA10 remained significant for both BCR and Mets in multivariate analysis, suggesting that it can be used to increase accuracy in stratifying patients eligible for active surveillance.
HDDA10 is of added value to GG and other clinical-pathological parameters in predicting BCR and Mets endpoint, especially in the low to intermediate patients' risk groups. HDDA10 prognostic value should be further validated prospectively in stratifying patients specifically in low to intermediate GS (GG1-2), such as active surveillance programs.
验证前列腺癌中具有侵袭性和惰性疾病区分潜力的先前特征的 10 基因特征,该特征涉及低和中危患者风险组内的疾病。
使用病例对照研究设计,从梅奥诊所肿瘤登记处选择 545 名接受根治性前列腺切除术的患者。该队列的训练集(n=359)用于构建基于高维判别分析(HDDA10)的 10 基因模型,以预测临床患者结局的多个终点。来自同一机构的独立集(n=219)被用作验证集。
HDDA10 显示出对预测转移(Mets)(AUC 0.68,p=6.4E-6)和生化复发(BCR)(AUC=0.65,p=0.003)的显著性能,优于 BCR 中的 Gleason 分级分组(GG)(AUC 0.57,p=0.03),并具有相当的 Mets 终点性能(GG AUC 0.66,p=8.1E-5)。HDDA10 的预后意义优于 GG2+3(GS7)患者的任何临床病理参数,在 BCR 方面达到 AUC 0.74(p=0.0037),优于 Gleason 模式 4(AUC 0.64)(p=0.015)和 Mets 的 AUC 0.68 与 Gleason 模式 4 的 AUC 0.65(p=0.01)。HDDA10 在多变量分析中仍然是 BCR 和 Mets 的显著因素,表明它可用于提高对适合主动监测的患者进行分层的准确性。
HDDA10 在预测 BCR 和 Mets 终点方面,除了 GG 和其他临床病理参数外,还具有附加价值,特别是在低至中危患者风险组中。HDDA10 的预后价值应在低至中 GS(GG1-2)患者的分层中进行前瞻性验证,例如在主动监测计划中。