Jia Angela Y, Sun Yilun, Patel Maitry, Baydoun Atallah, Vince Randy A, Shoag Jonathan E, Brown Jason R, Barata Pedro C, Schipper Matthew J, Dess Robert T, Jackson William C, Roy Soumyajit, Nguyen Paul L, Berlin Alejandro, Mehra Rohit, Schaeffer Edward M, Kashani Rojano, Kishan Amar U, Zaorsky Nicholas G, Morgan Todd M, Spratt Daniel E
Department of Radiation Oncology, University Hospitals Seidman Cancer Center and Case Western Reserve University, Cleveland, OH.
Department of Radiation Oncology, University of Michigan, Ann Arbor, MI.
JCO Precis Oncol. 2025 Jun;9:e2400705. doi: 10.1200/PO-24-00705. Epub 2025 Jun 6.
The 22-gene Decipher genomic classifier (GC) (22-gene GC) is the only gene expression test with National Comprehensive Cancer Network (NCCN) level 1 evidence for localized prostate cancer (PCa) treatment decision making. It is unclear whether other commercial signatures-Genomic Prostate Score (GPS) or Prolaris (cell cycle progression [CCP])-correlate sufficiently to explain differences in evidence strength. This study assesses correlation between these three classifiers on a per-patient basis by performing a cross-comparison of these signatures in a large cohort of patients diagnosed with PCa.
Primary PCa biopsy samples underwent whole-transcriptome gene expression microarray analysis. 22-gene GC scores were calculated using the commercially locked model. To reduce bias, GPS and CCP signatures were retrained for prediction of metastasis to harmonize end points. Pearson correlations and linear regressions (univariable/multivariable) adjusting for age, grade group, prostate-specific antigen (PSA), and T stage were calculated between signatures.
Among 50,881 patients (median age 68 years, median PSA 6.2 ng/mL), 60% were NCCN intermediate-risk. The GPS-derived and CCP-derived models had poor goodness-of-fit to 22-gene GC ( = 0.36 and 0.32, respectively). Multivariable analysis adjusting for clinical factors showed similar results. Given the many variables that may contribute to or correlate with the 22-gene GC, a multivariable analysis was performed to assess how much of the variation could be attributed to known factors. A variance analysis revealed approximately 60% of 22-gene GC variation remained unexplained. GPS-derived and CCP-derived models accounted for 24.7% and 22.7% of variance, respectively, with additional contributions from Gleason score.
Correlation between 22-gene GC and either GPS-derived or CCP-derived signatures is minimal to moderate. These tests are not interchangeable, and their use should be guided by the specific evidence supporting each signature.
22基因Decipher基因组分类器（GC）（22基因GC）是唯一一项具有美国国立综合癌症网络（NCCN）1类证据，可用于局部前列腺癌（PCa）治疗决策的基因表达检测。目前尚不清楚其他商业标志物——基因组前列腺评分（GPS）或Prolaris（细胞周期进程[CCP]）——是否具有足够的相关性来解释证据强度的差异。本研究通过在一大群被诊断为PCa的患者中对这些标志物进行交叉比较，评估这三种分类器在个体患者基础上的相关性。
原发性PCa活检样本进行全转录组基因表达微阵列分析。使用商业锁定模型计算22基因GC评分。为减少偏差，对GPS和CCP标志物进行重新训练以预测转移，从而统一终点。计算各标志物之间的Pearson相关性和针对年龄、分级组、前列腺特异性抗原（PSA）和T分期进行调整的线性回归（单变量/多变量）。
在50881例患者（中位年龄68岁，中位PSA 6.2 ng/mL）中，60%为NCCN中危患者。GPS衍生模型和CCP衍生模型与22基因GC的拟合优度较差（分别为0.36和0.32）。对临床因素进行调整的多变量分析显示了类似结果。鉴于可能影响或与22基因GC相关的变量众多，进行了多变量分析以评估有多少变异可归因于已知因素。方差分析显示，约60%的22基因GC变异仍无法解释。GPS衍生模型和CCP衍生模型分别占方差的24.7%和22.7%，Gleason评分也有额外贡献。
22基因GC与GPS衍生或CCP衍生标志物之间的相关性为轻度至中度。这些检测不可互换，其使用应根据支持每种标志物的具体证据来指导。
