Veltri R W, Miller M C, An G
UroCor, Inc., Research and Development, Oklahoma City, Oklahoma 73104, USA.
Urology. 2001 Apr;57(4 Suppl 1):164-70. doi: 10.1016/s0090-4295(00)00965-1.
Standardized processes should be used in the identification and development of intermediate endpoint biomarkers (IEB) for the prediction of patient-specific disease outcomes. Using our own experiences, we outline some of our standardized processes. Using computer-assisted image analysis, we developed a new biomarker of genetic instability, termed quantitative nuclear grade (QNG). The QNG biomarker is derived using nuclear images analyzed from the tumor areas of Feulgen-stained 5-microm biopsy or radical prostatectomy tissue sections. From the variances of 41 to 60 different nuclear size, shape, and chromatin organization features, a QNG solution is computed using either logistic regression or artificial neural networks. QNG can then be used as an input for models that solve for a patient-specific probability to accurately predict disease outcomes. Preoperatively, QNG predicted both the pathologic stage and progression of prostate cancer using biopsies (P <0.0001). Postoperatively, QNG proved extremely valuable in the prediction of biochemical progression using radical prostatectomy specimens with more than 10 years of follow-up (P <0.0001). We also demonstrate the identification of novel, differentially expressed, prostate cancer genes using RNA fingerprinting methods and the clinical utility of testing for these genes in both blood and tissue samples. Also illustrated is the improvement of serum biomarker performance by combining molecular forms of PSA with new biomarkers. In conclusion, the development of new IEBs requires planning based upon an understanding of the molecular pathogenesis of disease. IEB selection and clinical evaluation should employ standardized methods of testing and validation, followed by publication. QNG is 1 example of a new, highly predictive, IEB for prostate cancer that has been developed using these processes.
在识别和开发用于预测患者特异性疾病结局的中间终点生物标志物(IEB)时,应使用标准化流程。根据我们自己的经验,我们概述了一些标准化流程。通过计算机辅助图像分析,我们开发了一种新的遗传不稳定性生物标志物,称为定量核分级(QNG)。QNG生物标志物是通过对Feulgen染色的5微米活检或根治性前列腺切除术组织切片的肿瘤区域分析的核图像得出的。从41到60种不同的核大小、形状和染色质组织特征的差异中,使用逻辑回归或人工神经网络计算出QNG解决方案。然后,QNG可以用作模型的输入,该模型求解患者特异性概率以准确预测疾病结局。术前,QNG使用活检预测前列腺癌的病理分期和进展(P<0.0001)。术后,QNG在使用超过10年随访的根治性前列腺切除术标本预测生化进展方面被证明具有极高的价值(P<0.0001)。我们还展示了使用RNA指纹识别方法鉴定新的、差异表达的前列腺癌基因,以及在血液和组织样本中检测这些基因的临床效用。还说明了通过将PSA的分子形式与新的生物标志物相结合来提高血清生物标志物性能。总之,新IEB的开发需要基于对疾病分子发病机制的理解进行规划。IEB的选择和临床评估应采用标准化的测试和验证方法,随后进行发表。QNG是使用这些流程开发的一种新的、高度预测性的前列腺癌IEB的例子。