Ability to predict metastasis based on pathology findings and alterations in nuclear structure of normal-appearing and cancer peripheral zone epithelium in the prostate
Ability to predict metastasis based on pathology findings and alterations in nuclear structure of normal-appearing and cancer peripheral zone epithelium in the prostate
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DOI：
10.1158/1078-0432.ccr-03-0635
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发表时间：
2004-05-15
影响因子：
11.5
通讯作者：
Partin, AW
中科院分区：
文献类型：
--
作者：
Veltri, RW;Khan, MA;Partin, AW
目的：前列腺的恶性转化产生腺体结构（Gleason分级）和核结构的显著改变，这些改变提供了有价值的预后信息。邻近癌症的正常细胞核（NN）也可能在恶性肿瘤中改变功能。我们使用定量图像细胞术研究了邻近外周带（PZ）前列腺癌（PCa）的NN以及PZ癌细胞核（CaN）。核结构的信息与常规病理结果相结合，预测转移性前列腺癌的进展和/或death.Experimental Design：组织微阵列的正常外观和癌症领域的准备从182病理学家选择的石蜡块。使用Auto-Cyte病理学工作站从组织微阵列捕获Feulgen染色的CaN和NN。基于NN和CaN确定的核形态测量描述符，使用多变量逻辑回归计算定量核等级（QNG）解决方案。多变量logistic回归和Kaplan-Meier图也被用来预测风险的远处转移和/或PCa特异性死亡使用QNG解决方案和常规pathology.Results：病理模型产生了72.5%的受试者操作特征曲线下的面积。QNG-NN和QNG-CaN解决方案分别获得了81.6%和79.9%的受试者操作特征曲线下的面积，但使用了不同的核形态测量描述符。Kaplan-Meier曲线的病理变量，QNG-NN和QNG-CaN的解决方案，结合病理学定义三个统计学上显著不同的风险组的远处转移和/或死亡（P < 0.0001）。结论：在癌或正常外观核周边区癌区域附近的变化可以预测PCa的进展和/或死亡。QNG-NN和QNG-CA解决方案可以与病理学变量相结合，以提高对远处转移的预测。
Purpose: Malignant transformation in the prostate produces significant alterations in glandular architecture (Gleason grade) and nuclear structure that provide valuable prognostic information. Normal-appearing nuclei (NN) adjacent to cancer may also have altered functions in response to malignancy. We studied NN adjacent to peripheral zone (PZ) prostate cancer (PCa), as well as the PZ cancer nuclei (CaN) using quantitative image cytometry. The nuclear structure information was combined with routine pathological findings to predict metastatic PCa progression and/or death.Experimental Design: Tissue microarrays of normal-appearing and cancer areas were prepared from 182 pathologist-selected paraffin blocks. Feulgen-stained CaN and NN were captured from the tissue microarrays; using the Auto-Cyte Pathology Workstation. Multivariate logistic regression was used to calculate quantitative nuclear grade (QNG) solutions based on nuclear morphometric descriptors determined from NN and CaN. Multivariate logistic regression and Kaplan-Meier plots were also used to predict risk for distant metastasis and/or PCa-specific death using QNG solutions and routine pathology.Results: The pathology model yielded an area under the receiver operator characteristic curve of 72.5%. The QNG-NN and QNG-CaN solutions yielded an area under the receiver operator characteristic curve of 81.6 and 79.9%, respectively, but used different sets of nuclear morphometric descriptors. Kaplan-Meier plots for the pathology variables, the QNG-NN and QNG-CaN solutions, were combined with pathology to defined three statistically significantly distinct risk groups for distant metastasis and/or death (P < 0.0001).Conclusions: Alterations in cancer or normal-appearing nuclei adjacent to peripheral zone cancer areas can predict PCa progression and/or death. The QNG-NN and QNG-CA solutions could be combined with pathology variables to improve the prediction of distant metastasis.