The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer.
The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer.
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DOI：
10.1186/1471-2407-6-159
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发表时间：
2006-06-16
期刊：
影响因子：
3.8
通讯作者：
Worzel WP
中科院分区：
文献类型：
--
作者：
Mitra AP;Almal AA;George B;Fry DW;Lenehan PF;Pagliarulo V;Cote RJ;Datar RH;Worzel WP
先前的膀胱癌研究表明淋巴结受累是预后和生存的独立指标。本研究旨在建立一种客观的方法来检测原发性尿路上皮癌组织的淋巴结转移。本研究包括60例不同分期膀胱肿瘤患者的原发膀胱肿瘤组织和5例正常尿路上皮对照组织。整个队列被分为由节点阳性和节点阴性受试者组成的训练集和验证集。使用标准化竞争性RT-PCR对70个基因进行定量表达谱分析，并通过称为遗传编程的迭代机器学习过程运行训练集样本的表达值，该过程采用n倍交叉验证技术来生成有限复杂性的分类器规则。然后将这些数据用于投票算法，将验证集样本分类为与淋巴结转移相关或不相关的样本。与病理淋巴结状态相比，使用70个基因生成的分类器规则在验证集上的准确率为81%。这些规则显示，ICAM1、MAP2K6和KDR具有强烈的偏好，导致基因表达基序累积表明，在节点阳性病例中，ICAM1>MAP2K6>KDR模式。此外，这些基序显示CDK8在淋巴结阳性肿瘤中相对于ICAM1表达较低，而ANXA5本身相对较高。仅使用ICAM1、MAP2K6和KDR生成的规则具有相当的鲁棒性，当在验证集上单独使用时，单个代表性规则的准确率为90%，这表明这些基因在淋巴结转移中起着至关重要的作用。我们的研究展示了使用来自原发性膀胱肿瘤组织的标准化定量基因表达值作为遗传编程系统的输入，以生成用于确定节点状态的分类器规则。我们的方法还表明，ICAM1、MAP2K6、KDR、CDK8和ANXA5以独特的数学组合参与了节点阳性的进程。需要进一步的研究来确定更多的类别特异性特征，并确认这些基因在膀胱癌淋巴结转移进化中的作用。
Previous studies on bladder cancer have shown nodal involvement to be an independent indicator of prognosis and survival. This study aimed at developing an objective method for detection of nodal metastasis from molecular profiles of primary urothelial carcinoma tissues. The study included primary bladder tumor tissues from 60 patients across different stages and 5 control tissues of normal urothelium. The entire cohort was divided into training and validation sets comprised of node positive and node negative subjects. Quantitative expression profiling was performed for a panel of 70 genes using standardized competitive RT-PCR and the expression values of the training set samples were run through an iterative machine learning process called genetic programming that employed an N-fold cross validation technique to generate classifier rules of limited complexity. These were then used in a voting algorithm to classify the validation set samples into those associated with or without nodal metastasis. The generated classifier rules using 70 genes demonstrated 81% accuracy on the validation set when compared to the pathological nodal status. The rules showed a strong predilection for ICAM1, MAP2K6 and KDR resulting in gene expression motifs that cumulatively suggested a pattern ICAM1>MAP2K6>KDR for node positive cases. Additionally, the motifs showed CDK8 to be lower relative to ICAM1, and ANXA5 to be relatively high by itself in node positive tumors. Rules generated using only ICAM1, MAP2K6 and KDR were comparably robust, with a single representative rule producing an accuracy of 90% when used by itself on the validation set, suggesting a crucial role for these genes in nodal metastasis. Our study demonstrates the use of standardized quantitative gene expression values from primary bladder tumor tissues as inputs in a genetic programming system to generate classifier rules for determining the nodal status. Our method also suggests the involvement of ICAM1, MAP2K6, KDR, CDK8 and ANXA5 in unique mathematical combinations in the progression towards nodal positivity. Further studies are needed to identify more class-specific signatures and confirm the role of these genes in the evolution of nodal metastasis in bladder cancer.
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影响因子：
2.1
作者：
Ferrer, FA;Miller, LJ;Kreutzer, DL
通讯作者：
Kreutzer, DL
DOI：
10.1016/s0006-291x(02)00243-7
发表时间：
2002-04-26
影响因子：
3.1
作者：
Crawford, EL;Warner, KA;Willey, JC
通讯作者：
Willey, JC
影响因子：
6.2
作者：
Esteva, FJ;Sahin, AA;Bacus, SS
通讯作者：
Bacus, SS
DOI：
10.1073/pnas.132598099
发表时间：
2002-06-11
影响因子：
11.1
作者：
Hawkins, TE;Das, D;Moss, SE
通讯作者：
Moss, SE
DOI：
10.1016/j.bbrc.2004.07.124
发表时间：
2004-10-01
影响因子：
3.1
作者：
Hayes, MJ;Moss, SE
通讯作者：
Moss, SE