Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer.
Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer.
复制标题
基于聚类的方法开发基因组拷贝数改变特征以预测前列腺癌的转移潜力。
DOI：
10.1155/2012/873570
复制
发表时间：
2012
影响因子：
1.1
通讯作者：
Ostrer,Harry
中科院分区：
文献类型：
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作者：
Pearlman,Alexander;Campbell,Christopher;Brooks,Eric;Genshaft,Alex;Shajahan,Shahin;Ittman,Michael;Bova,GSteven;Melamed,Jonathan;Holcomb,Ilona;Schneider,RobertJ;Ostrer,Harry
对于前列腺癌和许多其他癌症来说，癌症从局部肿瘤到远处转移的转变还不是很清楚，部分原因是缺乏肿瘤样本，特别是来自长期临床随访的癌症患者的转移。为了克服这一局限性，我们开发了一种半监督聚类方法，使用肿瘤基因组DNA拷贝数改变将每个患者分类为推断的转移潜力临床结果组。我们的数据集包括来自5个独立队列的前列腺癌患者的294个原发肿瘤和49个转移瘤。这些改变是基于达尔文的进化选择理论建模的，与这些改变的基因组区域重叠的基因被用来为前列腺癌原发肿瘤制定转移潜力评分。由一些预测基因编码的蛋白质的功能促进细胞凋亡途径的逃逸，在转移中失控。我们使用Cox比例风险模型评估了诊断时可用的其他临床预测因子的转移潜力评分，并显示我们提出的评分是无转移生存的唯一重要预测因子。转移基因标记和相关评分可以直接应用于前列腺癌阳性患者活检的拷贝数改变谱。
The transition of cancer from a localized tumor to a distant metastasis is not well understood for prostate and many other cancers, partly, because of the scarcity of tumor samples, especially metastases, from cancer patients with long‐term clinical follow‐up. To overcome this limitation, we developed a semi‐supervised clustering method using the tumor genomic DNA copy number alterations to classify each patient into inferred clinical outcome groups of metastatic potential. Our data set was comprised of 294 primary tumors and 49 metastases from 5 independent cohorts of prostate cancer patients. The alterations were modeled based on Darwin’s evolutionary selection theory and the genes overlapping these altered genomic regions were used to develop a metastatic potential score for a prostate cancer primary tumor. The function of the proteins encoded by some of the predictor genes promote escape from anoikis, a pathway of apoptosis, deregulated in metastases. We evaluated the metastatic potential score with other clinical predictors available at diagnosis using a Cox proportional hazards model and show our proposed score was the only significant predictor of metastasis free survival. The metastasis gene signature and associated score could be applied directly to copy number alteration profiles from patient biopsies positive for prostate cancer.