Gene expression profiling for the prediction of lymph node metastasis in patients with cervical cancer
Gene expression profiling for the prediction of lymph node metastasis in patients with cervical cancer
复制标题
DOI：
10.1111/j.1349-7006.2007.00652.x
复制
发表时间：
2008-01-01
期刊：
影响因子：
5.7
通讯作者：
Kim, Byoung-Gie
中科院分区：
文献类型：
--
作者：
Kim, Tae-Joong;Choi, Jung-Joo;Kim, Byoung-Gie
我们研究了原发性宫颈肿瘤组织的基因表达谱是否可用于预测淋巴结（LN）转移，并将其与常规磁共振成像进行了比较。我们获取了43例原发性宫颈癌样本（16例有LN转移，27例无LN转移）用于微阵列分析。通过支持向量机方法并使用10倍交叉验证，从训练集中建立了一个LN转移的预测模型。由156个独特基因的特征得出的“LN预测模型”（P < 0.01）预测准确率为77%。在10个基因中的4个（RBM8A、SDHB、SERPINB13和γ -干扰素）中确定了微阵列所测mRNA表达与半定量逆转录 - 聚合酶链反应之间的相关性。磁共振成像预测LN转移的准确率为69%。这些结果表明，基因表达谱能够可靠地预测宫颈癌的LN转移。
We investigated whether gene expression profiling of primary cervical tumor tissue could be used to predict lymph node (LN) metastasis and compared this with conventional magnetic resonance imaging. We obtained 43 primary cervical cancer samples (16 with LN metastasis and 27 without LN metastasis) for microarray analysis. A prediction model for LN metastasis from the training set was developed by support vector machine methods using a 10-fold cross-validation. The 'LN prediction model' derived from the signature of 156 distinctive genes (P < 0.01) had a prediction accuracy of 77%. Correlation between mRNA expressions measured by microarray and semiquantitative reverse transcription-polymerase chain reaction was ascertained in four (RBM8A, SDHB, SERPINB13, and gamma-interferon) out of 10 genes. Magnetic resonance imaging showed accuracy (69%) for the prediction of LN metastasis. These results suggest that gene expression profiling allows reliable prediction of LN metastasis in cervical cancer.