Converting a microarray signature into a diagnostic test: a trial of custom 74 gene array for clarification and prediction the prognosis of gastric cancer.
Converting a microarray signature into a diagnostic test: a trial of custom 74 gene array for clarification and prediction the prognosis of gastric cancer.
复制标题
将微阵列特征转化为诊断测试：定制 74 基因阵列的试验，用于阐明和预测胃癌的预后。
DOI：
10.1371/journal.pone.0081561
复制
发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Si JM
中科院分区：
文献类型：
--
作者：
Yin Y;Zhuo W;Zhao Y;Chen S;Li J;Wang L;Zhou T;Si JM
胃癌（GC）与高死亡率和晚期预后不良相关。此外，没有有效的方法用于在早期诊断胃癌或预测结果以选择患者特异性治疗方案。因此，研究新的胃癌诊断方法具有重要意义。 为了便于其在诊断环境中的使用，将具有诊断和预后信息的74个基因的组翻译成定制的微阵列，该微阵列含有适合于高通量处理的1，042个探针的缩减组。在这份报告中，我们首次证明了定制的微型阵列可以用作胃癌的可靠诊断工具。AUC值为0.565（95%CI 0.305-0.825），表明试验效果良好，根据ROC曲线计算的诊断灵敏度和特异性分别为70%和80%。 数据清楚地证明了小型定制微阵列的可重复性和稳健性。该阵列是一个很好的工具，用于分类和预测疾病的结果在胃癌患者。
Gastric cancer (GC) is associated with high mortality rates and an unfavorable prognosis at advanced stages. In addition, there are no effective methods for diagnosing gastric cancer at an early stage or for predicting the outcome for the purpose of selecting patient-specific treatment options. Therefore, it is important to investigate new methods for GC diagnosis. To facilitate its use in a diagnostic setting, a group of 74 genes with diagnostic and prognostic information was translated into a customized microarray containing a reduced set of 1,042 probes suitable for high throughput processing. In this report, we demonstrate for the first time that the custom mini-array can be used as a reliable diagnostic tool in gastric cancer. With an AUC value of 0.565 (95% CI 0.305-0.825) indicating a perfect test, the sensitivity and specificity of diagnosis from the ROC curve were calculated to be 70% and 80%, respectively. The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is an excellent tool for classifying and predicting the outcome of disease in gastric cancer patients.
登录
查看更多内容
影响因子：
2.9
作者：
Kinoshita, Jun;Fushida, Sachio;Ohta, Tetsuo
通讯作者：
Ohta, Tetsuo
影响因子：
64.8
作者：
Matson, Clinton K.;Murphy, Mark W.;Sarver, Aaron L.;Griswold, Michael D.;Bardwell, Vivian J.;Zarkower, David
通讯作者：
Zarkower, David
影响因子：
2.1
作者：
Yang, Dongyun;Hendifar, Andrew;Lenz, Heinz-Josef
通讯作者：
Lenz, Heinz-Josef
影响因子：
29.4
作者：
Lee HJ;Nam KT;Park HS;Kim MA;Lafleur BJ;Aburatani H;Yang HK;Kim WH;Goldenring JR
通讯作者：
Goldenring JR
影响因子：
254.7
作者：
Parkin, DM;Bray, F;Pisani, P
通讯作者：
Pisani, P