庞达, 杨艳梅, 张国强, 马玉彦, 唐雅莉, 龚建平. 血清SELDI蛋白质指纹图谱在乳腺癌腋淋巴结转移中的应用研究[J]. 中国肿瘤临床, 2008, 35(17): 1010-1014.
引用本文: 庞达, 杨艳梅, 张国强, 马玉彦, 唐雅莉, 龚建平. 血清SELDI蛋白质指纹图谱在乳腺癌腋淋巴结转移中的应用研究[J]. 中国肿瘤临床, 2008, 35(17): 1010-1014.
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PANG Da, YANG Yanmei, ZHANG Guoqiang, MA Yuyan, TANG Yali, GONG Jianping. The Applied Research of Serum Protein Fingerprints in the Prediction of Axillary[J]. CHINESE JOURNAL OF CLINICAL ONCOLOGY, 2008, 35(17): 1010-1014.
Citation: PANG Da, YANG Yanmei, ZHANG Guoqiang, MA Yuyan, TANG Yali, GONG Jianping. The Applied Research of Serum Protein Fingerprints in the Prediction of Axillary[J]. CHINESE JOURNAL OF CLINICAL ONCOLOGY, 2008, 35(17): 1010-1014.
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血清SELDI蛋白质指纹图谱在乳腺癌腋淋巴结转移中的应用研究

The Applied Research of Serum Protein Fingerprints in the Prediction of Axillary

    摘要
  • 摘要: 目的 :应用SELDI技术和生物信息学方法从血清中筛选乳腺癌蛋白质标志物并构建检测模型,为预测腋淋巴结(axillary lymph nodes,ALN)转移等提供可能的简便易行的方法。 方法 :应用SELDI-TOF-MS作为蛋白质组学摘要 目的 :应用SELDI技术和生物信息学方法从血清中筛选乳腺癌蛋白质标志物并构建检测模型,为预测腋研究平台,采用CM10芯片,对乳腺癌的血清进行了检测,探讨了乳腺癌患者血清蛋白质指纹图谱与是否发生ALN转移的关系,并结合生物信息学方法建立了相应的检测模型。 结果 :通过对ALN有(无)转移的乳腺癌患者血清蛋白指纹图谱数据的比较,找到了11个差异蛋白质峰(P<0.05),M/Z为M2164.16,M3269.90和M3272.31的3个蛋白质峰被选择用于构建分类决策树模型,该模型的交叉验证(测试组)总准确率为81.8%,ALN有转移的乳腺癌患者检出率为83.3%,ALN无转移的检出率为80%。 结论 :构建的分类决策树模型能达到区分ALN是否有转移的最佳效果,SELDI技术在确定乳腺癌患者是否发生腋淋巴结转移方面有一定的意义。

     

    Abstract: Objective : To screen serum tumor biomarkers by SELDI-TOF-MS to establish a subset to be used in the prediction of axillary lymph node metastasis of breast cancer and to establish diagnostic models of breast cancer. Methodse : Serum samples from breast cancer patients with or without ALN metastasis were analyzed by SELDI-TOF on a PBSII-C ProteinChip reader. Protein profiles were generated using CM10 protein chips. Protein peak clustering and classification analyses were performed utilizing the Biomarker Wizard and Biomarker Pattern software packages, respectively. Results : The data of breast cancer patients with or without metastasis to ALN were compared and 11 discrepant protein peaks were found (P<0.05). The decision tree model was composed of three protein peaks (M2164.16, M3269.90 and M3272.31). The diagnostic accuracy was 81.8%. Conclusion : The established serum proteomic pattern can best divide breast cancer patients into those with ALN metastasis and those without ALN metastasis. SELDI-TOF-MS can facilitate the prediction of axillary lymph node metastasis.

     

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