• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Molecular Biochemistry >In silico design and performance of peptide microarrays for breast cancer tumour-auto-antibody testing
【24h】

In silico design and performance of peptide microarrays for breast cancer tumour-auto-antibody testing

机译：用于乳腺癌肿瘤自动抗体测试的肽芯片的计算机设计和性能

获取原文
       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The simplicity and potential of minimally invasive testing using sera from patients makes auto-antibody based biomarkers a very promising tool for use in cancer diagnostics. Protein microarrays have been used for the identification of such auto-antibody signatures. Because high throughput protein expression and purification is laborious, synthetic peptides might be a good alternative for microarray generation and multiplexed analyses. In this study, we designed 1185 antigenic peptides, deduced from proteins expressed by 642 cDNA expression clones found to be sero-reactive in both breast tumour patients and controls. The sero-reactive proteins and the corresponding peptides were used for the production of protein and peptide microarrays. Serum samples from females with benign and malignant breast tumours and healthy control sera (n=16 per group) were then analysed. Correct classification of the serum samples on peptide microarrays were 78% for discrimination of ‘malignant versus healthy controls’, 72% for ‘benign versus malignant’ and 94% for ‘benign versus controls’. On protein arrays, correct classification for these contrasts was 69%, 59% and 59%, respectively. The over-representation analysis of the classifiers derived from class prediction showed enrichment of genes associated with ribosomes, spliceosomes, endocytosis and the pentose phosphate pathway. Sequence analyses of the peptides with the highest sero-reactivity demonstrated enrichment of the zinc-finger domain. Peptides’ sero-reactivities were found negatively correlated with hydrophobicity and positively correlated with positive charge, high inter-residue protein contact energies and a secondary structure propensity bias. This study hints at the possibility of using in silico designed antigenic peptide microarrays as an alternative to protein microarrays for the improvement of tumour auto-antibody based diagnostics.
机译：使用患者血清进行微创检测的简单性和潜力使基于自身抗体的生物标记物成为用于癌症诊断的非常有前途的工具。蛋白微阵列已用于鉴定这种自身抗体的特征。由于高通量的蛋白质表达和纯化非常费力，因此合成肽可能是微阵列生成和多重分析的理想选择。在这项研究中，我们设计了1185个抗原肽，由642个cDNA表达克隆表达的蛋白质推导，这些克隆在乳腺肿瘤患者和对照中均具有血清反应性。血清反应蛋白和相应的肽用于生产蛋白和肽微阵列。然后分析了患有良性和恶性乳腺肿瘤以及健康对照血清（每组n = 16）的女性的血清样本。多肽微阵列上血清样品的正确分类是“良性与恶性对照”的78％，“良性与恶性对照”的72％和“良性与对照”的94％。在蛋白质阵列上，这些对比的正确分类分别为69％，59％和59％。对来自类别预测的分类器的过度陈述分析表明，与核糖体，剪接体，内吞作用和磷酸戊糖途径相关的基因富集。具有最高血清反应性的肽的序列分析表明富集了锌指结构域。多肽的血清反应性与疏水性呈负相关，与正电荷，高残基间蛋白质接触能和二级结构倾向性呈正相关。这项研究提示使用计算机设计的抗原肽微阵列作为蛋白质微阵列的替代品以改善基于肿瘤自身抗体的诊断的可能性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号