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利用磁珠鉴定 FGA 肽作为鼻咽癌相关生物标志物。

Identifying FGA peptides as nasopharyngeal carcinoma-associated biomarkers by magnetic beads.

机构信息

Department of Radiation Oncology, Cancer Center, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China.

出版信息

J Cell Biochem. 2012 Jul;113(7):2268-78. doi: 10.1002/jcb.24097.

DOI:10.1002/jcb.24097
PMID:22334501
Abstract

Early diagnosis and treatment is known to improve prognosis for nasopharyngeal carcinoma (NPC). The study determined the specific peptide profiles by comparing the serum differences between NPC patients and healthy controls, and provided the basis for the diagnostic model and identification of specific biomarkers of NPC. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) can be used to detect the molecular mass of peptides. Mass spectra of peptides were generated after extracting and purification of 40 NPC samples in the training set, 21 in the single center validation set and 99 in the multicenter validation set using weak cationic-exchanger magnetic beads. The spectra were analyzed statistically using FlexAnalysis™ and ClinProt™ bioinformatics software. The four most significant peaks were selected out to train a genetic algorithm model to diagnose NPC. The diagnostic sensitivity and specificity were 100% and 100% in the training set, 90.5% and 88.9% in the single center validation set, 91.9% and 83.3% in the multicenter validation set, and the false positive rate (FPR) and false negative rate (FNR) were obviously lower in the NPC group (FPR, 16.7%; FNR, 8.1%) than in the other cancer group (FPR, 39%; FNR, 61%), respectively. So, the diagnostic model including four peptides can be suitable for NPC but not for other cancers. FGA peptide fragments identified may serve as tumor-associated biomarkers for NPC.

摘要

早期诊断和治疗被认为可以改善鼻咽癌(NPC)的预后。本研究通过比较 NPC 患者和健康对照者的血清差异,确定了特定的肽谱,为 NPC 的诊断模型和鉴定提供了基础,并鉴定了 NPC 的特异性生物标志物。基质辅助激光解吸电离飞行时间质谱(MALDI-TOF-MS)可用于检测肽的分子质量。使用弱阳离子交换磁珠从 40 例训练集中的 NPC 样本、21 例单中心验证集中的 NPC 样本和 99 例多中心验证集中的 NPC 样本中提取和纯化后,生成肽的质谱。使用 FlexAnalysis™和 ClinProt™生物信息学软件对其进行统计分析。从四个最显著的峰中选择出来,以训练用于诊断 NPC 的遗传算法模型。在训练集中,诊断的敏感性和特异性均为 100%和 100%,在单中心验证集中,敏感性和特异性分别为 90.5%和 88.9%,在多中心验证集中,敏感性和特异性分别为 91.9%和 83.3%,而 NPC 组的假阳性率(FPR)和假阴性率(FNR)明显低于其他癌症组(FPR,16.7%;FNR,8.1%)(FPR,39%;FNR,61%)。因此,包含四个肽的诊断模型可适用于 NPC,但不适用于其他癌症。鉴定的 FGA 肽片段可能作为 NPC 的肿瘤相关生物标志物。

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