Department of Laboratory Medicine, Medical Faculty, University of Modena and Reggio Emilia, Via del Pozzo 71, 41100, Modena, Italy.
Proteome Sci. 2011 Sep 19;9(1):55. doi: 10.1186/1477-5956-9-55.
Non Small Cell Lung Cancer (NSCLC) is the major cause of cancer related-death. Many patients receive diagnosis at advanced stage leading to a poor prognosis. At present, no satisfactory screening tests are available in clinical practice and the discovery and validation of new biomarkers is mandatory. Surface Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-ToF-MS) is a recent high-throughput technique used to detect new tumour markers. In this study we performed SELDI-ToF-MS analysis on serum samples treated with the ProteoMiner™ kit, a combinatorial library of hexapeptide ligands coupled to beads, to reduce the wide dynamic range of protein concentration in the sample. Serum from 44 NSCLC patients and 19 healthy controls were analyzed with IMAC30-Cu and H50 ProteinChip Arrays.
Comparing SELDI-ToF-MS protein profiles of NSCLC patients and healthy controls, 28 protein peaks were found significantly different (p < 0.05), and were used as predictors to build decision classification trees. This statistical analysis selected 10 protein peaks in the low-mass range (2-24 kDa) and 6 in the high-mass range (40-80 kDa). The classification models for the low-mass range had a sensitivity and specificity of 70.45% (31/44) and 68.42% (13/19) for IMAC30-Cu, and 72.73% (32/44) and 73.68% (14/19) for H50 ProteinChip Arrays.
These preliminary results suggest that SELDI-ToF-MS protein profiling of serum samples pretreated with ProteoMiner™ can improve the discovery of protein peaks differentially expressed between NSCLC patients and healthy subjects, useful to build classification algorithms with high sensitivity and specificity. However, identification of the significantly different protein peaks needs further study in order to provide a better understanding of the biological nature of these potential biomarkers and their role in the underlying disease process.
非小细胞肺癌（NSCLC）是癌症相关死亡的主要原因。许多患者在晚期被诊断出，预后较差。目前，临床实践中没有令人满意的筛查试验，因此必须发现和验证新的生物标志物。表面增强激光解吸/电离飞行时间质谱（SELDI-ToF-MS）是一种最近的高通量技术，用于检测新的肿瘤标志物。在这项研究中，我们使用 ProteoMiner™试剂盒（一种与珠子偶联的六肽配体组合文库）对血清样本进行 SELDI-ToF-MS 分析，以降低样本中蛋白质浓度的宽动态范围。对 44 例 NSCLC 患者和 19 例健康对照者的血清进行了 IMAC30-Cu 和 H50 ProteinChip 阵列分析。
比较 NSCLC 患者和健康对照组的 SELDI-ToF-MS 蛋白图谱，发现 28 个蛋白峰有显著差异（p<0.05），并作为预测因子构建决策分类树。这项统计分析选择了低质量范围（2-24 kDa）的 10 个蛋白峰和高质量范围（40-80 kDa）的 6 个蛋白峰。低质量范围的分类模型对 IMAC30-Cu 的敏感性和特异性分别为 70.45%（31/44）和 68.42%（13/19），对 H50 ProteinChip 阵列的敏感性和特异性分别为 72.73%（32/44）和 73.68%（14/19）。
这些初步结果表明，用 ProteoMiner™预处理血清样本的 SELDI-ToF-MS 蛋白谱分析可以提高 NSCLC 患者与健康受试者之间差异表达蛋白峰的发现，有助于构建具有高敏感性和特异性的分类算法。然而，对显著差异的蛋白峰的鉴定需要进一步研究，以便更好地了解这些潜在生物标志物的生物学特性及其在潜在疾病过程中的作用。
