PDF(Pubmed)
Abstract：
BACKGROUND: Currently, no effective measures are available to predict the curative efficacy of small-cell lung cancer (SCLC) chemotherapy. We expect to develop a method for effectively predicting the SCLC chemotherapy efficacy and prognosis in clinical practice in order to offer more pertinent therapeutic protocols for individual patients.
METHODS: We adopted matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and ClinPro Tools system to detect serum samples from 154 SCLC patients with different curative efficacy of standard chemotherapy and analyze the different peptides/proteins of SCLC patients to discover predictive tumor markers related to chemotherapy efficacy. Ten peptide/protein peaks were significantly different in the two groups.
RESULTS: A genetic algorithm model consisting of four peptides/proteins was developed from the training group to separate patients with different chemotherapy efficacies. Among them, three peptides/proteins (m/z 3323.35, 6649.03 and 6451.08) showed high expression in the disease progression group, whereas the peptide/protein at m/z 4283.18 was highly expressed in the disease response group. The classifier exhibited an accuracy of 91.4% (53/58) in the validation group. The survival analysis showed that the median progression-free survival (PFS) of 30 SCLC patients in disease response group was 9.0 months; in 28 cases in disease progression group, the median PFS was 3.0 months, a statistically significant difference (χ2 = 46.98, P < 0.001). The median overall survival (OS) of the two groups was 13.0 months and 7.0 months, a statistically significant difference (χ2 = 40.64, P < 0.001).
CONCLUSIONS: These peptides/proteins may be used as potential biological markers for prediction of the curative efficacy and prognosis for SCLC patients treated with standard regimen chemotherapy.
METHODS: We adopted matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and ClinPro Tools system to detect serum samples from 154 SCLC patients with different curative efficacy of standard chemotherapy and analyze the different peptides/proteins of SCLC patients to discover predictive tumor markers related to chemotherapy efficacy. Ten peptide/protein peaks were significantly different in the two groups.
RESULTS: A genetic algorithm model consisting of four peptides/proteins was developed from the training group to separate patients with different chemotherapy efficacies. Among them, three peptides/proteins (m/z 3323.35, 6649.03 and 6451.08) showed high expression in the disease progression group, whereas the peptide/protein at m/z 4283.18 was highly expressed in the disease response group. The classifier exhibited an accuracy of 91.4% (53/58) in the validation group. The survival analysis showed that the median progression-free survival (PFS) of 30 SCLC patients in disease response group was 9.0 months; in 28 cases in disease progression group, the median PFS was 3.0 months, a statistically significant difference (χ2 = 46.98, P < 0.001). The median overall survival (OS) of the two groups was 13.0 months and 7.0 months, a statistically significant difference (χ2 = 40.64, P < 0.001).
CONCLUSIONS: These peptides/proteins may be used as potential biological markers for prediction of the curative efficacy and prognosis for SCLC patients treated with standard regimen chemotherapy.
摘要：
背景：目前，目前尚无有效的措施来预测小细胞肺癌(SCLC)化疗的疗效.我们期望开发一种在临床实践中有效预测SCLC化疗疗效和预后的方法，以便为个体患者提供更有针对性的治疗方案。
方法：我们采用基质辅助激光解吸/电离飞行时间质谱（MALDI-TOF-MS）和ClinProTools系统检测154例标准化疗疗效不同的SCLC患者的血清样本，并分析SCLC患者的不同肽/蛋白，以发现与化疗疗效相关的预测肿瘤标志物。10个肽/蛋白峰在两组间有显著差异。
结果：从训练组开发了由四种肽/蛋白质组成的遗传算法模型，以分离具有不同化疗疗效的患者。其中,三种肽/蛋白(m/z3323.35,6649.03和6451.08)在疾病进展组中高表达,而m/z4283.18的肽/蛋白在疾病反应组中高表达。分类器在验证组中表现出91.4%(53/58)的准确度。生存分析显示,疾病缓解组30例SCLC患者的中位无进展生存期(PFS)为9.0个月;疾病进展组28例,中位PFS为3.0个月，差异有统计学意义(χ2=46.98,P<0.001)。两组的中位总生存期(OS)分别为13.0个月和7.0个月,差异有统计学意义(χ2=40.64,P<0.001)。
结论：这些肽/蛋白可作为潜在的生物学标志物，用于预测接受标准方案化疗的SCLC患者的疗效和预后。
方法：我们采用基质辅助激光解吸/电离飞行时间质谱（MALDI-TOF-MS）和ClinProTools系统检测154例标准化疗疗效不同的SCLC患者的血清样本，并分析SCLC患者的不同肽/蛋白，以发现与化疗疗效相关的预测肿瘤标志物。10个肽/蛋白峰在两组间有显著差异。
结果：从训练组开发了由四种肽/蛋白质组成的遗传算法模型，以分离具有不同化疗疗效的患者。其中,三种肽/蛋白(m/z3323.35,6649.03和6451.08)在疾病进展组中高表达,而m/z4283.18的肽/蛋白在疾病反应组中高表达。分类器在验证组中表现出91.4%(53/58)的准确度。生存分析显示,疾病缓解组30例SCLC患者的中位无进展生存期(PFS)为9.0个月;疾病进展组28例,中位PFS为3.0个月，差异有统计学意义(χ2=46.98,P<0.001)。两组的中位总生存期(OS)分别为13.0个月和7.0个月,差异有统计学意义(χ2=40.64,P<0.001)。
结论：这些肽/蛋白可作为潜在的生物学标志物，用于预测接受标准方案化疗的SCLC患者的疗效和预后。
