激光解吸电离-飞行时间质谱技术和CM10蛋白质芯片检测术前大肠癌分期的意义

Preoperative molecular staging of colorectal cancers by CM10 ProteinChip and SELDI-TOF-MS analysis

目的筛选新的大肠癌候选肿瘤标志物,建立分期诊断模型,并探讨其临床意义。方法采用表面加强激光解吸电离-飞行时间质谱(SELDI-TOF-MS)技术和CM10蛋白质芯片,检测76例大肠癌患者术前血清蛋白质指纹图谱;运用支持向量机分析判别处理数据、筛选标志物,建立并验证分期模型;应用时间序列分析的方法,将DukesA、B、C、D各期以二维散点图的形式表示。结果诊断模型Ⅰ由6个蛋白质峰组合构建,其质荷比分别为2759．6、2964．7、2048．0、4795．9、4139．8和37 761．6,鉴别局限性大肠癌(Dukes A、B期)和区域性(Dukes C期)大肠癌的总准确率为86．7％。诊断模型Ⅱ由3个蛋白质峰组合构建,其质荷比分别为6885．3、2058．3和8567．8,鉴别局限区域性(Dukes A、B、C期)和系统性(Dukes D期)大肠癌的总准确率为75．0％。诊断模型Ⅲ鉴别Dukes A期和B期大肠癌的总准确率为86．2％;诊断模型Ⅳ鉴别Dukes A期和C期大肠癌的总准确率为84．6％;诊断模型V鉴别Dukes B期和C期大肠癌的总准确率为85．7％;诊断模型Ⅵ鉴别Dukes B期和D期大肠癌的总准确率为80．0％;诊断模型Ⅶ鉴别Dukes C期和D期大肠癌的总准确率为78．7％。通过二维散点图,可以明显看出Dukes A、B、C、D各期之间的区别。结论通过SELDI-TOF- MS技术和CM10蛋白质芯片所筛选的候选肿瘤标志物可以指导大肠癌的综合治疗,所建立的诊断模型可以辅助临床明确大肠癌的术前分期。

Objective To detect the serum proteomic patterns by using SELDI-TOF-MS and CM10 ProteinChip techniques in colorectal cancer （CRC） patients, and to evaluate the significance of the proteomic patterns in colorectal cancer staging. Methods A total of 76 serum samples were obtained from CRC patients at different clinical stages, including Dukes A （n = 10）, Dukes B （n = 19）, Dukes C （n = 16） and Dukes D （n =31 ）. Different stage models were developed and validated by bioinformatics methods of support vector machines, discriminant analysis and time-sequence analysis. Results The model I formed by six proteins of peaks at m/z 2759.6, 2964.7, 2048. 0, 4795.9, 4139.8 and 37 761.6 could do the best as potential biomarkers to distinguish local CRC patients （ Dukes A and Dukes B） from regional CRC patients （ Dukes C ） with an accuracy of 86.7%. The model Ⅱ formed by 3 proteins of peaks at m/z 6885.3, 2058.3 and 8567.8 could do the best to distinguish locoregional CRC patients （ Dukes A, B and C） from systematic CRC patients （Dukes D） with an accuracy of 75.0%. The mode Ⅲ could distinguish Dukes A from Dukes B with an accuracy of 86.2% （25/29）. The model Ⅳ could distinguish Dukes A from Dukes C with an accuracy of 84.6% （22/26）. The model Ⅴ could distinguish Dukes B from Dukes C with an accuracy of 85.7% （ 30/35 ）. The model Ⅵ could distinguish Dukes B from Dukes D with an accuracy of 80.0% （40/50）. The model Ⅶ could distinguish Dukes C from Dukes D with an accuracy of 78.7% （37/47）. Different stage groups could be distinguished by the two-dimensional scattered spots figure obviously. Conclusion Our findings indicate that this method can well be used in preoperative staging of colorectal cancers and the screened tumor markers may serve for guidance of integrating treatment of colorectal cancers.