多配体聚糖结合蛋白在大肠癌组织中的表达及其对预后的影响

目的通过对109例结肠癌患者中多配体聚糖结合蛋白（SDCBP）表达的分析，探讨其临床意义及对患者预后的影响。方
法免疫组织化学法检测109例有10年随访资料，诊断为原发性结直肠癌患者中SDCBP的表达，分析其表达与结直肠癌患者各
临床因素之间的关系，生存分析采用Kaplan-Meier和Cox回归分析法。结果SDCBP的表达对结直肠肠癌患者的淋巴结转移、
TNM分期及术后的生存期均有显著影响（P=0.001）、（P=0.033）、（P=0.004），但与患者的年龄，性别，肿瘤浸润深度，组织分化以
及病理类型没有关系。Kaplan-Meier法检验，结果显示，109例结直肠癌患者中SDCBP高低表达组患者术后平均生存期及7年累计生
存率分别为：52.300±6.508（月）、86.184±5.358（月）；38.6±6.4（%）、61.5±6.7（%），整体水平及各组间水平的差异经Log-rank法分
析均有统计学意义（χ2=10.585，P=0.001）；Cox回归分析法发现：SDCBP的高表达和发生淋巴结转移是患者死亡的主要影响因
素（B=0.605，P=0.034；B=0.677，P=0.013）。结论SDCBP可作为提示大肠癌淋巴结转移、TNM分期及预后的一项指标。

Prognostic value of syndecan binding protein in colorectal carcinoma

Objective To analyze the clinical significance of syndecan binding protein (SDCBP) expression in human colorectal
carcinoma (CRC) and its value in predicting the postoperative survival of the patients. Methods The follow-up data for 10
years were collected from 109 primary CRC patients with immunohistochemical data of SDCBP expression in the tumor
tissues. The relationship between SDCBP expression and the clinical factors was analyzed, and survival analysis was
performed using the Kaplan-Meier and Cox regression analysis models. Results SDCBP expression in CRC was significantly
associated with the postoperative survival time (χ2=8.336, P=0.004) and lymph node metastasis (P=0.001) of the patients, but not
with age, gender, depth of invasion, tissue differentiation or histological type of the tumor. Kaplan-Meier survival curves
showed that the patients expression high levels of SDCBP in the CRC tissues had a significantly shorter postoperative mean
survival time and a lower 7-year survival rate than those with low SDCBP expressions [52.300±6.508 vs 86.184±5.358 months,
(38.6±6.4)% vs (61.5±6.7)%; χ2=10.585, P=0.001]. Multivariate Cox analysis revealed that a high expression of SDCBP (B=0.605, P=
0.034) and lymph node metastasis (B=0.677, P=0.013) were the main factors related to death in CRC patients. Conclusion
SDCBP expression level can serve as an indicator for lymph node metastasis, TNM staging, and outcome prediction of CRC.