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目的初步探讨多基因蛋白联合检测判断卵巢上皮性癌(卵巢癌)预后的价值。方法选择广西医科大学附属肿瘤医院1991—2001年间确诊为卵巢癌Ⅱ～Ⅲ期的患者共80例,患者均接受理想的肿瘤细胞减灭术和以铂类为主的化疗,其中预后好组(指存活期≥2年)46例,预后差组(指存活期<2年)34例。采用组织芯片与免疫组化法对两组患者癌组织进行多个基因蛋白(共17个,即 ToPo-Ⅱ、Ki-67、MGMT、PCNA、p27、p53、p16、P-gp、LRP、GST-π、bcl-2、C-myc、Fas、bax、MSH2、MRP、BCRP 蛋白)表达的检测,并分析其与卵巢癌患者预后的关系;对两组中表达有差异的6个蛋白(即 P-gp、BCRP、MGMT、MSH2、p27和 p16蛋白)进行多基因蛋白联合检测,并对据此判断的卵巢癌患者预后的价值进行分析。结果 (1)预后差组 P-gp、BCRP、MSH2蛋白阳性表达率(分别为62%、50%和50%)明显高于预后好组(分别为33%、28%和28%,P<0.05);而预后好组 MGMT、p27、p16蛋白阳性表达率(分别为43%、54%和43%)明显高于预后差组(分别为18%、29%和24%,P<0.05)。(2)Cox 模型分析显示,MRP、C-myc、LRP、p16、p27、MGMT、ToPo-Ⅱ、P-gp、GST-π蛋白表达与卵巢癌患者的预后有关(P<0.01)。其中,MRP、C-myc、LRP、ToPo-Ⅱ、P-gp、GST-π蛋白阳性表达者预后差,而MGMT、p27、p16蛋白阳性表达者预后好。(3)多基因蛋白联合检测结果显示,P-gp+MGMT 蛋白联合检测呈阳性表达者与预后密切相关(P<0.01),两者联合检测对卵巢癌患者预后总的预测准确率达70%。结论 P-gp、MGMT、p27、p16蛋白可作为预测卵巢癌患者预后的标志物,而多基因蛋白联合检测则能更好地预测卵巢癌患者的预后。
Objective To investigate the value of combined detection of multiple genes in the prognosis of epithelial ovarian cancer (ovarian cancer). Methods A total of 80 patients with stage Ⅱ ~ Ⅲ ovarian cancer diagnosed in Cancer Hospital Affiliated to Guangxi Medical University from 1991 to 2001 were selected. All patients underwent ideal cytoreductive surgery and platinum-based chemotherapies. The patients with good prognosis Refers to the survival of ≥ 2 years) 46 cases, poor prognosis group (refer to survival <2 years) in 34 cases. Tissue microarrays and immunohistochemistry were performed on a total of 17 cancer-bearing human cancers including ToPo-Ⅱ, Ki-67, MGMT, PCNA, p27, p53, p16, P-gp, LRP, GST Bcl-2, C-myc, Fas, bax, MSH2, MRP, BCRP) in ovarian cancer patients were detected and their relationship with prognosis of ovarian cancer patients was analyzed. P-gp, BCRP, MGMT, MSH2, p27 and p16 proteins), and analyzed the prognostic value of ovarian cancer patients. Results (1) The positive rates of P-gp, BCRP and MSH2 in the poor prognosis group were significantly higher than those in the good prognosis group (33%, 28% and 28%, P < 0.05). However, the positive expression rates of MGMT, p27 and p16 protein in the prognosis group were significantly higher than those in the poor prognosis group (43%, 54% and 43% respectively) (18%, 29% and 24%, P <0.05) . (2) Cox model analysis showed that the expression of MRP, C-myc, LRP, p16, p27, MGMT, ToPo-Ⅱ, P-gp and GST-π were correlated with the prognosis of patients with ovarian cancer (P <0.01). Among them, the positive expression of MRP, C-myc, LRP, ToPo-Ⅱ, P-gp, GST-π protein was poor prognosis, while MGMT, p27, p16 protein positive expression of prognosis is good. (3) Combined detection of polygenetic protein showed that the combined detection of P-gp + MGMT protein and prognosis were closely related to prognosis (P <0.01). The combined detection of these two genes had a total predictive accuracy of 70% . Conclusion P-gp, MGMT, p27 and p16 proteins can be used as predictors of prognosis in patients with ovarian cancer, and combined detection of polygenes can better predict the prognosis of patients with ovarian cancer.