【摘要】 目的探讨成纤维细胞生长因子(bFGF)及微血管密度(MVD)在卵巢浆液性肿瘤组织中的表达。方法采用免疫组化方法检测76例卵巢浆液性肿瘤(良性浆液性囊腺瘤10例、交界性浆液性囊腺瘤8例及浆液性囊腺癌58例)中微血管密度(MVD)、碱性成纤维细胞生长因子(bFGF)的表达,并分析二者间相关关系。结果良性、交界性及恶性浆液性卵巢肿瘤组织中MVD值分别为7.8±2.4,17.5±3.3及27.6±7.5,bFGF的表达分别为(9.86±6.7)%,(24.8±10.0)%及(40.7±17.2)%,各组间差异有统计学意义(P<0.01及P<0.05)。高分化、中分化及低分化浆液性卵巢癌组织中MVD值分别为18.3±3.4、24.2±3.1及32.3±6.4,bFGF的表达分别为(25.0±17.7)%,(37.9±17.2)%及(47.7±13.1)%,各组间差异有统计学意义(P<0.01及P<0.05);浆液性卵巢癌FIGOⅢ-Ⅳ期的MVD值高于Ⅰ-Ⅱ期的MVD值,分别为28.9±4.7及22.0±4.7,差异有统计学意义(P<0.01);bFGF的表达在浆液性卵巢癌Ⅲ-Ⅳ期的表达高于Ⅰ-Ⅱ期的表达,分别为(41.8±15.9)%及(35.9±22.3)%,但差异无统计学意义(P>0.05)。浆液性卵巢癌中bFGF的表达与肿瘤组织中MVD的值呈正相关关系(r=0.393,P<0.01)。结论血管生成可能在浆液性卵巢肿瘤的发生发展中起重要促进作用。更多还原

【Abstract】 Objective To explore the expression of MVD and bFGF in serous ovarian neoplasms. Methods Immunohistochemical method was used to examine microvessel density(MVD)and the expression of basic fibroblast growth factor(bFGF)in 76 cases of serous ovarian neoplasms(10 cases of benign ovarian cystadenomas,8 cases of bordline ovarian cystadenomas and 58 cases of ovarian cystadenocarcinomas).The relationship between MVD and bFGF was analyzed. Results In patients with benign ovarian cystadenomas,bordline ovarian cystadenomas and ovarian cystadenocarcinomas,the MVD incneased gradually(7.8±2.4,17.5±3.3 and 27.6±7.5,P<0.01 or P<0.05),while bFGF expression was(9.86±6.7)%,(24.8±10.0)%,and(40.7±17.2)%,respectively(P<0.01 or P<0.05).In patients with ovarian cystadenocarcinomas,MVDs were 18.3±3.4,24.2±3.1,and 32.3±6.4 in grade 1,grade 2 and grade 3,respectively(P<0.01 or P<0.05),and bFGF expression was(25.0±17.7)%,(37.9±17.2)%,(47.7±13.1)%,respectively(P<0.01 or P<0.05).MVD was higher in patients with FIGO stage Ⅲ-Ⅳ than that in stage Ⅰ-Ⅱ(28.9±4.7 vs 22.0±4.7,P<0.01),while bFGF expression was(55.1±22.9)% and (40.18±18.0)%,but there was no significant difference(P>0.05).A significantly positive correlation between bFGF expression and MVD in patients with ovarian cystadenocarcinomas(r=0.393,P<0.01). Conclusion Angiogenesis plays an important role in the development of serous ovarian neoplasams.更多还原