医学
胸苷磷酸化酶
高碘酸-席夫染色
免疫组织化学
内科学
阶段(地层学)
肾切除术
肾细胞癌
肾透明细胞癌
单变量分析
清除单元格
淋巴结
病理
肿瘤科
疾病
癌症
肾
多元分析
生物
古生物学
作者
Vartanian Aa,Stepanova Ev,Gutorov Sl,Solomko ESh,Grigorieva In,Inna M. Sokolova,Baryshnikov Ay,Lichinitser Mr
出处
期刊:PubMed
日期:2009-08-01
卷期号:16 (4): 4726-32
被引量:15
摘要
The ability of aggressive tumors to form nonendothelial tumor cell-lined microvascular channels is known as "vasculogenic mimicry" (VM). VM channels are revealed as periodic acid-Schiff (PAS)-positive patterns, and in some tumors their presence predicts clinical outcomes.We aimed to study VM channels in clear cell renal cell carcinoma (cRCC) tumors and explore their prognostic significance and relationship to other suggested prognostic factors such as thymidine phosphorylase (TP) and vascular endothelial growth factor (VEGF) expression.We retrospectively studied 45 patients who had undergone radical nephrectomy for clinically confined cRCC (stage T2-T3NOMO) at the Russian Cancer Research Center. The tumor sections were reviewed for disease stage, nuclear grade, perirenal fat invasion, and lymph node involvement, and we performed immunohistochemical staining for VEGF and TP expression, and PAS staining. Disease-free survival probabilities were determined by Kaplan-Meier estimates and prognostic factors were evaluated by univariate analysis.PAS-positive patterns observed in the cRCC tumor included back-to-back closed loops, networks, arcs, and parallel patterns. There was a significant decrease in disease-free survival among patients with PAS-positive networks (p = 0.005), but not among patients with other PAS-positive patterns. TP expression was also a significant predictor of disease-free survival (p = 0.035), but this factor did not correlate with the presence of PAS-positive networks. Notably, in our small sample, the six patients whose tumors were positive for both factors had the highest risk of cancer recurrence.The presence of PAS-positive networks is an independent and relevant prognostic parameter for disease-free survival in patients with cRCC. Our data suggest that the combination of PAS-positive networks and TP expression may identify patients with the highest risk of cancer recurrence.
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