Suppr超能文献

金属蛋白酶-1、金属蛋白酶-7 和 p53 的免疫表达及其与结直肠腺癌临床病理预后因素的相关性。

Metalloproteinase-1, metalloproteinase-7, and p53 immunoexpression and their correlation with clinicopathological prognostic factors in colorectal adenocarcinoma.

机构信息

Coloproctology Service, Hospital Santa Casa de Misericórdia de Maceió, Alagoas, Brazil.

出版信息

Int J Biol Markers. 2009 Jul-Sep;24(3):156-64. doi: 10.1177/172460080902400305.

Abstract

AIM

The aim of this study was to analyze the immunoexpression of metalloproteinase-1, metalloproteinase-7, and p53 in colorectal adenocarcinoma, and to correlate this with clinicopathological prognostic factors.

MATERIAL AND METHODS

Formalin-fixed paraffin-embedded tumor tissue from 82 patients was analyzed by means of immunohistochemistry, using the streptavidin-biotin method and the tissue microarray technique. Protein tissue expression was correlated with the variables of the degree of cell differentiation, stage, relapse-free survival, recurrence, survival, and specific mortality.

RESULTS

All of the tumors were positive for metalloproteinase-1, while 50 (61%) were positive for metalloproteinase-7, and 32 (39%) were negative for the latter. For p53, 70 (85.4%) of the tumors were positive and 12 (14.6%) were negative. Correlation of the marker expressions separately and in conjunction did not produce any statistically significant data.

CONCLUSION

The immunoexpression of metalloproteinase-1, metalloproteinase-7, and p53 did not correlate with recurrence, mortality, relapse-free survival, survival, degree of cell differentiation, or staging of colorectal cancer.

摘要

目的

本研究旨在分析结直肠腺癌中基质金属蛋白酶-1、基质金属蛋白酶-7 和 p53 的免疫表达,并将其与临床病理预后因素相关联。

材料与方法

采用免疫组织化学链霉亲和素-生物素法和组织微阵列技术,对 82 例患者的福尔马林固定石蜡包埋肿瘤组织进行分析。蛋白组织表达与细胞分化程度、分期、无复发生存、复发、生存和特定死亡率等变量相关联。

结果

所有肿瘤均为基质金属蛋白酶-1 阳性,而 50 例(61%)为基质金属蛋白酶-7 阳性,32 例(39%)为基质金属蛋白酶-7 阴性。p53 阳性 70 例(85.4%),阴性 12 例(14.6%)。分别和联合标记物表达的相关性没有产生任何统计学上显著的数据。

结论

基质金属蛋白酶-1、基质金属蛋白酶-7 和 p53 的免疫表达与结直肠癌的复发、死亡率、无复发生存、生存、细胞分化程度或分期无关。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验