Suppr超能文献

乳腺癌中的肿瘤血管生成及基底膜结构与肿瘤组织学和预后的关系

Tumour vascularity and basement membrane structure in breast cancer as related to tumour histology and prognosis.

作者信息

Lipponen P, Ji H, Aaltomaa S, Syrjänen K

机构信息

Department of Pathology, University of Kuopio, Finland.

出版信息

J Cancer Res Clin Oncol. 1994;120(11):645-50. doi: 10.1007/BF01245375.

Abstract

A series of 202 breast cancer biopsy specimens were analysed immunohistochemically for collagen IV to demonstrate basement membrane (BM) structures and blood vessels within tumour tissue. Integrity of the BM was graded into four categories and the number of vascular channels per square millimetre of tumour tissue were counted. Defective BM structures were significantly related to high grade, lack of tubule formation, invasive disease, high S-phase fraction and variability in nuclear size and shape. High vascular channel density was related to poor tumour differentiation and a high proliferation rate of cancer cells as well as to the absence of tubule formation, inconspicuous intraductal growth and low progesterone receptor content. High vascular density and defective BM structures were signs of poor prognosis and short recurrence-free survival in the entire cohort and also in local tumours. In multivariate analysis, the vascular density had independent prognostic value, as did the diameter, axillary lymph node status and mitotic rate. The counting of vascular channels within the tumour provides additional prognostic information in breast cancer, in contrast to analysis of the BM integrity which shows hardly any prognostic information additional to that provided by the special histological features, e.g. tubule formation and intraductal growth pattern.

摘要

对202份乳腺癌活检标本进行免疫组织化学分析,检测IV型胶原,以显示肿瘤组织内的基底膜(BM)结构和血管。BM的完整性分为四类,并计算每平方毫米肿瘤组织内血管通道的数量。BM结构缺陷与高级别、缺乏小管形成、浸润性疾病、高S期分数以及核大小和形状的变异性显著相关。高血管通道密度与肿瘤分化差、癌细胞增殖率高以及缺乏小管形成、导管内生长不明显和孕酮受体含量低有关。高血管密度和BM结构缺陷是整个队列以及局部肿瘤预后不良和无复发生存期短的迹象。在多变量分析中,血管密度具有独立的预后价值,肿瘤直径、腋窝淋巴结状态和有丝分裂率也具有独立的预后价值。与BM完整性分析相比,肿瘤内血管通道的计数为乳腺癌提供了额外的预后信息,BM完整性分析几乎没有提供除特殊组织学特征(如小管形成和导管内生长模式)之外的任何预后信息。

相似文献

引用本文的文献

1
Deep learning identification of stiffness markers in breast cancer.深度学习识别乳腺癌的硬度标志物。
Biomaterials. 2022 Jun;285:121540. doi: 10.1016/j.biomaterials.2022.121540. Epub 2022 Apr 27.

本文引用的文献

1
Microglandular adenosis, apocrine adenosis, and tubular carcinoma of the breast. An immunohistochemical comparison.
Am J Surg Pathol. 1993 Feb;17(2):99-109. doi: 10.1097/00000478-199302000-00001.
10
Angiogenic factors.血管生成因子。
Science. 1987 Jan 23;235(4787):442-7. doi: 10.1126/science.2432664.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验