| Home | E-Submission | Sitemap | Editorial Office |  
top_img
Journal of Korean Neurosurgical Society 1996;25(3): 473-482.
A Comparative Study of PCNA(Proliferating Cell Nuclear Antigen) and AgNORs(Argyrophilic Nucleolar Organizer Regions) in Malignancy of Brain Tumors.
Whan Whae Koo, Han Kyum Kim, Seong Ho Kim, Shi Hun Song, Kwan Tac Kim, Youn Kim
Department of Neurosugery, College of Medicine, Chungnam National University, Taejon, Korea.
ABSTRACT
The authors studied the expression of proliferating cell nuclear antigen (PCNA) and the number of argyrophilic nucleolar organizer regions (AgNORs) in 94 cases of various brain tumors and in 5 cases of normal brains. PCN was recognized immunohistochemically in paraffin sections by the monoclonal antibody PC-10. AgNORs could be demonstrated using the silver impregnation method. The PCNA index was not significantly different from the histological grading of glioma(glioblastoma multiforme: 41.40+/-29.14%, anaplastic astrocytoma: 35.00+/-41.02%, and low grade astrocytoma: 22.37+/-30.85%) and there was a wide range of staining even in the same tissue section. However, the AgNORs count per cell correlated well with the pathologic grading of glioma (glioblastoma multiforme : 3.19+/-0.71, anaplastic astrocytoma : 2.06+/-0.16, and low grade astrocytoma : 1.27+/-0.29) with statistical significance. In meningiomas, AgNORs were useful to differentiate benign meningiomas(1.25+/-0.19) and malignant meningiomas(1.78+/-0.35) The authors suggest that the AgNORs count is a faster, less expensive, and a more predictive method in the malignancy of brain tumors than the PCNA immunochemistry expression.
Key Words: PCNA(Proliferating Cell Nuclear Antigen); AgNORs(Argyrophilic Necleolar Organizer Regions); Normal
Editorial Office
1F, 18, Heolleung-ro 569-gil, Gangnam-gu, Seoul, Republic of Korea
TEL: +82-2-525-7552   FAX: +82-2-525-7554   E-mail: office@jkns.or.kr
About |  Browse Articles |  Current Issue |  For Authors and Reviewers
Copyright © Korean Neurosurgical Society.                 Developed in M2PI
Close layer