Related Experiment Video
Updated: Mar 27, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Prognostic Significance of Two Dimensional AgNOR Evaluation in Local Advanced Rectal Cancer Treated with
Mete Gundog1, Oguz G Yildiz, Nalan Imamoglu
1Department of Radiation Oncology, Kayseri Education and Research Hospital, University of Erciyes, Kayseri, Turkey
Abstract:
The prognostic significance of AgNOR proteins in stage II-III rectal cancers treated with chemoradiotherapy was evaluated. Silver staining was applied to the 3μm sections of parafin blocked tissues from 30 rectal cancer patients who received 5-FU based chemoradiotherapy from May 2003 to June 2006. The microscopic displays of the cells were transferred into the computer via a video camera. AgNOR area (nucleolus organizer region area) and nucleus area values were determined as a nucleolus organizer regions area/total nucleus area (NORa/ TNa). The mean NORa/TNa value was found to be 9.02±3.68. The overall survival and disease free survival in the high NORa/TNa (>9.02) patients were 52.2 months and 39.4 months respectively, as compared to 100.7 months and 98.4 months in the low NORa/TNa (<9.02) cases. (p<0.001 and p<0.001 respectively). In addition, the prognosis in the high NORa/TNa patients was worse than low NORa/TNa patients (p<0.05). In terms of overall survival and disease-free survival, a statistically significant negative correlation was found with the value of NORa/TNa in the correlations tests. Cox regression analyses demostrated that overall survival and disease-free survival were associated with lymph node status (negative or positive) and the NORa/TNa value. We suggest that two-dimensional AgNOR evaluation may be a safe and usable parameter for prognosis and an indicator of cell proliferation instead of AgNOR dots.
More Related Videos
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
03:05Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
Published on: February 16, 2024