Related Experiment Video
Updated: Feb 19, 2026

Characterization and Functional Prediction of Bacteria in Ovarian Tissues
Published on: October 23, 2021
The AgNORs count in predicting long-term survival in serous ovarian cancer
Leszek Gottwald1, Marian Danilewicz2, Wojciech Fendler3
1Department of Radiotherapy, Chair of Oncology, Medical University of Lodz, Poland.
Introduction:
The value of argyrophilic nucleolar organizer regions (AgNORs) to predict survival in patients with ovarian cancer has not been clearly explained yet. The aim of study was to assess the value of analysis of the mean number of AgNORs per nucleus (mAgNOR) and mean percentage of nuclei with five or more AgNORs per nucleus (pAgNOR) in the prediction of disease-free survival (DFS) and overall survival (OS) in patients with serous ovarian cancer.
Material And Methods:
The study examined 52 patients treated for serous ovarian cancer with a follow-up period of 2-143 months. After silver staining paraffin specimens from primary surgery, mAgNOR and pAgNOR in cancer cells were counted and analyzed. Age, grading, radicality of surgery and FIGO staging were analyzed as covariates.
Results:
Mean mAgNOR equaled 4.4 ±0.9 and pAgNOR equaled 42.2 ±20.8%. Both mAgNOR and pAgNOR were the lowest in G1 tumors. The mAgNOR and pAgNOR were lower in stage I than stage IV cancers. The DFS and OS rates were respectively 15.4% and 21.2%. In univariate analysis FIGO staging, grading, and pAgNOR were associated with worse prognosis, while radicality of surgery remained a significant protective factor in terms of DFS. Higher FIGO staging and older age worsened OS. In multivariate analysis FIGO staging remained significantly associated with both DFS (HR 1.98; 95% CI 1.05-3.71) and OS (HR 1.76; 95% CI 1.00-3.10), while age affected OS rates (HR 1.78; 95% CI 1.04-2.95).
Conclusions:
mAgNOR and pAgNOR are useful markers of cellular kinetics. Prospective studies in larger populations are needed to confirm these results in terms of AgNORs' effects on survival.
More Related Videos
07:59Evaluating the Angiogenetic Properties of Ovarian Cancer Stem-Like Cells using the Three-Dimensional Co-Culture System, NICO-1
Published on: December 5, 2020
09:08Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
Published on: January 12, 2020