Improvement of breast cancer prognostication using cell kinetic-based silver-stainable nucleolar organizer region quantification of the MIB-1 positive tumor cell compartment.
Recently, it was stated that the proliferative activity (P) of a cell population could be indirectly calculated by multiplying the MIB-1 immunopositivity and silver-stainable nucleolar organizer region (AgNOR) features extracted exclusively in MIB-1 positive (pos.) nuclei: P=MIB-1 x AgNOR(MIB-1pos.). To study the prognostic significance of this hypothesis, MIB- immunohistochemistry and AgNOR staining were applied on a series of 89 cases of breast cancer with an 8-year follow-up period. The mean MIB-1 immunopositivity (MIB-1mean) was evaluated immunohistometrically on paraffin sections using a TV image analysis system CM-2 (Hund, Wetzlar, Germany). Later, a combined MIB-1/AgNOR staining was applied and evaluated using a TV image analysis system AMBA (IBSB, Berlin, Germany). The AgNOR features of 150 randomly chosen tumor nuclei were investigated, irrespective of their MIB-1 status (AgNOR count, AgNOR area). Later, a second measurement was performed on 100 MIB-1 positive tumor nuclei exclusively (AgNOR countMIB-1pos., AgNOR areaMIB-1pos.). AgNOR count and AgNOR countMIB-1pos. showed a different data distribution [2.7+/-0.7 (mean+/-SD) vs 3.9+/-1.1; r=0.315, P=0.014]. Similar results were obtained for AgNOR area and AgNOR areaMIB-1pos. (5.1+/-2.1 microm2 vs 7.5+/-2.4 microm2; r=0.501, P<0.001). Kaplan-Meier survival curves revealed significant differences for MIB-1mean (P=0.0018) and AgNOR areaMIB-1pos. (P=0.0340). In Cox models, both parameters provided independent prognostic information. Using their combination, the P, three groups of patients with statistically different survival could be separated (P=0.0014). Thus, the combination of MIB-1-immunopositivity and AgNOR measurements in MIB-1 positive nuclei appears to be more useful in breast cancer prognosis than the exclusive application of one of the two methods. By this combined application, probably effects of tumor biology are represented more precisely.
Biesterfeld
S
S
Institute of Pathology, Technical University of Aachen, Germany. Biesterfeld@pat.RWTH-Aachen.de
Farokhzad
F
F
Klüppel
D
D
Schneider
S
S
Hufnagl
P
P
D000230:Adenocarcinoma / Q000175:diagnosis* / Q000378:metabolism / Q000628:therapy; D034961:Antigens, Nuclear; D014408:Biomarkers, Tumor / Q000378:metabolism*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000378:metabolism / Q000628:therapy; D005260:Female; D006801:Humans; D019044:Image Cytometry / Q000379:methods; D007091:Image Processing, Computer-Assisted; D019394:Ki-67 Antigen; D008875:Middle Aged; D009687:Nuclear Proteins / Q000378:metabolism*; D009697:Nucleolus Organizer Region / Q000737:chemistry*; D011379:Prognosis; D016622:Silver Staining / Q000379:methods; D016019:Survival Analysis
D034961:Antigens, Nuclear; D014408:Biomarkers, Tumor; D019394:Ki-67 Antigen; D009687:Nuclear Proteins