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Background: The most common primary CNS neoplasms are astrocytomas, derived from an immortalized astrocyte, accounting for 4-5 % of all cancer related death. Ki-67 and P53 are two cellular proteins playing roles in pathogenesis and evolution of astrocytomas.Ki-67 is an antigen represents a nuclear non histone protein, produced by cells in the proliferative phases. P53 gene produces a protein functions as a tumor suppressor gene. Both biomarkers were considered to be of prognostic value.
Aims: The paper aims theassessment of p53 and ki-67 immunoexpression in astrocytomas,relation of these markers with histologic grade of astrocytomas, andto use p53 and Ki-67 as a prognostic tool.
Materials and Methods:Forty-five patients with astrocytoma were conducted in the study which performed in Department of Pathology, Faculty of Medicine, university of Kufa in the period from January 2018 through April 2019.Cases were collected from “neurosurgical hospital in Baghdad, and laboratory of histopathology in Al-sadder Medical city in Al-Najaf and from some private laboratories of the same governorate”, ages ranging from 2-65 years with a mean of 29.04 years.EnVision method (polymer based immunohistochemistry) was used for evaluation of p53 and ki-67.
Results: Grade II patients predominant the studied sample and constitute (55.6%), whereas patients of grade I constitute (22.2%), grades IV and III compose (13.3%) and (8.9%) respectively.P53 was detected in (33.34%) of the cases and was “significantly positively correlated” with grade IV, gender not with age.Ki-67 LI was (>5%) in (31.11%) of patients and was “significantly positively correlated” with tumor grade, age of the patient but not with gender, both biomarkers were “positively correlated with each other, and with grade of astrocytoma”.
Conclusions and recommendations:p53 and ki-67 over expression have an important role in pathogenesis of astrocytoma, as their positivity associated with higher tumor grade, so merging these biomarkers with histopathological grade in a prognostic index will accurately predict clinical outcome and the effectiveness of anti cancer therapy.