Intense p53 immunostaining may predict for a poor prognosis in central nervous system primitive neuroectodermal tumor of childhood.
Background: Medulloblastoma is a common childhood primary brain tumor. Potential prognostic indicators for patients with local disease are age, extent of resection, and gender. However, none of these are well established. Immunohistologic staining is a potentially useful means to identify high-risk patients. The purpose of this clinical pathologic study was to investigate the prognostic significance of GFAP, synaptophysin, Ki-67, and p53 immunostaining in medulloblastoma/central nervous system primitive neuroectodermal tumors (CNS PNETs.)
Materials and methods: The records of 40 patients with CNS PNETs were reviewed. Their surgical specimens were immunostained for p53, glial fibrillary acidic protein (GFAP), synaptophysin, and Ki-67. The p53 specimens were scored blindly for the intensity of staining of nuclei (intense vs weak) and the quantity of cells stained. The Ki-67, GFAP, and synaptophysin specimens were analyzed for quantity of cells stained.
Results: Ten patients' specimens stained intensely for the p53 protein. Eleven had weakly staining nuclei. Nineteen specimens had no staining. The patients with specimens that stained intensely had a statistically significant decreased disease free survival (P = 0.03). Mere presence or quantity of p53 nuclear staining did not correlate with disease free survival. Immunohistochemical staining for Ki-67, GFAP, and synaptophysin did not correlate with disease free survival. Clinical parameters of age, gender, and extent of resection also did not approach statistical significance for disease free survival.
Conclusion: Intense nuclear staining for p53 was the only variable in this clinical pathologic study that reached statistical significance for disease free survival. This suggests that intense staining for p53 may be the most important prognostic indicator for non-metastatic CNS PNETs. p53 Immunostaining with antibodies against p53 in CNS PNETs should be studied in a multi-institutional setting with larger numbers of patients.