MPC-09 THE OPTIMIZATION OF TREATMENTS FOR SO-CALLED PRIMITIVE NEUROECTODERMAL TUMORS WITH MOLECULAR ANALYSIS
Abstract INTRODUCTION In the previous WHO classification of central nervous tumors, the supratentorial tumors comprise small round blue cells with aggressive clinical features had been defined as primitive neuroectodermal tumor (PNET). Recent molecular analysis revealed that they do not belong to a single entity, but they are re-classified as the tumors of other well-defined tumors and newly defined tumor species. These facts were reflected to the new classifications. While, there are few studies those showed the re-consideration of treatments for tumors diagnosed as so-called PNET. In this study, we propose the optimization of treatments for tumors diagnosed by the new classification to clarify which treatments were effective for the tumors those were diagnosed as PNET. MATERIALS AND METHODS The tumor samples diagnosed as so-called PNETs were analyzed. The molecular information was extracted from tumor specimens. We used high throughput analysis with microarray, FISH, and immunohistochemistry. They all had treated in our institution in last 6 years and their clinical courses were followed by medical records. Informed parental consent was obtained from their guardians and this study was approved by the institutional review board of Juntendo university. RESULTS Nine tumor samples were able to be analyzed and they are re-classified into high-grade glioma, neuroblastoma, sarcoma, embryonal tumors with multilayered rosettes, C19MC altered (ETMR). They resembled each other closely in morphology, and therefore, it was not able to be classified by histopathological findings. There was a case of pineoblastoma, whose molecular background suggested that the tumor was re-classified into neuroblastoma. In terms of treatments, we have succeeded in neuroblastoma cases so far, ETMRs were required multiple surgeries and radiations to maintain remissions. CONCLUSIONS Re-classification of diagnosis based on the molecular background is necessary to clarify the optimization of treatments for pediatric brain tumors, and the comprehensive methods is required. We present our methods for molecular diagnosis in clinical field and future plans.
