Algorithmic approach utilizing histology and immunohistochemistry for the current classification of diffuse glioma.

Abstract

Introduction: Diffuse glioma constitutes 28% of primary brain tumors. Until recently morphologic appearance was the only criterion for classifying these tumors. However, WHO 2016 incorporates molecular information in the primary diagnosis of gliomas such as Isocitrate dehydrogenase 1 (IDH1), Alpha thalassemia/mental retardation syndrome X inked (ATRX) as well as 1p/19q codeletion on FISH. In a resource-limited setup where FISH is not available, Alpha internexin (INA) has been suggested as a surrogate IHC marker.

Material and methods: Cross-sectional study conducted in the Department of Pathology for two years. Tissue blocks and clinical as well as radiological details were obtained from departmental archives. After assessing the morphologic details, routine IHC markers such as GFAP, Ki67 and P53 along with molecular markers like IDH-1, ATRX, and lNA were applied.

Results: Out of 55 cases of diffuse glioma, 23 cases of astrocytoma and 32 cases of oligodendroglioma with an overall mean age of presentation of 41.49 ± 12.47 years. IDH-1 expression among diffuse glioma was 89.1% in our study. Alteration in the ATRX gene expression was observed in 95.7% of astrocytomas. 75% of oligodendrogliomas expressed INA with no significant difference in expression between the two grades. Based on the algorithmic approach using molecular surrogate markers, diffuse gliomas were categorized into six distinct groups. IDH-mutant, ATRX loss of expression astrocytoma and IDH-mutant, INA positive oligodendroglioma are two categories that do not require further molecular testing. This comprises 72.7% of the cases and these do not warrant further workup.

Conclusion: Implementation of combined phenotypic-genotypic diagnosis with the use of histomorphology and immunohistochemical surrogates for molecular genetic alterations will yield more homogeneous and narrowly defined diagnostic entities which will provide better prognostication and definitive treatment. It also is cost-effective in a resource-limited setup.