Role of IDH1 Immunostain In Differentiating Between Diffuse Astrocytoma and Reactive Astrocytosis

  • Duaa S Helal Faculty of Medicine, Tanta university, Egypt.
  • Mohamed A Elrashidy Faculty of Medicine, Tanta university, Egypt.
Keywords: IDH1, immunohistochemistery, glioma, gliosis

Abstract

Background: The distinction of diffuse astrocytoma from astrocytosis is a major challenge in neuropathology. Reactive astrocytosis can occur in a variety of non neoplastic CNS lesions and can be seen in some CNS tumors. This can be particularly challenging with small biopsies considering the marked differences in prognosis and therapy after a pathologic diagnosis. Somatic IDH1 mutations are present in the vast majority of lowgrade diffuse astrocytoma (WHO grade II). Methods: In the present study we investigated the specificity of anti-IDH1 immunostaining in differentiating diffuse low grade astrocytomas from reactive CNS lesions. Results: The study included 24 WHO grade II diffuse astrocytomas and 22 reactive conditions with astrocytosis (8 infarcts, 10 gliosis, and 4 traumatic brain injury). All cases were stained by IDH1 immunostain. Positive granular cytoplasmic staining of tumor cells for IDH1 was found in 13 out of 24 (54.2%) WHO grade II astrocytomas, but was entirely absent in all 22 reactive samples . Tumor cells in astrocytoma cases demonstrated staining both in the densely cellular areas of the tumor, as well as in the less cellular infiltrating tumor edges. While reactive astrocytes at the tumor edges were IDH1 negative. Conclusion: This study showed that IDH1 is a useful immunohistochemical marker to differentiate reactive gliosis from low-grade astrocytoma. IDH1 has potential as an independent marker to diagnose neoplastic conditions especially in small surgical samples with high specificity.

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Published
2016-03-15
How to Cite
Helal, D. S., & Elrashidy, M. A. (2016). Role of IDH1 Immunostain In Differentiating Between Diffuse Astrocytoma and Reactive Astrocytosis. Asian Journal of Medical Research, 5(2), 1-4. Retrieved from https://aijournals.com/index.php/ajmr/article/view/149