Diagnostic algorithm for pathological evaluation of gliomas in a resource-constrained setting.

Area of Science:

• Neuro-oncology
• Molecular Pathology
• Cancer Diagnostics

Background:

• Gliomas are primary brain tumors requiring integrated histo-molecular diagnosis per WHO classification.
• Molecular testing is often unavailable, necessitating reliance on histopathology and immunohistochemistry (IHC).
• IDH1 and ATRX markers are crucial for glioma diagnosis, prognosis, and treatment.

Purpose of the Study:

• To develop a diagnostic algorithm for gliomas integrating morphology, IDH1, and ATRX status.
• To stratify gliomas into prognostic subgroups using IHC markers.

Main Methods:

• An analytical cross-sectional study of 60 glioma cases.
• Evaluation of IDH1 and ATRX mutation status using IHC.
• Classification into three molecular groups based on IDH1 and ATRX status.

Main Results:

• The study included astrocytic (n=51) and oligodendroglial tumors (n=9).
• IDH1 mutations were present in 26 cases, and ATRX mutations (loss of ATRX) in 17 cases.
• Gliomas were stratified into three prognostic groups: IDH1-/ATRX+ (n=34), IDH1+/ATRX+ (n=9), and IDH1+/ATRX- (n=17).

Conclusions:

• An integrated diagnostic approach combining clinicoradiological, histopathological, and molecular data is essential for glioma diagnosis.
• IDH1 and ATRX evaluation via IHC offers diagnostic and prognostic value, aiding in tumor differentiation and outcome prediction.
• IHC serves as a viable surrogate for molecular tests in resource-constrained environments, enabling prognostic stratification.