Immunohistochemical expression of PDL1 and Ki67 in glioma and its correlation with treatment and overall survival
Year: 2025
Type: article
Study design: Observational Study
Abstract: CONTEXT: Gliomas are the most common primary brain tumors with an infiltrative nature; hence, complete removal is difficult, and despite radiotherapy and chemotherapy, there have been a high recurrence and poor survival rates. Hence, novel therapeutic strategies are needed to reduce recurrence and improve prognosis. Programmed death cell ligand (PD-L1) is a major prognostic biomarker for immune therapy in many cancers by using anti-PD-L1 antibodies. Studies have shown an upregulation in the PD-L1 and a therapeutic potential for improving survival. The current study was undertaken to evaluate immunohistochemical expression of PDL1 and Ki67 in gliomas and their correlation with clinicopathological parameters, prognostic and survival outcomes. METHODS AND MATERIAL: Histologically confirmed glioma cases were assessed for PD-L1 and Ki-67 immunohistochemical expression. Detailed clinicopathological study and prognostic outcomes were analyzed in these Glioma cases. RESULTS: Out of 65 glioma cases, 40 (61.5%) were found to be high-grade glioma and the rest 25 (38.5%) were low-grade glioma. Diffuse/fibrillary expression of PD-L1 was found in 60% of glioma cases. A low Ki67 proliferation index of ≤4% was observed in 27 cases (14.5%), with 5-10% expression in 12 (18.5%) and >10% expression in 26 cases (40.0%). The majority of the cases with <10% Ki67 expression had negative to low-grade PDL expression, while the majority with >10% Ki67 expression had moderate to strong PDL expression. This association was found to be significant statistically. CONCLUSIONS: In the study, a statistically significant correlation between PD-L1 expression and tumor cell proliferation was observed with a histological grade. Association of survival rate was seen with the expression of the markers. However, studies with larger samples would be needed for confirmation.
Institution: King George's Medical University
Language: English
Subfield: Genetics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4409128678