KDELR3 overexpression as a novel prognostic and diagnostic biomarker in glioma: comprehensive bioinformatic analysis insights

Abstract

Abstract Glioma, the most prevalent primary intracranial malignancy among adults, is distinguished by its high morbidity and recurrence rates, posing a considerable threat to patients’ quality of life and survival prospects. Consequently, the pursuit of efficacious molecular prognostic markers holds paramount importance. The exploration of the role of the KDELR3 kinase family in various neoplastic conditions constitutes an emerging area of research. However, the biological functions of KDELR3 and its prognostic implications in brain tumors remain largely undocumented. This study endeavored to ascertain the potential of KDELR3 as a prognostic indicator for glioma. We integrated a comprehensive dataset encompassing 1127 glioma samples, sourced from our cohort, The Cancer Genome Atlas (TCGA), and the Chinese Glioma Genome Atlas (CGGA), to delve into the expression patterns of KDELR3 in glioma and their associated implications. Notably, KDELR3 was markedly overexpressed in glioma and demonstrated a positive correlation with clinical progression. By utilizing Kaplan-Meier survival analysis and the Cox proportional hazards regression model, we evaluated the prognostic significance of KDELR3, revealing it as an independent predictor of adverse outcomes in glioma patients. Furthermore, gene set enrichment analysis unveiled potential signaling pathways associated with KDELR3 expression in glioma, primarily encompassing Cytokine-cytokine receptor interaction, extracellular matrix (ECM)-receptor interaction, and complement and coagulation cascades. In summation, our findings provide profound insights into the potential role of KDELR3 and its application as a novel and promising prognostic biomarker for glioma.

Keywords

• KDELR3
• Glioma
• Biomarker
• Prognosis
• Bioinformatics