Współczesna Onkologia

Abstract

4/2025 vol. 29
Original paper

Immunometabolic landscape of glioblastoma – a comparative analysis of circulating cytokines and biochemical markers

  1. Biochemistry Department, Andijan State Medical Institute, Andijan, Uzbekistan
  2. Department of Anatomy and Clinical Anatomy, Andijan State Medical Institute, Andijan, Uzbekistan
  3. Department of Chemistry, Andijan State University, Andijan, Uzbekistan
Contemp Oncol (Pozn) 2025; 29 (4): 377–383
Online publish date: 2025/11/11
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Introduction

Glioblastoma (GBM) is the most aggressive primary brain tumour in adults. Systemic immunometabolic alterations are increasingly implicated in its pathogenesis, yet sex- and age-specific patterns remain unclear, especially in Uzbekistan. To characterize circulating cytokine and biochemical profiles in newly diagnosed GBM patients and assess sex- and age-related differences.

Material and methods

This cross-sectional study included 26 GBM patients (18 females, 8 males) and 26 matched healthy controls. Serum interleukin (IL)-10, IL-1β, IL-6, tumor necrosis factor-α, and IFN-γ were measured by enzyme-linked immunosorbent assay, and biochemical parameters (alkaline phosphatase, alanine aminotransferase – ALT, aspartate aminotransferase – AST, bilirubin, calcium, magnesium, iron, creatinine, uric acid, lactate dehydrogenase – LDH, phosphorus) were analysed by automated assays. Data were evaluated using ANOVA, t-tests, correlations, and principal component analysis (p < 0.05).

Results

No sex-based differences were observed (p > 0.05). Older patients had higher uric acid (p = 0.029) and borderline elevated IL-10 (p = 0.048) levels. Pro-inflammatory cytokines correlated with metabolic markers (ALT, AST, uric acid, LDH) and bilirubin correlated with iron/LDH.

Conclusions

Glioblastoma-related immunometabolic profiles are influenced mainly by tumour-intrinsic factors rather than sex, while age contributes to metabolic shifts. These findings provide novel regional data and support cytokine-biochemical profiling for biomarker development.

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