Evaluation of Circulating miRNAs In the Prediction and Diagnosis of Brain Tumors
Keywords:
Circulating miRNAs, Brain Tumors, AUC, Sensitivity, SpecificityAbstract
Heterogeneities in clinical brain tumor phenotypes and restriction to standard diagnostic methods, including CT and MRI imaging or invasive biopsies are remaining challenges. Noninvasive biomarkers, which could be used in early prediction and diagnosis of brain tumors, are attracting more attention. Circulating microRNAs (miRNAs) show promise as biomarkers because they are stable in peripheral blood and are linked to tumor-associated molecular networks. The purpose of this research was to determine whether the expression levels of circulating miRNAs could be used to diagnose and predict brain tumors. Subjects and Methods: A cross-sectional diagnostic study was carried out in Al-Forat Al-Awsat Oncology Center, Al-Najaf City, Iraq from February 2025 to August 2025. A total of 78 patients with clinical suspicion of brain tumors were included. MiRNA levels in circulation from peripheral blood collected before radiological evaluation were quantified. All patients were subjected to brain CT scan afterwards as the gold standard of diagnosis. According to CT scans, 48 cases of brain tumor were confirmed, and another 30 cases presented no intracranial tumor as the control group. Sera obtained from patients with brain tumors were not different from the tumor-negative cases, both in terms of miRNA expression (p < 0.002). In binary logistic regression, circulating miRNAs levels were independently associated with the increased odds of presence of a brain tumor (p = 0.012). Receiver operating characteristic (ROC) curve analysis further confirmed circulating miRNAs with good diagnostic value, an AUC of 0.84, and a sensitivity and specificity of 83.3% and 80.0% using the optimum cut-off value. In summary, circulating miRNAs may be promising non-invasive diagnostic and predictive biomarkers for brain tumors that could be used in clinical practice as a supplement of radiological imaging.
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