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Circulating microRNAs as Biomarkers of Brain Metastases in Lung Cancer: A Pilot Study
Karol Marschollek1, Maciej Powierża2, Dorota Kujawa2
1Clinical Department of Neurology, University Centre of Neurology and Neurosurgery, Faculty of Medicine, Wroclaw Medical University, Borowska 213, 50-556 Wrocław, Poland.
None:
Background/Objectives: There is an ongoing search for reliable biomarkers of lung cancer (LC) and its progression, including nervous system involvement. MicroRNAs (miRNAs) play a crucial role in the regulation of gene expression and represent a promising focus of investigation in this field. The aim of this study was to assess the profile of miRNA expression in patients diagnosed with lung cancer, with or without brain metastases. Methods: This study comprised 13 patients diagnosed with non-small cell lung cancer (mean age 64.8 years, 61.5% females): 6 with brain metastases (LC + BM) and 7 without them (LC), and a control group of 6 healthy volunteers (HC). The expression levels of 179 miRNAs were assessed and compared between the study groups using quantitative reverse-transcription PCR (qRT-PCR). Results: In LC + BM subgroup, two miRNAs were found to be downregulated in comparison with HC: miR-409-3p (logFC = -17.42, p = 0.029) and miR-485-3p (logFC = -17.30, p = 0.026). An exploratory, probe-based feature-ranking analysis identified eleven miRNAs that were repeatedly selected across the resampling runs: miR-363-3p, miR-210-3p, miR-194-5p, miR-409-3p, miR-22-3p, miR-2110, miR-326, miR-485-3p, miR-223-5p, miR-16-2-3p, and miR-139-5p. Among these, miR-363-3p, miR-210-3p, and miR-194-5p exhibited the highest empirical stability. Predictive modeling was subsequently evaluated using a fully nested cross-validation framework in which feature selection and model training were repeated within each training fold. Under this stringent evaluation, the classification performance was close to chance across all the evaluated algorithms, indicating a limited predictive utility of the identified miRNAs for distinguishing patients with and without brain metastases in the present dataset. Conclusions: Notable differences in miRNA expression profiles were revealed for the patients with brain metastases from lung cancer, suggesting the role of the selected miRNAs in cancer metastasis to the CNS. However, while our analysis provides exploratory insights, the findings should be interpreted with caution and require validation in larger, independent cohorts before any clinical or translational implications can be established.
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