Gliomas are heterogeneous brain tumors that are often studied with a focus on survival rates. However, clinical outcomes include not only survival but also functional status and health-related quality of life (HRQoL). While microRNAs (miRNAs) are recognized as diagnostic and prognostic biomarkers, the aim of this study was to link invasiveness-related miRNA profiles with HRQoL to support individualized treatment strategies for glioma patients.

The expression of 17 invasiveness-related miRNAs (miR-7, miR-10b, miR-17, miR-21, miR-30b, miR-34a, miR-93, miR-139, miR-143, miR-148a, miR-181a, miR-181b, miR-181d, miR-193a, miR-200c, miR-221, and miR-335) was analyzed via quantitative real-time polymerase chain reaction. miRNA associations with 9 HRQoL parameters (functional status, overall QoL, tumor-related symptoms, depression, cumulative learning, delayed recall, psychomotor speed, executive functions, and verbal fluency), patient clinical characteristics (sex, age, tumor grade, IDH and MGMT status), and tumor characteristics (volume, level of edema, and hemisphere) were assessed via the Mann–Whitney U test, Spearman correlation, Kaplan–Meier and Cox regression analyses. Decision tree modeling was applied to identify key miRNAs that predict individual HRQoL features.

miR-21 demonstrated the strongest clinical relevance, showing statistically significant associations with five key parameters: patient age, tumor grade, IDH mutation status, tumor volume, and hemisphere. Survival analysis revealed that the higher expression of miR-10b, miR-21, miR-148a, miR-193a, miR-200c, miR-221, and miR-335 was significantly associated with shorter overall survival, while miR-139 – with improved survival. Among the HRQoL domains, overall QoL exhibited the greatest number of miRNA correlations and miR-139 demonstrated the greatest number of significant associations across HRQoL parameters. miR-181a appeared in the greatest number of predictive models (for functional status, overall QoL, and depression), where the functional status model, based on Karnofsky performance status scores, showed excellent performance (specificity = 100%, overall accuracy = 77,6%).

This study highlights the potential of invasiveness-related miRNAs as dual-purpose biomarkers that are informative not only for glioma prognosis but also for predicting HRQoL outcomes. By integrating molecular profiling with patient-centered metrics, our findings support the development of more personalized, QoL-aware care strategies for glioma patients.