English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Although magnetic resonance imaging (MRI) provides accurate anatomical and spatial details regarding gliomas, it is not reliable at predicting biological behaviour and is confounded by problems such as pseudo-progression. A circulating biomarker has potential to improve predictions of glioma outcomes and identify tumor progression post treatment, however no such biomarker is currently available. We aimed to discover a microRNA (miRNA) serum biomarker for longitudinal monitoring of glioma patients as well as identify miRNAs that are predictive of survival outcomes. To investigate this a prospectively collected cohort of 91 gliomas and 17 healthy controls underwent pre- and post-operative serum miRNA profiling using the next-generation sequencing platform Nanostring®. Differentially expressed miRNAs were discovered using a machine learning random forest analysis. Candidate miRNAs were then assessed by droplet digital PCR in 11 patients with multiple follow-up samples and compared to tumor volume based on MRI. A lasso-regression model was used to identify candidate miRNAs from pre-operative serum that were associated with both progression-free and overall survival. We identified a 9-gene miRNA signature that could distinguish between glioma and healthy controls with 99.8% accuracy. From this signature, we identified two miRNAs that demonstrated dynamic changes which correlated closely with tumor volume in both LGG and GBM. Importantly, miRNA levels did not increase in two cases of pseudo-progression, indicating the potential utility of this test in guiding treatment decisions. Additionally, altered expressions of 6 miRNAs were found to be associated with overall and progression-free survival and were incorporated in a predictive model with already known survival factors. In conclusion, we have identified a highly accurate 9-miRNA signature associated with glioma serum and observed specific miRNAs that both correlated with tumor volume over long-term follow up and were predictive of survival. These results support a large prospective validation study of serum miRNA biomarkers in glioma.

BIOM-49. SERUM microRNA IS A PROGNOSTIC AND POST-OPERATIVE MONITORING BIOMARKER IN GLIOMA