Longitudinal analysis of serum-derived extracellular vesicle RNA to monitor dacomitinib treatment response in EGFR-amplified recurrent glioblastoma patients

Background: Glioblastoma (GBM) is a highly aggressive and invasive brain tumor associated with high patient mortality. A large fraction of GBM tumors have been identified as epidermal growth factor receptor (EGFR) amplified and ~50% also are EGFRvIII mutant positive. In a previously reported multicenter phase II study, we have described the response of recurrent GBM (rGBM) patients to dacomitinib, an EGFR tyrosine kinase inhibitor (TKI). As a continuation of that report, we leverage the tumor cargo-encapsulating extracellular vesicles (EVs) and explore their genetic composition as carriers of tumor biomarker.

Methods: Serum samples were longitudinally collected from EGFR-amplified rGBM patients who clinically benefitted from dacomitinib therapy (responders) and those who did not (nonresponders), as well as from a healthy cohort of individuals. The serum EV transcriptome was evaluated to map the RNA biotype distribution and distinguish GBM disease.

Results: Using long RNA sequencing, we show enriched detection of over 10 000 coding RNAs from serum EVs. The EV transcriptome yielded a unique signature that facilitates differentiation of GBM patients from healthy donors. Further analysis revealed genetic enrichment that enables stratification of responders from nonresponders prior to dacomitinib treatment as well as following administration.

Conclusion: This study demonstrates that genetic composition analysis of serum EVs may aid in therapeutic stratification to identify patients with dacomitinib-responsive GBM.