BIOM-13. MICROPERFUSION-MEDIATED SOLUBLE EXTRACELLULAR ENVIRONMENT ANALYSIS FOR DETERMINATION OF CHEMOTHERAPEUTIC EFFICACY IN BRAIN TUMORS

Abstract Glioblastoma (GBM) is the most prevalent and lethally recurrent central nervous system neoplasm, but its therapeutic advancement has stagnated for over 15 years. One major hurdle in front of clinical breakthroughs has been the relative lack of real-time, treatment-responsive biomarkers that occur during therapy. The methods of microdialysis and microperfusion, now entering both clinical and pre-clinical settings, offers an opportunity to overcome this hurdle by providing real-time, biologically relevant monitoring of the tumor microenvironment (TME). The goal of this project is to identify changes in the soluble extra-cellular regional environment of the tumor (SECRETome) of GBM in response to standard-of-care treatments using intra-tumoral microperfusion. In this study, we evaluated the response of murine GBM tumors to temozolomide (TMZ) during therapy by combining transcriptional changes to metabolic phenotypes obtained from SECRETome analysis. Our data demonstrated a 2-fold increase in levels of microperfusion-sampled 2-hydroxyglutarate (2-HG) on day 3 post-TMZ therapy as compared to untreated tumors. This expression is correlated with our RNAseq analysis wherein we observed an >600 fold increase in malate dehydrogenase 1 (MDH1 - an enzyme that converts alpha-ketoglutarate to 2-HG) on Day 4 post-TMZ treatment (p = 4.20e-04) as compared to untreated tumors. Therefore, we found that interstitial elevation of a TMZ-associated metabolite can be used to probe the genetic changes that occur within GBM during therapy. This proof-of-concept study demonstrates that microperfusion-mediated TME sampling can be used to understand the complex biological responses process that occurs during GBM chemotherapy, and may provide unique insights into how to better treat these tumors in the future. Moreover, the future establishment of clinical intra-operative microdialysis/microperfusion can be extrapolated to improve the pace of clinical therapeutic translation through homologous, treatment-responsive biomarkers in humans.