197 | Development of a preclinical algorithm for the selection of potentially effective drugs for Glioblastoma treatment and in vitro validation

Disorders of the Nervous System

Author: Melanie Ailen Pérez Küper | Email: melaniepk@hotmail.com

Melanie Pérez Küper , Nazareno Gonzalez , Matías Garcia Fallit , Jorge A. Peña Agudelo , Alejandro Nicola Candia , Adriana Seilicovich , Marianela Candolfi

1° Instituto de Investigaciones Biomédicas (INBIOMED, CONICET-UBA), Facultad de Medicina, Universidad de Buenos Aires, Argentina.
2° Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Argentina
3° Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina.
4° Departamento de Biología Celular e Histología, Facultad de Medicina, Universidad de Buenos Aires, Argentina.

Glioblastoma (GBM) is the most frequent primary malignant brain tumor in adults. Although the survival of these patients is ~12 months, their treatment, i.e. surgery, chemotherapy with temozolomide and radiation, has not changed since 2005.
We developed an in silico model for the selection of potentially effective drugs that are used in the clinic. We used gene expression and drug sensitivity data (IC50) of cancer cell lines from the Genomics of Drug Sensitivity in Cancer (GDSC) database and applied this algorithm to predict IC50 values for GBM samples deposited in The Cancer Genome Atlas (TCGA). Following validation steps, we selected chemotherapeutic drugs that met parameters such as high predicted sensitivity for GBM, ability to cross the blood-brain barrier, overexpression of the target in GBM vs. normal tissue, and correlation with worse prognosis.
We initiated the in vitro evaluation of Etoposide, an inhibitor of topoisomerase II (TOP2). We assessed the effect of Etoposide on the viability of the GBM cell lines with high (U-87) and low (U251) TOP2 expression. We found that GBM cells were much more sensitive to Etoposide than to temozolomide, and their sensitivity was dependent on TOP2 expression levels (higher TOP2 levels led to higher IC50 values). Etoposide did not exert toxicity in primary mouse astrocytes at the therapeutically effective concentrations. Our findings suggest that this algorithm could help to rationally select drugs for preclinical evaluation.