Microfluidic profiling of apoptosis-related genes after treatment with BH3-mimetic agents in astrocyte and glioblastoma cell lines

Abstract

Glioblastoma (GB) is the most frequent and biologically the most aggressive primary brain tumor in adults. Standard treatment for newly diagnosed GB consists of surgical resection, radiotherapy and chemotherapy. Resistance to therapy is a major obstacle, even with optimal treatment with a survival median of only 12-15 months. The heterogeneity and treatment response of GB makes this tumor type a challenging area of research. The aim of our study was to study the response of normal human astrocyte (HA) and human GB (T98G) cell lines to apoptosis inhibitors in vitro. ABT-737 is an inhibitor of anti-apoptotic proteins Bcl-2, Bcl-xL, Bcl-w, while MIM-1 is an Mcl-1 protein inhibitor. The viability of the cells was assayed biochemically using the cytotoxic methyl thiazolyl tetrazolium (MTT) assay. Changes in the expression of apoptosis-associated genes (n=93) in two human brain cell lines after treatment with the apoptosis inhibitors ABT-737 and MIM-1 (individually), between the apoptosis inhibitor treated group and the control group, were determined using a commercially pre-designed microfluidic array. Significant changes in apoptotic gene expression with more than a 2.0-fold difference in their expression levels were obtained in both cell lines; the most altered genes were in the HA cell line after MIM-1 treatment (n=42). These results contribute to the importance of apoptosis in normal and cancerous brain tissues and provide information on the effect of apoptosis inhibitors on cell viability and gene expression. Despite extensive investigations, a cure for GB is currently not available. The identification of an apoptotic gene panel and determining the sensitivity of normal and GB brain cells to individual apoptosis inhibitors could help to improve clinical practice and increase our understanding of brain tumor cell metabolism and apoptosis inhibitors in GB cells and astrocytes. Recognizing expression changes in pro-apoptotic and anti-apoptotic genes could contribute to the development of new treatments.