Response-Predictive Gene Expression Profiling of Glioma Progenitor Cells In Vitro

Abstract

BackgroundHigh-grade gliomas are amongst the most deadly human tumors. Treatment results are disappointing. Still, in several trials around 20% of patients respond to therapy. To date, diagnostic strategies to identify patients that will profit from a specific therapy do not exist.MethodsIn this study, we used serum-free short-term treated in vitro cell cultures to predict treatment response in vitro. This approach allowed us (a) to enrich specimens for brain tumor initiating cells and (b) to confront cells with a therapeutic agent before expression profiling.ResultsAs a proof of principle we analyzed gene expression in 18 short-term serum-free cultures of high-grade gliomas enhanced for brain tumor initiating cells (BTIC) before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated progenitor cells allowed to predict therapy-induced impairment of proliferation in vitro.ConclusionFor the tyrosine kinase inhibitor Sunitinib used in this dataset, the approach revealed additional predictive information in comparison to the evaluation of classical signaling analysis.

Metformin inhibits proliferation and migration of glioblastoma cells independently of TGF-β2

“…Upon approval by the ethics committee of the University of Regensburg (No 11-103-0182) and after receipt of written informed consent, BTICs were established from resected, untreated human malignant gliomas as previously described. 55 The local neuropathology department established the diagnosis and WHO grading. Routine histopathology was accompanied by testing for IDH1 mutation (by pyrosequencing or conventional Sanger sequencing) and MGMT promoter methylation status (by methylation specific PCR 56 ).…”

Proneural and mesenchymal glioma stem cells display major differences in splicing and lncRNA profiles

“…In particular, CLK4 was included in a 6-gene signature that predicts cell proliferation of high-grade glioma cultures after in vitro treatment with the tyrosine kinase inhibitor sunitinib. 54 PHF5A, a component of the spliceosome machinery, maintains proper exon recognition of C-rich 3′ splice sites in GSCs derived from GBM patients, and its knockdown leads to cell cycle arrest and loss of viability. 55 Depletion of PRPF40B modulates ASS selection of apoptotic genes through direct interactions with SF1 and U2AF2, leading to decreased cell survival.…”

Fridge: Focused fine‐tuning of ridge regression for personalized predictions

“…Lastly, we compare fridge to standard ridge in a simulation study based on real high‐dimensional covariates, with simulated y i and known β coefficients. The data consist of gene expression profiles measured in 40 glioma patients, and the data are described and analyzed in detail in Section 6. The simulation was done on the 1000 genes with the largest variance, and was conducted by drawing standard normally distributed residuals, ε i ∼ N (0,1), and regression coefficients from the normal distribution, β ∼ N (0,0.05), to ensure a suitable signal‐to‐noise ratio.…”

“…Decisions regarding treatment for glioma patients are currently based on age and performance status, and increased use of molecular markers would be beneficial. As a follow‐up validation study, 18 samples of high‐grade gliomas were treated with Sunitinib (tyrosine kinase inhibitor) to measure treatment response in terms of decrease in proliferation rate, or cell growth, over a 6‐hour period, compared with a control sample of the same tissue . To illustrate logistic fridge, we dichotomize the outcome in a high and low treatment response group, relative to the median value.…”

“…As a follow-up validation study, 18 samples of high-grade gliomas were treated with Sunitinib (tyrosine kinase inhibitor) to measure treatment response in terms of decrease in proliferation rate, or cell growth, over a 6-hour period, compared with a control sample of the same tissue. 21 To illustrate logistic fridge, we dichotomize the outcome in a high and low treatment response group, relative to the median value. Before treatment, genetic expression profiles of 19 410 genes were measured using Affymetrix Human gene 1.1 arrays, and for analysis, we used the 3000 genes most correlated with the treatment response.…”