Comparative drug pair screening across multiple glioblastoma cell lines reveals novel drug-drug interactions
Artikel i vetenskaplig tidskrift, 2013

Glioblastoma multiforme (GBM) is the most aggressive brain tumor in adults, and despite state-of-the-art treatment, survival remains poor and novel therapeutics are sorely needed. The aim of the present study was to identify new synergistic drug pairs for GBM. In addition, we aimed to explore differences in drug-drug interactions across multiple GBM-derived cell cultures and predict such differences by use of transcriptional biomarkers. We performed a screen in which we quantified drug-drug interactions for 465 drug pairs in each of the 5 GBM cell lines U87MG, U343MG, U373MG, A172, and T98G. Selected interactions were further tested using isobole-based analysis and validated in 5 glioma-initiating cell cultures. Furthermore, drug interactions were predicted using microarray-based transcriptional profiling in combination with statistical modeling. Of the 5 465 drug pairs, we could define a subset of drug pairs with strong interaction in both standard cell lines and glioma-initiating cell cultures. In particular, a subset of pairs involving the pharmaceutical compounds rimcazole, sertraline, pterostilbene, and gefitinib showed a strong interaction in a majority of the cell cultures tested. Statistical modeling of microarray and interaction data using sparse canonical correlation analysis revealed several predictive biomarkers, which we propose could be of importance in regulating drug pair responses. We identify novel candidate drug pairs for GBM and suggest possibilities to prospectively use transcriptional biomarkers to predict drug interactions in individual cases.

tumor

temozolomide

drug combination responses

cultures

antidepressant sertraline

gene

predictive medicine

classification

glioblastoma therapy

therapeutics

carcinoma

glioblastoma stem cell

apoptosis

combination

progression

Författare

L. Schmidt

T. Kling

N. Monsefi

M. Olsson

C. Hansson

S. Baskaran

B. Lundgren

U. Martens

M. Haggblad

B. Westermark

K. F. Nilsson

L. Uhrbom

L. Karlsson-Lindahl

Philip Gerlee

Chalmers, Matematiska vetenskaper, Matematik

Göteborgs universitet

S. Nelander

Neuro-Oncology

1522-8517 (ISSN)

Vol. 15 11 1469-1478

Ämneskategorier

Cancer och onkologi

DOI

10.1093/neuonc/not111