Drug and disease signature integration identifies synergistic combinations in glioblastoma

Abstract

Glioblastoma (GBM) is the most common primary adult brain tumor. Despite extensive efforts, the median survival for GBM patients is approximately 14 months. GBM therapy could benefit greatly from patient-specific targeted therapies that maximize treatment efficacy. Here we report a platform termed SynergySeq to identify drug combinations for the treatment of GBM by integrating information from The Cancer Genome Atlas (TCGA) and the Library of Integrated Network-Based Cellular Signatures (LINCS). We identify differentially expressed genes in GBM samples and devise a consensus gene expression signature for each compound using LINCS L1000 transcriptional profiling data. The SynergySeq platform computes disease discordance and drug concordance to identify combinations of FDA-approved drugs that induce a synergistic response in GBM. Collectively, our studies demonstrate that combining disease-specific gene expression signatures with LINCS small molecule perturbagen-response signatures can identify preclinical combinations for GBM, which can potentially be tested in humans.

Polymer Nanoformulation of Sorafenib and All-Trans Retinoic Acid for Synergistic Inhibition of Thyroid Cancer

“…Synergistic drug combinations are promising cancer treatment strategies, which can improve the therapeutic effect by integrating the functions of multiple drugs (Lehar et al, 2009;Stathias et al, 2018). However, there are still some problems in the clinical application, including poor specificity of drug distribution and serious systemic side effects (Boutros et al, 2016).…”

The Clinical Kinase Index: Prioritizing Understudied Kinases as Targets for the Treatment of Cancer

“…It is probable that there exists a strategy for targeting multiple, orthogonal pathways that work in a synergistic manner, as opposed to targeting kinases with overlapping pathways. The discovery of novel kinase targets may lead to synergy efforts to target orthogonal signaling pathways which will be a crucial strategy for treating the complex disease of cancer [12]. It has already been shown that this strategy may prevent or reduce the incidence of resistance pathways and kinome reprogramming, which is inevitable upon singular treatment with a highly specific kinase drug such as EGFR inhibitor, lapatinib [13, 14].…”

Precision oncology : oncogenic stat3 signalling in brain tumours

“…As any signalling pathway is better represented by a set of genes rather than a single candidate, we established a transcriptomic signature representing the STAT3 pathway activation status (Appendix A). A recent study demonstrated that drug-treated GBM cells contain transcriptomic information that portends prognostic outcome in clinical databases (Stathias et al, 2018). This further suggests that corresponding responder and non-responder patient cohorts can be identified for targeted therapy; thus sparing non-responder patients from unwarranted financial burden and chemotherapeutic side effects.…”

“…These efforts highlight the cellular and molecular heterogeneity in GBM tumours, and further underscores the necessity to prescribe treatment regimens based on a stratified population. Furthermore, a recent study supports that therapeutic resistance is reflected in gene expression profiles of molecular subtypes, and may not correspond to differences in somatic mutations (Stathias et al, 2018). Thus, GPC-derived mouse xenograft models provide a core capability of precision oncology-driven preclinical studies.…”

“…The premise of our approach lies in TCGA studies elucidating that gene expression drives GBM disease progression and prognostic outcome. We therefore tapped into a recent article where drug and disease signature integration identifies synergistic combinations in GBM(Stathias et al, 2018). This study utilized the Library of Integrated Network-Based Cellular Signatures (LINCS) database where several commercial cancer cell lines were treated with FDAapproved and experimental small molecule drugs, and the transcriptomic profile of each treated cell line was acquired(Keenan et al, 2018).…”