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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.

SUBMITTER: Stathias V

PROVIDER: S-EPMC6294341 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Drug and disease signature integration identifies synergistic combinations in glioblastoma.

Stathias Vasileios V Jermakowicz Anna M AM Maloof Marie E ME Forlin Michele M Walters Winston W Suter Robert K RK Durante Michael A MA Williams Sion L SL Harbour J William JW Volmar Claude-Henry CH Lyons Nicholas J NJ Wahlestedt Claes C Graham Regina M RM Ivan Michael E ME Komotar Ricardo J RJ Sarkaria Jann N JN Subramanian Aravind A Golub Todd R TR Schürer Stephan C SC Ayad Nagi G NG

Nature communications 20181214 1

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). ...[more]

PMID: 30552330

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Project description:Glioblastoma (GBM) is a highly aggressive and heterogeneous form of brain cancer. Genotypic and phenotypic heterogeneity drives drug resistance and tumor recurrence. Combination chemotherapy could overcome drug resistance; however, GBM's location behind the blood-brain barrier severely limits chemotherapeutic options. Interstitial therapy, delivery of chemotherapy locally to the tumor site, via a biodegradable polymer implant can overcome the blood-brain barrier and increase the range of drugs available for therapy. Ideal drug candidates for interstitial therapy are those that are potent against GBM and work in combination with both standard-of-care therapy and new precision medicine targets. Herein we evaluated paclitaxel for interstitial therapy, investigating the effect of combination with both temozolomide, a clinical standard-of-care chemotherapy for GBM, and everolimus, a mammalian target of rapamycin (mTOR) inhibitor that modulates aberrant signaling present in >80% of GBM patients. Tested against a panel of GBM cell lines in vitro, paclitaxel was found to be effective at nanomolar concentrations, complement therapy with temozolomide, and synergize strongly with everolimus. The strong synergism seen with paclitaxel and everolimus was then explored in vivo. Paclitaxel and everolimus were separately formulated into fibrous scaffolds composed of acetalated dextran, a biodegradable polymer with tunable degradation rates, for implantation in the brain. Acetalated dextran degradation rates were tailored to attain matching release kinetics (~3% per day) of both paclitaxel and everolimus to maintain a fixed combination ratio of the two drugs. Combination interstitial therapy of both paclitaxel and everolimus significantly reduced GBM growth and improved progression free survival in two clinically relevant orthotopic models of GBM resection and recurrence. This work illustrates the advantages of synchronized interstitial therapy of paclitaxel and everolimus for post-surgical tumor control of GBM.

Project description:BackgroundGlioblastoma multiforme (GBM) is a highly lethal, stage IV brain tumour with a prevalence of approximately 2 per 10,000 people globally. The cell surface proteins or surfaceome serve as information gateway in many oncogenic signalling pathways and are important in modulating cancer phenotypes. Dysregulation in surfaceome expression and activity have been shown to promote tumorigenesis. The expression of GBM surfaceome is a case in point; OMICS screening in a cell-based system identified that this sub-proteome is largely perturbed in GBM. Additionally, since these cell surface proteins have 'direct' access to drugs, they are appealing targets for cancer therapy. However, a comprehensive GBM surfaceome landscape has not been fully defined yet. Thus, this study aimed to define GBM-associated surfaceome genes and identify key cell-surface genes that could potentially be developed as novel GBM biomarkers for therapeutic purposes.MethodsWe integrated the RNA-Seq data from TCGA GBM (n = 166) and GTEx normal brain cortex (n = 408) databases to identify the significantly dysregulated surfaceome in GBM. This was followed by an integrative analysis that combines transcriptomics, proteomics and protein-protein interaction network data to prioritize the high-confidence GBM surfaceome signature.ResultsOf the 2381 significantly dysregulated genes in GBM, 395 genes were classified as surfaceome. Via the integrative analysis, we identified 6 high-confidence GBM molecular signature, HLA-DRA, CD44, SLC1A5, EGFR, ITGB2, PTPRJ, which were significantly upregulated in GBM. The expression of these genes was validated in an independent transcriptomics database, which confirmed their upregulated expression in GBM. Importantly, high expression of CD44, PTPRJ and HLA-DRA is significantly associated with poor disease-free survival. Last, using the Drugbank database, we identified several clinically-approved drugs targeting the GBM molecular signature suggesting potential drug repurposing.ConclusionsIn summary, we identified and highlighted the key GBM surface-enriched repertoires that could be biologically relevant in supporting GBM pathogenesis. These genes could be further interrogated experimentally in future studies that could lead to efficient diagnostic/prognostic markers or potential treatment options for GBM.

Project description:BackgroundMelanoma is the most aggressive and deadly form of skin cancer with increasing case numbers worldwide. The development of inhibitors targeting mutated BRAF (found in around 60% of melanoma patients) has markedly improved overall survival of patients with late-stage tumors, even more so when combined with MEK inhibitors targeting the same signaling pathway. However, invariably patients become resistant to this targeted therapy resulting in rapid progression with treatment-refractory disease. The purpose of this study was the identification of new kinase inhibitors that do not lead to the development of resistance in combination with BRAF inhibitors (BRAFi), or that could be of clinical benefit as a 2nd line treatment for late-stage melanoma patients that have already developed resistance.MethodsWe have screened a 274-compound kinase inhibitor library in 3 BRAF mutant melanoma cell lines (each one sensitive or made resistant to 2 distinct BRAFi). The screening results were validated by dose-response studies and confirmed the killing efficacies of many kinase inhibitors. Two different tools were applied to investigate and quantify potential synergistic effects of drug combinations: the Chou-Talalay method and the Synergyfinder application. In order to exclude that resistance to the new treatments might occur at later time points, synergistic combinations were administered to fluorescently labelled parental and resistant cells over a period of > 10 weeks.ResultsEight inhibitors targeting Wee1, Checkpoint kinase 1/2, Aurora kinase, MEK, Polo-like kinase, PI3K and Focal adhesion kinase killed melanoma cells synergistically when combined with a BRAFi. Additionally, combination of a Wee1 and Chk inhibitor showed synergistic killing effects not only on sensitive cell lines, but also on intrinsically BRAFi- and treatment induced-resistant melanoma cells. First in vivo studies confirmed these observations. Interestingly, continuous treatment with several of these drugs, alone or in combination, did not lead to emergence of resistance.ConclusionsHere, we have identified new, previously unexplored (in the framework of BRAFi resistance) inhibitors that have an effect not only on sensitive but also on BRAFi-resistant cells. These promising combinations together with the new immunotherapies could be an important step towards improved 1st and 2nd line treatments for late-stage melanoma patients.

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Drug and disease signature integration identifies synergistic combinations in glioblastoma.

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Drug and disease signature integration identifies synergistic combinations in glioblastoma.

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