Dasatinib in recurrent glioblastoma: failure as a teacher

Glioblastoma treatment slowly moves toward change: novel druggable targets and translational horizons in 2022

INTRODUCTION

Glioblastoma (GBM) is the most common primary brain tumor in adults. GBM treatment options have been the same for the past 30 years and have only modestly extended survival, despite aggressive multimodal treatments. The progressively better knowledge of GBM biology and a comprehensive analysis of its genomic profile have elucidated GBM heterogeneity, contributing to a more effective molecular classification and to the development of innovative targeted therapeutic approaches.

AREAS COVERED

This article reports all the noteworthy innovations for immunotherapy and targeted therapy, providing insights into the current advances in trial designs, including combination therapies with immuno-oncology agents and target combinations.

EXPERT OPINION

GBM molecular heterogeneity and brain anatomical characteristics critically restrain drug effectiveness. Nevertheless, stimulating insights for future research and drug development come from innovative treatment strategies for GBM, such as multi-specific 'off-the-shelf' CAR-T therapy, oncolytic viral therapy and autologous dendritic cell vaccination. Disappointing results from targeted therapies-clinical trials are mainly due to complex interferences between signaling pathways and biological processes leading to drug resistance: hence, it is imperative in the future to develop combinatorial approaches and multimodal therapies.

Integrative genomic analysis facilitates precision strategies for glioblastoma treatment

Glioblastoma (GBM) is the most common form of malignant primary brain tumor with a dismal prognosis. Currently, the standard treatments for GBM rarely achieve satisfactory results, which means that current treatments are not individualized and precise enough. In this study, a multiomics-based GBM classification was established and three subclasses (GPA, GPB, and GPC) were identified, which have different molecular features both in bulk samples and at single-cell resolution. A robust GBM poor prognostic signature (GPS) score model was then developed using machine learning method, manifesting an excellent ability to predict the survival of GBM. NVP−BEZ235, GDC−0980, dasatinib and XL765 were ultimately identified to have subclass-specific efficacy targeting patients with a high risk of poor prognosis. Furthermore, the GBM classification and GPS score model could be considered as potential biomarkers for immunotherapy response. In summary, an integrative genomic analysis was conducted to advance individual-based therapies in GBM.

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A multiomics-based classification of GBM was established

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Single-cell transcriptomic profiling of GBM subclasses was revealed using Scissor

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A robust prognostic risk model was developed for GBM by machine learning method

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Prediction of potential agents based on molecular and prognostic risk stratification

Small Molecule Inhibitors in Adult High-Grade Glioma: From the Past to the Future

Glioblastoma is the most common primary malignant tumor in the brain and has a dismal prognosis despite patients accepting standard therapies. Alternation of genes and deregulation of proteins, such as receptor tyrosine kinase, PI3K/Akt, PKC, Ras/Raf/MEK, histone deacetylases, poly (ADP-ribose) polymerase (PARP), CDK4/6, branched-chain amino acid transaminase 1 (BCAT1), and Isocitrate dehydrogenase (IDH), play pivotal roles in the pathogenesis and progression of glioma. Simultaneously, the abnormalities change the cellular biological behavior and microenvironment of tumor cells. The differences between tumor cells and normal tissue become the vulnerability of tumor, which can be taken advantage of using targeted therapies. Small molecule inhibitors, as an important part of modern treatment for cancers, have shown significant efficacy in hematologic cancers and some solid tumors. To date, in glioblastoma, there have been more than 200 clinical trials completed or ongoing in which trial designers used small molecules as monotherapy or combination regimens to correct the abnormalities. In this review, we summarize the dysfunctional molecular mechanisms and highlight the outcomes of relevant clinical trials associated with small-molecule targeted therapies. Based on the outcomes, the main findings were that small-molecule inhibitors did not bring more benefit to newly diagnosed glioblastoma, but the clinical studies involving progressive glioblastoma usually claimed “noninferiority” compared with historical results. However, as to the clinical inferiority trial, similar dosing regimens should be avoided in future clinical trials.

Patient-Derived Tumor Organoids for Guidance of Personalized Drug Therapies in Recurrent Glioblastoma

An obstacle to effective uniform treatment of glioblastoma, especially at recurrence, is genetic and cellular intertumoral heterogeneity. Hence, personalized strategies are necessary, as are means to stratify potential targeted therapies in a clinically relevant timeframe. Functional profiling of drug candidates against patient-derived glioblastoma organoids (PD-GBO) holds promise as an empirical method to preclinically discover potentially effective treatments of individual tumors. Here, we describe our establishment of a PD-GBO-based functional profiling platform and the results of its application to four patient tumors. We show that our PD-GBO model system preserves key features of individual patient glioblastomas in vivo. As proof of concept, we tested a panel of 41 FDA-approved drugs and were able to identify potential treatment options for three out of four patients; the turnaround from tumor resection to discovery of treatment option was 13, 14, and 15 days, respectively. These results demonstrate that this approach is a complement and, potentially, an alternative to current molecular profiling efforts in the pursuit of effective personalized treatment discovery in a clinically relevant time period. Furthermore, these results warrant the use of PD-GBO platforms for preclinical identification of new drugs against defined morphological glioblastoma features.

Signaling pathways and therapeutic approaches in glioblastoma multiforme (Review)

Glioblastoma multiforme (GBM) is the most aggressive type of primary brain tumor and is associated with a poor clinical prognosis. Despite the progress in the understanding of the molecular and genetic changes that promote tumorigenesis, effective treatment options are limited. The present review intended to identify and summarize major signaling pathways and genetic abnormalities involved in the pathogenesis of GBM, as well as therapies that target these pathways. Glioblastoma remains a difficult to treat tumor; however, in the last two decades, significant improvements in the understanding of GBM biology have enabled advances in available therapeutics. Significant genomic events and signaling pathway disruptions (NF‑κB, Wnt, PI3K/AKT/mTOR) involved in the formation of GBM were discussed. Current therapeutic options may only marginally prolong survival and the current standard of therapy cures only a small fraction of patients. As a result, there is an unmet requirement for further study into the processes of glioblastoma pathogenesis and the discovery of novel therapeutic targets in novel signaling pathways implicated in the evolution of glioblastoma.

In Vitro Validation of the Therapeutic Potential of Dendrimer-Based Nanoformulations against Tumor Stem Cells

Tumor cells with stem cell properties are considered to play major roles in promoting the development and malignant behavior of aggressive cancers. Therapeutic strategies that efficiently eradicate such tumor stem cells are of highest clinical need. Herein, we performed the validation of the polycationic phosphorus dendrimer-based approach for small interfering RNAs delivery in in vitro stem-like cells as models. As a therapeutic target, we chose Lyn, a member of the Src family kinases as an example of a prominent enzyme class widely discussed as a potent anti-cancer intervention point. Our selection is guided by our discovery that Lyn mRNA expression level in glioma, a class of brain tumors, possesses significant negative clinical predictive value, promoting its potential as a therapeutic target for future molecular-targeted treatments. We then showed that anti-Lyn siRNA, delivered into Lyn-expressing glioma cell model reduces the cell viability, a fact that was not observed in a cell model that lacks Lyn-expression. Furthermore, we have found that the dendrimer itself influences various parameters of the cells such as the expression of surface markers PD-L1, TIM-3 and CD47, targets for immune recognition and other biological processes suggested to be regulating glioblastoma cell invasion. Our findings prove the potential of dendrimer-based platforms for therapeutic applications, which might help to eradicate the population of cancer cells with augmented chemotherapy resistance. Moreover, the results further promote our functional stem cell technology as suitable component in early stage drug development.

Transcriptomic Portraits and Molecular Pathway Activation Features of Adult Spinal Intramedullary Astrocytomas

In this study, we report 31 spinal intramedullary astrocytoma (SIA) RNA sequencing (RNA-seq) profiles for 25 adult patients with documented clinical annotations. To our knowledge, this is the first clinically annotated RNA-seq dataset of spinal astrocytomas derived from the intradural intramedullary compartment. We compared these tumor profiles with the previous healthy central nervous system (CNS) RNA-seq data for spinal cord and brain and identified SIA-specific gene sets and molecular pathways. Our findings suggest a trend for SIA-upregulated pathways governing interactions with the immune cells and downregulated pathways for the neuronal functioning in the context of normal CNS activity. In two patient tumor biosamples, we identified diagnostic KIAA1549-BRAF fusion oncogenes, and we also found 16 new SIA-associated fusion transcripts. In addition, we bioinformatically simulated activities of targeted cancer drugs in SIA samples and predicted that several tyrosine kinase inhibitory drugs and thalidomide analogs could be potentially effective as second-line treatment agents to aid in the prevention of SIA recurrence and progression.

Uncovering Spatiotemporal Heterogeneity of High-Grade Gliomas: From Disease Biology to Therapeutic Implications

Glioblastomas (GBM) are the most common and aggressive tumors of the central nervous system. Rapid tumor growth and diffuse infiltration into healthy brain tissue, along with high intratumoral heterogeneity, challenge therapeutic efficacy and prognosis. A better understanding of spatiotemporal tumor heterogeneity at the histological, cellular, molecular, and dynamic levels would accelerate the development of novel treatments for this devastating brain cancer. Histologically, GBM is characterized by nuclear atypia, cellular pleomorphism, necrosis, microvascular proliferation, and pseudopalisades. At the cellular level, the glioma microenvironment comprises a heterogeneous landscape of cell populations, including tumor cells, non-transformed/reactive glial and neural cells, immune cells, mesenchymal cells, and stem cells, which support tumor growth and invasion through complex network crosstalk. Genomic and transcriptomic analyses of gliomas have revealed significant inter and intratumoral heterogeneity and insights into their molecular pathogenesis. Moreover, recent evidence suggests that diverse dynamics of collective motion patterns exist in glioma tumors, which correlate with histological features. We hypothesize that glioma heterogeneity is not stochastic, but rather arises from organized and dynamic attributes, which favor glioma malignancy and influences treatment regimens. This review highlights the importance of an integrative approach of glioma histopathological features, single-cell and spatially resolved transcriptomic and cellular dynamics to understand tumor heterogeneity and maximize therapeutic effects.

A novel patient stratification strategy to enhance the therapeutic efficacy of dasatinib in glioblastoma

BACKGROUND

Glioblastoma is the most common primary malignancy of the central nervous system with dismal prognosis. Genomic signatures classify isocitrate dehydrogenase 1 (IDH)-wildtype glioblastoma into three subtypes: proneural, mesenchymal and classical. Dasatinib, an inhibitor of proto-oncogene kinase Src (SRC), is one of many therapeutics which, despite promising preclinical results, has failed to improve overall survival in glioblastoma patients in clinical trials. We examined whether glioblastoma subtypes differ in their response to dasatinib and could hence be evaluated for patient enrichment strategies in clinical trials.

METHODS

We carried out in silico analyses on glioblastoma gene expression (TCGA) and single-cell RNA-Seq data. In addition, in vitro experiments using glioblastoma stem-like cells (GSCs) derived from primary patient tumors were performed, with complementary gene expression profiling and immunohistochemistry analysis of tumor samples.

RESULTS

Patients with the mesenchymal subtype of glioblastoma showed higher SRC pathway activation based on gene expression profiling. Accordingly, mesenchymal GSCs were more sensitive to SRC inhibition by dasatinib compared to proneural and classical GSCs. Notably, SRC phosphorylation status did not predict response to dasatinib treatment. Furthermore, serpin peptidase inhibitor clade H member 1 (SERPINH1), a collagen related heat-shock protein associated with cancer progression, was shown to correlate with dasatinib response and with the mesenchymal subtype.

CONCLUSION

This work highlights further molecular-based patient selection strategies in clinical trials and suggests the mesenchymal subtype as well as SERPINH1 to be associated with response to dasatinib. Our findings indicate that stratification based on gene expression subtyping should be considered in future dasatinib trials.

Inhibitors of Src Family Kinases, Inducible Nitric Oxide Synthase, and NADPH Oxidase as Potential CNS Drug Targets for Neurological Diseases

Neurological diseases share common neuroinflammatory and oxidative stress pathways. Both phenotypic and molecular changes in microglia, astrocytes, and neurons contribute to the progression of disease and present potential targets for disease modification. Src family kinases (SFKs) are present in both neurons and glial cells and are upregulated following neurological insults in both human and animal models. In neurons, SFKs interact with post-synaptic protein domains to mediate hyperexcitability and neurotoxicity. SFKs are upstream of signaling cascades that lead to the modulation of neurotransmitter receptors and the transcription of pro-inflammatory cytokines as well as producers of free radicals through the activation of glia. Inducible nitric oxide synthase (iNOS/NOS-II) and nicotinamide adenine dinucleotide phosphate (NADPH) oxidase 2 (NOX2), the major mediators of reactive nitrogen/oxygen species (RNS/ROS) production in the brain, are also upregulated along with the pro-inflammatory cytokines following neurological insult and contribute to disease progression. Persistent neuronal hyperexcitability, RNS/ROS, and cytokines can exacerbate neurodegeneration, a common pathognomonic feature of the most prevalent neurological disorders such as Alzheimer's disease, Parkinson's disease, and epilepsy. Using a wide variety of preclinical disease models, inhibitors of the SFK-iNOS-NOX2 signaling axis have been tested to cure or modify disease progression. In this review, we discuss the SFK-iNOS-NOX2 signaling pathway and their inhibitors as potential CNS targets for major neurological diseases.

Connexin43 Region 266-283, via Src Inhibition, Reduces Neural Progenitor Cell Proliferation Promoted by EGF and FGF-2 and Increases Astrocytic Differentiation

Neural progenitor cells (NPCs) are self-renewing cells that give rise to the major cells in the nervous system and are considered to be the possible cell of origin of glioblastoma. The gap junction protein connexin43 (Cx43) is expressed by NPCs, exerting channel-dependent and -independent roles. We focused on one property of Cx43—its ability to inhibit Src, a key protein in brain development and oncogenesis. Because Src inhibition is carried out by the sequence 266–283 of the intracellular C terminus in Cx43, we used a cell-penetrating peptide containing this sequence, TAT-Cx43_266–283, to explore its effects on postnatal subventricular zone NPCs. Our results show that TAT-Cx43_266–283 inhibited Src activity and reduced NPC proliferation and survival promoted by epidermal growth factor (EGF) and fibroblast growth factor-2 (FGF-2). In differentiation conditions, TAT-Cx43_266–283 increased astrocyte differentiation at the expense of neuronal differentiation, which coincided with a reduction in Src activity and β-catenin expression. We propose that Cx43, through the region 266–283, reduces Src activity, leading to disruption of EGF and FGF-2 signaling and to down-regulation of β-catenin with effects on proliferation and differentiation. Our data indicate that the inhibition of Src might contribute to the complex role of Cx43 in NPCs and open new opportunities for further research in gliomagenesis.

Cell Lineage-Based Stratification for Glioblastoma

Glioblastoma, the predominant adult malignant brain tumor, has been computationally classified into molecular subtypes whose functional relevance remains to be comprehensively established. Tumors from genetically engineered glioblastoma mouse models initiated by identical driver mutations in distinct cells of origin portray unique transcriptional profiles reflective of their respective lineage. Here, we identify corresponding transcriptional profiles in human glioblastoma and describe patient-derived xenografts with species-conserved subtype-discriminating functional properties. The oligodendrocyte lineage-associated glioblastoma subtype requires functional ERBB3 and harbors unique therapeutic sensitivities. These results highlight the importance of cell lineage in glioblastoma independent of driver mutations and provide a methodology for functional glioblastoma classification for future clinical investigations.

Mining Drug-Target Associations in Cancer: Analysis of Gene Expression and Drug Activity Correlations

Cancer is a complex disease affecting millions of people worldwide, with over a hundred clinically approved drugs available. In order to improve therapy, treatment, and response, it is essential to draw better maps of the targets of cancer drugs and possible side interactors. This study presents a large-scale screening method to find associations of cancer drugs with human genes. The analysis is focused on the current collection of Food and Drug Administration (FDA)-approved drugs (which includes about one hundred chemicals). The approach integrates global gene-expression transcriptomic profiles with drug-activity profiles of a set of 60 human cell lines obtained for a collection of chemical compounds (small bioactive molecules). Using a standardized expression for each gene versus standardized activity for each drug, Pearson and Spearman correlations were calculated for all possible pairwise gene-drug combinations. These correlations were used to build a global bipartite network that includes 1007 gene-drug significant associations. The data are integrated into an open web-tool called GEDA (Gene Expression and Drug Activity) which includes a relational view of cancer drugs and genes, disclosing the putative indirect interactions found for FDA-approved drugs as well as the known targets of these drugs. The results also provide insight into the complex action of pharmaceuticals, presenting an alternative view to address predicted pleiotropic effects of the drugs.

Small molecule tyrosine kinase inhibitors in glioblastoma

Glioblastoma (GBM) is the most common malignant primary brain tumor, with poor survival despite treatment with surgery, radiotherapy, and chemotherapy with temozolomide. Little progress has been made over the last two decades, and there remain unmet medical needs. Approximately 45% of patients with GBM carry EGFR mutations, and 13% of them possess altered PDGFR genes. Moreover, VEGF/VEGFR mutations are also observed in the patient population. Tyrosine kinase inhibitors (TKIs) are emerging cancer therapy drugs that inhibit signal transduction cascades affecting cell proliferation, migration, and angiogenesis. Indications for small molecule TKIs have been successfully expanded to multiple types of cancer; however, none of the TKIs have been approved for patients with GBM. In this review, we summarize clinical trials of small molecule TKIs in patients with GBM and plausible hypotheses for negative clinical study results. We also discuss the potential TKI candidates that presented significant preclinical outcomes in patients with GBM.

Feasibility of Targeting Glioblastoma Stem Cells: From Concept to Clinical Trials

OBJECTIVE

Glioblastoma is a highly aggressive and invasive brain and Central Nervous System (CNS) tumor. Current treatment options do not prolong overall survival significantly because the disease is highly prone to relapse. Therefore, research to find new therapies is of paramount importance. It has been discovered that glioblastomas contain a population of cells with stem-like properties and that these cells are may be responsible for tumor recurrence.

METHODS

A review of relevant papers and clinical trials in the field was conducted. A PubMed search with related keywords was used to gather the data. For example, "glioblastoma stem cells AND WNT signaling" is an example used to find information on clinical trials using the database ClinicalTrials.gov.

RESULTS

Cancer stem cell research has several fundamental issues and uncertainties that should be taken into consideration. Theoretically, a number of treatment options that target glioblastoma stem cells are available for patients. However, only a few of them have obtained promising results in clinical trials. Several strategies are still under investigation.

CONCLUSION

The majority of treatments to target cancer stem cells have failed during clinical trials. Taking into account a number of biases in the field and the number of unsuccessful investigations, the application of the cancer stem cells concept is questionable in clinical settings, at least with respect to glioblastoma.

Dissecting the role of crosstalk between glioblastoma subpopulations in tumor cell spreading

Glioblastoma (GBM) is a highly infiltrative brain cancer, which is thus difficult to operate. GBM cells frequently harbor Epidermal Growth Factor Receptor amplification (EGFRwt) and/or activating mutation (EGFRvIII), generating at least two different cellular subpopulations within the tumor. We examined the relationship between the diffusive architectures of GBM tumors and the paracrine interactions between those subpopulations. Our aim was to shed light on what drives GBM cells to reach large cell–cell distances, and whether this characteristic can be manipulated. We established a methodology that quantifies the infiltration abilities of cancer cells through computation of cell–cell separation distance distributions in 3D. We found that aggressive EGFRvIII cells modulate the migration and infiltrative properties of EGFRwt cells. EGFRvIII cells secrete HGF and IL6, leading to enhanced activity of Src protein in EGFRwt cells, and rendering EGFRwt cells higher velocity and augmented ability to spread. Src inhibitor, dasatinib, at low non-toxic concentrations, reduced the infiltrative properties of EGFRvIII/EGFRwt neurospheres. Furthermore, dasatinib treatment induced compact multicellular microstructure packing of EGFRvIII/EGFRwt cells, impairing their ability to spread. Prevention of cellular infiltration or induction of compact microstructures may assist the detection of GBM tumors and tumor remnants in the brains and improve their surgical removal.

Ultrasmall Core-Shell Silica Nanoparticles for Precision Drug Delivery in a High-Grade Malignant Brain Tumor Model

PURPOSE

Small-molecule inhibitors have revolutionized treatment of certain genomically defined solid cancers. Despite breakthroughs in treating systemic disease, central nervous system (CNS) metastatic progression is common, and advancements in treating CNS malignancies remain sparse. By improving drug penetration across a variably permeable blood-brain barrier and diffusion across intratumoral compartments, more uniform delivery and distribution can be achieved to enhance efficacy.

EXPERIMENTAL DESIGN

Ultrasmall fluorescent core-shell silica nanoparticles, Cornell prime dots (C' dots), were functionalized with α_v integrin-binding (cRGD), or nontargeting (cRAD) peptides, and PET labels (¹²⁴I, ⁸⁹Zr) to investigate the utility of dual-modality cRGD-C' dots for enhancing accumulation, distribution, and retention (ADR) in a genetically engineered mouse model of glioblastoma (mGBM). mGBMs were systemically treated with ¹²⁴I-cRGD- or ¹²⁴I-cRAD-C' dots and sacrificed at 3 and 96 hours, with concurrent intravital injections of FITC-dextran for mapping blood-brain barrier breakdown and the nuclear stain Hoechst. We further assessed target inhibition and ADR following attachment of dasatinib, creating nanoparticle-drug conjugates (Das-NDCs). Imaging findings were confirmed with ex vivo autoradiography, fluorescence microscopy, and p-S6RP IHC.

RESULTS

Improvements in brain tumor delivery and penetration, as well as enhancement in the ADR, were observed following administration of integrin-targeted C' dots, as compared with a nontargeted control. Furthermore, attachment of the small-molecule inhibitor, dasatinib, led to its successful drug delivery throughout mGBM, demonstrated by downstream pathway inhibition.

CONCLUSIONS

These results demonstrate that highly engineered C' dots are promising drug delivery vehicles capable of navigating the complex physiologic barriers observed in a clinically relevant brain tumor model.

Conjugation of Dasatinib with MHI-148 Has a Significant Advantageous Effect in Viability Assays for Glioblastoma Cells

We hypothesized that conjugation of the near-infrared dye MHI-148 with the anti-leukemia drug dasatinib might produce a potential theranostic for glioblastoma. In fact, the conjugate was found to bind the kinases Src and Lyn, and to inhibit the viability of a glioblastoma cell line with significantly greater potency than dasatinib alone, MHI-148 alone, or a mixture of dasatinib and MHI-148 at the same concentration. It was also used to successfully image a subcutaneous glioblastoma tumor in vivo.

A Near-IR Fluorescent Dasatinib Derivative That Localizes in Cancer Cells

Kinase inhibitors (KIs) have had a huge impact on clinical treatment of various cancers, but they are far from perfect medicines. In particular, their efficacies are limited to certain cancer types and, in many cases, provide only temporary remission. This paper explores the possibility of covalently binding a fluorophore for in vivo optical imaging to the KI dasatinib where the particular fluorophore chosen for this study, a heptamethine cyanine (Cy) derivative, tends to accumulate in tumors. Thus, we hypothesized that the dasatinib-fluorophore conjugate might target tumor cells more effectively than the parent KI, give enhanced suppression of viability, and simultaneously serve as a probe for optical imaging. As far as we are aware, the dasatinib conjugate (1) is the first reported to contain this KI and a probe for near-IR imaging, and it is certainly the first conjugate of a tumor-targeting near-IR dye and a KI of any kind. Conjugate 1 suppressed the viability of liver cancer cells (HepG2) more effectively than dasatinib at the same concentration. In scratch assays, 1 prevented regrowth of the tumor cells. Conjugate 1 is cell permeable, and confocal imaging indicates the fluorescence of those cells is concentrated in the mitochondria than lysosomes. In general, this study suggests there is untapped potential for conjugates of KIs with tumor-targeting near-IR dyes in the development of theranostics for optical imaging and treatment of cancer.

Impact of Variable RNA-Sequencing Depth on Gene Expression Signatures and Target Compound Robustness: Case Study Examining Brain Tumor (Glioma) Disease Progression

Purpose

Gene expression profiling can uncover biologic mechanisms underlying disease and is important in drug development. RNA sequencing (RNA-seq) is routinely used to assess gene expression, but costs remain high. Sample multiplexing reduces RNA-seq costs; however, multiplexed samples have lower cDNA sequencing depth, which can hinder accurate differential gene expression detection. The impact of sequencing depth alteration on RNA-seq–based downstream analyses such as gene expression connectivity mapping is not known, where this method is used to identify potential therapeutic compounds for repurposing.

Methods

In this study, published RNA-seq profiles from patients with brain tumor (glioma) were assembled into two disease progression gene signature contrasts for astrocytoma. Available treatments for glioma have limited effectiveness, rendering this a disease of poor clinical outcome. Gene signatures were subsampled to simulate sequencing alterations and analyzed in connectivity mapping to investigate target compound robustness.

Results

Data loss to gene signatures led to the loss, gain, and consistent identification of significant connections. The most accurate gene signature contrast with consistent patient gene expression profiles was more resilient to data loss and identified robust target compounds. Target compounds lost included candidate compounds of potential clinical utility in glioma (eg, suramin, dasatinib). Lost connections may have been linked to low-abundance genes in the gene signature that closely characterized the disease phenotype. Consistently identified connections may have been related to highly expressed abundant genes that were ever-present in gene signatures, despite data reductions. Potential noise surrounding findings included false-positive connections that were gained as a result of gene signature modification with data loss.

Conclusion

Findings highlight the necessity for gene signature accuracy for connectivity mapping, which should improve the clinical utility of future target compound discoveries.

Investigational new drugs for brain cancer

INTRODUCTION

Despite substantial improvements in standards of care, the most common aggressive pediatric and adult high-grade gliomas (HGG) carry uniformly fatal diagnoses due to unique treatment limitations, high recurrence rates and the absence of effective treatments following recurrence. Recent advancements in our understanding of the pathophysiology, genetics and epigenetics as well as mechanisms of immune surveillance during gliomagenesis have created new knowledge to design more effective and target-directed therapies to improve patient outcomes.

AREAS COVERED

In this review, the authors discuss the critical genetic, epigenetic and immunologic aberrations found in gliomas that appear rational and promising for therapeutic developments in the presence and future. The current state of the latest therapeutic developments including tumor-specific targeted drug therapies, metabolic targeting, epigenetic modulation and immunotherapy are summarized and suggestions for future directions are offered. Furthermore, they highlight contemporary issues related to the clinical development, such as challenges in clinical trials and toxicities.

EXPERT OPINION

The commitment to understanding the process of gliomagenesis has created a catalogue of aberrations that depict multiple mechanisms underlying this disease, many of which are suitable to therapeutic inhibition and are currently tested in clinical trials. Thus, future treatment endeavors will employ multiple treatment modalities that target disparate tumor characteristics personalized to the patient's individual tumor.