Integrated mapping of pharmacokinetics and pharmacodynamics in a patient-derived xenograft model of glioblastoma

Strategies to Improve Drug Delivery Across the Blood-Brain Barrier for Glioblastoma

PURPOSE OF REVIEW

Glioblastoma remains resistant to most conventional treatments. Despite scientific advances in the past three decades, there has been a dearth of effective new treatments. New approaches to drug delivery and clinical trial design are needed.

RECENT FINDINGS

We discuss how the blood-brain barrier and tumor microenvironment pose challenges for development of effective therapies for glioblastoma. Next, we discuss treatments in development that aim to overcome these barriers, including novel drug designs such as nanoparticles and antibody-drug conjugates, novel methods of drug delivery, including convection-enhanced and intra-arterial delivery, and novel methods to enhance drug penetration, such as blood-brain barrier disruption by focused ultrasound and laser interstitial thermal therapy. Lastly, we address future opportunities, positing combination therapy as the best strategy for effective treatment, neoadjuvant and window-of-opportunity approaches to simultaneously enhance therapeutic effectiveness with interrogation of on-treatment biologic endpoints, and adaptive platform and basket trials as imperative for future trial design. New approaches to GBM treatment should account for the blood-brain barrier and immunosuppression by improving drug delivery, combining treatments, and integrating novel clinical trial designs.

Evaluation of Inlet Temperature with Three Sprayer Designs for Desorption Electrospray Ionization Mass Spectrometry Tissue Analysis

Mass spectrometry imaging (MSI) allows for the spatially resolved detection of endogenous and exogenous molecules and atoms in biological samples, typically prepared as thin tissue sections. Desorption electrospray ionization (DESI) is one of the most commonly utilized MSI modalities in preclinical research. DESI ion source technology is still rapidly evolving, with new sprayer designs and heated inlet capillaries having recently been incorporated in commercially available systems. In this study, three iterations of DESI sprayer designs are evaluated: (1) the first, and until recently only, commercially available Waters sprayer; (2) a developmental desorption electro-flow focusing ionization (DEFFI)-type sprayer; and (3) a prototype of the newly released Waters commercial sprayer. A heated inlet capillary is also employed, allowing for controlled inlet temperatures up to 500 °C. These three sprayers are evaluated by comparative tissue imaging analyses of murine testes across this temperature range. Single ion intensity versus temperature trends are evaluated as exemplar cases for putatively identified species of interest, such as lactate and glutamine. A range of trends are observed, where intensities follow either increasing, decreasing, bell-shaped, or other trends with temperature. Data for all sprayers show approximately similar trends for the ions studied, with the commercial prototype sprayer (sprayer version 3) matching or outperforming the other sprayers for the ions investigated. Finally, the mass spectra acquired using sprayer version 3 are evaluated by uniform manifold approximation and projection (UMAP) and k-means clustering. This approach is shown to provide valuable insight that is complementary to the presented univariate evaluation for reviewing the parameter space in this study. Full spectral temperature optimization data are provided as supporting data to enable other researchers to design experiments that are optimal for specific ions.

Recent developments and applications of ambient mass spectrometry imaging in pharmaceutical research: an overview

The application of ambient mass spectrometry imaging "MSI" is expanding in the areas of fundamental research on drug delivery and multiple phases of the process of identifying and developing drugs. Precise monitoring of a drug's pharmacological workflows, such as intake, distribution, metabolism, and discharge, is made easier by MSI's ability to determine the concentrations of the initiating drug and its metabolites across dosed samples without losing spatial data. Lipids, glycans, and proteins are just a few of the many phenotypes that MSI may be used to concurrently examine. Each of these substances has a particular distribution pattern and biological function throughout the body. MSI offers the perfect analytical tool for examining a drug's pharmacological features, especially in vitro and in vivo effectiveness, security, probable toxic effects, and putative molecular pathways, because of its high responsiveness in chemical and physical environments. The utilization of MSI in the field of pharmacy has further extended from the traditional tissue examination to the early stages of drug discovery and development, including examining the structure-function connection, high-throughput capabilities in vitro examination, and ex vivo research on individual cells or tumor spheroids. Additionally, an enormous array of endogenous substances that may function as tissue diagnostics can be scanned simultaneously, giving the specimen a highly thorough characterization. Ambient MSI techniques are soft enough to allow for easy examination of the native sample to gather data on exterior chemical compositions. This paper provides a scientific and methodological overview of ambient MSI utilization in research on pharmaceuticals.

Visualisation of drug distribution in skin using correlative optical spectroscopy and mass spectrometry imaging

A correlative methodology for label-free chemical imaging of soft tissue has been developed, combining non-linear optical spectroscopies and mass spectrometry to achieve sub-micron spatial resolution and critically improved drug detection sensitivity. The approach was applied to visualise the kinetics of drug reservoir formation within human skin following in vitro topical treatment with a commercial diclofenac gel. Non-destructive optical spectroscopic techniques, namely stimulated Raman scattering, second harmonic generation and two photon fluorescence microscopies, were used to provide chemical and structural contrast. The same tissue sections were subsequently analysed by secondary ion mass spectrometry, which offered higher sensitivity for diclofenac detection throughout the epidermis and dermis. A method was developed to combine the optical and mass spectrometric datasets using image registration techniques. The label-free, high-resolution visualisation of tissue structure coupled with sensitive chemical detection offers a powerful method for drug biodistribution studies in the skin that impact directly on topical pharmaceutical product development.

Ryu J, Akassoglou K, Talebian S, Chu P, Pisani L, Musolino P, Steinman L, Doyle K, Robinson WH, Sharpe O, Cayrol R, Orchard P, Lund T, Vogel H, Lenail M, Han MH, Bonkowsky JL, Van Haren KP. A novel mouse model of cerebral adrenoleukodystrophy highlights NLRP3 activity in lesion pathogenesis

Objective

We sought to create and characterize a mouse model of the inflammatory, cerebral demyelinating phenotype of X-linked adrenoleukodystrophy (ALD) that would facilitate the study of disease pathogenesis and therapy development. We also sought to cross-validate potential therapeutic targets such as fibrin, oxidative stress, and the NLRP3 inflammasome, in post-mortem human and murine brain tissues.

Background

ALD is caused by mutations in the gene ABCD1 encoding a peroxisomal transporter. More than half of males with an ABCD1 mutation develop the cerebral phenotype (cALD). Incomplete penetrance and absence of a genotype-phenotype correlation imply a role for environmental triggers. Mechanistic studies have been limited by the absence of a cALD phenotype in the Abcd1-null mouse.

Methods

We generated a cALD phenotype in 8-week-old, male Abcd1-null mice by deploying a two-hit method that combines cuprizone (CPZ) and experimental autoimmune encephalomyelitis (EAE) models. We employed in vivo MRI and post-mortem immunohistochemistry to evaluate myelin loss, astrogliosis, blood-brain barrier (BBB) disruption, immune cell infiltration, fibrin deposition, oxidative stress, and Nlrp3 inflammasome activation in mice. We used bead-based immunoassay and immunohistochemistry to evaluate IL-18 in CSF and post-mortem human cALD brain tissue.

Results

MRI studies revealed T2 hyperintensities and post-gadolinium enhancement in the medial corpus callosum of cALD mice, similar to human cALD lesions. Both human and mouse cALD lesions shared common histologic features of myelin phagocytosis, myelin loss, abundant microglial activation, T and B-cell infiltration, and astrogliosis. Compared to wild-type controls, Abcd1-null mice had more severe cerebral inflammation, demyelination, fibrin deposition, oxidative stress, and IL-18 activation. IL-18 immunoreactivity co-localized with macrophages/microglia in the perivascular region of both human and mouse brain tissue.

Interpretation

This novel mouse model of cALD suggests loss of Abcd1 function predisposes to more severe cerebral inflammation, oxidative stress, fibrin deposition, and Nlrp3 pathway activation, which parallels the findings seen in humans with cALD. We expect this model to enable long-sought investigations into cALD mechanisms and accelerate development of candidate therapies for lesion prevention, cessation, and remyelination.

Next-generation pathology practices with mass spectrometry imaging

Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology-related research. In this review, we summarize common MSI techniques, including matrix-assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next-generation pathology practices.

Dysregulated lipid metabolism in TMZ-resistant glioblastoma: pathways, proteins, metabolites and therapeutic opportunities

Glioblastoma (GBM) is a highly aggressive and lethal brain tumor with limited treatment options, such as the chemotherapeutic agent, temozolomide (TMZ). However, many GBM tumors develop resistance to TMZ, which is a major obstacle to effective therapy. Recently, dysregulated lipid metabolism has emerged as an important factor contributing to TMZ resistance in GBM. The dysregulation of lipid metabolism is a hallmark of cancer and alterations in lipid metabolism have been linked to multiple aspects of tumor biology, including proliferation, migration, and resistance to therapy. In this review, we aimed to summarize current knowledge on lipid metabolism in TMZ-resistant GBM, including key metabolites and proteins involved in lipid synthesis, uptake, and utilization, and recent advances in the application of metabolomics to study lipid metabolism in GBM. We also discussed the potential of lipid metabolism as a target for novel therapeutic interventions. Finally, we highlighted the challenges and opportunities associated with developing these interventions for clinical use, and the need for further research to fully understand the role of lipid metabolism in TMZ resistance in GBM. Our review suggests that targeting dysregulated lipid metabolism may be a promising approach to overcome TMZ resistance and improve outcomes in patients with GBM.

Bench-to-bedside investigations of H3 K27-altered diffuse midline glioma: drug targets and potential pharmacotherapies

INTRODUCTION

H3 K27-altered diffuse midline glioma (DMG) is the most common malignant brainstem tumor in the pediatric population. Despite enormous preclinical and clinical efforts, the prognosis remains dismal, with fewer than 10% of patients surviving for two years after diagnosis. Fractionated radiation remains the only standard treatment options for DMG. Developing novel treatments and therapeutic delivery methods is critical to improving outcomes in this devastating disease.

AREAS COVERED

This review addresses recent advances in molecularly targeted pharmacotherapy and immunotherapy in DMG. The clinical presentation, diagnostic workup, unique pathological challenges, and current clinical trials are highlighted throughout.

EXPERT OPINION

Promising pharmacotherapies targeting various components of DMG pathology and the application of immunotherapies have the potential to improve patient outcomes. However, novel approaches are needed to truly revolutionize treatment for this tumor. First, combinational therapy should be employed, as DMG can develop resistance to single-agent approaches and many therapies are susceptible to rapid clearance from the brain. Second, drug-tumor residence time, i.e. the time for which a therapeutic is present at efficacious concentrations within the tumor, must be maximized to facilitate a durable treatment response. Engineering extended drug delivery methods with minimal off-tumor toxicity should be a focus of future studies.

Polymer nanocarriers for targeted local delivery of agents in treating brain tumors

Glioblastoma (GBM), the deadliest brain cancer, presents a multitude of challenges to the development of new therapies. The standard of care has only changed marginally in the past 17 years, and few new chemotherapies have emerged to supplant or effectively combine with temozolomide. Concurrently, new technologies and techniques are being investigated to overcome the pharmacokinetic challenges associated with brain delivery, such as the blood brain barrier (BBB), tissue penetration, diffusion, and clearance in order to allow for potent agents to successful engage in tumor killing. Alternative delivery modalities such as focused ultrasound and convection enhanced delivery allow for the local disruption of the BBB, and the latter in particular has shown promise in achieving broad distribution of agents in the brain. Furthermore, the development of polymeric nanocarriers to encapsulate a variety of cargo, including small molecules, proteins, and nucleic acids, have allowed for formulations that protect and control the release of said cargo to extend its half-life. The combination of local delivery and nanocarriers presents an exciting opportunity to address the limitations of current chemotherapies for GBM toward the goal of improving safety and efficacy of treatment. However, much work remains to establish standard criteria for selection and implementation of these modalities before they can be widely implemented in the clinic. Ultimately, engineering principles and nanotechnology have opened the door to a new wave of research that may soon advance the stagnant state of GBM treatment development.

Orthotopic Glioblastoma Models for Evaluation of the Clinical Target Volume Concept

Simple Summary

The accurate and precise definition of the target volume is of enormous importance for the treatment success of radiotherapy. In glioblastoma, the microscopic tumor extension is unclear, which limits the specificity of irradiation leading to either increased risk of local failure or enhanced toxicity rates. In this study, we investigated the microscopic tumor extensions of two different untreated and irradiated orthotopic brain tumor models and correlated this with histologically stained cancer stem cell markers as well as invasion markers and analyses using Matrix-Assisted Laser Desorption/Ionization (MALDI). We found specific MALDI peaks as potential markers for normal brain tissue but also others for demarcation of tumor areas. Furthermore, MMP14 staining revealed mainly positive cells in the tumor border, which could reflect the invasive front in both models. Altogether, the results of this study indicate that an individualized target volume definition for radiotherapy based on biological tumor characteristics in glioblastoma models seems possible.

Abstract

In times of high-precision radiotherapy, the accurate and precise definition of the primary tumor localization and its microscopic spread is of enormous importance. In glioblastoma, the microscopic tumor extension is uncertain and, therefore, population-based margins for Clinical Target Volume (CTV) definition are clinically used, which could either be too small—leading to increased risk of loco-regional recurrences—or too large, thus, enhancing the probability of normal tissue toxicity. Therefore, the aim of this project is to investigate an individualized definition of the CTV in preclinical glioblastoma models based on specific biological tumor characteristics. The microscopic tumor extensions of two different orthotopic brain tumor models (U87MG_mCherry; G7_mCherry) were evaluated before and during fractionated radiotherapy and correlated with corresponding histological data. Representative tumor slices were analyzed using Matrix-Assisted Laser Desorption/Ionization (MALDI) and stained for putative stem-like cell markers as well as invasion markers. The edges of the tumor are clearly shown by the MALDI segmentation via unsupervised clustering of mass spectra and are consistent with the histologically defined border in H&E staining in both models. MALDI component analysis identified specific peaks as potential markers for normal brain tissue (e.g., 1339 m/z), whereas other peaks demarcated the tumors very well (e.g., 1562 m/z for U87MG_mCherry) irrespective of treatment. MMP14 staining revealed only a few positive cells, mainly in the tumor border, which could reflect the invasive front in both models. The results of this study indicate that MALDI information correlates with microscopic tumor spread in glioblastoma models. Therefore, an individualized CTV definition based on biological tumor characteristics seems possible, whereby the visualization of tumor volume and protein heterogeneity can be potentially used to define radiotherapy-sensitive and resistant areas.

Adoption of Machine Learning in Pharmacometrics: An Overview of Recent Implementations and Their Considerations

Pharmacometrics is a multidisciplinary field utilizing mathematical models of physiology, pharmacology, and disease to describe and quantify the interactions between medication and patient. As these models become more and more advanced, the need for advanced data analysis tools grows. Recently, there has been much interest in the adoption of machine learning (ML) algorithms. These algorithms offer strong function approximation capabilities and might reduce the time spent on model development. However, ML tools are not yet an integral part of the pharmacometrics workflow. The goal of this work is to discuss how ML algorithms have been applied in four stages of the pharmacometrics pipeline: data preparation, hypothesis generation, predictive modelling, and model validation. We will also discuss considerations before the use of ML algorithms with respect to each topic. We conclude by summarizing applications that hold potential for adoption by pharmacometricians.

Design and Measurement of Drug Tissue Concentration Asymmetry and Tissue Exposure-Effect (Tissue PK-PD) Evaluation

The "free drug hypothesis" assumes that, in the absence of transporters, the steady state free plasma concentrations equal to that at the site of action that elicit pharmacologic effects. While it is important to utilize the free drug hypothesis, exceptions exist that the free plasma exposures, either at C_max, C_trough, and C_average, or at other time points, cannot represent the corresponding free tissue concentrations. This "drug concentration asymmetry" in both total and free form can influence drug disposition and pharmacological effects. In this review, we first discuss options to assess total and free drug concentrations in tissues. Then various drug design strategies to achieve concentration asymmetry are presented. Last, the utilities of tissue concentrations in understanding exposure-effect relationships and translational projections to humans are discussed for several therapeutic areas and modalities. A thorough understanding in plasma and tissue exposures correlation with pharmacologic effects can provide insightful guidance to aid drug discovery.

Overcoming differential tumor penetration of BRAF inhibitors using computationally guided combination therapy

BRAF-targeted kinase inhibitors (KIs) are used to treat malignancies including BRAF-mutant non-small cell lung cancer, colorectal cancer, anaplastic thyroid cancer, and, most prominently, melanoma. However, KI selection criteria in patients remain unclear, as are pharmacokinetic/pharmacodynamic (PK/PD) mechanisms that may limit context-dependent efficacy and differentiate related drugs. To address this issue, we imaged mouse models of BRAF-mutant cancers, fluorescent KI tracers, and unlabeled drug to calibrate in silico spatial PK/PD models. Results indicated that drug lipophilicity, plasma clearance, faster target dissociation, and, in particular, high albumin binding could limit dabrafenib action in visceral metastases compared to other KIs. This correlated with retrospective clinical observations. Computational modeling identified a timed strategy for combining dabrafenib and encorafenib to better sustain BRAF inhibition, which showed enhanced efficacy in mice. This study thus offers principles of spatial drug action that may help guide drug development, KI selection, and combination.

Tumor Drug Concentration and Phosphoproteomic Profiles After Two Weeks of Treatment With Sunitinib in Patients with Newly Diagnosed Glioblastoma

PURPOSE

Tyrosine kinase inhibitors (TKI) have poor efficacy in patients with glioblastoma (GBM). Here, we studied whether this is predominantly due to restricted blood-brain barrier penetration or more to biological characteristics of GBM.

PATIENTS AND METHODS

Tumor drug concentrations of the TKI sunitinib after 2 weeks of preoperative treatment was determined in 5 patients with GBM and compared with its in vitro inhibitory concentration (IC50) in GBM cell lines. In addition, phosphotyrosine (pTyr)-directed mass spectrometry (MS)-based proteomics was performed to evaluate sunitinib-treated versus control GBM tumors.

RESULTS

The median tumor sunitinib concentration of 1.9 μmol/L (range 1.0-3.4) was 10-fold higher than in concurrent plasma, but three times lower than sunitinib IC50s in GBM cell lines (median 5.4 μmol/L, 3.0-8.5; P = 0.01). pTyr-phosphoproteomic profiles of tumor samples from 4 sunitinib-treated versus 7 control patients revealed 108 significantly up- and 23 downregulated (P < 0.05) phosphopeptides for sunitinib treatment, resulting in an EGFR-centered signaling network. Outlier analysis of kinase activities as a potential strategy to identify drug targets in individual tumors identified nine kinases, including MAPK10 and INSR/IGF1R.

CONCLUSIONS

Achieved tumor sunitinib concentrations in patients with GBM are higher than in plasma, but lower than reported for other tumor types and insufficient to significantly inhibit tumor cell growth in vitro. Therefore, alternative TKI dosing to increase intratumoral sunitinib concentrations might improve clinical benefit for patients with GBM. In parallel, a complex profile of kinase activity in GBM was found, supporting the potential of (phospho)proteomic analysis for the identification of targets for (combination) treatment.

Noninvasive Imaging of CD4+ T Cells in Humanized Mice

Antibody-based PET (immunoPET) with radiotracers that recognize specific cells of the immune system provides an opportunity to monitor immune cell trafficking at the organismal scale. We previously reported the visualization of human CD8+ T cells, including CD8+ tumor-infiltrating lymphocytes (TIL), in mice using a humanized CD8-targeted minibody. Given the important role of CD4+ T cells in adaptive immune responses of health and disease including infections, tumors, and autoimmunity, we explored immunoPET using an anti-human-CD4 minibody. We assessed the ability of [64Cu]Cu-NOTA-IAB41 to bind to various CD4+ T-cell subsets in vitro. We also determined the effect of the CD4-targeted minibody on CD4+ T-cell abundance, proliferation, and activation state in vitro. We subsequently evaluated the ability of the radiotracer to visualize CD4+ T cells in T-cell rich organs and orthotopic brain tumors in vivo. For the latter, we injected the [64Cu]Cu-NOTA-IAB41 radiotracer into humanized mice that harbored intracranial patient-derived glioblastoma (GBM) xenografts and performed in vivo PET, ex vivo autoradiography, and anti-CD4 IHC on serial brain sections. [64Cu]Cu-NOTA-IAB41 specifically detects human CD4+ T cells without impacting their abundance, proliferation, and activation. In humanized mice, [64Cu]Cu-NOTA-IAB41 can visualize various peripheral tissues in addition to orthotopically implanted GBM tumors. [64Cu]Cu-NOTA-IAB41 is able to visualize human CD4+ T cells in humanized mice and can provide noninvasive quantification of CD4+ T-cell distribution on the organismal scale.

Exploration and functionalization of M1-macrophage extracellular vesicles for effective accumulation in glioblastoma and strong synergistic therapeutic effects

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with an extremely low survival rate. New and effective approaches for treatment are therefore urgently needed. Here, we successfully developed M1-like macrophage-derived extracellular vesicles (M1EVs) that overcome multiple challenges via guidance from two macrophage-related observations in clinical specimens from GBM patients: enrichment of M2 macrophages in GBM; and origination of a majority of infiltrating macrophage from peripheral blood. To maximize the synergistic effect, we further functionalized the membranes of M1EVs with two hydrophobic agents (the chemical excitation source CPPO (C) and the photosensitizer Ce6 (C)) and loaded the hydrophilic hypoxia-activated prodrug AQ4N (A) into the inner core of the M1EVs. After intravenous injection, the inherent nature of M1-derived extracellular vesicles CCA-M1EVs allowed for blood-brain barrier penetration, and modulated the immunosuppressive tumor microenvironment via M2-to-M1 polarization, which increased hydrogen peroxide (H₂O₂) levels. Furthermore, the reaction between H₂O₂ and CPPO produced chemical energy, which could be used for Ce6 activation to generate large amounts of reactive oxygen species to achieve chemiexcited photodynamic therapy (CDT). As this reaction consumed oxygen, the aggravation of tumor hypoxia also led to the conversion of non-toxic AQ4N into toxic AQ4 for chemotherapy. Therefore, CCA-M1EVs achieved synergistic immunomodulation, CDT, and hypoxia-activated chemotherapy in GBM to exert a potent therapeutic effect. Finally, we demonstrated the excellent effect of CCA-M1EVs against GBM in cell-derived xenograft and patient-derived xenograft models, underscoring the strong potential of our highly flexible M1EVs system to support multi-modal therapies for difficult-to-treat GBM.

ADVANCES IN HIGH-RESOLUTION MALDI MASS SPECTROMETRY FOR NEUROBIOLOGY

Research in the field of neurobiology and neurochemistry has seen a rapid expansion in the last several years due to advances in technologies and instrumentation, facilitating the detection of biomolecules critical to the complex signaling of neurons. Part of this growth has been due to the development and implementation of high-resolution Fourier transform (FT) mass spectrometry (MS), as is offered by FT ion cyclotron resonance (FTICR) and Orbitrap mass analyzers, which improves the accuracy of measurements and helps resolve the complex biological mixtures often analyzed in the nervous system. The coupling of matrix-assisted laser desorption/ionization (MALDI) with high-resolution MS has drastically expanded the information that can be obtained with these complex samples. This review discusses notable technical developments in MALDI-FTICR and MALDI-Orbitrap platforms and their applications toward molecules in the nervous system, including sequence elucidation and profiling with de novo sequencing, analysis of post-translational modifications, in situ analysis, key advances in sample preparation and handling, quantitation, and imaging. Notable novel applications are also discussed to highlight key developments critical to advancing our understanding of neurobiology and providing insight into the exciting future of this field. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

massNet: integrated processing and classification of spatially resolved mass spectrometry data using deep learning for rapid tumor delineation

MOTIVATION

Mass spectrometry imaging (MSI) provides rich biochemical information in a label-free manner and therefore holds promise to substantially impact current practice in disease diagnosis. However, the complex nature of MSI data poses computational challenges in its analysis. The complexity of the data arises from its large size, high-dimensionality and spectral nonlinearity. Preprocessing, including peak picking, has been used to reduce raw data complexity; however, peak picking is sensitive to parameter selection that, perhaps prematurely, shapes the downstream analysis for tissue classification and ensuing biological interpretation.

RESULTS

We propose a deep learning model, massNet, that provides the desired qualities of scalability, nonlinearity and speed in MSI data analysis. This deep learning model was used, without prior preprocessing and peak picking, to classify MSI data from a mouse brain harboring a patient-derived tumor. The massNet architecture established automatically learning of predictive features, and automated methods were incorporated to identify peaks with potential for tumor delineation. The model's performance was assessed using cross-validation, and the results demonstrate higher accuracy and a substantial gain in speed compared to the established classical machine learning method, support vector machine.

AVAILABILITY AND IMPLEMENTATION

https://github.com/wabdelmoula/massNet. The data underlying this article are available in the NIH Common Fund's National Metabolomics Data Repository (NMDR) Metabolomics Workbench under project id (PR001292) with http://dx.doi.org/10.21228/M8Q70T.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Multimodal platform for assessing drug distribution and response in clinical trials

BACKGROUND

Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy.

METHODS

Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI. Phosphoproteomics was measured in the same tumors to identify biomarkers of drug target engagement and cellular adaptive response. Multiplexed tissue imaging was performed on sister sections to evaluate spatial co-localization of drug and cellular response. The integrated platform was then applied on clinical specimens from glioblastoma patients enrolled in the phase 1 clinical trial.

RESULTS

PDX tumors exposed to different doses of adavosertib revealed intra- and inter-tumoral heterogeneity of drug distribution and integration of the heterogeneous drug distribution with phosphoproteomics and multiplexed tissue imaging revealed new markers of molecular response to adavosertib. Analysis of paired clinical specimens from patients enrolled in the phase 1 clinical trial informed the translational potential of the identified biomarkers in studying patient's response to adavosertib.

CONCLUSIONS

The multimodal platform identified a signature of drug efficacy and patient-specific adaptive responses applicable to preclinical and clinical drug development. The information generated by the approach may inform mechanisms of success and failure in future early phase clinical trials, providing information for optimizing clinical trial design and guiding future application into clinical practice.

Self-supervised clustering of mass spectrometry imaging data using contrastive learning

Mass spectrometry imaging (MSI) is widely used for the label-free molecular mapping of biological samples. The identification of co-localized molecules in MSI data is crucial to the understanding of biochemical pathways. One of key challenges in molecular colocalization is that complex MSI data are too large for manual annotation but too small for training deep neural networks. Herein, we introduce a self-supervised clustering approach based on contrastive learning, which shows an excellent performance in clustering of MSI data. We train a deep convolutional neural network (CNN) using MSI data from a single experiment without manual annotations to effectively learn high-level spatial features from ion images and classify them based on molecular colocalizations. We demonstrate that contrastive learning generates ion image representations that form well-resolved clusters. Subsequent self-labeling is used to fine-tune both the CNN encoder and linear classifier based on confidently classified ion images. This new approach enables autonomous and high-throughput identification of co-localized species in MSI data, which will dramatically expand the application of spatial lipidomics, metabolomics, and proteomics in biological research.

Rationally designed drug delivery systems for the local treatment of resected glioblastoma

Glioblastoma (GBM) is a particularly aggressive brain cancer associated with high recurrence and poor prognosis. The standard of care, surgical resection followed by concomitant radio- and chemotherapy, leads to low survival rates. The local delivery of active agents within the tumor resection cavity has emerged as an attractive means to initiate oncological treatment immediately post-surgery. This complementary approach bypasses the blood-brain barrier, increases the local concentration at the tumor site while reducing or avoiding systemic side effects. This review will provide a global overview on the local treatment for GBM with an emphasis on the lessons learned from past clinical trials. The main parameters to be considered to rationally design fit-of-purpose biomaterials and develop drug delivery systems for local administration in the GBM resection cavity to prevent the tumor recurrence will be described. The intracavitary local treatment of GBM should i) use materials that facilitate translation to the clinic; ii) be characterized by easy GMP effective scaling up and easy-handling application by the neurosurgeons; iii) be adaptable to fill the tumor-resected niche, mold to the resection cavity or adhere to the exposed brain parenchyma; iv) be biocompatible and possess mechanical properties compatible with the brain; v) deliver a therapeutic dose of rationally-designed or repurposed drug compound(s) into the GBM infiltrative margin. Proof of concept with high translational potential will be provided. Finally, future perspectives to facilitate the clinical translation of the local perisurgical treatment of GBM will be discussed.

Peak learning of mass spectrometry imaging data using artificial neural networks

Mass spectrometry imaging (MSI) is an emerging technology that holds potential for improving, biomarker discovery, metabolomics research, pharmaceutical applications and clinical diagnosis. Despite many solutions being developed, the large data size and high dimensional nature of MSI, especially 3D datasets, still pose computational and memory complexities that hinder accurate identification of biologically relevant molecular patterns. Moreover, the subjectivity in the selection of parameters for conventional pre-processing approaches can lead to bias. Therefore, we assess if a probabilistic generative model based on a fully connected variational autoencoder can be used for unsupervised analysis and peak learning of MSI data to uncover hidden structures. The resulting msiPL method learns and visualizes the underlying non-linear spectral manifold, revealing biologically relevant clusters of tissue anatomy in a mouse kidney and tumor heterogeneity in human prostatectomy tissue, colorectal carcinoma, and glioblastoma mouse model, with identification of underlying m/z peaks. The method is applied for the analysis of MSI datasets ranging from 3.3 to 78.9 GB, without prior pre-processing and peak picking, and acquired using different mass spectrometers at different centers.

Mechanically matching the rheological properties of brain tissue for drug-delivery in human glioblastoma models

Peptide functionalized hyaluronic acid (HACF) cross-linked by cucurbit[8]uril (CB[8]), a new class of drug-delivery reservoirs, is used to enable improved drug bioavailability for glioblastoma tumors in patient-derived xenograft (PDX) models. The mechanical and viscoelastic properties of native human and mouse tissues are measured over 8 h via oscillatory rheology under physiological conditions. Treatment with drug-loaded hydrogels allowed for a significant survival impact of 45 % (55.5-80.5 days). A relationship between the type of PDX tumor formed-a consequence of the heterogeneic nature of GB tumors-and changes in the initial survival is observed owing to greater local pressure from stiffer tumors. These biocompatible and tailorable materials warrant use as drug delivery reservoirs in PDX resection models, where the mechanical properties can be readily adjusted to match the stiffness of local tissue and thus have potential to improve the survival of GB patients.

A Deep Convolutional Neural Network for Annotation of Magnetic Resonance Imaging Sequence Type

The explosion of medical imaging data along with the advent of big data analytics has launched an exciting era for clinical research. One factor affecting the ability to aggregate large medical image collections for research is the lack of infrastructure for automated data annotation. Among all imaging modalities, annotation of magnetic resonance (MR) images is particularly challenging due to the non-standard labeling of MR image types. In this work, we aimed to train a deep neural network to annotate MR image sequence type for scans of brain tumor patients. We focused on the four most common MR sequence types within neuroimaging: T1-weighted (T1W), T1-weighted post-gadolinium contrast (T1Gd), T2-weighted (T2W), and T2-weighted fluid-attenuated inversion recovery (FLAIR). Our repository contains images acquired using a variety of pulse sequences, sequence parameters, field strengths, and scanner manufacturers. Image selection was agnostic to patient demographics, diagnosis, and the presence of tumor in the imaging field of view. We used a total of 14,400 two-dimensional images, each visualizing a different part of the brain. Data was split into train, validation, and test sets (9600, 2400, and 2400 images, respectively) and sets consisted of equal-sized groups of image types. Overall, the model reached an accuracy of 99% on the test set. Our results showed excellent performance of deep learning techniques in predicting sequence types for brain tumor MR images. We conclude deep learning models can serve as tools to support clinical research and facilitate efficient database management.

Quantitative Analysis of Tyrosine Phosphorylation from FFPE Tissues Reveals Patient-Specific Signaling Networks

Human tissue samples commonly preserved as formalin-fixed paraffin-embedded (FFPE) tissues after diagnostic or surgical procedures in the clinic represent an invaluable source of clinical specimens for in-depth characterization of signaling networks to assess therapeutic options. Tyrosine phosphorylation (pTyr) plays a fundamental role in cellular processes and is commonly dysregulated in cancer but has not been studied to date in FFPE samples. In addition, pTyr analysis that may otherwise inform therapeutic interventions for patients has been limited by the requirement for large amounts of frozen tissue. Here we describe a method for highly sensitive, quantitative analysis of pTyr signaling networks, with hundreds of sites quantified from one to two 10-μm sections of FFPE tissue specimens. A combination of optimized magnetic bead-based sample processing, optimized pTyr enrichment strategies, and tandem mass tag multiplexing enabled in-depth coverage of pTyr signaling networks from small amounts of input material. Phosphotyrosine profiles of flash-frozen and FFPE tissues derived from the same tumors suggested that FFPE tissues preserve pTyr signaling characteristics in patient-derived xenografts and archived clinical specimens. pTyr analysis of FFPE tissue sections from breast cancer tumors as well as lung cancer tumors highlighted patient-specific oncogenic driving kinases, indicating potential targeted therapies for each patient. These data suggest the capability for direct translational insight from pTyr analysis of small amounts of FFPE tumor tissue specimens. SIGNIFICANCE: This study reports a highly sensitive method utilizing FFPE tissues to identify dysregulated signaling networks in patient tumors, opening the door for direct translational insights from FFPE tumor tissue banks in hospitals.

Conformable hierarchically engineered polymeric micromeshes enabling combinatorial therapies in brain tumours

The poor transport of molecular and nanoscale agents through the blood-brain barrier together with tumour heterogeneity contribute to the dismal prognosis in patients with glioblastoma multiforme. Here, a biodegradable implant (μMESH) is engineered in the form of a micrometre-sized poly(lactic-co-glycolic acid) mesh laid over a water-soluble poly(vinyl alcohol) layer. Upon poly(vinyl alcohol) dissolution, the flexible poly(lactic-co-glycolic acid) mesh conforms to the resected tumour cavity as docetaxel-loaded nanomedicines and diclofenac molecules are continuously and directly released into the adjacent tumour bed. In orthotopic brain cancer models, generated with a conventional, reference cell line and patient-derived cells, a single μMESH application, carrying 0.75 mg kg^-1 of docetaxel and diclofenac, abrogates disease recurrence up to eight months after tumour resection, with no appreciable adverse effects. Without tumour resection, the μMESH increases the median overall survival (∼30 d) as compared with the one-time intracranial deposition of docetaxel-loaded nanomedicines (15 d) or 10 cycles of systemically administered temozolomide (12 d). The μMESH modular structure, for the independent coloading of different molecules and nanomedicines, together with its mechanical flexibility, can be exploited to treat a variety of cancers, realizing patient-specific dosing and interventions.

Complete inhibition of ABCB1 and ABCG2 at the blood-brain barrier by co-infusion of erlotinib and tariquidar to improve brain delivery of the model ABCB1/ABCG2 substrate [11C]erlotinib

P-glycoprotein (ABCB1) and breast cancer resistance protein (ABCG2) restrict at the blood-brain barrier (BBB) the brain distribution of the majority of currently known molecularly targeted anticancer drugs. To improve brain delivery of dual ABCB1/ABCG2 substrates, both ABCB1 and ABCG2 need to be inhibited simultaneously at the BBB. We examined the feasibility of simultaneous ABCB1/ABCG2 inhibition with i.v. co-infusion of erlotinib and tariquidar by studying brain distribution of the model ABCB1/ABCG2 substrate [¹¹C]erlotinib in mice and rhesus macaques with PET. Tolerability of the erlotinib/tariquidar combination was assessed in human embryonic stem cell-derived cerebral organoids. In mice and macaques, baseline brain distribution of [¹¹C]erlotinib was low (brain distribution volume, V_T,brain < 0.3 mL/cm³). Co-infusion of erlotinib and tariquidar increased V_T,brain in mice by 3.0-fold and in macaques by 3.4- to 5.0-fold, while infusion of erlotinib alone or tariquidar alone led to less pronounced V_T,brain increases in both species. Treatment of cerebral organoids with erlotinib/tariquidar led to an induction of Caspase-3-dependent apoptosis. Co-infusion of erlotinib/tariquidar may potentially allow for complete ABCB1/ABCG2 inhibition at the BBB, while simultaneously achieving brain-targeted EGFR inhibition. Our protocol may be applicable to enhance brain delivery of molecularly targeted anticancer drugs for a more effective treatment of brain tumors.

Recent Advances in Tumor Targeting via EPR Effect for Cancer Treatment

Cancer causes the second-highest rate of death world-wide. A major shortcoming inherent in most of anticancer drugs is their lack of tumor selectivity. Nanodrugs for cancer therapy administered intravenously escape renal clearance, are unable to penetrate through tight endothelial junctions of normal blood vessels and remain at a high level in plasma. Over time, the concentration of nanodrugs builds up in tumors due to the EPR effect, reaching several times higher than that of plasma due to the lack of lymphatic drainage. This review will address in detail the progress and prospects of tumor-targeting via EPR effect for cancer therapy.

Nanoparticle-mediated convection-enhanced delivery of a DNA intercalator to gliomas circumvents temozolomide resistance

In patients with glioblastoma, resistance to the chemotherapeutic temozolomide (TMZ) limits any survival benefits conferred by the drug. Here we show that the convection-enhanced delivery of nanoparticles containing disulfide bonds (which are cleaved in the reductive environment of the tumour) and encapsulating an oxaliplatin prodrug and a cationic DNA intercalator inhibit the growth of TMZ-resistant cells from patient-derived xenografts, and hinder the progression of TMZ-resistant human glioblastoma tumours in mice without causing any detectable toxicity. Genome-wide RNA profiling and metabolomic analyses of a glioma cell line treated with the cationic intercalator or with TMZ showed substantial differences in the signalling and metabolic pathways altered by each drug. Our findings suggest that the combination of anticancer drugs with distinct mechanisms of action with selective drug release and convection-enhanced delivery may represent a translational strategy for the treatment of TMZ-resistant gliomas.

High-Density, Targeted Monitoring of Tyrosine Phosphorylation Reveals Activated Signaling Networks in Human Tumors

Tyrosine phosphorylation (pTyr) plays a pivotal role in signal transduction and is commonly dysregulated in cancer. As a result, profiling tumor pTyr levels may reveal therapeutic insights critical to combating disease. Existing discovery and targeted mass spectrometry-based methods used to monitor pTyr networks involve a tradeoff between broad coverage of the pTyr network, reproducibility in target identification across analyses, and accurate quantification. To address these limitations, we developed a targeted approach, termed "SureQuant pTyr," coupling low input pTyr enrichment with a panel of isotopically labeled internal standard peptides to guide data acquisition of low-abundance tyrosine phosphopeptides. SureQuant pTyr allowed for reliable quantification of several hundred commonly dysregulated pTyr targets with high quantitative accuracy, improving the robustness and usability of targeted mass spectrometry assays. We established the clinical applicability of SureQuant pTyr by profiling pTyr signaling levels in human colorectal tumors using minimal sample input, characterizing patient-specific oncogenic-driving mechanisms. While in some cases pTyr profiles aligned with previously reported proteomic, genomic, and transcriptomic molecular characterizations, we highlighted instances of new insights gained using pTyr characterization and emphasized the complementary nature of pTyr measurements with traditional biomarkers for improving patient stratification and identifying therapeutic targets. The turn-key nature of this approach opens the door to rapid and reproducible pTyr profiling in research and clinical settings alike and enables pTyr-based measurements for applications in precision medicine. SIGNIFICANCE: SureQuant pTyr is a mass spectrometry-based targeted method that enables sensitive and selective targeted quantitation of several hundred low-abundance tyrosine phosphorylated peptides commonly dysregulated in cancer, including oncogenic signaling networks.

In Vivo Efficacy of Tesevatinib in EGFR-Amplified Patient-Derived Xenograft Glioblastoma Models May Be Limited by Tissue Binding and Compensatory Signaling

Tesevatinib is a potent oral brain penetrant EGFR inhibitor currently being evaluated for glioblastoma therapy. Tesevatinib distribution was assessed in wild-type (WT) and Mdr1a/b^(-/-)Bcrp^(-/-) triple knockout (TKO) FVB mice after dosing orally or via osmotic minipump; drug-tissue binding was assessed by rapid equilibrium dialysis. Two hours after tesevatinib dosing, brain concentrations in WT and TKO mice were 0.72 and 10.03 μg/g, respectively. Brain-to-plasma ratios (Kp) were 0.53 and 5.73, respectively. With intraperitoneal infusion, brain concentrations were 1.46 and 30.6 μg/g (Kp 1.16 and 25.10), respectively. The brain-to-plasma unbound drug concentration ratios were substantially lower (WT mice, 0.03-0.08; TKO mice, 0.40-1.75). Unbound drug concentrations in brains of WT mice were 0.78 to 1.59 ng/g. In vitro cytotoxicity and EGFR pathway signaling were evaluated using EGFR-amplified patient-derived glioblastoma xenograft models (GBM12, GBM6). In vivo pharmacodynamics and efficacy were assessed using athymic nude mice bearing either intracranial or flank tumors treated by oral gavage. Tesevatinib potently reduced cell viability [IC₅₀ GBM12 = 11 nmol/L (5.5 ng/mL), GBM6 = 102 nmol/L] and suppressed EGFR signaling in vitro However, tesevatinib efficacy compared with vehicle in intracranial (GBM12, median survival: 23 vs. 18 days, P = 0.003) and flank models (GBM12, median time to outcome: 41 vs. 33 days, P = 0.007; GBM6, 44 vs. 33 days, P = 0.007) was modest and associated with partial inhibition of EGFR signaling. Overall, tesevatinib efficacy in EGFR-amplified PDX GBM models is robust in vitro but relatively modest in vivo, despite a high brain-to-plasma ratio. This discrepancy may be explained by drug-tissue binding and compensatory signaling.

Recent advances in the use of stimulated Raman scattering in histopathology

Stimulated Raman histopathology (SRH) utilises the intrinsic vibrational properties of lipids, proteins and nucleic acids to generate contrast providing rapid image acquisition that allows visualisation of histopathological features. It is currently being trialled in the intraoperative setting, where the ability to image unprocessed samples rapidly and with high resolution offers several potential advantages over the use of conventional haematoxylin and eosin stained images. Here we review recent advances in the field including new updates in instrumentation and computer aided diagnosis. We also discuss how other non-linear modalities can be used to provide additional diagnostic contrast which together pave the way for enhanced histopathology and open up possibilities for in vivo pathology.

Neuropharmacokinetic visualization of regional and subregional unbound antipsychotic drug transport across the blood-brain barrier

Comprehensive determination of the extent of drug transport across the region-specific blood-brain barrier (BBB) is a major challenge in preclinical studies. Multiple approaches are needed to determine the regional free (unbound) drug concentration at which a drug engages with its therapeutic target. We present an approach that merges in vivo and in vitro neuropharmacokinetic investigations with mass spectrometry imaging to quantify and visualize both the extent of unbound drug BBB transport and the post-BBB cerebral distribution of drugs at regional and subregional levels. Direct imaging of the antipsychotic drugs risperidone, clozapine, and olanzapine using this approach enabled differentiation of regional and subregional BBB transport characteristics at 20-µm resolution in small brain regions, which could not be achieved by other means. Our approach allows investigation of heterogeneity in BBB transport and presents new possibilities for molecular psychiatrists by facilitating interpretation of regional target-site exposure results and decision-making.

Phosphoproteomic strategies in cancer research: a minireview

Understanding the cellular processes is central to comprehend disease conditions and is also true for cancer research. Proteomic studies provide significant insight into cancer mechanisms and aid in the diagnosis and prognosis of the disease. Phosphoproteome is one of the most studied complements of the whole proteome given its importance in the understanding of cellular processes such as signaling and regulations. Over the last decade, several new methods have been developed for phosphoproteome analysis. A significant amount of these efforts pertains to cancer research. The current use of powerful analytical instruments in phosphoproteomic approaches has paved the way for deeper and sensitive investigations. However, these methods and techniques need further improvements to deal with challenges posed by the complexity of samples and scarcity of phosphoproteins in the whole proteome, throughput and reproducibility. This review aims to provide a comprehensive summary of the variety of steps used in phosphoproteomic methods applied in cancer research including the enrichment and fractionation strategies. This will allow researchers to evaluate and choose a better combination of steps for their phosphoproteome studies.

Cross-validated Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging Quantitation Protocol for a Pharmaceutical Drug and Its Drug-Target Effects in the Brain Using Time-of-Flight and Fourier Transform Ion Cyclotron Resonance Analyzers

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is an established tool in drug development, which enables visualization of drugs and drug metabolites at spatial localizations in tissue sections from different organs. However, robust and accurate quantitation by MALDI-MSI still remains a challenge. We present a quantitative MALDI-MSI method using two instruments with different types of mass analyzers, i.e., time-of-flight (TOF) and Fourier transform ion cyclotron resonance (FTICR) MS, for mapping levels of the in vivo-administered drug citalopram, a selective serotonin reuptake inhibitor, in mouse brain tissue sections. Six different methods for applying calibration standards and an internal standard were evaluated. The optimized method was validated according to authorities’ guidelines and requirements, including selectivity, accuracy, precision, recovery, calibration curve, sensitivity, reproducibility, and stability parameters. We showed that applying a dilution series of calibration standards followed by a homogeneously applied, stable, isotopically labeled standard for normalization and a matrix on top of the tissue section yielded similar results to those from the reference method using liquid chromatography–tandem mass spectrometry (LC–MS/MS). The validation results were within specified limits and the brain concentrations for TOF MS (51.1 ± 4.4 pmol/mg) and FTICR MS (56.9 ± 6.0 pmol/mg) did not significantly differ from those of the cross-validated LC–MS/MS method (55.0 ± 4.9 pmol/mg). The effect of in vivo citalopram administration on the serotonin neurotransmitter system was studied in the hippocampus, a brain region that is the principal target of the serotonergic afferents along with the limbic system, and it was shown that serotonin was significantly increased (2-fold), but its metabolite 5-hydroxyindoleacetic acid was not. This study makes a substantial step toward establishing MALDI-MSI as a fully quantitative validated method.

Development of a Potent Brain-Penetrant EGFR Tyrosine Kinase Inhibitor against Malignant Brain Tumors

The epidermal growth factor receptor (EGFR) is genetically altered in nearly 60% of glioblastoma tumors; however, tyrosine kinase inhibitors (TKIs) against EGFR have failed to show efficacy for patients with these lethal brain tumors. This failure is attributed to the inability of clinically tested EGFR TKIs to cross the blood-brain barrier (BBB) and achieve adequate pharmacological levels to inhibit various oncogenic forms of EGFR that drive glioblastoma. Through SAR analysis, we developed compound 5 (JCN037) from an anilinoquinazoline scaffold by ring fusion of the 6,7-dialkoxy groups to reduce the number of rotatable bonds and polar surface area and by introduction of an ortho-fluorine and meta-bromine on the aniline ring for improved potency and BBB penetration. Relative to the conventional EGFR TKIs erlotinib and lapatinib, JCN037 displayed potent activity against EGFR amplified/mutant patient-derived cell cultures, significant BBB penetration (2:1 brain-to-plasma ratio), and superior efficacy in an EGFR-driven orthotopic glioblastoma xenograft model.

Opportunities for Quantitative Translational Modeling in Oncology

A 2-day meeting was held by members of the UK Quantitative Systems Pharmacology Network () in November 2018 on the topic of Translational Challenges in Oncology. Participants from a wide range of backgrounds were invited to discuss current and emerging modeling applications in nonclinical and clinical drug development, and to identify areas for improvement. This resulting perspective explores opportunities for impactful quantitative pharmacology approaches. Four key themes arose from the presentations and discussions that were held, leading to the following recommendations: Evaluate the predictivity and reproducibility of animal cancer models through precompetitive collaboration. Apply mechanism of action (MoA) based mechanistic models derived from nonclinical data to clinical trial data. Apply MoA reflective models across trial data sets to more robustly quantify the natural history of disease and response to differing interventions. Quantify more robustly the dose and concentration dependence of adverse events through mathematical modelling techniques and modified trial design.

Epigenetic Targeting of Mcl-1 Is Synthetically Lethal with Bcl-xL/Bcl-2 Inhibition in Model Systems of Glioblastoma

Apoptotic resistance remains a hallmark of glioblastoma (GBM), the most common primary brain tumor in adults, and a better understanding of this process may result in more efficient treatments. By utilizing chromatin immunoprecipitation with next-generation sequencing (CHIP-seq), we discovered that GBMs harbor a super enhancer around the Mcl-1 locus, a gene that has been known to confer cell death resistance in GBM. We utilized THZ1, a known super-enhancer blocker, and BH3-mimetics, including ABT263, WEHI-539, and ABT199. Combined treatment with BH3-mimetics and THZ1 led to synergistic growth reduction in GBM models. Reduction in cellular viability was accompanied by significant cell death induction with features of apoptosis, including disruption of mitochondrial membrane potential followed by activation of caspases. Mechanistically, THZ1 elicited a profound disruption of the Mcl-1 enhancer region, leading to a sustained suppression of Mcl-1 transcript and protein levels, respectively. Mechanism experiments suggest involvement of Mcl-1 in the cell death elicited by the combination treatment. Finally, the combination treatment of ABT263 and THZ1 resulted in enhanced growth reduction of tumors without induction of detectable toxicity in two patient-derived xenograft models of GBM in vivo. Taken together, these findings suggest that combined epigenetic targeting of Mcl-1 along with Bcl-2/Bcl-xL is potentially therapeutically feasible.

Comparative study of preclinical mouse models of high-grade glioma for nanomedicine research: the importance of reproducing blood-brain barrier heterogeneity

The clinical translation of new nanoparticle-based therapies for high-grade glioma (HGG) remains extremely poor. This has partly been due to the lack of suitable preclinical mouse models capable of replicating the complex characteristics of recurrent HGG (rHGG), namely the heterogeneous structural and functional characteristics of the blood-brain barrier (BBB). The goal of this study is to compare the characteristics of the tumor BBB of rHGG with two different mouse models of HGG, the ubiquitously used U87 cell line xenograft model and a patient-derived cell line WK1 xenograft model, in order to assess their suitability for nanomedicine research.

Method: Structural MRI was used to assess the extent of BBB opening in mouse models with a fully developed tumor, and dynamic contrast enhanced MRI was used to obtain values of BBB permeability in contrast enhancing tumor. H&E and immunofluorescence staining were used to validate results obtained from the in vivo imaging studies.

Results: The extent of BBB disruption and permeability in the contrast enhancing tumor was significantly higher in the U87 model than in rHGG. These values in the WK1 model are similar to those of rHGG. The U87 model is not infiltrative, has an entirely abnormal and leaky vasculature and it is not of glial origin. The WK1 model infiltrates into the non-neoplastic brain parenchyma, it has both regions with intact BBB and regions with leaky BBB and remains of glial origin.

Conclusion: The WK1 mouse model more accurately reproduces the extent of BBB disruption, the level of BBB permeability and the histopathological characteristics found in rHGG patients than the U87 mouse model, and is therefore a more clinically relevant model for preclinical evaluations of emerging nanoparticle-based therapies for HGG.

Novel Breast Cancer Brain Metastasis Patient-Derived Orthotopic Xenograft Model for Preclinical Studies

The vast majority of mortality in breast cancer results from distant metastasis. Brain metastases occur in as many as 30% of patients with advanced breast cancer, and the 1-year survival rate of these patients is around 20%. Pre-clinical animal models that reliably reflect the biology of breast cancer brain metastasis are needed to develop and test new treatments for this deadly condition. The patient-derived xenograft (PDX) model maintains many features of a donor tumor, such as intra-tumor heterogeneity, and permits the testing of individualized treatments. However, the establishment of orthotopic PDXs of brain metastasis is procedurally difficult. We have developed a method for generating such PDXs with high tumor engraftment and growth rates. Here, we describe this method and identify variables that affect its outcomes. We also compare the brain-orthotopic PDXs with ectopic PDXs grown in mammary pads of mice, and show that the responsiveness of PDXs to chemotherapeutic reagents can be dramatically affected by the site that they are in.

Evaluation of the tumor-targeting efficiency and intratumor heterogeneity of anticancer drugs using quantitative mass spectrometry imaging

The development of improved or targeted drugs that discriminate between normal and tumor tissues is the key therapeutic issue in cancer research. However, the development of an analytical method with a high accuracy and sensitivity to achieve quantitative assessment of the tumor targeting of anticancer drugs and even intratumor heterogeneous distribution of these drugs at the early stages of drug research and development is a major challenge. Mass spectrometry imaging is a label-free molecular imaging technique that provides spatial-temporal information on the distribution of drugs and metabolites in organisms, and its application in the field of pharmaceutical development is rapidly increasing. Methods: The study presented here accurately quantified the distribution of paclitaxel (PTX) and its prodrug (PTX-R) in whole-body animal sections based on the virtual calibration quantitative mass spectrometry imaging (VC-QMSI) method, which is label-free and does not require internal standards, and then applied this technique to evaluate the tumor targeting efficiency in three treatment groups-the PTX-injection treatment group, PTX-liposome treatment group and PTX-R treatment group-in nude mice bearing subcutaneous A549 xenograft tumors. Results: These results indicated that PTX was widely distributed in multiple organs throughout the dosed body in the PTX-injection group and the PTX-liposome group. Notably, in the PTX-R group, both the prodrug and metabolized PTX were mainly distributed in the tumor tissue, and this group showed a significant difference compared with the PTX-liposome group, the relative targeting efficiency of PTX-R group was increased approximately 50-fold, leading to substantially decreased systemic toxicities. In addition, PTX-R showed a significant and specific accumulation in the poorly differentiated intratumor area and necrotic area. Conclusion: This method was demonstrated to be a reliable, feasible and easy-to-implement strategy to quantitatively map the absorption, distribution, metabolism and excretion (ADME) of a drug in the whole-body and tissue microregions and could therefore evaluate the tumor-targeting efficiency of anticancer drugs to predict drug efficacy and safety and provide key insights into drug disposition and mechanisms of action and resistance. Thus, this strategy could significantly facilitate the design and optimization of drugs at the early stage of drug research and development.

ABC Transporters at the Blood-Brain Interfaces, Their Study Models, and Drug Delivery Implications in Gliomas

Drug delivery into the brain is regulated by the blood-brain interfaces. The blood-brain barrier (BBB), the blood-cerebrospinal fluid barrier (BCSFB), and the blood-arachnoid barrier (BAB) regulate the exchange of substances between the blood and brain parenchyma. These selective barriers present a high impermeability to most substances, with the selective transport of nutrients and transporters preventing the entry and accumulation of possibly toxic molecules, comprising many therapeutic drugs. Transporters of the ATP-binding cassette (ABC) superfamily have an important role in drug delivery, because they extrude a broad molecular diversity of xenobiotics, including several anticancer drugs, preventing their entry into the brain. Gliomas are the most common primary tumors diagnosed in adults, which are often characterized by a poor prognosis, notably in the case of high-grade gliomas. Therapeutic treatments frequently fail due to the difficulty of delivering drugs through the brain barriers, adding to diverse mechanisms developed by the cancer, including the overexpression or expression de novo of ABC transporters in tumoral cells and/or in the endothelial cells forming the blood-brain tumor barrier (BBTB). Many models have been developed to study the phenotype, molecular characteristics, and function of the blood-brain interfaces as well as to evaluate drug permeability into the brain. These include in vitro, in vivo, and in silico models, which together can help us to better understand their implication in drug resistance and to develop new therapeutics or delivery strategies to improve the treatment of pathologies of the central nervous system (CNS). In this review, we present the principal characteristics of the blood-brain interfaces; then, we focus on the ABC transporters present on them and their implication in drug delivery; next, we present some of the most important models used for the study of drug transport; finally, we summarize the implication of ABC transporters in glioma and the BBTB in drug resistance and the strategies to improve the delivery of CNS anticancer drugs.

Localized Metabolomic Gradients in Patient-Derived Xenograft Models of Glioblastoma

Glioblastoma (GBM) is increasingly recognized as a disease involving dysfunctional cellular metabolism. GBMs are known to be complex heterogeneous systems containing multiple distinct cell populations and are supported by an aberrant network of blood vessels. A better understanding of GBM metabolism, its variation with respect to the tumor microenvironment, and resulting regional changes in chemical composition is required. This may shed light on the observed heterogeneous drug distribution, which cannot be fully described by limited or uneven disruption of the blood-brain barrier. In this work, we used mass spectrometry imaging (MSI) to map metabolites and lipids in patient-derived xenograft models of GBM. A data analysis workflow revealed that distinctive spectral signatures were detected from different regions of the intracranial tumor model. A series of long-chain acylcarnitines were identified and detected with increased intensity at the tumor edge. A 3D MSI dataset demonstrated that these molecules were observed throughout the entire tumor/normal interface and were not confined to a single plane. mRNA sequencing demonstrated that hallmark genes related to fatty acid metabolism were highly expressed in samples with higher acylcarnitine content. These data suggest that cells in the core and the edge of the tumor undergo different fatty acid metabolism, resulting in different chemical environments within the tumor. This may influence drug distribution through changes in tissue drug affinity or transport and constitute an important consideration for therapeutic strategies in the treatment of GBM. SIGNIFICANCE: GBM tumors exhibit a metabolic gradient that should be taken into consideration when designing therapeutic strategies for treatment.See related commentary by Tan and Weljie, p. 1231.

Systems biology approaches to measure and model phenotypic heterogeneity in cancer

The recent wide-spread adoption of single cell profiling technologies has revealed that individual cancers are not homogenous collections of deregulated cells, but instead are comprised of multiple genetically and phenotypically distinct cell subpopulations that exhibit a wide range of responses to extracellular signals and therapeutic insult. Such observations point to the urgent need to understand cancer as a complex, adaptive system. Cancer systems biology studies seek to develop the experimental and theoretical methods required to understand how biological components work together to determine how cancer cells function. Ultimately, such approaches will lead to improvements in how cancer is managed and treated. In this review, we discuss recent advances in cancer systems biology approaches to quantify, model, and elucidate mechanisms of heterogeneity.

Acridine Orange: A Review of Novel Applications for Surgical Cancer Imaging and Therapy

Introduction: Acridine orange (AO) was first extracted from coal tar in the late nineteenth century and was used as a fluorescent dye. In this paper, we review emergent research about novel applications of AO for fluorescence surgery and cancer therapy. Materials and methods: We performed a systematic search in the MEDLINE, PubMed, Cochrane library, Google Scholar, Embase, Web of Science, and Scopus database using combinations of the term "acridine orange" with the following: "surgical oncology," "neuropathology," "microsurgery," "intraoperative fluorescence," "confocal microscopy," "pathology," "endomicroscopy," "guidance," "fluorescence guidance," "oncology," "surgery," "neurooncology," and "photodynamic therapy." Peer-reviewed articles published in English were included in this review. We have also scanned references for relevant articles. Results: We have reviewed studies on the various application of AO in microscopy, endomicroscopy, intraoperative fluorescence guidance, photodynamic therapy, sonodynamic therapy, radiodynamic therapy. Conclusion: Although the number of studies on the clinical use of AO is limited, pilot studies have demonstrated the safety and feasibility of its application as an intraoperative fluorescent dye and as a novel photo- and radio-sensitizator. Further clinical studies are necessary to more definitively assess the clinical benefit AO-based fluorescence guidance, therapy for sarcomas, and to establish feasibility of this new approach for the treatment of other tumor types.

Pre- and Postoperative Neratinib for HER2-Positive Breast Cancer Brain Metastases: Translational Breast Cancer Research Consortium 022

PURPOSE

This pilot study was performed to test our ability to administer neratinib monotherapy before clinically recommended craniotomy in patients with HER2-positive metastatic breast cancer to the central nervous system, to examine neratinib's central nervous system penetration at craniotomy, and to examine postoperative neratinib maintenance.

PATIENTS AND METHODS

Patients with HER2-positive brain metastases undergoing clinically indicated cranial resection of a parenchymal tumor received neratinib 240 mg orally once a day for 7 to 21 days preoperatively, and resumed therapy postoperatively in 28-day cycles. Exploratory evaluations of time to disease progression, survival, and correlative tissue, cerebrospinal fluid (CSF), and blood-based analyses examining neratinib concentrations were planned. The study was registered at ClinicalTrials.gov under number NCT01494662.

RESULTS

We enrolled 5 patients between May 22, 2013, and October 18, 2016. As of March 1, 2019, patients had remained on the study protocol for 1 to 75+ postoperative cycles pf therapy. Two patients had grade 3 diarrhea. Evaluation of the CSF showed low concentrations of neratinib; nonetheless, 2 patients continued to receive therapy without disease progression for at least 13 cycles, with one on-study treatment lasting for nearly 6 years. Neratinib distribution in surgical tissue was variable for 1 patient, while specimens from 2 others did not produce conclusive results as a result of limited available samples.

CONCLUSION

Neratinib resulted in expected rates of diarrhea in this small cohort, with 2 of 5 patients receiving the study treatment for durable periods. Although logistically challenging, we were able to test a limited number of CSF- and parenchymal-based neratinib concentrations. Our findings from resected tumor tissue in one patient revealed heterogeneity in drug distribution and tumor histopathology.

The Physics of Cancer

While often described as a "disease of the genes," cancer is, in fact, a complex dynamic system in which evolving cells both affect and are affected by the physical properties of their environment. About 10 years ago, after a number of multidisciplinary workshops and meetings, the NCI leadership embarked on a bold program to systematically integrate physical sciences into cancer biology and treatment through formation of the Physical Sciences-Oncology Network (PS-ON). Here, we highlight key areas in which the two disciplines have been successfully integrated and lessons learned from the first decade of the PS-ON experiment.

Automatic 3D Nonlinear Registration of Mass Spectrometry Imaging and Magnetic Resonance Imaging Data

Multimodal integration between mass spectrometry imaging (MSI) and radiology-established modalities such as magnetic resonance imaging (MRI) would allow the investigations of key questions in complex biological systems such as the central nervous system. Such integration would provide complementary multiscale data to bridge the gap between molecular and anatomical phenotypes, potentially revealing new insights into molecular mechanisms underlying anatomical pathologies presented on MRI. Automatic coregistration between 3D MSI/MRI is a computationally challenging process due to dimensional complexity, MSI data sparsity, lack of direct spatial-correspondences, and nonlinear tissue deformation. Here, we present a new computational approach based on stochastic neighbor embedding to nonlinearly align 3D MSI to MRI data, identify and reconstruct biologically relevant molecular patterns in 3D, and fuse the MSI datacube to the MRI space. We demonstrate our method using multimodal high-spectral resolution matrix-assisted laser desorption ionization (MALDI) 9.4 T MSI and 7 T in vivo MRI data, acquired from a patient-derived, xenograft mouse brain model of glioblastoma following administration of the EGFR inhibitor drug of Erlotinib. Results show the distribution of some identified molecular ions of the EGFR inhibitor erlotinib, a phosphatidylcholine lipid, and cholesterol, which were reconstructed in 3D and mapped to the MRI space. The registration quality was evaluated on two normal mouse brains using the Dice coefficient for the regions of brainstem, hippocampus, and cortex. The method is generic and can therefore be applied to hyperspectral images from different mass spectrometers and integrated with other established in vivo imaging modalities such as computed tomography (CT) and positron emission tomography (PET).