MR Elastography Analysis of Glioma Stiffness and IDH1-Mutation Status

Advances in liquid biopsy and virtual biopsy for care of patients with glioma: a narrative review

INTRODUCTION

The World Health Organization's 2021 classification of central nervous system neoplasms incorporated molecular and genetic features for classifying gliomas. Classification of gliomas located in deep-seated structures became a clinical conundrum given the absence of crucial pathological and molecular data. Advances in noninvasive imaging modalities offered virtual biopsy as a novel solution to this problem by identifying surrogate radiomic signatures. Liquid biopsies of blood or cerebrospinal fluid provided another enormous opportunity for identifying genomic, metabolomic and proteomic signatures.

AREAS COVERED

We summarize and appraise the current state of evidence with regards to virtual biopsy and liquid biopsy in the care of patients with gliomas. PubMed, Embase and Google Scholar were searched on 7/30/2024 for relevant articles published after the year 2013 in the English language.

EXPERT OPINION

A large body of preclinical and preliminary clinical evidence suggests that virtual biopsy is possible with the combined use of multiple novel imaging modalities in conjunction with machine learning and radiomics. Likewise, liquid biopsy in conjunction with focused ultrasound may be a valuable tool to obtain proteomic and genomic data regarding glioma in a minimally invasive manner. These modalities will likely become an integral part of care for patients with glioma in the future.

Actuated Hydrogel Platforms To Study Brain Cell Behavior

The human brain is a highly complex organ characterized by intricate neural networks, biochemical signaling, and unique mechanical properties. The soft and dynamic viscoelastic extracellular matrix (ECM) plays a crucial role in supporting different types of brain cells and influencing their behavior. Understanding how brain cells respond to mechanical stimuli within this complex environment is essential for unraveling fundamental mechanisms of healthy, unhealthy, and regenerative functions within the central nervous system. This requires the development of advanced materials and techniques to study the interplay between mechanical cues and cell responses. Hydrogels have become essential in this research, mimicking the brain's ECM in both chemical composition and mechanical behavior. Conventional hydrogels, while helpful, are static and lack dynamic stimulation. On the other hand, dynamic hydrogels provide reversible, dynamic stimulation, closely replicating the brain's ECM properties. This review discusses current hydrogel platforms used to investigate brain function in health and disease, focusing on traumatic brain injury (TBI)-like conditions and brain tumors. These dynamic materials offer sophisticated tools for understanding brain cell mechanobiology and developing new therapeutic approaches.

Matrix Stiffness Regulates GBM Migration and Chemoradiotherapy Responses via Chromatin Condensation in 3D Viscoelastic Matrices

Glioblastoma multiforme (GBM) progression is associated with changes in matrix stiffness, and different regions of the tumor niche exhibit distinct stiffnesses. Using elastic hydrogels, previous work has demonstrated that matrix stiffness modulates GBM behavior and drug responses. However, brain tissue is viscoelastic, and how stiffness impacts the GBM invasive phenotype and response to therapy within a viscoelastic niche remains largely unclear. Here, we report a three-dimensional (3D) viscoelastic GBM hydrogel system that models the stiffness heterogeneity present within the tumor niche. We find that GBM cells exhibit enhanced migratory ability, proliferation, and resistance to radiation in soft matrices, mimicking the tumor core and perifocal margins. Conversely, GBM cells remain confined and demonstrate increased resistance to chemotherapy in stiff matrices mimicking edematous tumor regions. We identify that stiffness-induced changes in the GBM phenotype are regulated by nuclear mechanosensing and chromatin condensation. Pharmacologically decondensing the chromatin significantly impedes GBM migration and overcomes stiffness-induced chemoresistance and radioresistance. Our findings highlight that stiffness regulates aggressive GBM behavior in viscoelastic matrices through mechanotransduction processes. Finally, we reveal the critical role of chromatin condensation in mediating GBM migration and therapy resistance, offering a potential new therapeutic target to improve GBM treatment outcomes.

Tumor cells escape immunosurveillance by hampering LFA-1

During tumor immunosurveillance, leukocytes play a crucial role in the cellular defense system, working collaboratively with other immune components to recognize and eliminate aberrant cells. Integral to this process is the integrin Lymphocyte Function-Associated Antigen 1 (LFA-1). LFA-1 facilitates adhesion during leukocyte migration and helps establish stable cell-to-cell contacts between leukocytes and their targets. Additionally, as a receptor, LFA-1 signaling activates leukocytes, promoting their differentiation and effector functions against cancer. However, tumors can develop mechanisms to evade immune clearance by disrupting LFA-1 functions or hijacking its pathways. In this review, we first detail how leukocytes utilize LFA-1 during immunosurveillance and then explore how tumors counteract this process in the tumor microenvironment (TME) by either altering LFA-1 functions or exploiting it to drive tumorigenesis. Moreover, we discuss therapeutic strategies targeting LFA-1, including inhibitors tested in laboratory studies and animal models, highlighting their potential as anticancer interventions and the need for further research to evaluate their clinical utility.

Iron promotes isocitrate dehydrogenase mutant glioma cell motility

Enriched iron metabolic features such as high transferrin receptor (TfR) expression and high iron content are commonly observed in aggressive gliomas and can be associated with poor clinical responses. However, the underlying question of how iron contributes to tumor aggression remains elusive. Gliomas harboring isocitrate dehydrogenase (IDH) mutations account for a high percentage (>70 %) of recurrent tumors and cells with an acquired IDH mutation have been reported to have increased motility and invasion. This study aims to investigate how an acquired IDH mutation modulates iron metabolism and the implication(s) of iron on tumor cell growth. IDH mutant cells (U87R132H) grow significantly faster which is accompanied with increased TfR expression and iron uptake in vitro compared to wild-type U87 cells. This phenotype is retained in vivo. Biomechanically, U87R132H cells are significantly less stiff and supplementation with ferrous ammonium sulfate (Fe2+) augments membrane fluidity to drive U87R132H cells into a super motile state. These findings provide insight into how an acquired IDH mutation may be able to modulate iron metabolism, allowing iron to serve as a biomechanical driver of tumor progression.

MR Elastography Using the Gravitational Transducer

MR elastography is a non-invasive imaging technique that provides quantitative maps of tissue biomechanical properties, i.e., elasticity and viscosity. Currently, hepatic MR elastography is deployed in the clinic to assess liver fibrosis in MAFLD patients. In addition, research has demonstrated MR elastography's ability to non-invasively assess chronic liver disease and to characterize breast cancer lesions and brain tumors. MR elastography requires efficient mechanical wave generation and penetration, motion-sensitized MRI sequences, and MR elastography inversion algorithms to retrieve the biomechanical properties of the tissue. MR elastography promises to enable non-invasive and versatile assessment of tissue, leading to better diagnosis and staging of several clinical conditions.

Advanced imaging techniques and non-invasive biomarkers in pediatric brain tumors: state of the art

In the pediatric age group, brain neoplasms are the second most common tumor category after leukemia, with an annual incidence of 6.13 per 100,000. Conventional MRI sequences, complemented by CT whenever necessary, are fundamental for the initial diagnosis and surgical planning as well as for post-operative evaluations, assessment of response to treatment, and surveillance; however, they have limitations, especially concerning histopathologic or biomolecular phenotyping and grading. In recent years, several advanced MRI sequences, including diffusion-weighted imaging, diffusion tensor imaging, arterial spin labelling (ASL) perfusion, and MR spectroscopy, have emerged as a powerful aid to diagnosis as well as prognostication; furthermore, other techniques such as diffusion kurtosis, amide proton transfer imaging, and MR elastography are being translated from the research environment to clinical practice. Molecular imaging, especially PET with amino-acid tracers, complement MRI in several aspects, including biopsy targeting and outcome prediction. Finally, radiomics with radiogenomics are opening entirely new perspectives for a quantitative approach aiming at identifying biomarkers that can be used for personalized, precision management strategies.

Mechanical properties of pediatric low-grade gliomas in children with and without neurofibromatosis type 1

INTRODUCTION

Prognoses for pediatric brain tumors are suboptimal, as even in low-grade tumors, management techniques can lead to damage in the developing brain. Therefore, advanced neuroimaging methods are critical for developing optimal management plans and improving patient care. Magnetic resonance elastography (MRE) has allowed for the characterization of adult gliomas by their mechanical properties, which are uniquely sensitive to the complex interplay of cellularity, vasculature, and interstitium. However, pediatric tumors differ in behavior and cytoarchitecture, and their mechanical properties have never been assessed.

METHODS

Here, we conduct the first study of pediatric brain tumor mechanical properties by using MRE to measure tissue stiffness and damping ratio in low grade gliomas (LGGs). We additionally measure the mechanical properties of non-neoplastic focal abnormal signal intensities (FASIs) in children with neurofibromatosis type 1 (NF1).

RESULTS

23 patients age 4-17 years who had MR imaging results consistent with a primary LGG or with NF1 were included in this study. We found that pediatric gliomas are on an average 10.9% softer (p = 0.010) with a 17.3% lower (p = 0.009) viscosity than reference tissue. Softness of tumors appeared consistent across tumor subtypes and unrelated to tumor size or contrast-enhancement. In NF1 we found that, unlike gliomas, FASIs are stiffer, though not significantly, than reference tissue by an average of 10.4% and have a 16.7% lower damping ratio.

CONCLUSIONS

Measuring tumor mechanical properties patterning and heterogeneity has potential to aid in prediction of biological behavior and inform management strategies for pediatric patients.

Intraoperative Comparison Between Strain Elastography and Preoperative Magnetic Resonance Imaging Features in High-Grade Gliomas Using Fusion Imaging: A Pilot Study

OBJECTIVE

To compare the elastographic patterns of high-grade gliomas (HGGs) solid portions and those of adjacent healthy brain parenchyma, on intraoperative ultrasound, with magnetic resonance image (MRI) characteristics.

METHODS

Clinical records and images of HGGs patients, operated between June and December 2018, were retrospectively reviewed. Fusion images were used to compare preoperative gadolinium-enhanced T1-weighted MRI/fluid-attenuated inversion recovery images (Gd-T1 MRI/FLAIR) to intraoperative strain elastography (SE). FLAIR/Gd-T1 MRI images were used to define enhancement patterns (absent/whole lesion/peripheral) and lesions' characteristics (primary and secondary pattern, further subdivided in solid/necrotic/cystic/infiltrating). HGGs SE patterns were categorized as homogeneous/inhomogeneous, while lesions' primary and secondary patterns as stiff/intermediate/elastic. The SE motive of neighboring healthy brain parenchyma was defined similarly.

RESULTS

Eighteen patients (M:F, 11:7; mean age: 53 years) harboring 14 glioblastomas (77.8%) and 4 anaplastic astrocytomas (22.2%) were compared. Glioblastomas typically enhanced peripherally and had a primary necrotic pattern (78.6% and 64.3%, respectively), while anaplastic astrocytomas did not enhance and were solid (75% both) at T1-Gd MRI and FLAIR images. At SE anaplastic astrocytomas had a homogeneous stiff primary pattern, whereas the majority of glioblastomas primary patterns were heterogeneous (85.7%) and intermediate (78.6%).

CONCLUSIONS

Three major SE patterns defined HGGs and adjacent healthy brain parenchyma. SE patterns varied according to HGG histotypes and Gd-T1 MRI/FLAIR characteristics.

Mechanical Properties of Inflamed Appendix Tissues

Background/Objectives: Histopathological examination enables visualization of morphological changes in cells and tissues. In recent years, there has been increasing interest in assessing the mechanical properties of tissues that cannot be determined by standard histopathological examinations. Mechanobiology is crucial in human physiology and holds promise for uncovering new diagnostic markers for disease processes such as carcinogenesis and inflammation. In this study, we concentrated on measuring the mechanical properties of appendix biopsy specimens to identify potential mechanomarkers of inflammation. Appendix tissues provided the opportunity to measure mechanical properties both with an atomic force microscope and a shear rheometer. Methods: The atomic force microscope AFM-NanoWizard 4 BioScience JPK/Bruker was used for the evaluation of the elastic modulus (i.e., Young's modulus) of appendix tissues. Young's modulus was derived from the Hertz-Sneddon model applied to force-indentation curves. The rheological properties of macroscopic samples were measured on a parallel-plate, strain-controlled shear rheometer Anton Paar MCR302. Results: The data collected suggest that elasticity, expressed as Young's modulus and the storage modulus, could be considered a marker indicating appendix tissue inflammation. Young's modulus of inflamed appendix tissues was found to be significantly lower than that of healthy ones, with an average reduction of 67%. Furthermore, it was observed that inflamed appendix tissues, in comparison to healthy ones, respond differently under varying axial and shear stresses, enabling their identification. Conclusions: Our findings suggest that the specific mechanical properties of inflamed vermiform appendices could serve as novel mechanomarkers for the early detection and monitoring of appendicitis.

The Networking Brain: How Extracellular Matrix, Cellular Networks, and Vasculature Shape the In Vivo Mechanical Properties of the Brain

Mechanically, the brain is characterized by both solid and fluid properties. The resulting unique material behavior fosters proliferation, differentiation, and repair of cellular and vascular networks, and optimally protects them from damaging shear forces. Magnetic resonance elastography (MRE) is a noninvasive imaging technique that maps the mechanical properties of the brain in vivo. MRE studies have shown that abnormal processes such as neuronal degeneration, demyelination, inflammation, and vascular leakage lead to tissue softening. In contrast, neuronal proliferation, cellular network formation, and higher vascular pressure result in brain stiffening. In addition, brain viscosity has been reported to change with normal blood perfusion variability and brain maturation as well as disease conditions such as tumor invasion. In this article, the contributions of the neuronal, glial, extracellular, and vascular networks are discussed to the coarse-grained parameters determined by MRE. This reductionist multi-network model of brain mechanics helps to explain many MRE observations in terms of microanatomical changes and suggests that cerebral viscoelasticity is a suitable imaging marker for brain disease.

Mechanobiological insight into brain diseases based on mechanosensitive channels: Common mechanisms and clinical potential

BACKGROUND

As physical signals, mechanical cues regulate the neural cells in the brain. The mechanosensitive channels (MSCs) perceive the mechanical cues and transduce them by permeating specific ions or molecules across the plasma membrane, and finally trigger a series of intracellular bioelectrical and biochemical signals. Emerging evidence supports that wide-distributed, high-expressed MSCs like Piezo1 play important roles in several neurophysiological processes and neurological disorders.

AIMS

To systematically conclude the functions of MSCs in the brain and provide a novel mechanobiological perspective for brain diseases.

METHOD

We summarized the mechanical cues and MSCs detected in the brain and the research progress on the functional roles of MSCs in physiological conditions. We then concluded the pathological activation and downstream pathways triggered by MSCs in two categories of brain diseases, neurodegenerative diseases and place-occupying damages. Finally, we outlined the methods for manipulating MSCs and discussed their medical potential with some crucial outstanding issues.

RESULTS

The MSCs present underlying common mechanisms in different brain diseases by acting as the "transportation hubs" to transduce the distinct signal patterns: the upstream mechanical cues and the downstream intracellular pathways. Manipulating the MSCs is feasible to alter the complicated downstream processes, providing them promising targets for clinical treatment.

CONCLUSIONS

Recent research on MSCs provides a novel insight into brain diseases. The common mechanisms mediated by MSCs inspire a wide range of therapeutic potentials targeted on MSCs in different brain diseases.

Glioblastoma mechanobiology at multiple length scales

Glioblastoma multiforme (GBM), a primary brain cancer, is one of the most aggressive forms of human cancer, with a very low patient survival rate. A characteristic feature of GBM is the diffuse infiltration of tumor cells into the surrounding brain extracellular matrix (ECM) that provide biophysical, topographical, and biochemical cues. In particular, ECM stiffness and composition is known to play a key role in controlling various GBM cell behaviors including proliferation, migration, invasion, as well as the stem-like state and response to chemotherapies. In this review, we discuss the mechanical characteristics of the GBM microenvironment at multiple length scales, and how biomaterial scaffolds such as polymeric hydrogels, and fibers, as well as microfluidic chip-based platforms have been employed as tissue mimetic models to study GBM mechanobiology. We also highlight how such tissue mimetic models can impact the field of GBM mechanobiology.

Wavelet MRE: Imaging propagating broadband acoustic waves with wavelet-based motion-encoding gradients

PURPOSE

To demonstrate a novel MR elastography (MRE) technique, termed here wavelet MRE. With this technique, broadband motion sensitivity is achievable. Moreover, the true tissue displacement can be reconstructed with a simple inverse transform.

METHODS

A wavelet MRE sequence was developed with motion-encoding gradients based on Haar wavelets. From the phase images' displacement was estimated using an inverse transform. Simulations were performed using a frequency sweep and a transient as ground-truth motions. A PVC phantom was scanned using wavelet MRE and standard MRE with both transient (one and 10 cycles of 90-Hz motion) and steady-state dual-frequency motion (30 and 60 Hz) for comparison. The technique was tested in a human brain, and motion trajectories were estimated for each voxel.

RESULTS

In simulation, the displacement information estimated from wavelet MRE closely matched the true motion. In the phantom test, the MRE phase data generated from the displacement information derived from wavelet MRE agreed well with standard MRE data. Testing of wavelet MRE to assess transient motion waveforms in the brain was successful, and the tissue motion observed was consistent with a previous study.

CONCLUSION

The uniform and broadband frequency response of wavelet MRE makes it a promising method for imaging transient, multifrequency motion, or motion with unknown frequency content. One potential application is measuring the response of brain tissue undergoing low-amplitude, transient vibrations as a model for the study of traumatic brain injury.

MT-125 Inhibits Non-Muscle Myosin IIA and IIB, Synergizes with Oncogenic Kinase Inhibitors, and Prolongs Survival in Glioblastoma

We have identified a NMIIA and IIB-specific small molecule inhibitor, MT-125, and have studied its effects in GBM. MT-125 has high brain penetrance and retention and an excellent safety profile; blocks GBM invasion and cytokinesis, consistent with the known roles of NMII; and prolongs survival as a single agent in murine GBM models. MT-125 increases signaling along both the PDGFR- and MAPK-driven pathways through a mechanism that involves the upregulation of reactive oxygen species, and it synergizes with FDA-approved PDGFR and mTOR inhibitors in vitro . Combining MT-125 with sunitinib, a PDGFR inhibitor, or paxalisib, a combined PI3 Kinase/mTOR inhibitor significantly improves survival in orthotopic GBM models over either drug alone, and in the case of sunitinib, markedly prolongs survival in ∼40% of mice. Our results provide a powerful rationale for developing NMII targeting strategies to treat cancer and demonstrate that MT-125 has strong clinical potential for the treatment of GBM.

Highlights

MT-125 is a highly specific small molecule inhibitor of non-muscle myosin IIA and IIB, is well-tolerated, and achieves therapeutic concentrations in the brain with systemic dosing.Treating preclinical models of glioblastoma with MT-125 produces durable improvements in survival.MT-125 stimulates PDGFR- and MAPK-driven signaling in glioblastoma and increases dependency on these pathways.Combining MT-125 with an FDA-approved PDGFR inhibitor in a mouse GBM model synergizes to improve median survival over either drug alone, and produces tumor free, prolonged survival in over 40% of mice.

Advances in Neuro-Oncological Imaging: An Update on Diagnostic Approach to Brain Tumors

This study delineates the pivotal role of imaging within the field of neurology, emphasizing its significance in the diagnosis, prognostication, and evaluation of treatment responses for central nervous system (CNS) tumors. A comprehensive understanding of both the capabilities and limitations inherent in emerging imaging technologies is imperative for delivering a heightened level of personalized care to individuals with neuro-oncological conditions. Ongoing research in neuro-oncological imaging endeavors to rectify some limitations of radiological modalities, aiming to augment accuracy and efficacy in the management of brain tumors. This review is dedicated to the comparison and critical examination of the latest advancements in diverse imaging modalities employed in neuro-oncology. The objective is to investigate their respective impacts on diagnosis, cancer staging, prognosis, and post-treatment monitoring. By providing a comprehensive analysis of these modalities, this review aims to contribute to the collective knowledge in the field, fostering an informed approach to neuro-oncological care. In conclusion, the outlook for neuro-oncological imaging appears promising, and sustained exploration in this domain is anticipated to yield further breakthroughs, ultimately enhancing outcomes for individuals grappling with CNS tumors.

Supershear Rayleigh wave imaging for quantitative assessment of biomechanical properties of brain using air-coupled optical coherence elastography

Recently, supershear Rayleigh waves (SRWs) have been proposed to characterize the biomechanical properties of soft tissues. The SRWs propagate along the surface of the medium, unlike surface Rayleigh waves, SRWs propagate faster than bulk shear waves. However, their behavior and application in biological tissues is still elusive. In brain tissue elastography, shear waves combined with magnetic resonance elastography or ultrasound elastography are generally used to quantify the shear modulus, but high spatial resolution elasticity assessment in 10 μm scale is still improving. Here, we develop an air-coupled ultrasonic transducer for noncontact excitation of SRWs and Rayleigh waves in brain tissue, use optical coherent elastography (OCE) to detect, and reconstruct the SRW propagation process; in combing with a derived theoretical model of SRWs on a free boundary surface, we quantify the shear modulus of brain tissue with high spatial resolution. We first complete validation experiments using a homogeneous isotropic agar phantom, and the experimental results clearly show the SRW is 1.9649 times faster than the bulk shear waves. Furthermore, the propagation velocity of SRWs in both the frontal and parietal lobe regions of the brain is all 1.87 times faster than the bulk shear wave velocity. Finally, we evaluated the anisotropy in different brain regions, and the medulla oblongata region had the highest anisotropy index. Our study shows that the OCE system using the SRW model is a new potential approach for high-resolution assessment of the biomechanical properties of brain tissue.

Clinical application of magnetic resonance elastography in pediatric neurological disorders

Magnetic resonance elastography is a relatively new, rapidly evolving quantitative magnetic resonance imaging technique which can be used for mapping the viscoelastic mechanical properties of soft tissues. MR elastography measurements are akin to manual palpation but with the advantages of both being quantitative and being useful for regions which are not available for palpation, such as the human brain. MR elastography is noninvasive, well tolerated, and complements standard radiological and histopathological studies by providing in vivo measurements that reflect tissue microstructural integrity. While brain MR elastography studies in adults are becoming frequent, published studies on the utility of MR elastography in children are sparse. In this review, we have summarized the major scientific principles and recent clinical applications of brain MR elastography in diagnostic neuroscience and discuss avenues for impact in assessing the pediatric brain.

Correlation analysis of MR elastography and Ki-67 expression in intrahepatic cholangiocarcinoma

BACKGROUND

Intrahepatic cholangiocarcinoma (iCCA) is an aggressive primary liver cancer with dismal outcome, high Ki-67 expression is associated with active progression and poor prognosis of iCCA, the application of MRE in the prediction of iCCA Ki-67 expression has not yet been investigated until now. We aimed to evaluate the value of magnetic resonance elastography (MRE) in assessing Ki-67 expression for iCCA.

RESULTS

In the whole cohort, 97 patients (57 high Ki-67 and 40 low Ki-67; 58 males, 39 females; mean age, 58.89 years, ranges 36-70 years) were included. At the multivariate analysis, tumor stiffness (odds ratio (OR) = 1.669 [95% CI: 1.307-2.131], p < 0.001) and tumor apparent diffusion coefficient (ADC) (OR = 0.030 [95% CI: 0.002, 0.476], p = 0.013) were independent significant variables associated with Ki-67. Areas under the curve of tumor stiffness for the identification of high Ki-67 were 0.796 (95% CI 0.702, 0.871). Tumor stiffness was moderately correlated with Ki-67 level (r = 0.593, p < 0.001). When both predictive variables of tumor stiffness and ADC were integrated, the best performance was achieved with area under the curve values of 0.864 (95% CI 0.780-0.926).

CONCLUSION

MRE-based tumor stiffness correlated with Ki-67 in iCCA and could be investigated as a potential prognostic biomarker. The combined model incorporating both tumor stiffness and ADC increased the predictive performance.

CRITICAL RELEVANCE STATEMENT

MRE-based tumor stiffness might be a surrogate imaging biomarker to predict Ki-67 expression in intrahepatic cholangiocarcinoma patients, reflecting tumor cellular proliferation. The combined model incorporating both tumor stiffness and apparent diffusion coefficient increased the predictive performance.

KEY POINTS

• MRE-based tumor stiffness shows a significant correlation with Ki-67. • The combined model incorporating tumor stiffness and apparent diffusion coefficient demonstrated an optimized predictive performance for Ki-67 expression. • MRE-based tumor stiffness could be investigated as a potential prognostic biomarker for intrahepatic cholangiocarcinoma.

Applying Shear Wave and Magnetic Resonance Elastography to Grade Brain Tumors: Systematic Review and Meta-Analysis

BACKGROUND

Reports find that magnetic resonance elastography (MRE) and shear wave elastography (SWE) can classify intracranial tumors according to stiffness. However, systematic syntheses of these articles are lacking. In this report, a systematic review and meta-analysis was performed to evaluate whether SWE and MRE can predict meningioma and glioma grades.

METHODS

PubMed and Scopus were searched between February 10, 2022. and March 2, 2022. using manual search criteria. Eight out of 106 non-duplicate records were included, encompassing 84 patients with low-grade tumors (age 42 ± 13 years, 71% female) and 92 patients with high-grade tumors (age 50 ± 13 years, 42% female). Standardized mean difference in stiffness between high-grade and low-grade tumors were measured using a forest plot. The I2, χ2, and t tests were performed, and bubble plots were constructed to measure heterogeneity. An adapted QUADAS-2 scale evaluated study quality. Additionally, a funnel plot was constructed, and an Egger's intercept test determined study bias.

RESULTS

Low-grade tumors were stiffer than high-grade tumors (Cohen's D = -1.25; 95% CI -1.88, -0.62). Moderate heterogeneity was observed (I2 = 67%; P = 0.006) but controlling for publication year (I2 = 0.2%) and age (I2 = 0.0%-17%) reduced heterogeneity. Included studies revealed unclear or high bias for the reference standard and flow and timing (>50%).

CONCLUSIONS

Elastography techniques have potential to grade tumors intraoperatively and postoperatively. More studies are needed to evaluate the clinical utility of these technologies.

Tumor sound, auditory cues, and tissue pathology in glioma surgery: a proof-of-concept study

OBJECTIVE

Visual, tactile, and auditory cues are used during surgery to differentiate tissue type. Auditory cues in glioma surgery have not been studied previously. The objectives of this study were 1) to evaluate the feasibility of recording sound generated by the suction device during glioma surgery in matched tissue samples, and 2) to characterize the acoustic variation that occurs in different tissue samples.

METHODS

This was a prospective observational proof-of-concept study. Recordings were attempted in 20 patients in order meet the accrual target of 10 patients with matched sound and tissue data. For each patient, three 30- to 60-second recordings were made at these sites: normal white matter, infiltrative margin, and tumor. Tissue samples at each site were then reviewed by experienced neuropathologists, and agreement with surgical identification was estimated with the kappa statistic. Acoustic parameters were characterized for each sample.

RESULTS

Data from 20 patients were analyzed. Patient-related or technical issues resulted in missing data for 10 patients, but the final 10 patients had both audio and tissue data for analysis. Among all tissue samples, fair agreement was observed between surgeon identification and actual pathology (κ = 0.24, standard error 0.096, p = 0.006). Acoustic data suggested that 1) the acoustic stimulus is broadband, 2) acoustic features are somewhat consistent within cases, 3) high-entropy values indicate irregularity of sound over time, and 4) bimodal pitch distributions could differentially reflect cues of interest.

CONCLUSIONS

This study supports the feasibility of collecting intraoperative data on acoustic features during glioma surgery, and it provides an example of how an analysis could be performed to compare different types of tissues.

MR Elastography in Cancer

ABSTRACT

The mechanical traits of cancer include abnormally high solid stress as well as drastic and spatially heterogeneous changes in intrinsic mechanical tissue properties. Whereas solid stress elicits mechanosensory signals promoting tumor progression, mechanical heterogeneity is conducive to cell unjamming and metastatic spread. This reductionist view of tumorigenesis and malignant transformation provides a generalized framework for understanding the physical principles of tumor aggressiveness and harnessing them as novel in vivo imaging markers. Magnetic resonance elastography is an emerging imaging technology for depicting the viscoelastic properties of biological soft tissues and clinically characterizing tumors in terms of their biomechanical properties. This review article presents recent technical developments, basic results, and clinical applications of magnetic resonance elastography in patients with malignant tumors.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 2

Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Nanomechanical Signatures in Glioma Cells Depend on CD44 Distribution in IDH1 Wild-Type but Not in IDH1R132H Mutant Early-Passage Cultures

Atomic force microscopy (AFM) recently burst into biomedicine, providing morphological and functional characteristics of cancer cells and their microenvironment responsible for tumor invasion and progression, although the novelty of this assay needs to coordinate the malignant profiles of patients' specimens to diagnostically valuable criteria. Applying high-resolution semi-contact AFM mapping on an extended number of cells, we analyzed the nanomechanical properties of glioma early-passage cell cultures with a different IDH1 R132H mutation status. Each cell culture was additionally clustered on CD44+/- cells to find possible nanomechanical signatures that differentiate cell phenotypes varying in proliferative activity and the characteristic surface marker. IDH1 R132H mutant cells compared to IDH1 wild-type ones (IDH1wt) characterized by two-fold increased stiffness and 1.5-fold elasticity modulus. CD44+/IDH1wt cells were two-fold more rigid and much stiffer than CD44-/IDH1wt ones. In contrast to IDH1 wild-type cells, CD44+/IDH1 R132H and CD44-/IDH1 R132H did not exhibit nanomechanical signatures providing statistically valuable differentiation of these subpopulations. The median stiffness depends on glioma cell types and decreases according to the following manner: IDH1 R132H mt (4.7 mN/m), CD44+/IDH1wt (3.7 mN/m), CD44-/IDH1wt (2.5 mN/m). This indicates that the quantitative nanomechanical mapping would be a promising assay for the quick cell population analysis suitable for detailed diagnostics and personalized treatment of glioma forms.

Gastrointestinal pan-cancer landscape of tumor matrix heterogeneity identifies biologically distinct matrix stiffness subtypes predicting prognosis and chemotherapy efficacy

Gastrointestinal (GI) cancers are a heterogeneous group of primary solid tumors, arising in GI tract from the esophagus to rectum. Matrix stiffness (MS) is a critical physical factor for cancer progression; however, its importance in tumor progression remains to be comprehensively recognized. Herein, we conducted a comprehensive pan-cancer analysis of MS subtypes across seven GI-cancer types. Using unsupervised clustering based on literature-derived MS-specific pathway signatures, the GI-tumor samples were divided into three MS subtypes, termed as the Soft, Mixed and Stiff. Then, distinct prognoses, biological features, tumor microenvironments and mutation landscapes among three MS subtypes were revealed. The Stiff tumor subtype was associated with the poorest prognosis, the most malignant biological behaviors, and the immunosuppressive tumor stromal microenvironment. Furthermore, multiple machine learning algorithms were used to develop an 11-gene MS-signature to identify the MS subtypes of GI-caner and predict chemotherapy sensitivity, which were further validated in two external GI-cancer cohorts. This novel MS-based classification on GI-cancers could enhance our understanding of the important role of MS in tumor progression, and may have implications for the optimization of individualized cancer management.

Preparation of Hydrogels Based on Modified Pectins by Tuning Their Properties for Anti-Glioma Therapy

The extracellular matrix (ECM) of the central nervous system (CNS), characterized by low stiffness and predominance of carbohydrates on protein components, mediates limited cell proliferation and migration. Pectins are polysaccharides derived from plants and could be very promising for a tunable hydrogel design that mimics the neural ECM. Aiming to regulate gel structure and viscoelastic properties, we elaborated 10 variants of pectin-based hydrogels via tuning the concentration of the polymer and the number of free carboxyl groups expressed in the degree of esterification (DE). Viscoelastic properties of hydrogels varied in the range of 3 to 900 Pa for G' and were chosen as the first criteria for the selection of variants suitable for CNS remodeling. For extended reciprocal characterization, two pairs of hydrogels were taken to test pectins with opposite DEs close to 0% and 50%, respectively, but with a similar rheology exceeding 100 Pa (G'), which was achieved by adjusting the concentration of pectin. Hydrogel swelling properties and in vitro stability, together with structure characterization using SEM and FTIR spectroscopy, displayed some differences that may sense for biomedical application. Bioassays on C6 and U87MG glioblastoma cultures testified the potential prospects of the anti-glioma activity of hydrogels developed by decreasing cell proliferation and modulating migration but supporting the high viability of neural cells.

Biological role of matrix stiffness in tumor growth and treatment

In recent years, the biological role of changes in physical factors in carcinogenesis and progression has attracted increasing attention. Matrix stiffness, also known as ECM stress, is a critical physical factor of tumor microenvironment and remains alternating during carcinogenesis as a result of ECM remodeling through activation of cancer-associated fibroblasts and extracellular collagen accumulation, crosslinking and fibrosis. Different content and density of extracellular collagen in ECM endows matrix with varying stiffness. Physical signals induced by matrix stiffness are transmitted to tumor cells primarily by the integrins receptor family and trigger a series of mechanotransduction that result in changes in tumor cell morphology, proliferative capacity, and invasive ability. Importantly, accumulating evidence revealed that changes in matrix stiffness in tumor tissues greatly control the sensitivity of tumor cells in response to chemotherapy, radiotherapy, and immunotherapy through integrin signaling, YAP signaling, and related signaling pathways. Here, the present review analyzes the current research advances on matrix stiffness and tumor cell behavior with a view to contributing to tumor cell growth and treatment, with the hope of improving the understanding of the biological role of matrix stiffness in tumors.

Improving in situ acoustic intensity estimates using MR acoustic radiation force imaging in combination with multifrequency MR elastography

PURPOSE

Magnetic resonance acoustic radiation force imaging (MR-ARFI) enables focal spot localization during nonablative transcranial ultrasound therapies. As the acoustic radiation force is proportional to the applied acoustic intensity, measured MR-ARFI displacements could potentially be used to estimate the acoustic intensity at the target. However, variable brain stiffness is an obstacle. The goal of this study was to develop and assess a method to accurately estimate the acoustic intensity at the focus using MR-ARFI displacements in combination with viscoelastic properties obtained with multifrequency MR elastography (MRE).

METHODS

Phantoms with a range of viscoelastic properties were fabricated, and MR-ARFI displacements were acquired within each phantom using multiple acoustic intensities. Voigt model parameters were estimated for each phantom based on storage and loss moduli measured using multifrequency MRE, and these were used to predict the relationship between acoustic intensity and measured displacement.

RESULTS

Using assumed viscoelastic properties, MR-ARFI displacements alone could not accurately estimate acoustic intensity across phantoms. For example, acoustic intensities were underestimated in phantoms stiffer than the assumed stiffness and overestimated in phantoms softer than the assumed stiffness. This error was greatly reduced using individualized viscoelasticity measurements obtained from MRE.

CONCLUSION

We demonstrated that viscoelasticity information from MRE could be used in combination with MR-ARFI displacements to obtain more accurate estimates of acoustic intensity. Additionally, Voigt model viscosity parameters were found to be predictive of the relaxation rate of each phantom's time-varying displacement response, which could be used to optimize patient-specific MR-ARFI pulse sequences.

Biomimetic Hydrogels in the Study of Cancer Mechanobiology: Overview, Biomedical Applications, and Future Perspectives

Hydrogels are biocompatible polymers that are tunable to the system under study, allowing them to be widely used in medicine, bioprinting, tissue engineering, and biomechanics. Hydrogels are used to mimic the three-dimensional microenvironment of tissues, which is essential to understanding cell–cell interactions and intracellular signaling pathways (e.g., proliferation, apoptosis, growth, and survival). Emerging evidence suggests that the malignant properties of cancer cells depend on mechanical cues that arise from changes in their microenvironment. These mechanobiological cues include stiffness, shear stress, and pressure, and have an impact on cancer proliferation and invasion. The hydrogels can be tuned to simulate these mechanobiological tissue properties. Although interest in and research on the biomedical applications of hydrogels has increased in the past 25 years, there is still much to learn about the development of biomimetic hydrogels and their potential applications in biomedical and clinical settings. This review highlights the application of hydrogels in developing pre-clinical cancer models and their potential for translation to human disease with a focus on reviewing the utility of such models in studying glioblastoma progression.

Nanomechanical and Morphological AFM Mapping of Normal Tissues and Tumors on Live Brain Slices Using Specially Designed Embedding Matrix and Laser-Shaped Cantilevers

Cell and tissue nanomechanics has been intriguingly introduced into biomedical research, not only complementing traditional immunophenotyping and molecular analysis, but also bringing unexpected new insights for clinical diagnostics and bioengineering. However, despite the progress in the study of individual cells in culture by atomic force microscopy (AFM), its application for mapping live tissues has a number of technical limitations. Here, we elaborate a new technique to study live slices of normal brain tissue and tumors by combining morphological and nanomechanical AFM mapping in high throughput scanning mode, in contrast to the typically utilized force spectroscopy mode based on single-point probe application. This became possible due to the combined use of an appropriate embedding matrix for vibratomy and originally modified AFM probes. The embedding matrix composition was carefully developed by regulating the amounts of agar and collagen I to reach optimal viscoelastic properties for obtaining high-quality live slices that meet AFM requirements. AFM tips were rounded by irradiating them with focused nanosecond laser pulses, while the resulting tip morphology was verified by scanning electron microscopy. Live slices preparation and AFM investigation take only 55 min and could be combined with a vital cell tracer analysis or immunostaining, thus making it promising for biomedical research and clinical diagnostics.

Mechanical Properties of the Extracellular Environment of Human Brain Cells Drive the Effectiveness of Drugs in Fighting Central Nervous System Cancers

The evaluation of nanomechanical properties of tissues in health and disease is of increasing interest to scientists. It has been confirmed that these properties, determined in part by the composition of the extracellular matrix, significantly affect tissue physiology and the biological behavior of cells, mainly in terms of their adhesion, mobility, or ability to mutate. Importantly, pathophysiological changes that determine disease development within the tissue usually result in significant changes in tissue mechanics that might potentially affect the drug efficacy, which is important from the perspective of development of new therapeutics, since most of the currently used in vitro experimental models for drug testing do not account for these properties. Here, we provide a summary of the current understanding of how the mechanical properties of brain tissue change in pathological conditions, and how the activity of the therapeutic agents is linked to this mechanical state.

Advanced Neuroimaging Approaches to Pediatric Brain Tumors

Simple Summary

After leukemias, brain tumors are the most common cancers in children, and early, accurate diagnosis is critical to improve patient outcomes. Beyond the conventional imaging methods of computed tomography (CT) and magnetic resonance imaging (MRI), advanced neuroimaging techniques capable of both structural and functional imaging are moving to the forefront to improve the early detection and differential diagnosis of tumors of the central nervous system. Here, we review recent developments in neuroimaging techniques for pediatric brain tumors.

Abstract

Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.

The Unfolded Protein Response Sensor PERK Mediates Stiffness-Dependent Adaptation in Glioblastoma Cells

Glioblastoma multiforme (GBM) is the most aggressive brain tumor in adults. In addition to genetic causes, the tumor microenvironment (TME), including stiffening of the extracellular matrix (ECM), is a main driver of GBM progression. Mechano-transduction and the unfolded protein response (UPR) are essential for tumor-cell adaptation to harsh TME conditions. Here, we studied the effect of a variable stiff ECM on the morphology and malignant properties of GBM stem cells (GSCs) and, moreover, examined the possible involvement of the UPR sensor PERK herein. For this, stiffness-tunable human blood plasma (HBP)/alginate hydrogels were generated to mimic ECM stiffening. GSCs showed stiffness-dependent adaptation characterized by elongated morphology, increased proliferation, and motility which was accompanied by F-Actin cytoskeletal remodeling. Interestingly, in PERK-deficient GSCs, stiffness adaptation was severely impaired, which was evidenced by low F-Actin levels, the absence of F-Actin remodeling, and decreased cell proliferation and migration. This impairment could be linked with Filamin-A (FLN-A) expression, a known interactor of PERK, which was strongly reduced in PERK-deficient GSCs. In conclusion, we identified a novel PERK/FLNA/F-Actin mechano-adaptive mechanism and found a new function for PERK in the cellular adaptation to ECM stiffening.

Predicting pituitary adenoma consistency with preoperative magnetic resonance elastography

OBJECTIVE

Pituitary adenoma is one of the most common primary intracranial neoplasms. Most of these tumors are soft, but up to 17% may have a firmer consistency. Therefore, knowing the tumor consistency in the preoperative setting could be helpful. Multiple imaging methods have been proposed to predict tumor consistency, but the results are controversial. This study aimed to evaluate the efficacy of MR elastography (MRE) in predicting tumor consistency and its potential use in a series of patients with pituitary adenomas.

METHODS

Thirty-eight patients with pituitary adenomas (≥ 2.5 cm) were prospectively evaluated with MRI and MRE before surgery. Absolute MRE stiffness values and relative MRE stiffness ratios, as well as the relative ratio of T1 signal, T2 signal, and diffusion-weighted imaging apparent diffusion coefficient (ADC) values were determined prospectively by calculating the ratio of those values in the tumor to adjacent left temporal white matter. Tumors were classified into three groups according to surgical consistency (soft, intermediate, and firm). Statistical analysis was used to identify the predictive value of the different radiological parameters in determining pituitary adenoma consistency.

RESULTS

The authors included 32 (84.21%) nonfunctional and 6 (15.79%) functional adenomas. The mean maximum tumor diameter was 3.7 cm, and the mean preoperative tumor volume was 16.4 cm3. Cavernous sinus invasion was present in 20 patients (52.63%). A gross-total resection was possible in 9 (23.68%) patients. The entire cohort's mean absolute tumor stiffness value was 1.8 kPa (range 1.1-3.7 kPa), whereas the mean tumor stiffness ratio was 0.66 (range 0.37-1.6). Intraoperative tumor consistency was significantly correlated with absolute and relative tumor stiffness (p = 0.0087 and 0.007, respectively). Tumor consistency alone was not a significant factor for predicting gross-total resection. Patients with intermediate and firm tumors had more complications compared to patients with soft tumors (50.00% vs 12.50%, p = 0.02) and also had longer operative times (p = 0.0002).

CONCLUSIONS

Whereas other MRI sequences have proven to be unreliable in determining tumor consistency, MRE has been shown to be a reliable tool for predicting adenoma consistency. Preoperative knowledge of tumor consistency could be potentially useful for surgical planning, counseling about potential surgical risks, and estimating the length of operative time.

Impact of material homogeneity assumption on cortical stiffness estimates by MR elastography

PURPOSE

Inversion algorithms used to convert acquired MR elastography wave data into material property estimates often assume that the underlying materials are locally homogeneous. Here we evaluate the impact of that assumption on stiffness estimates in gray-matter regions of interest in brain MR elastography.

METHODS

We describe an updated neural network inversion framework using finite-difference model-derived data to train convolutional neural network inversion algorithms. Neural network inversions trained on homogeneous simulations (homogeneous learned inversions [HLIs]) or inhomogeneous simulations (inhomogeneous learned inversions [ILIs]) are generated with a variety of kernel sizes. These inversions are evaluated in a brain MR elastography simulation experiment and in vivo in a test-retest repeatability experiment including 10 healthy volunteers.

RESULTS

In simulation and in vivo, HLI and ILI with small kernels produce similar results. As kernel size increases, the assumption of homogeneity has a larger effect, and HLI and ILI stiffness estimates show larger differences. At each inversion's optimal kernel size in simulation (7 × 7 × 7 for HLI, 11 × 11 × 11 for ILI), ILI is more sensitive to true changes in stiffness in gray-matter regions of interest in simulation. In vivo, there is no difference in the region-level repeatability of stiffness estimates between the inversions, although ILI appears to better maintain the stiffness map structure as kernel size increases, while decreasing the spatial variance in stiffness estimates.

CONCLUSIONS

This study suggests that inhomogeneous inversions provide small but significant benefits even when large stiffness gradients are absent.

Engineering in vitro immune-competent tissue models for testing and evaluation of therapeutics

Advances in 3D cell culture, microscale fluidic control, and cellular analysis have enabled the development of more physiologically-relevant engineered models of human organs with precise control of the cellular microenvironment. Engineered models have been used successfully to answer fundamental biological questions and to screen therapeutics, but these often neglect key elements of the immune system. There are immune elements in every tissue that contribute to healthy and diseased states. Including immune function will be essential for effective preclinical testing of therapeutics for inflammatory and immune-modulated diseases. In this review, we first discuss the key components to consider in designing engineered immune-competent models in terms of physical, chemical, and biological cues. Next, we review recent applications of models of immunity for screening therapeutics for cancer, preclinical evaluation of engineered T cells, modeling autoimmunity, and screening vaccine efficacy. Future work is needed to further recapitulate immune responses in engineered models for the most informative therapeutic screening and evaluation.

Magnetic Resonance Elastography in Intracranial Neoplasms: A Scoping Review

BACKGROUND

Magnetic resonance elastography (MRE) allows noninvasive assessment of intracranial tumor mechanics and may thus be predictive of intraoperative conditions. Variations in the use of technical terms complicate reading of current literature, and there is need of a review using consolidated nomenclature.

OBJECTIVES

We present an overview of current literature on MRE relating to human intracranial neoplasms using standardized nomenclature suggested by the MRE guidelines committee. We then discuss the implications of the findings, and suggest approaches for future research.

METHOD

We performed a systematic literature search in PubMed, Embase, and Web of Science; the articles were screened for relevance and then subjected to full text review. Technical terms were consolidated.

RESULTS

We identified 12 studies on MRE in patients with intracranial tumors, including meningiomas, glial tumors including glioblastomas, vestibular schwannomas, hemangiopericytoma, central nervous system lymphoma, pituitary macroadenomas, and brain metastases. The studies had varying objectives that included prediction of intraoperative consistency, histological separation, prediction of adhesiveness, and exploration of the mechanobiology of tumor invasiveness and malignancy. The technical terms were translated using standardized nomenclature. The literature was highly heterogeneous in terms of image acquisition techniques, post-processing, and study design and was generally limited by small and variable cohorts.

CONCLUSIONS

MRE shows potential in predicting tumor consistency, adhesion, and mechanical homogeneity. Furthermore, MRE provides insight into malignant tumor behavior and its relation to tissue mechanics. MRE is still at a preclinical stage, but technical advances, improved understanding of soft tissue rheological impact, and larger samples are likely to enable future clinical introduction.

PNJ scaffolds promote microenvironmental regulation of glioblastoma stem-like cell enrichment and radioresistance

Glioblastoma (GBM) brain tumors contain a subpopulation of self-renewing multipotent Glioblastoma stem-like cells (GSCs) that are believed to drive the near inevitable recurrence of GBM. We previously engineered temperature responsive scaffolds based on the polymer poly(N-isopropylacrylamide-co-Jeffamine M-1000 acrylamide) (PNJ) for the purpose of enriching GSCs in vitro from patient-derived samples. Here, we used PNJ scaffolds to study microenvironmental regulation of self-renewal and radiation response in patient-derived GSCs representing classical and proneural subtypes. GSC self-renewal was regulated by the composition of PNJ scaffolds and varied with cell type. PNJ scaffolds protected against radiation-induced cell death, particularly in conditions that also promoted GSC self-renewal. Additionally, cells cultured in PNJ scaffolds exhibited increased expression of the transcription factor HIF2α, which was not observed in neurosphere culture, providing a potential mechanistic basis for differences in radio-resistance. Differences in PNJ regulation of HIF2α in irradiated and untreated conditions also offered evidence of stem plasticity. These data show PNJ scaffolds provide a unique biomaterial for evaluating dynamic microenvironmental regulation of GSC self-renewal, radioresistance, and stem plasticity.

Decreased tissue stiffness in glioblastoma by MR elastography is associated with increased cerebral blood flow

PURPOSE

Understanding how mechanical properties relate to functional changes in glioblastomas may help explain different treatment response between patients. The aim of this study was to map differences in biomechanical and functional properties between tumor and healthy tissue, to assess any relationship between them and to study their spatial distribution.

METHODS

Ten patients with glioblastoma and 17 healthy subjects were scanned using MR Elastography, perfusion and diffusion MRI. Stiffness and viscosity measurements G' and G'', cerebral blood flow (CBF), apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were measured in patients' contrast-enhancing tumor, necrosis, edema, and gray and white matter, and in gray and white matter for healthy subjects. A regression analysis was used to predict CBF as a function of ADC, FA, G' and G''.

RESULTS

Median G' and G'' in contrast-enhancing tumor were 13% and 37% lower than in normal-appearing white matter (P < 0.01), and 8% and 6% lower in necrosis than in contrast-enhancing tumor, respectively (P < 0.05). Tumors showed both inter-patient and intra-patient heterogeneity. Measurements approached values in normal-appearing tissue when moving outward from the tumor core, but abnormal tissue properties were still present in regions of normal-appearing tissue. Using both a linear and a random-forest model, prediction of CBF was improved by adding MRE measurements to the model (P < 0.01).

CONCLUSIONS

The inclusion of MRE measurements in statistical models helped predict perfusion, with stiffer tissue associated with lower perfusion values.

Brain and Breast Cancer Cells with PTEN Loss of Function Reveal Enhanced Durotaxis and RHOB Dependent Amoeboid Migration Utilizing 3D Scaffolds and Aligned Microfiber Tracts

BACKGROUND

Glioblastoma multiforme (GBM) and metastatic triple-negative breast cancer (TNBC) with PTEN mutations often lead to brain dissemination with poor patient outcome, thus new therapeutic targets are needed. To understand signaling, controlling the dynamics and mechanics of brain tumor cell migration, we implemented GBM and TNBC cell lines and designed 3D aligned microfibers and scaffolds mimicking brain structures.

METHODS

3D microfibers and scaffolds were printed using melt electrowriting. GBM and TNBC cell lines with opposing PTEN genotypes were analyzed with RHO-ROCK-PTEN inhibitors and PTEN rescue using live-cell imaging. RNA-sequencing and qPCR of tumor cells in 3D with microfibers were performed, while scanning electron microscopy and confocal microscopy addressed cell morphology.

RESULTS

In contrast to the PTEN wildtype, GBM and TNBC cells with PTEN loss of function yielded enhanced durotaxis, topotaxis, adhesion, amoeboid migration on 3D microfibers and significant high RHOB expression. Functional studies concerning RHOB-ROCK-PTEN signaling confirmed the essential role for the above cellular processes.

CONCLUSIONS

This study demonstrates a significant role of the PTEN genotype and RHOB expression for durotaxis, adhesion and migration dependent on 3D. GBM and TNBC cells with PTEN loss of function have an affinity for stiff brain structures promoting metastasis. 3D microfibers represent an important tool to model brain metastasizing tumor cells, where RHO-inhibitors could play an essential role for improved therapy.

Viscoelastic biomechanical models to predict inward brain-shift using public benchmark data

Brain-shift during neurosurgery compromises the accuracy of tracking the boundaries of the tumor to be resected. Although several studies have used various finite element models (FEMs) to predict inward brain-shift, evaluation of their accuracy and efficiency based on public benchmark data has been limited. This study evaluates several FEMs proposed in the literature (various boundary conditions, mesh sizes, and material properties) by using intraoperative imaging data (the public REtroSpective Evaluation of Cerebral Tumors [RESECT] database). Four patients with low-grade gliomas were identified as having inward brain-shifts. We computed the accuracy (using target registration error) of several FEM-based brain-shift predictions and compared our findings. Since information on head orientation during craniotomy is not included in this database, we tested various plausible angles of head rotation. We analyzed the effects of brain tissue viscoelastic properties, mesh size, craniotomy position, CSF drainage level, and rigidity of meninges and then quantitatively evaluated the trade-off between accuracy and central processing unit time in predicting inward brain-shift across all models with second-order tetrahedral FEMs. The mean initial target registration error (TRE) was 5.78 ± 3.78 mm with rigid registration. FEM prediction (edge-length, 5 mm) with non-rigid meninges led to a mean TRE correction of 1.84 ± 0.83 mm assuming heterogeneous material. Results show that, for the low-grade glioma patients in the study, including non-rigid modeling of the meninges was significant statistically. In contrast including heterogeneity was not significant. To estimate the optimal head orientation and CSF drainage, an angle step of 5° and an CSF height step of 5 mm were enough leading to <0.26 mm TRE fluctuation.

Atomic Force Microscope Nanoindentation Analysis of Diffuse Astrocytic Tumor Elasticity: Relation with Tumor Histopathology

This study aims to investigate the influence of isocitrate dehydrogenase gene family (IDH) mutations, World Health Organization (WHO) grade, and mechanical preconditioning on glioma and adjacent brain elasticity through standard monotonic and repetitive atomic force microscope (AFM) nanoindentation. The elastic modulus was measured ex vivo on fresh tissue specimens acquired during craniotomy from the tumor and the peritumoral white matter of 16 diffuse glioma patients. Linear mixed-effects models examined the impact of tumor traits and preconditioning on tissue elasticity. Tissues from IDH-mutant cases were stiffer than those from IDH-wildtype ones among anaplastic astrocytoma patients (p = 0.0496) but of similar elasticity to IDH-wildtype cases for diffuse astrocytoma patients (p = 0.480). The tumor was found to be non-significantly softer than white matter in anaplastic astrocytomas (p = 0.070), but of similar elasticity to adjacent brain in diffuse astrocytomas (p = 0.492) and glioblastomas (p = 0.593). During repetitive indentation, both tumor (p = 0.002) and white matter (p = 0.003) showed initial stiffening followed by softening. Stiffening was fully reversed in white matter (p = 0.942) and partially reversed in tumor (p = 0.015). Tissue elasticity comprises a phenotypic characteristic closely related to glioma histopathology. Heterogeneity between patients should be further explored.

Nanomechanical Hallmarks of Helicobacter pylori Infection in Pediatric Patients

Background: the molecular mechanism of gastric cancer development related to Helicobacter pylori (H. pylori) infection has not been fully understood, and further studies are still needed. Information regarding nanomechanical aspects of pathophysiological events that occur during H. pylori infection can be crucial in the development of new prevention, treatment, and diagnostic measures against clinical consequences associated with H. pylori infection, including gastric ulcer, duodenal ulcer, and gastric cancer. Methods: in this study, we assessed mechanical properties of children’s healthy and H. pylori positive stomach tissues and the mechanical response of human gastric cells exposed to heat-treated H. pylori cells using atomic force microscopy (AFM NanoWizard 4 BioScience JPK Instruments Bruker). Elastic modulus (i.e., the Young’s modulus) was derived from the Hertz–Sneddon model applied to force-indentation curves. Human tissue samples were evaluated using rapid urease tests to identify H. pylori positive samples, and the presence of H. pylori cells in those samples was confirmed using immunohistopathological staining. Results and conclusion: collected data suggest that nanomechanical properties of infected tissue might be considered as markers indicated H. pylori presence since infected tissues are softer than uninfected ones. At the cellular level, this mechanical response is at least partially mediated by cell cytoskeleton remodeling indicating that gastric cells are able to tune their mechanical properties when subjected to the presence of H. pylori products. Persistent fluctuations of tissue mechanical properties in response to H. pylori infection might, in the long-term, promote induction of cancer development.

Using 3D in vitro cell culture models in anti-cancer drug discovery

INTRODUCTION

The high failure rate in drug discovery remains a costly and time-consuming challenge. Improving the odds of success in the early steps of drug development requires disease models with high biological relevance for biomarker discovery and drug development. The adoption of three-dimensional (3D) cell culture systems over traditional monolayers in cell-based assays is considered a promising step toward improving the success rate in drug discovery.

AREAS COVERED

In this article, the author focuses on new technologies for 3D cell culture and their applications in cancer drug discovery. Besides the most common 3D cell-culture systems for tumor cells, the article emphasizes the need for 3D cell culture technologies that can mimic the complex tumor microenvironment and cancer stem cell niche.

EXPERT OPINION

There has been a rapid increase in 3D cell culture technologies in recent years in an effort to more closely mimic in vivo physiology. Each 3D cell culture system has its own strengths and weaknesses with regard to in vivo tumor growth and the tumor microenvironment. This requires careful consideration of which 3D cell culture system is chosen for drug discovery and should be based on factors like drug target and tumor origin.

Natural killer cell immune synapse formation and cytotoxicity are controlled by tension of the target interface

Natural killer (NK) cells can kill infected or transformed cells via a lytic immune synapse. Diseased cells may exhibit altered mechanical properties but how this impacts NK cell responsiveness is unknown. We report that human NK cells were stimulated more effectively to secrete granzymes A and B, FasL (also known as FasLG), granulysin and IFNγ, by stiff (142 kPa) compared to soft (1 kPa) planar substrates. To create surrogate spherical targets of defined stiffness, sodium alginate was used to synthesise soft (9 kPa), medium (34 kPa) or stiff (254 kPa) cell-sized beads, coated with antibodies against activating receptor NKp30 (also known as NCR3) and the integrin LFA-1 (also known as ITGAL). Against stiff beads, NK cells showed increased degranulation. Polarisation of the microtubule-organising centre and lytic granules were impaired against soft targets, which instead resulted in the formation of unstable kinapses. Thus, by varying target stiffness to characterise the mechanosensitivity of immune synapses, we identify soft targets as a blind spot in NK cell recognition. This article has an associated First Person interview with the co-first authors of the paper.

Advanced Spheroid, Tumouroid and 3D Bioprinted In-Vitro Models of Adult and Paediatric Glioblastoma

The life expectancy of patients with high-grade glioma (HGG) has not improved in decades. One of the crucial tools to enable future improvement is advanced models that faithfully recapitulate the tumour microenvironment; they can be used for high-throughput screening that in future may enable accurate personalised drug screens. Currently, advanced models are crucial for identifying and understanding potential new targets, assessing new chemotherapeutic compounds or other treatment modalities. Recently, various methodologies have come into use that have allowed the validation of complex models—namely, spheroids, tumouroids, hydrogel-embedded cultures (matrix-supported) and advanced bioengineered cultures assembled with bioprinting and microfluidics. This review is designed to present the state of advanced models of HGG, whilst focusing as much as is possible on the paediatric form of the disease. The reality remains, however, that paediatric HGG (pHGG) models are years behind those of adult HGG. Our goal is to bring this to light in the hope that pGBM models can be improved upon.

Harnessing brain waves: a review of brain magnetic resonance elastography for clinicians and scientists entering the field

Brain magnetic resonance elastography (MRE) is an imaging technique capable of accurately and non-invasively measuring the mechanical properties of the living human brain. Recent studies have shown that MRE has potential to provide clinically useful information in patients with intracranial tumors, demyelinating disease, neurodegenerative disease, elevated intracranial pressure, and altered functional states. The objectives of this review are: (1) to give a general overview of the types of measurements that have been obtained with brain MRE in patient populations, (2) to survey the tools currently being used to make these measurements possible, and (3) to highlight brain MRE-based quantitative biomarkers that have the highest potential of being adopted into clinical use within the next 5 to 10 years. The specifics of MRE methodology strategies are described, from wave generation to material parameter estimations. The potential clinical role of MRE for characterizing and planning surgical resection of intracranial tumors and assessing diffuse changes in brain stiffness resulting from diffuse neurological diseases and altered intracranial pressure are described. In addition, the emerging technique of functional MRE, the role of artificial intelligence in MRE, and promising applications of MRE in general neuroscience research are presented.

Is There a Relationship between the Elasticity of Brain Tumors, Changes in Diffusion Tensor Imaging, and Histological Findings? A Pilot Study Using Intraoperative Ultrasound Elastography

Intraoperative ultrasound elastography (IOUS-E) is a novel image modality applied in brain tumor assessment. However, the potential links between elastographic findings and other histological and neuroimaging features are unknown. This study aims to find associations between brain tumor elasticity, diffusion tensor imaging (DTI) metrics, and cell proliferation. A retrospective study was conducted to analyze consecutively admitted patients who underwent craniotomy for supratentorial brain tumors between March 2018 and February 2020. Patients evaluated by IOUS-E and preoperative DTI were included. A semi-quantitative analysis was performed to calculate the mean tissue elasticity (MTE). Diffusion coefficients and the tumor proliferation index by Ki-67 were registered. Relationships between the continuous variables were determined using the Spearman ρ test. A predictive model was developed based on non-linear regression using the MTE as the dependent variable. Forty patients were evaluated. The pathologic diagnoses were as follows: 21 high-grade gliomas (HGG); 9 low-grade gliomas (LGG); and 10 meningiomas. Cases with a proliferation index of less than 10% had significantly higher medians of MTE (110.34 vs. 79.99, p < 0.001) and fractional anisotropy (FA) (0.24 vs. 0.19, p = 0.020). We found a strong positive correlation between MTE and FA (r_s (38) = 0.91, p < 0.001). A cubic spline non-linear regression model was obtained to predict tumoral MTE from FA (R² = 0.78, p < 0.001). According to our results, tumor elasticity is associated with histopathological and DTI-derived metrics. These findings support the usefulness of IOUS-E as a complementary tool in brain tumor surgery.

GliMR: Cross-Border Collaborations to Promote Advanced MRI Biomarkers for Glioma

Purpose

There is an annual incidence of 50,000 glioma cases in Europe. The optimal treatment strategy is highly personalised, depending on tumour type, grade, spatial localization, and the degree of tissue infiltration. In research settings, advanced magnetic resonance imaging (MRI) has shown great promise as a tool to inform personalised treatment decisions. However, the use of advanced MRI in clinical practice remains scarce due to the downstream effects of siloed glioma imaging research with limited representation of MRI specialists in established consortia; and the associated lack of available tools and expertise in clinical settings. These shortcomings delay the translation of scientific breakthroughs into novel treatment strategy. As a response we have developed the network “Glioma MR Imaging 2.0” (GliMR) which we present in this article.

Methods

GliMR aims to build a pan-European and multidisciplinary network of experts and accelerate the use of advanced MRI in glioma beyond the current “state-of-the-art” in glioma imaging. The Action Glioma MR Imaging 2.0 (GliMR) was granted funding by the European Cooperation in Science and Technology (COST) in June 2019.

Results

GliMR’s first grant period ran from September 2019 to April 2020, during which several meetings were held and projects were initiated, such as reviewing the current knowledge on advanced MRI; developing a General Data Protection Regulation (GDPR) compliant consent form; and setting up the website.

Conclusion

The Action overcomes the pre-existing limitations of glioma research and is funded until September 2023. New members will be accepted during its entire duration.