MRI in Glioma Immunotherapy: Evidence, Pitfalls, and Perspectives

Tumor biomechanics as a novel imaging biomarker to assess response to immunotherapy in a murine glioma model

Glioblastoma is the most common and aggressive primary malignant brain tumor with poor prognosis. Novel immunotherapeutic approaches are currently under investigation. Even though magnetic resonance imaging (MRI) is the most important imaging tool for treatment monitoring, response assessment is often hampered by therapy-related tissue changes. As tumor and therapy-associated tissue reactions differ structurally, we hypothesize that biomechanics could be a pertinent imaging proxy for differentiation. Longitudinal MRI and magnetic resonance elastography (MRE) were performed to monitor response to immunotherapy with a toll-like receptor 7/8 agonist in orthotopic syngeneic experimental glioma. Imaging results were correlated to histology and light sheet microscopy data. Here, we identify MRE as a promising non-invasive imaging method for immunotherapy-monitoring by quantifying changes in response-related tumor mechanics. Specifically, we show that a relative softening of treated compared to untreated tumors is linked to the inflammatory processes following therapy-induced re-education of tumor-associated myeloid cells. Mechanistically, combined effects of myeloid influx and inflammation including extracellular matrix degradation following immunotherapy form the basis of treated tumors being softer than untreated glioma. This is a very early indicator of therapy response outperforming established imaging metrics such as tumor volume. The overall anti-tumor inflammatory processes likely have similar effects on human brain tissue biomechanics, making MRE a promising tool for gauging response to immunotherapy in glioma patients early, thereby strongly impacting patient pathway.

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.

Response assessment of GBM during immunotherapy by delayed contrast treatment response assessment maps

Introduction

Assessing the treatment response of glioblastoma multiforme during immunotherapy (IT) is an open issue. Treatment response assessment maps (TRAMs) might help distinguish true tumor progression (TTP) and pseudoprogression (PsP) in this setting.

Methods

We recruited 16 naïve glioblastoma patients enrolled in a phase II trial consisting of the Stupp protocol (a standardized treatment for glioblastoma involving combined radiotherapy and chemotherapy with temozolomide, followed by adjuvant temozolomide) plus IT with dendritic cells. Patients were followed up till progression or death; seven underwent a second surgery for suspected progression. Clinical, immunological, and MRI data were collected from all patients and histology in case of second surgery. Patients were classified as responders (progression-free survival, PFS > 12 months), and non-responders (PFS ≤ 12), HIGH-NK (natural killer cells, i.e., immunological responders), and LOW-NK (immunological non-responders) based on immune cell counts in peripheral blood. TRAMs differentiate contrast-enhancing lesions with different washout dynamics into hypothesized tumoral (conventionally blue-colored) vs. treatment-related (red-colored).

Results

Using receiver operating characteristic (ROC) curves, a threshold of -0.066 in VBlue/VCE (volume of the blue portion of tumoral area/volume of contrast enhancement) variation between values obtained in the MRI performed before PsP/TTP and at TTP/PSP allowed to discriminate TTP from PsP with a sensitivity of 71.4% and a specificity of 100%. Among HIGH-NK patients, at month 6 there was a significant reduction compared to baseline and month 2 in median "blue" volumes.

Discussion

In conclusion, in our pilot study TRAMs support the discrimination between tumoral and treatment-related enhancing features in immunological responders vs. non-responders, the distinction between PsP and TTP, and might provide surrogate markers of immunological response.

Deep CNNs for glioma grading on conventional MRIs: Performance analysis, challenges, and future directions

The increasing global incidence of glioma tumors has raised significant healthcare concerns due to their high mortality rates. Traditionally, tumor diagnosis relies on visual analysis of medical imaging and invasive biopsies for precise grading. As an alternative, computer-assisted methods, particularly deep convolutional neural networks (DCNNs), have gained traction. This research paper explores the recent advancements in DCNNs for glioma grading using brain magnetic resonance images (MRIs) from 2015 to 2023. The study evaluated various DCNN architectures and their performance, revealing remarkable results with models such as hybrid and ensemble based DCNNs achieving accuracy levels of up to 98.91%. However, challenges persisted in the form of limited datasets, lack of external validation, and variations in grading formulations across diverse literature sources. Addressing these challenges through expanding datasets, conducting external validation, and standardizing grading formulations can enhance the performance and reliability of DCNNs in glioma grading, thereby advancing brain tumor classification and extending its applications to other neurological disorders.

Subtype-Selective Peptide and Protein Neurotoxic Inhibitors of Nicotinic Acetylcholine Receptors Enhance Proliferation of Patient-Derived Glioblastoma Cell Lines

Glioblastoma multiforme (GBM) is the most aggressive type of brain cancer, with a poor prognosis. GBM cells, which develop in the environment of neural tissue, often exploit neurotransmitters and their receptors to promote their own growth and invasion. Nicotinic acetylcholine receptors (nAChRs), which play a crucial role in central nervous system signal transmission, are widely represented in the brain, and GBM cells express several subtypes of nAChRs that are suggested to transmit signals from neurons, promoting tumor invasion and growth. Analysis of published GBM transcriptomes revealed spatial heterogeneity in nAChR subtype expression, and functional nAChRs of α1*, α7, and α9 subtypes are demonstrated in our work on several patient-derived GBM microsphere cultures and on the U87MG GBM cell line using subtype-selective neurotoxins and fluorescent calcium mobilization assay. The U87MG cell line shows reactions to nicotinic agonists similar to those of GBM patient-derived culture. Selective α1*, α7, and α9 nAChR neurotoxins stimulated cell growth in the presence of nicotinic agonists. Several cultivating conditions with varying growth factor content have been proposed and tested. The use of selective neurotoxins confirmed that cell cultures obtained from patients are representative GBM models, but the use of media containing fetal bovine serum can lead to alterations in nAChR expression and functioning.

Progress in the research of immunotherapy‑related hyperprogression (Review)

Immunotherapy has become an effective method for the treatment of a variety of malignant tumors. However, with the development of immunotherapy, the phenomenon of hyperprogression in patients with cancer has gradually attracted attention. Hyperprogression refers to a condition in which the progression of a disease during treatment of a patient with cancer is suddenly accelerated. To date, no reliable marker has been found to predict accelerated tumor growth during immune checkpoint inhibitor (ICI) treatment. The aim the present study was to summarize the definition of hyperprogression and the difference between hyperprogression and pseudocytosis, and investigate the potential mechanisms of hyperprogression including clinical characteristics, potential molecular markers and the immune microenvironment. The effect of macrophage-related different types and factors on tumors in the immune microenvironment was analyzed, and the findings may be used to determine the future directions of research in hyperprogression.

Safety and feasibility of intra-arterial delivery of teniposide to high grade gliomas after blood-brain barrier disruption: a case series

BACKGROUND

This case series describes the safety and efficacy of superselective intra-arterial (IA) cerebral infusion of teniposide for the treatment of patients with glioma, to provide new ideas and methods for the treatment of high grade gliomas.

METHODS

12 patients with glioma who were previously treated with standard therapy were treated with superselective IA cerebral infusion of teniposide. Patients received at least two cycles of treatment (one cycle: 150 mg/time, used for 1 day, repeated at 28 day intervals) after blood-brain barrier disruption. Patients received individualized treatment on the tumor location. The ophthalmic artery was bypassed during the super-selective arterial infusion.

RESULTS

No significant differences in biochemical indexes and Karnofsky performance status (KPS) score were observed before and after treatment, and no evident adverse events occurred (P>0.05). In a recent response evaluation (August 2023), two (8%) patients presented with a complete response (16.7%), four had a partial response (33.3%), four had stable disease (33.3%), and two showed progressive disease (16.7%). The overall response rate and disease control rate were 50.0% and 83.3%, respectively. In addition, we described the detailed course of treatment in two patients. Case No 1 (recurrent tumor) and case No 2 (primary tumor) received six and three cycles of teniposide infusion, respectively. After treatment, the tumors of the patients were significantly reduced without evident adverse effects.

CONCLUSION

This small series suggests that superselective IA cerebral infusion of teniposide may be a safe and effective therapy in the multimodal treatment of malignant glioma and warrants further study in larger prospective investigations.

Methods behind oncolytic virus-based DC vaccines in cancer: Toward a multiphase combined treatment strategy for Glioblastoma (GBM) patients

Glioblastoma (GBM) remains an orphan cancer disease with poor outcome. Novel treatment strategies are needed. Immunotherapy has several modes of action. The addition of active specific immunotherapy with dendritic cell vaccines resulted in improved overall survival of patients. Integration of DC vaccination within the first-line combined treatment became a challenge, and immunogenic cell death immunotherapy during chemotherapy was introduced. We used a retrospective analysis using real world data to evaluate the complex combined treatment, which included individualized multimodal immunotherapy during and after standard of care, and which required adaptations during treatment, and found a further improvement of overall survival. We also discuss the use of real world data as evidence. Novel strategies to move the field of individualized multimodal immunotherapy forward for GBM patients are reviewed.

The Role of Liquid Biopsy in the Diagnosis and Prognosis of WHO Grade 4 Astrocytoma

Liquid biopsy, as a non-invasive diagnostic tool, has recently gained significant attention in the field of oncology. It involves the analysis of various biomarkers present in bodily fluids, such as blood or cerebrospinal fluid, to provide information about the underlying cancer. In the case of WHO grade 4 astrocytomas, liquid biopsy has the potential to significantly impact the diagnosis and prognosis of this aggressive malignant brain tumor. By detecting specific genetic mutations, such as IDH1 or EGFR, and monitoring levels of circulating tumor DNA, liquid biopsy can aid in the early detection and monitoring of disease progression. This innovative approach is gradually being acknowledged as a less invasive and cost-effective procedure for cancer diagnosis and management to improve patient outcomes and quality of life. Various kinds of biomarkers circulating in cerebrospinal fluid (CSF), such as circulating tumor cells (CTC) and different types of nucleic acids like cell-free DNA (cfDNA), cell-free RNA (ctRNA), and microRNAs (miRNA), have been identified. These biomarkers, which require dependable detection methods, are comparatively simple to obtain and allow for repeated measurements, making them significantly superior for disease monitoring. This review aims to compare the latest liquid biopsy analysis tools for both CSF and plasma in the central nervous system.

Assessment of treatment response to dendritic cell vaccine in patients with glioblastoma using a multiparametric MRI-based prediction model

PURPOSE

Autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) is a promising treatment modality for glioblastomas. The purpose of this study was to investigate the potential utility of multiparametric MRI-based prediction model in evaluating treatment response in glioblastoma patients treated with DCVax-L.

METHODS

Seventeen glioblastoma patients treated with standard-of-care therapy + DCVax-L were included. When tumor progression (TP) was suspected and repeat surgery was being contemplated, we sought to ascertain the number of cases correctly classified as TP + mixed response or pseudoprogression (PsP) from multiparametric MRI-based prediction model using histopathology/mRANO criteria as ground truth. Multiparametric MRI model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI-derived parameters. A comparison of overall survival (OS) was performed between patients treated with standard-of-care therapy + DCVax-L and standard-of-care therapy alone (external controls). Additionally, Kaplan-Meier analyses were performed to compare OS between two groups of patients using PsP, Ki-67, and MGMT promoter methylation status as stratification variables.

RESULTS

Multiparametric MRI model correctly predicted TP + mixed response in 72.7% of cases (8/11) and PsP in 83.3% (5/6) with an overall concordance rate of 76.5% with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.54; p = 0.026). DCVax-L-treated patients had significantly prolonged OS than those treated with standard-of-care therapy (22.38 ± 12.8 vs. 13.8 ± 9.5 months, p = 0.040). Additionally, glioblastomas with PsP, MGMT promoter methylation status, and Ki-67 values below median had longer OS than their counterparts.

CONCLUSION

Multiparametric MRI-based prediction model can assess treatment response to DCVax-L in patients with glioblastoma.

Brain magnetic resonance spectroscopy to differentiate recurrent neoplasm from radiation necrosis: A systematic review and meta-analysis

BACKGROUND AND PURPOSE

Postradiation treatment necrosis is one of the most serious late sequelae and appears within 6 months. The magnetic resonance spectroscopy imaging (MRSI) has been used for the detection of brain tumors. The study aimed to determine the radiological accuracy and efficacy in distinguishing recurrent brain tumor from radiation-induced necrosis by identifying pseudoprogression.

METHODS

The research was performed in accordance with the preferred reporting items for systematic review and meta-analysis guidelines. International electronic databases including 15 English sources were investigated. A total of 4281 papers with 2159 citations from 15 databases from 2011 to 2021 met the search strategies of magnetic resonance (MR) spectroscopy in recurrent brain tumors and postradiation necrosis.

RESULTS

Nine studies were enrolled in the meta-analysis with a total of 354 patients (203 male and 151 female) whose average age ranged from 4 to 74 years. Anbarloui et al., Elias et al., Nemattalla et al., Smith et al., Zeng et al., and Weybright et al. showed strong evidence of heterogeneity regarding choline/N-acetylaspartate (Cho/NAA) ratio in the evaluation of the nine studies. Elias et al., Nemattalla et al., Bobek-Billewicz et al., and Smith et al. showed a high heterogeneity in Cho/creatine (Cr) ratio. Elias et al., Nemattalla et al., Smith et al., and Weybright et al. revealed high heterogeneity in NAA/Cr ratio estimates.

CONCLUSION

MR spectroscopy is effective in distinguishing recurrent brain tumors from necrosis. Our meta-analysis revealed that Cho/NAA, Cho/Cr, and NAA/Cr ratios were significantly better predictor of detected recurrent tumor. Therefore, the MRSI is an informative tool in the distinction of tumor recurrence versus necrosis.

Mathematical modelling of the dynamics of image-informed tumor habitats in a murine model of glioma

Tumors exhibit high molecular, phenotypic, and physiological heterogeneity. In this effort, we employ quantitative magnetic resonance imaging (MRI) data to capture this heterogeneity through imaging-based subregions or "habitats" in a murine model of glioma. We then demonstrate the ability to model and predict the growth of the habitats using coupled ordinary differential equations (ODEs) in the presence and absence of radiotherapy. Female Wistar rats (N = 21) were inoculated intracranially with 10⁶ C6 glioma cells, a subset of which received 20 Gy (N = 5) or 40 Gy (N = 8) of radiation. All rats underwent diffusion-weighted and dynamic contrast-enhanced MRI at up to seven time points. All MRI data at each visit were subsequently clustered using k-means to identify physiological tumor habitats. A family of four models consisting of three coupled ODEs were developed and calibrated to the habitat time series of control and treated rats and evaluated for predictive capability. The Akaike Information Criterion was used for model selection, and the normalized sum-of-square-error (SSE) was used to evaluate goodness-of-fit in model calibration and prediction. Three tumor habitats with significantly different imaging data characteristics (p < 0.05) were identified: high-vascularity high-cellularity, low-vascularity high-cellularity, and low-vascularity low-cellularity. Model selection resulted in a five-parameter model whose predictions of habitat dynamics yielded SSEs that were similar to the SSEs from the calibrated model. It is thus feasible to mathematically describe habitat dynamics in a preclinical model of glioma using biology-based ODEs, showing promise for forecasting heterogeneous tumor behavior.

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noninvasive treatment monitoring is crucial for longitudinal tumor characterization and the early detection of non-responders. While various medical imaging techniques can provide a morphological picture of the lesion and its surrounding tissue, a molecular-oriented imaging approach holds the key to unraveling biological effects that occur much earlier in the immunotherapy timeline. Magnetic resonance imaging (MRI) is a highly versatile imaging modality, where the image contrast can be tailored to emphasize a particular biophysical property of interest using advanced engineering of the imaging pipeline. In this review, recent advances in molecular-MRI based cancer immunotherapy monitoring are described. Next, the presentation of the underlying physics, computational, and biological features are complemented by a critical analysis of the results obtained in preclinical and clinical studies. Finally, emerging artificial intelligence (AI)-based strategies to further distill, quantify, and interpret the image-based molecular MRI information are discussed in terms of perspectives for the future.

Challenges and opportunities for advanced neuroimaging of glioblastoma

Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.

Phase III trial of chemoradiotherapy with temozolomide plus nivolumab or placebo for newly diagnosed glioblastoma with methylated MGMT promoter

BACKGROUND

Nearly all patients with newly diagnosed glioblastoma experience recurrence following standard-of-care radiotherapy (RT) + temozolomide (TMZ). The purpose of the phase III randomized CheckMate 548 study was to evaluate RT + TMZ combined with the immune checkpoint inhibitor nivolumab (NIVO) or placebo (PBO) in patients with newly diagnosed glioblastoma with methylated MGMT promoter (NCT02667587).

METHODS

Patients (N = 716) were randomized 1:1 to NIVO [(240 mg every 2 weeks × 8, then 480 mg every 4 weeks) + RT (60 Gy over 6 weeks) + TMZ (75 mg/m2 once daily during RT, then 150-200 mg/m2 once daily on days 1-5 of every 28-day cycle × 6)] or PBO + RT + TMZ following the same regimen. The primary endpoints were progression-free survival (PFS) and overall survival (OS) in patients without baseline corticosteroids and in all randomized patients.

RESULTS

As of December 22, 2020, median (m)PFS (blinded independent central review) was 10.6 months (95% CI, 8.9-11.8) with NIVO + RT + TMZ vs 10.3 months (95% CI, 9.7-12.5) with PBO + RT + TMZ (HR, 1.1; 95% CI, 0.9-1.3) and mOS was 28.9 months (95% CI, 24.4-31.6) vs 32.1 months (95% CI, 29.4-33.8), respectively (HR, 1.1; 95% CI, 0.9-1.3). In patients without baseline corticosteroids, mOS was 31.3 months (95% CI, 28.6-34.8) with NIVO + RT + TMZ vs 33.0 months (95% CI, 31.0-35.1) with PBO + RT + TMZ (HR, 1.1; 95% CI, 0.9-1.4). Grade 3/4 treatment-related adverse event rates were 52.4% vs 33.6%, respectively.

CONCLUSIONS

NIVO added to RT + TMZ did not improve survival in patients with newly diagnosed glioblastoma with methylated or indeterminate MGMT promoter. No new safety signals were observed.

Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy

Immunotherapy has become a fourth pillar in the treatment of brain tumors and, when combined with radiation therapy, may improve patient outcomes and reduce the neurotoxicity. As with other combination therapies, the identification of a treatment schedule that maximizes the synergistic effect of radiation- and immune-therapy is a fundamental challenge. Mechanism-based mathematical modeling is one promising approach to systematically investigate therapeutic combinations to maximize positive outcomes within a rigorous framework. However, successful clinical translation of model-generated combinations of treatment requires patient-specific data to allow the models to be meaningfully initialized and parameterized. Quantitative imaging techniques have emerged as a promising source of high quality, spatially and temporally resolved data for the development and validation of mathematical models. In this review, we will present approaches to personalize mechanism-based modeling frameworks with patient data, and then discuss how these techniques could be leveraged to improve brain cancer outcomes through patient-specific modeling and optimization of treatment strategies.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective

Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.

Methods

Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).

Results

High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.

Conclusion

Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics

Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.

MR susceptibility imaging for detection of tumor-associated macrophages in glioblastoma

PURPOSE

Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, we investigated MRI to quantify iron as an imaging biomarker for TAMs in GBM patients.

METHODS

21 adult patients with GBM underwent a 3D single echo gradient echo MRI sequence and quantitative susceptibility maps were generated. In 3 subjects, ex vivo imaging of surgical specimens was performed on a 9.4 Tesla MRI using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated. Each specimen was stained with hematoxylin and eosin, as well as CD68, CD86, CD206, and L-Ferritin.

RESULTS

Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the L-ferritin positivity percent (r = 0.56, p = 0.018) and the combination of tumor's enhancing zone and necrotic core and the L-Ferritin positivity percent (r = 0.72; p = 0.001). The mean susceptibility significantly correlated with positivity percent for CD68 (ρ = 0.52, p = 0.034) and CD86 (r = 0.7 p = 0.001), but not for CD206 (ρ = 0.09; p = 0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r = 0.6, p = 0.016). Similarly, mean R2* values significantly correlated with CD86 (r = 0.54, p = 0.03) but not with CD206 (r = 0.15, p = 0.5).

CONCLUSIONS

This study demonstrated the potential of MR quantitative susceptibility mapping as a non-invasive method for in vivo TAM quantification and phenotyping. Validation of these findings with large multicenter studies is needed.

Magnetic resonance spectroscopy outperforms perfusion in distinguishing between pseudoprogression and disease progression in patients with glioblastoma

Background

There is a need to establish biomarkers that distinguish between pseudoprogression (PsP) and true tumor progression in patients with glioblastoma (GBM) treated with chemoradiation.

Methods

We analyzed magnetic resonance spectroscopic imaging (MRSI) and dynamic susceptibility contrast (DSC) MR perfusion data in patients with GBM with PsP or disease progression after chemoradiation. MRSI metabolites of interest included intratumoral choline (Cho), myo-inositol (mI), glutamate + glutamine (Glx), lactate (Lac), and creatine on the contralateral hemisphere (c-Cr). Student T-tests and area under the ROC curve analyses were used to detect group differences in metabolic ratios and their ability to predict clinical status, respectively.

Results

28 subjects (63 ± 9 years, 19 men) were evaluated. Subjects with true progression (n = 20) had decreased enhancing region mI/c-Cr (P = .011), a marker for more aggressive tumors, compared to those with PsP, which predicted tumor progression (AUC: 0.84 [0.76, 0.92]). Those with true progression had elevated Lac/Glx (P = .0009), a proxy of the Warburg effect, compared to those with PsP which predicted tumor progression (AUC: 0.84 [0.75, 0.92]). Cho/c-Cr did not distinguish between PsP and true tumor progression. Despite rCBV (AUC: 0.70 [0.60, 0.80]) and rCBF (AUC: 0.75 [0.65, 0.84]) being individually predictive of tumor response, they added no additional predictive value when combined with MRSI metabolic markers.

Conclusions

Incorporating enhancing lesion MRSI measures of mI/c-Cr and Lac/Glx into brain tumor imaging protocols can distinguish between PsP and true progression and inform patient management decisions.

Diagnostic accuracy of diffusion-weighted imaging in differentiating glioma recurrence from posttreatment-related changes: a meta-analysis

BACKGROUND

Magnetic resonance imaging (MRI) is the most commonly used imaging method to evaluate glioma recurrence. However, conventional MRI has difficulty distinguishing glioma accurately. This study aimed to explore the value of diffusion weighted imaging (DWI) in evaluating glioma recurrence and post-treatment-related changes.

RESEARCH DESIGN AND METHODS

PubMed, Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database and China Science and Technology Journal Database were extensively searched in accordance with inclusion criteria and exclusion criteria to obtain appropriate included studies. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Combined sensitivity and specificity and the area under the summary receiver operating characteristic curve (SROC) with the 95% confidence interval (CI) were calculated.

RESULTS

Seventeen high-quality studies were included. The combined sensitivity was 0.82 (95% CI: 0.76-0.87), the specificity was 0.83 (95% CI: 0.76-0.89), the positive likelihood ratio was 4.9 (95% CI: 3.2-7.5), the negative likelihood ratio was 0.21 (95% CI: 0.15-0.30), the diagnostic odds ratio was 23 (95%: CI 11-48), and the area under the SROC was 0.90 (95% CI: 0.87-0.92).

CONCLUSIONS

This meta-analysis suggests that DWI has high sensitivity, specificity and accuracy in differentiating glioma recurrence.

The Role of the Immune Response in Brain Metastases: Novel Imaging Biomarkers for Immunotherapy

Brain metastases are a major clinical problem, and immunotherapy offers a novel treatment paradigm with the potential to synergize with existing focal therapies like surgery and radiosurgery or even replace them in future. The brain is a unique microenvironment structurally and immunologically. The immune response is likely to be crucial to the adaptation of systemic immune modulating agents against this disease. Imaging is frequently employed in the clinical diagnosis and management of brain metastasis, so it is logical that brain imaging techniques are investigated as a source of biomarkers of the immune response in these tumors. Current imaging techniques in clinical use include structural MRI (post-contrast T1W sequences, T2, and FLAIR), physiological sequences (perfusion- and diffusion-weighted imaging), and molecular imaging (MR spectroscopy and PET). These are reviewed for their application to predicting and measuring the response to immunotherapy in brain metastases.

Imaging Assessment of Tumor Response in the Era of Immunotherapy

Assessment of tumor response during treatment is one of the most important purposes of imaging. Before the appearance of immunotherapy, response evaluation criteria in solid tumors (RECIST) and positron emission tomography response criteria in solid tumors (PERCIST) were, respectively, the established morphologic and metabolic response criteria, and cessation of treatment was recommended when progressive disease was detected according to these criteria. However, various types of immunotherapy have been developed over the past 20 years, which show novel false positive findings on images, as well as distinct response patterns from conventional therapies. Antitumor immune response itself causes 18F-fluorodeoxyglucose (FDG) uptake in tumor sites, known as "flare phenomenon", so that positron emission tomography using FDG can no longer accurately identify remaining tumors. Furthermore, tumors often initially increase, followed by stability or decrease resulting from immunotherapy, which is called "pseudoprogression", so that progressive disease cannot be confirmed by computed tomography or magnetic resonance imaging at a single time point. As a result, neither RECIST nor PERCIST can accurately predict the response to immunotherapy, and therefore several new response criteria fixed for immunotherapy have been proposed. However, these criteria are still controversial, and also require months for response confirmation. The establishment of optimal response criteria and the development of new imaging technologies other than FDG are therefore urgently needed. In this review, we summarize the false positive images and the revision of response criteria for each immunotherapy, in order to avoid discontinuation of a truly effective immunotherapy.

ctDNA-Based Liquid Biopsy of Cerebrospinal Fluid in Brain Cancer

The correct characterisation of central nervous system (CNS) malignancies is crucial for accurate diagnosis and prognosis and also the identification of actionable genomic alterations that can guide the therapeutic strategy. Surgical biopsies are performed to characterise the tumour; however, these procedures are invasive and are not always feasible for all patients. Moreover, they only provide a static snapshot and can miss tumour heterogeneity. Currently, monitoring of CNS cancer is performed by conventional imaging techniques and, in some cases, cytology analysis of the cerebrospinal fluid (CSF); however, these techniques have limited sensitivity. To overcome these limitations, a liquid biopsy of the CSF can be used to obtain information about the tumour in a less invasive manner. The CSF is a source of cell-free circulating tumour DNA (ctDNA), and the analysis of this biomarker can characterise and monitor brain cancer. Recent studies have shown that ctDNA is more abundant in the CSF than plasma for CNS malignancies and that it can be sequenced to reveal tumour heterogeneity and provide diagnostic and prognostic information. Furthermore, analysis of longitudinal samples can aid patient monitoring by detecting residual disease or even tracking tumour evolution at relapse and, therefore, tailoring the therapeutic strategy. In this review, we provide an overview of the potential clinical applications of the analysis of CSF ctDNA and the challenges that need to be overcome in order to translate research findings into a tool for clinical practice.

Physiological Imaging Methods for Evaluating Response to Immunotherapies in Glioblastomas

Glioblastoma (GBM) is the most malignant brain tumor in adults, with a dismal prognosis despite aggressive multi-modal therapy. Immunotherapy is currently being evaluated as an alternate treatment modality for recurrent GBMs in clinical trials. These immunotherapeutic approaches harness the patient's immune response to fight and eliminate tumor cells. Standard MR imaging is not adequate for response assessment to immunotherapy in GBM patients even after using refined response assessment criteria secondary to amplified immune response. Thus, there is an urgent need for the development of effective and alternative neuroimaging techniques for accurate response assessment. To this end, some groups have reported the potential of diffusion and perfusion MR imaging and amino acid-based positron emission tomography techniques in evaluating treatment response to different immunotherapeutic regimens in GBMs. The main goal of these techniques is to provide definitive metrics of treatment response at earlier time points for making informed decisions on future therapeutic interventions. This review provides an overview of available immunotherapeutic approaches used to treat GBMs. It discusses the limitations of conventional imaging and potential utilities of physiologic imaging techniques in the response assessment to immunotherapies. It also describes challenges associated with these imaging methods and potential solutions to avoid them.

Network Pharmacology for Analyzing the Key Targets and Potential Mechanism of Wogonin in Gliomas

Objective: To analyze the key targets and potential mechanisms underlying the volatile components of Scutellaria baicalensis Georgi acting on gliomas through network pharmacology combined with biological experiments.

Methods: We have extracted the volatile components of Scutellaria baicalensis by gas chromatography-mass spectrometry (GC-MS) and determined the active components related to the onset and development of gliomas by combining the results with the data from the Traditional Chinese Medicine Systems Pharmacology database. We screened the same targets for the extracted active components and gliomas through network pharmacology and then constructed a protein-protein interaction network. Using a Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we analyzed the protein effects and regulatory pathways of the common targets. Lastly, we employed ELISA and Western blot in verifying the key targets in the regulatory pathway.

Results: We ultimately determined that the active component in S. baicalensis Georgi related to the onset and development of gliomas was Wogonin. The results of the network pharmacology revealed 85 targets for glioma and Wogonin. We used gene ontology to analyze these target genes and found that they involved 30 functions, such as phosphatidylinositol phosphokinase activation, while the KEGG analysis showed that there were 10 regulatory pathways involved. Through the following analysis, we found that most of the key target genes are distributed in the PI3K-Akt and interleukin 17 signaling pathways. We then cultured U251 glioma cells for the experiments. Compared with the control group, no significant change was noted in the caspase-3 expression; however, cleaved caspase-3 expression increased significantly and was dose-dependent on Wogonin. The expression of Bad and Bcl-2 with 25 μM of Wogonin has remained unchanged, but when the Wogonin dose was increased to 100 μM, the expression of Bad and Bcl-2 was noted to change significantly (Bad was significantly upregulated, while Bcl-2 was significantly downregulated) and was dose-dependent on Wogonin. The ELISA results showed that, compared with the control group, the secretion of tumor necrosis factor alpha, IL-1β, and IL-6 decreased as the Wogonin concentration increased. Tumor necrosis factor alpha downregulation had no significant dose-dependent effect on Wogonin, the inhibitory effect of 25 μM of Wogonin on IL-6 was not significant, and IL-1β downregulation had a significant dose-dependent effect on Wogonin.

Conclusion: Wogonin might promote the apoptosis of glioma cells by upregulating proapoptotic factors, downregulating antiapoptotic factors, and inhibiting the inflammatory response, thereby inhibiting glioma progression.

Current Advances in Immunotherapy for Glioblastoma

PURPOSE OF REVIEW

This review seeks to inform oncology clinicians and researchers about the development of novel immunotherapies for the treatment of glioblastoma. An enumeration of ongoing and recently completed clinical trials will be discussed with special attention given to current technologies implemented to overcome central nervous system-specific challenges including barriers to the peripheral immune system, impaired antigen presentation, and T cell dysfunction.

RECENT FINDINGS

The success of immunotherapy in other solid cancers has served as a catalyst to explore its application in glioblastoma, which has limited response to other treatments. Recent developments include multi-antigen vaccines that seek to overcome the heterogeneity of glioblastoma, as well as immune checkpoint inhibitors, which could amplify the adaptive immune response and may have promise in combinatorial approaches. Additionally, oncolytic and retroviruses have opened the door to a plethora of combinatorial approaches aiming to leverage their immunogenicity and/or ability to carry therapeutic transgenes. Treatment of glioblastoma remains a serious challenge both with regard to immune-based as well as other therapeutic strategies. The disease has proven to be highly resistant to treatment due to a combination of tumor heterogeneity, adaptive expansion of resistant cellular subclones, evasion of immune surveillance, and manipulation of various signaling pathways involved in tumor progression and immune response. Immunotherapeutics that are efficacious in other cancer types have unfortunately not enjoyed the same success in glioblastoma, illustrating the challenging and complex nature of this disease and demonstrating the need for development of multimodal treatment regimens utilizing the synergistic qualities of immune-mediated therapies.

Randomized Controlled Immunotherapy Clinical Trials for GBM Challenged

Simple Summary

Although multiple meta-analyses on active specific immunotherapy treatment for glioblastoma multiforme (GBM) have demonstrated a significant prolongation of overall survival, no single research group has succeeded in demonstrating the efficacy of this type of treatment in a prospective, double-blind, placebo-controlled, randomized clinical trial. In this paper, we explain how the complexity of the tumor biology and tumor–host interactions make proper stratification of a control group impossible. The individualized characteristics of advanced therapy medicinal products for immunotherapy contribute to heterogeneity within an experimental group. The dynamics of each tumor and in each patient aggravate comparative stable patient groups. Finally, combinations of immunotherapy strategies should be integrated with first-line treatment. We illustrate the complexity of a combined first-line treatment with individualized multimodal immunotherapy in a group of 70 adults with GBM and demonstrate that the integration of immunogenic cell death treatment within maintenance chemotherapy followed by dendritic cell vaccines and maintenance immunotherapy might provide a step towards improving the overall survival rate of GBM patients.

Abstract

Immunotherapies represent a promising strategy for glioblastoma multiforme (GBM) treatment. Different immunotherapies include the use of checkpoint inhibitors, adoptive cell therapies such as chimeric antigen receptor (CAR) T cells, and vaccines such as dendritic cell vaccines. Antibodies have also been used as toxin or radioactive particle delivery vehicles to eliminate target cells in the treatment of GBM. Oncolytic viral therapy and other immunogenic cell death-inducing treatments bridge the antitumor strategy with immunization and installation of immune control over the disease. These strategies should be included in the standard treatment protocol for GBM. Some immunotherapies are individualized in terms of the medicinal product, the immune target, and the immune tumor–host contact. Current individualized immunotherapy strategies focus on combinations of approaches. Standardization appears to be impossible in the face of complex controlled trial designs. To define appropriate control groups, stratification according to the Recursive Partitioning Analysis classification, MGMT promotor methylation, epigenetic GBM sub-typing, tumor microenvironment, systemic immune functioning before and after radiochemotherapy, and the need for/type of symptom-relieving drugs is required. Moreover, maintenance of a fixed treatment protocol for a dynamic, deadly cancer disease in a permanently changing tumor–host immune context might be inappropriate. This complexity is illustrated using our own data on individualized multimodal immunotherapies for GBM. Individualized medicines, including multimodal immunotherapies, are a rational and optimal yet also flexible approach to induce long-term tumor control. However, innovative methods are needed to assess the efficacy of complex individualized treatments and implement them more quickly into the general health system.

Pseudoprogression versus true progression in glioblastoma patients: A multiapproach literature review: Part 1 - Molecular, morphological and clinical features

With new therapeutic protocols, more patients treated for glioblastoma have experienced a suspicious radiologic image of progression (pseudoprogression) during follow-up. Pseudoprogression should be differentiated from true progression because the disease management is completely different. In the case of pseudoprogression, the follow-up continues, and the patient is considered stable. In the case of true progression, a treatment adjustment is necessary. Presently, a pseudoprogression diagnosis certainly needs to be pathologically confirmed. Some important efforts in the radiological, histopathological, and genomic fields have been made to differentiate pseudoprogression from true progression, and the assessment of response criteria exists but remains limited. The aim of this paper is to highlight clinical and pathological markers to differentiate pseudoprogression from true progression through a literature review.

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.

Advanced magnetic resonance imaging to support clinical drug development for malignant glioma

Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.

Glioma surveillance imaging: current strategies, shortcomings, challenges and outlook

Inaccurate assessment of surveillance imaging to assess response to glioma therapy may have life-changing consequences. Varied management plans including chemotherapy, radiotherapy or immunotherapy may all contribute to heterogeneous post-treatment appearances and the overlap between the morphological features of pseudoprogression, pseudoresponse and radiation necrosis can make their discrimination very challenging. Therefore, there has been a drive to develop objective strategies for post-treatment assessment of brain gliomas. This review discusses the most important of these approaches such as the RANO "Response Assessment in Neuro-Oncology", iRANO "Immunotherapy Response Assessment in Neuro-Oncology" and RAPNO "Response Assessment in Paediatric Neuro-Oncology" models. In addition to these systematic approaches for glioma surveillance, the relatively limited information provided by conventional imaging modalities alone has motivated the development of novel advanced magnetic resonance (MR) and metabolic imaging methods for further discrimination between viable tumour and treatment induced changes. Multiple clinical trials and meta-analyses have investigated the diagnostic performance of these novel techniques in the follow up of brain gliomas, including both single modality descriptive studies and comparative imaging assessment. In this manuscript, we review the literature and discuss the promises and pitfalls of frequently studied modalities in glioma surveillance imaging, including MR perfusion, MR diffusion and MR spectroscopy. In addition, we evaluate other promising MR techniques such as chemical exchange saturation transfer as well as fludeoxyglucose and non-FDG positron emission tomography techniques.

Patient‑derived orthotopic xenograft glioma models fail to replicate the magnetic resonance imaging features of the original patient tumor

Patient-derived orthotopic glioma xenograft models are important platforms used for pre-clinical research of glioma. In the present study, the diagnostic ability of magnetic resonance imaging (MRI) was examined with regard to the identification of biomarkers obtained from patient-derived glioma xenografts and human tumors. Conventional MRI, diffusion weighted imaging and dynamic contrast-enhanced (DCE)-MRI were used to analyze seven pairs of high grade gliomas with their corresponding xenografts obtained from non-obese diabetic-severe-combined immunodeficiency nude mice. Tumor samples were collected for transcriptome sequencing and histopathological staining, and differentially expressed genes were screened between the original tumors and the corresponding xenografts. Gene Ontology (GO) analysis was performed to predict the functions of these genes. In 6 cases of xenografts with diffuse growth, the degree of enhancement was significantly lower compared with the original tumors. Histopathological staining indicated that the microvascular area and microvascular diameter of the xenografts were significantly lower compared with the original tumors (P=0.009 and P=0.007, respectively). In one case, there was evidence of nodular tumor growth in the mouse. Both MRI and histopathological staining showed a clear demarcation between the transplanted tumors and the normal brain tissues. The relative apparent diffusion coefficient values of the 7 cases examined were significantly higher compared with the corresponding original tumors (P=0.001) and transfer coefficient values derived from DCE-MRI of the tumor area was significantly lower compared with the original tumors (P=0.016). GO analysis indicated that the expression levels of extracellular matrix-associated genes, angiogenesis-associated genes and immune function-associated genes in the original tumors were higher compared with the corresponding xenografts. In conclusion, the data demonstrated that the MRI features of patient-derived xenograft glioma models in mice were different compared with those of the original patient tumors. Differential gene expression may underlie the differences noted in the MRI features between original tumors and corresponding xenografts. The results of the present study highlight the precautions that should be taken when extrapolating data from patient-derived xenograft studies, and their applicability to humans.

Pretreatment Geriatric Assessments of Elderly Patients with Glioma: Development and Implications

Glioma is the most frequent primary brain tumor affecting adults, and the most lethal type is glioblastoma (GBM); currently, the available therapies only provide palliation. The treatments for low-grade glioma (LGG) include neurosurgical resection, watchful waiting, radiotherapy and chemotherapy, while the therapeutic strategies for high-grade glioma (HGG), particularly in elderly patients, have evolved to include radiotherapy, chemotherapy, and targeted monotherapy based on the characteristics of the investigated patients. Proper assessments aiming to predict and achieve the most satisfying prognosis among patients prior to surgery, radiotherapy, chemotherapy, targeted therapy or immunotherapy help summarize the pretreatment characteristics of patients, providing doctors comprehensive information to consider while determining whether the patients could benefit from ongoing treatments and deciding the proper treatment strategy for subsequent phases. This article aims to rigorously review the most recent evidence and discuss current mainstream assessments before the initiation of proper treatments for glioma, thus highlighting the potential necessity of pretreatment assessments.

Beyond the Blood: CSF-Derived cfDNA for Diagnosis and Characterization of CNS Tumors

Genetic data are rapidly becoming part of tumor classification and are integral to prognosis and predicting response to therapy. Current molecular tumor profiling relies heavily on tissue resection or biopsy. Tissue profiling has several disadvantages in tumors of the central nervous system, including the challenge associated with invasive biopsy, the heterogeneous nature of many malignancies where a small biopsy can underrepresent the mutational profile, and the frequent lack of obtaining a repeat biopsy, which limits routine monitoring to assess therapy response and/or tumor evolution. Circulating tumor, cell-free DNA (cfDNA), has been proposed as a liquid biopsy to address some limitations of tissue-based genetics. In cancer patients, a portion of cfDNA is tumor-derived and may contain somatic genetic alterations. In central nervous system (CNS) neoplasia, plasma tumor-derived cfDNA is very low or absent, likely due to the blood brain barrier. Interrogating cfDNA in cerebrospinal fluid (CSF) has several advantages. Compared to blood, CSF is paucicellular and therefore predominantly lacks non-tumor cfDNA; however, patients with CNS-limited tumors have significantly enriched tumor-derived cfDNA in CSF. In patients with metastatic CNS disease, mutations in CSF cfDNA are most concordant with the intracranial process. CSF cfDNA can also occasionally uncover additional genetic alterations absent in concurrent biopsy specimens, reflecting tumor heterogeneity. Although CSF is enriched for tumor-derived cfDNA, absolute quantities are low. Highly sensitive, targeted methods including next-generation sequencing and digital PCR are required to detect mutations in CSF cfDNA. Additional technical and bioinformatic approaches also facilitate enhanced ability to detect tumor mutations in CSF cfDNA.

Brain immunology and immunotherapy in brain tumours

Gliomas, the most common malignant primary brain tumours, remain universally lethal. Yet, seminal discoveries in the past 5 years have clarified the anatomy, genetics and function of the immune system within the central nervous system (CNS) and altered the paradigm for successful immunotherapy. The impact of standard therapies on the response to immunotherapy is now better understood, as well. This new knowledge has implications for a broad range of tumours that develop within the CNS. Nevertheless, the requirements for successful therapy remain effective delivery and target specificity, while the dramatic heterogeneity of malignant gliomas at the genetic and immunological levels remains a profound challenge.

Biopsy Confirmed Glioma Recurrence Predicted by Multi-Modal Neuroimaging Metrics

Histopathological verification is currently required to differentiate tumor recurrence from treatment effects related to adjuvant therapy in patients with glioma. To bypass the complications associated with collecting neural tissue samples, non-invasive classification methods are needed to alleviate the burden on patients while providing vital information to clinicians. However, uncertainty remains as to which tissue features on magnetic resonance imaging (MRI) are useful. The primary objective of this study was to quantitatively assess the reliability of combining MRI and diffusion tensor imaging metrics to discriminate between tumor recurrence and treatment effects in histopathologically identified biopsy samples. Additionally, this study investigates the noise adjuvant radiation therapy introduces when discriminating between tissue types. In a sample of 41 biopsy specimens, from a total of 10 patients, we derived region-of-interest samples from MRI data in the ipsilateral hemisphere that encompassed biopsies obtained during resective surgery. This study compares normalized intensity values across histopathology classifications and contralesional volumes reflected across the midline. Radiation makes noninvasive differentiation of abnormal-nontumor tissue to tumor recurrence much more difficult. This is because radiation exhibits opposing behavior on key MRI modalities: specifically, on post-contrast T1, FLAIR, and GFA. While radiation makes noninvasive differentiation of tumor recurrence more difficult, using a novel analysis of combined MRI metrics combined with clinical annotation and histopathological correlation, we observed that it is possible to successfully differentiate tumor tissue from other tissue types. Additional work will be required to expand upon these findings.

Current and Future Trends on Diagnosis and Prognosis of Glioblastoma: From Molecular Biology to Proteomics

Glioblastoma multiforme is the most aggressive malignant tumor of the central nervous system. Due to the absence of effective pharmacological and surgical treatments, the identification of early diagnostic and prognostic biomarkers is of key importance to improve the survival rate of patients and to develop new personalized treatments. On these bases, the aim of this review article is to summarize the current knowledge regarding the application of molecular biology and proteomics techniques for the identification of novel biomarkers through the analysis of different biological samples obtained from glioblastoma patients, including DNA, microRNAs, proteins, small molecules, circulating tumor cells, extracellular vesicles, etc. Both benefits and pitfalls of molecular biology and proteomics analyses are discussed, including the different mass spectrometry-based analytical techniques, highlighting how these investigation strategies are powerful tools to study the biology of glioblastoma, as well as to develop advanced methods for the management of this pathology.

Current and Future Imaging Methods for Evaluating Response to Immunotherapy in Neuro-Oncology

Imaging plays a central role in evaluating responses to therapy in neuro-oncology patients. The advancing clinical use of immunotherapies has demonstrated that treatment-related inflammatory responses mimic tumor growth via conventional imaging, thus spurring the development of new imaging approaches to adequately distinguish between pseudoprogression and progressive disease. To this end, an increasing number of advanced imaging techniques are being evaluated in preclinical and clinical studies. These novel molecular imaging approaches will serve to complement conventional response assessments during immunotherapy. The goal of these techniques is to provide definitive metrics of tumor response at earlier time points to inform treatment decisions, which has the potential to improve patient outcomes. This review summarizes the available immunotherapy regimens, clinical response criteria, current state-of-the-art imaging approaches, and groundbreaking strategies for future implementation to evaluate the anti-tumor and immune responses to immunotherapy in neuro-oncology applications.

Biomarkers and smart intracranial devices for the diagnosis, treatment, and monitoring of high-grade gliomas: a review of the literature and future prospects

Glioblastoma (GBM) is the most common primary brain neoplasm with median overall survival (OS) around 15 months. There is a dearth of effective monitoring strategies for patients with high-grade gliomas. Relying on magnetic resonance images of brain has its challenges, and repeated brain biopsies add significant morbidity. Hence, it is imperative to establish a less invasive way to diagnose, monitor, and guide management of patients with high-grade gliomas. Currently, multiple biomarkers are in various phases of development and include tissue, serum, cerebrospinal fluid (CSF), and imaging biomarkers. Here we review and summarize the potential biomarkers found in blood and CSF, including extracellular macromolecules, extracellular vesicles, circulating tumor cells, immune cells, endothelial cells, and endothelial progenitor cells. The ability to detect tumor-specific biomarkers in blood and CSF will potentially not only reduce the need for repeated brain biopsies but also provide valuable information about the heterogeneity of tumor, response to current treatment, and identify disease resistance. This review also details the status and potential scope of brain tumor-related cranial devices and implants including Ommaya reservoir, microelectromechanical systems-based depot device, Alzet mini-osmotic pump, Metronomic Biofeedback Pump (MBP), ipsum G1 implant, ultra-thin needle implant, and putative devices. An ideal smart cranial implant will overcome the blood-brain barrier, deliver various drugs, provide access to brain tissue, and potentially measure and monitor levels of various biomarkers.

Evaluation of the Implementation of the Response Assessment in Neuro-Oncology Criteria in the HERBY Trial of Pediatric Patients with Newly Diagnosed High-Grade Gliomas

BACKGROUND AND PURPOSE

HERBY was a Phase II multicenter trial setup to establish the efficacy and safety of adding bevacizumab to radiation therapy and temozolomide in pediatric patients with newly diagnosed non-brain stem high-grade gliomas. This study evaluates the implementation of the radiologic aspects of HERBY.

MATERIALS AND METHODS

We analyzed multimodal imaging compliance rates and scan quality for participating sites, adjudication rates and reading times for the central review process, the influence of different Response Assessment in Neuro-Oncology criteria in the final response, the incidence of pseudoprogression, and the benefit of incorporating multimodal imaging into the decision process.

RESULTS

Multimodal imaging compliance rates were the following: diffusion, 82%; perfusion, 60%; and spectroscopy, 48%. Neuroradiologists' responses differed for 50% of scans, requiring adjudication, with a total average reading time per patient of approximately 3 hours. Pseudoprogression occurred in 10/116 (9%) cases, 8 in the radiation therapy/temozolomide arm and 2 in the bevacizumab arm (P < .01). Increased target enhancing lesion diameter was a reason for progression in 8/86 cases (9.3%) but never the only radiologic or clinical reason. Event-free survival was predicted earlier in 5/86 (5.8%) patients by multimodal imaging (diffusion, n = 4; perfusion, n = 1).

CONCLUSIONS

The addition of multimodal imaging to the response criteria modified the assessment in a small number of cases, determining progression earlier than structural imaging alone. Increased target lesion diameter, accounting for a large proportion of reading time, was never the only reason to designate disease progression.

Genetically Engineered T-Cells for Malignant Glioma: Overcoming the Barriers to Effective Immunotherapy

Malignant gliomas carry a dismal prognosis. Conventional treatment using chemo- and radiotherapy has limited efficacy with adverse events. Therapy with genetically engineered T-cells, such as chimeric antigen receptor (CAR) T-cells, may represent a promising approach to improve patient outcomes owing to their potential ability to attack highly infiltrative tumors in a tumor-specific manner and possible persistence of the adaptive immune response. However, the unique anatomical features of the brain and susceptibility of this organ to irreversible tissue damage have made immunotherapy especially challenging in the setting of glioma. With safety concerns in mind, multiple teams have initiated clinical trials using CAR T-cells in glioma patients. The valuable lessons learnt from those trials highlight critical areas for further improvement: tackling the issues of the antigen presentation and T-cell homing in the brain, immunosuppression in the glioma microenvironment, antigen heterogeneity and off-tumor toxicity, and the adaptation of existing clinical therapies to reflect the intricacies of immune response in the brain. This review summarizes the up-to-date clinical outcomes of CAR T-cell clinical trials in glioma patients and examines the most pressing hurdles limiting the efficacy of these therapies. Furthermore, this review uses these hurdles as a framework upon which to evaluate cutting-edge pre-clinical strategies aiming to overcome those barriers.

Immunotherapy for High Grade Gliomas: A Clinical Update and Practical Considerations for Neurosurgeons

The current standard of care for patients with high grade gliomas includes surgical resection, chemotherapy, and radiation; but even still the majority of patients experience disease progression and succumb to their illness within a few years of diagnosis. Immunotherapy, which stimulates an anti-tumor immune response, has been revolutionary in the treatment of some hematological and solid malignancies, generating substantial excitement for its potential for patients with glioblastoma. The most commonly used immunotherapies include dendritic cell and peptide vaccines, checkpoint inhibitors, and adoptive T cell therapy. However, to date, the preclinical success of these approaches against high-grade glioma models has not been replicated in human clinical trials. Moreover, the complex response to these biologically active treatments can complicate management decisions, and the neurosurgical oncology community needs to be actively involved in and up to date on the use of these agents in high grade glioma patients. In this review, we discuss the challenges immunotherapy faces for high grade gliomas, the completed and ongoing clinical trials for the major immunotherapies, and the nuances in management for patients being actively treated with one of these agents.

Liquid biopsy for pediatric central nervous system tumors

Central nervous system (CNS) tumors are the most common solid tumors in children, and the leading cause of cancer-related death. Over the past decade, molecular profiling has been incorporated into treatment for pediatric CNS tumors, allowing for a more personalized approach to therapy. Through the identification of tumor-specific changes, it is now possible to diagnose, assign a prognostic subgroup, and develop targeted chemotherapeutic treatment plans for many cancer types. The successful incorporation of informative liquid biopsies, where the liquid biome is interrogated for tumor-associated molecular clues, has the potential to greatly complement the precision-based approach to treatment, and ultimately, to improve clinical outcomes for children with CNS tumors. In this article, the current application of liquid biopsy in cancer therapy will be reviewed, as will its potential for the diagnosis and therapeutic monitoring of pediatric CNS tumors.

Current concepts and challenges in the radiologic assessment of brain tumors in children: part 2

Assessing tumor response is a large part of everyday clinical work in neuroradiology. However in the setting of tumor treatment, distinguishing tumor progression from treatment-related changes is difficult on conventional MRI sequences. This is made even more challenging in children where mainstay advanced imaging techniques that are often used to decipher progression versus treatment-related changes have technical limitations. In this review, we highlight the challenges in pediatric neuro-oncologic tumor assessment with discussion of pseudophenomenon including pseudoresponse and pseudoprogression. Additionally, we discuss the advanced imaging techniques often employed in neuroradiology to distinguish between pseudophenomenon and true progressive disease.

Glioma response assessment: Classic pitfalls, novel confounders, and emerging imaging tools

Neuroimaging plays a pivotal role in the care of patients with infiltrating gliomas, in whom imaging changes are often the first indications of tumor response or progression. Unfortunately, evaluation of glioma response is often not straightforward, even for experienced radiologists. Post-surgical or radiation-related changes may mimic the appearance of disease progression, while medications such as corticosteroids and antiangiogenic agents may mimic tumor response without truly arresting tumor growth or improving patient survival. Immunotherapy response can result in inflammatory changes which manifest as progressively increasing tumor enhancement and edema over months. Many of these pitfalls can be minimized or avoided altogether by the use of modern brain tumor response criteria, while others will require new imaging tools before they can be fully addressed. Advanced MRI methods and novel positron emission tomography (PET) agents are proving important for this purpose, and their role will undoubtedly continue to grow in the future.

Multisite Concordance of DSC-MRI Analysis for Brain Tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project

BACKGROUND AND PURPOSE

Standard assessment criteria for brain tumors that only include anatomic imaging continue to be insufficient. While numerous studies have demonstrated the value of DSC-MR imaging perfusion metrics for this purpose, they have not been incorporated due to a lack of confidence in the consistency of DSC-MR imaging metrics across sites and platforms. This study addresses this limitation with a comparison of multisite/multiplatform analyses of shared DSC-MR imaging datasets of patients with brain tumors.

MATERIALS AND METHODS

DSC-MR imaging data were collected after a preload and during a bolus injection of gadolinium contrast agent using a gradient recalled-echo-EPI sequence (TE/TR = 30/1200 ms; flip angle = 72°). Forty-nine low-grade (n = 13) and high-grade (n = 36) glioma datasets were uploaded to The Cancer Imaging Archive. Datasets included a predetermined arterial input function, enhancing tumor ROIs, and ROIs necessary to create normalized relative CBV and CBF maps. Seven sites computed 20 different perfusion metrics. Pair-wise agreement among sites was assessed with the Lin concordance correlation coefficient. Distinction of low- from high-grade tumors was evaluated with the Wilcoxon rank sum test followed by receiver operating characteristic analysis to identify the optimal thresholds based on sensitivity and specificity.

RESULTS

For normalized relative CBV and normalized CBF, 93% and 94% of entries showed good or excellent cross-site agreement (0.8 ≤ Lin concordance correlation coefficient ≤ 1.0). All metrics could distinguish low- from high-grade tumors. Optimum thresholds were determined for pooled data (normalized relative CBV = 1.4, sensitivity/specificity = 90%:77%; normalized CBF = 1.58, sensitivity/specificity = 86%:77%).

CONCLUSIONS

By means of DSC-MR imaging data obtained after a preload of contrast agent, substantial consistency resulted across sites for brain tumor perfusion metrics with a common threshold discoverable for distinguishing low- from high-grade tumors.