The Rigidity Connection: Matrix Stiffness and Its Impact on Cancer Progression.

The extracellular matrix (ECM) has always been studied in the context of the structural support it provides tissues. However, more recently, it has become clear that ECM proteins do more to regulate biological processes relevant to cancer progression: from activating complex signaling pathways to presenting soluble growth factors. In 2009, Ulrich and colleagues provided evidence that the physical properties of the ECM could also contribute to glioblastoma tumor cell proliferation and invasion using tunable hydrogels, emphasizing a role for tumor rigidity in central nervous system cancer progression. Here, we will discuss the results of this landmark article, as well as highlight other work that has shown the importance of tissue stiffness in glioblastoma and other tumor types in the tumor microenvironment. Finally, we will discuss how this research has led to the development of novel treatments for cancer that target tumor rigidity. See related article by Ulrich and colleagues, Cancer Res 2009;69:4167-74.

GRIK1 promotes glioblastoma malignancy and is a novel prognostic factor of poor prognosis.

Primary tumors of the central nervous system (CNS) are classified into over 100 different histological types. The most common type of glioma is derived from astrocytes, and the most invasive glioblastoma (WHO IV) accounts for over 57% of these tumors. Glioblastoma (GBM) is the most common and fatal tumor of the CNS, with strong growth and invasion capabilities, which makes complete surgical resection almost impossible. Despite various treatment methods such as surgery, radiotherapy, and chemotherapy, glioma is still an incurable disease, and the median survival time of patients with GBM is shorter than 15 months. Thus, molecular mechanisms of GBM characteristic invasive growth need to be clarified to improve the poor prognosis. Glutamate ionotropic receptor kainate type subunit 1 (GRIK1) is essential for brain function and is involved in many mental and neurological diseases. However, GRIK1's pathogenic roles and mechanisms in GBM are still unknown. Single-nuclear RNA sequencing of primary and recurrent GBM samples revealed that GRIK1 expression was noticeably higher in the recurrent samples. Moreover, immunohistochemical staining of an array of GBM samples showed that high levels of GRIK1 correlated with poor prognosis of GBM, consistent with The Cancer Genome Atlas database. Knockdown of GRIK1 retarded GBM cells growth, migration, and invasion. Taken together, these findings show that GRIK1 is a unique and important component in the development of GBM and may be considered as a biomarker for the diagnosis and therapy in individuals with GBM.

Regorafenib and glioblastoma: a literature review of preclinical studies, molecular mechanisms and clinical effectiveness.

Glioblastoma IDH wild type (GBM) is a very aggressive brain tumour, characterised by an infiltrative growth pattern and by a prominent neoangiogenesis. Its prognosis is unfortunately dismal, and the median overall survival of GBM patients is short (15 months). Clinical management is based on bulk tumour removal and standard chemoradiation with the alkylating drug temozolomide, but the tumour invariably recurs leading to patient's death. Clinical options for GBM patients remained unaltered for almost two decades until the encouraging results obtained by the phase II REGOMA trial allowed the introduction of the multikinase inhibitor regorafenib as a preferred regimen in relapsed GBM treatment by the National Comprehensive Cancer Network (NCCN) 2020 Guideline. Regorafenib, a sorafenib derivative, targets kinases associated with angiogenesis (VEGFR 1-3), as well as oncogenesis (c-KIT, RET, FGFR) and stromal kinases (FGFR, PDGFR-b). It was already approved for metastatic colorectal cancers and hepatocellular carcinomas. The aim of the present review is to focus on both the molecular and clinical knowledge collected in these first three years of regorafenib use in GBM.

Beyond fluorescence-guided resection: 5-ALA-based glioblastoma therapies.

Glioblastoma is the most common primary malignant brain tumor. Despite advances in multimodal concepts over the last decades, prognosis remains poor. Treatment of patients with glioblastoma remains a considerable challenge due to the infiltrative nature of the tumor, rapid growth rates, and tumor heterogeneity. Standard therapy consists of maximally safe microsurgical resection followed by adjuvant radio- and chemotherapy with temozolomide. In recent years, local therapies have been extensively investigated in experimental as well as translational levels. External stimuli-responsive therapies such as Photodynamic Therapy (PDT), Sonodynamic Therapy (SDT) and Radiodynamic Therapy (RDT) can induce cell death mechanisms via generation of reactive oxygen species (ROS) after administration of five-aminolevulinic acid (5-ALA), which induces the formation of sensitizing porphyrins within tumor tissue. Preliminary data from clinical trials are available. The aim of this review is to summarize the status of such therapeutic approaches as an adjunct to current standard therapy in glioblastoma.

Glioblastoma: Not Just Another Cancer.

SUMMARY: This commentary urges a paradigm shift in how we approach research and drug development for glioblastoma, reimagining it as an aberrant brain-like organ, distinct from other cancers, to inspire innovative treatment strategies and interdisciplinary collaboration, addressing the minimal progress in extending glioblastoma patient survival despite years of research and investment.

Tumefactive Primary Central Nervous System Vasculitis: Dynamic Susceptibility Contrast Perfusion-Weighted Magnetic Resonance Imaging Findings With Histological Correlation.

Purpose: Primary central nervous system vasculitis (PCNSV) is a rare inflammatory disease affecting the central nervous system. In some cases, it presents with large, solitary lesion with extensive mass effect that mimic intracranial neoplasms. This condition results in a diagnostic confusion for neuroradiologists because the differentiation is almost impossible on conventional MRI sequences. The aim of this study is to reveal the significance of dynamic susceptibility contrast (DSC) perfusion-weighted imaging in differentiating of tumefactive PCNSV (t-PCNSV) lesions from intracranial neoplasms such as glio-blastomas and metastasis. Methods: In this retrospective study, DSC of 8 patients with biopsy-proven t-PCNSV has been compared with DSC obtained in 10 patients with glioblastoma, 10 patients with metastasis, who underwent surgery and histopathological confirmation. The ratio of relative cerebral blood volume (rrCBV) was calculated by rCBV (lesion) / rCBV (controlateral normal-appearing white matter) in the gadolinium-enhancing solid areas. Results: The mean rrCBV was 0.86±0.7 (range: 0.76-0.98) in the patients with t-PCNSV, 5,16±0.79 in patients with glioblastoma (range: 3.9-6.3), and 4.27±0.73 (range: 2.8-5.3) in patients with metastases. Conclusion: DSC-PWI seems to be useful in the diagnostic work-up of t-PCSNVs. A low rrCBV, i.e. a rCBV similar or lower to that of the contralateral normal white matter, seems to be consistent with the possibility of t-PCSNV.

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts.

BACKGROUND: A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials. METHODS: Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry, and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors. RESULTS: We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components. CONCLUSIONS: Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.

Exploring ncRNA-mediated regulation of EGFR signalling in glioblastoma: From mechanisms to therapeutics.

Glioblastoma (GBM) is the most prevalent and deadly primary brain tumor type, with a discouragingly low survival rate and few effective treatments. An important function of the EGFR signalling pathway in the development of GBM is to affect tumor proliferation, persistence, and treatment resistance. Advances in molecular biology in the last several years have shown how important ncRNAs are for controlling a wide range of biological activities, including cancer progression and development. NcRNAs have become important post-transcriptional regulators of gene expression, and they may affect the EGFR pathway by either directly targeting EGFR or by modifying important transcription factors and downstream signalling molecules. The EGFR pathway is aberrantly activated in response to the dysregulation of certain ncRNAs, which has been linked to GBM carcinogenesis, treatment resistance, and unfavourable patient outcomes. We review the literature on miRNAs, circRNAs and lncRNAs that are implicated in the regulation of EGFR signalling in GBM, discussing their mechanisms of action, interactions with the signalling pathway, and implications for GBM therapy. Furthermore, we explore the potential of ncRNA-based strategies to overcome resistance to EGFR-targeted therapies, including the use of ncRNA mimics or inhibitors to modulate the activity of key regulators within the pathway.

MiRNAs from the Dlk1-Dio3 locus and miR-224/452 cluster contribute to glioblastoma tumor heterogeneity.

Glioblastoma is one of the most common and aggressive brain tumors and has seen few improvements in patient outcomes. Inter-tumor heterogeneity between tumors of different patients as well as intra-tumor heterogeneity of cells within the same tumor challenge the development of effective drugs. MiRNAs play an essential role throughout the developing brain and regulate many key genes involved in oncogenesis, yet their role in driving many of the processes underlying tumor heterogeneity remains unclear. In this study, we highlight miRNAs from the Dlk1-Dio3 and miR-224/452 clusters which may be expressed cell autonomously and have expression that is associated with cell state genes in glioblastoma, most prominently in neural progenitor-like and mesenchymal-like states respectively. These findings implicate these miRNA clusters as potential regulators of glioblastoma intra-tumoral heterogeneity and may serve as valuable biomarkers for cell state identification.

Development and validation of a multi-modality fusion deep learning model for differentiating glioblastoma from solitary brain metastases. / åŒºåˆ†èƒ¶è´¨æ¯ç»†èƒžç˜¤å’Œå•å‘æ€§è„‘è½¬ç§»ç˜¤çš„å¤šæ¨¡æ€èžåˆæ·±åº¦å­¦ä¹ æ¨¡åž‹çš„å¼€å‘å’ŒéªŒè¯.

OBJECTIVES: Glioblastoma (GBM) and brain metastases (BMs) are the two most common malignant brain tumors in adults. Magnetic resonance imaging (MRI) is a commonly used method for screening and evaluating the prognosis of brain tumors, but the specificity and sensitivity of conventional MRI sequences in differential diagnosis of GBM and BMs are limited. In recent years, deep neural network has shown great potential in the realization of diagnostic classification and the establishment of clinical decision support system. This study aims to apply the radiomics features extracted by deep learning techniques to explore the feasibility of accurate preoperative classification for newly diagnosed GBM and solitary brain metastases (SBMs), and to further explore the impact of multimodality data fusion on classification tasks. METHODS: Standard protocol cranial MRI sequence data from 135 newly diagnosed GBM patients and 73 patients with SBMs confirmed by histopathologic or clinical diagnosis were retrospectively analyzed. First, structural T1-weight, T1C-weight, and T2-weight were selected as 3 inputs to the entire model, regions of interest (ROIs) were manually delineated on the registered three modal MR images, and multimodality radiomics features were obtained, dimensions were reduced using a random forest (RF)-based feature selection method, and the importance of each feature was further analyzed. Secondly, we used the method of contrast disentangled to find the shared features and complementary features between different modal features. Finally, the response of each sample to GBM and SBMs was predicted by fusing 2 features from different modalities. RESULTS: The radiomics features using machine learning and the multi-modal fusion method had a good discriminatory ability for GBM and SBMs. Furthermore, compared with single-modal data, the multimodal fusion models using machine learning algorithms such as support vector machine (SVM), Logistic regression, RF, adaptive boosting (AdaBoost), and gradient boosting decision tree (GBDT) achieved significant improvements, with area under the curve (AUC) values of 0.974, 0.978, 0.943, 0.938, and 0.947, respectively; our comparative disentangled multi-modal MR fusion method performs well, and the results of AUC, accuracy (ACC), sensitivity (SEN) and specificity(SPE) in the test set were 0.985, 0.984, 0.900, and 0.990, respectively. Compared with other multi-modal fusion methods, AUC, ACC, and SEN in this study all achieved the best performance. In the ablation experiment to verify the effects of each module component in this study, AUC, ACC, and SEN increased by 1.6%, 10.9% and 15.0%, respectively after 3 loss functions were used simultaneously. CONCLUSIONS: A deep learning-based contrast disentangled multi-modal MR radiomics feature fusion technique helps to improve GBM and SBMs classification accuracy.

EGFR/CEP7 high polysomy is separate and distinct from EGFR amplification in glioblastoma as determined by fluorescence in situ hybridization.

EGFR amplification in gliomas is commonly defined by an EGFR/CEP7 ratio of ≥2. In testing performed at a major reference laboratory, a small subset of patients had ≥5 copies of both EGFR and CEP7 yet were not amplified by the EGFR/CEP7 ratio and were designated high polysomy cases. To determine whether these tumors are more closely related to traditionally defined EGFR-amplified or nonamplified gliomas, a retrospective search identified 22 out of 1143 (1.9%) gliomas with an average of ≥5 copies/cell of EGFR and CEP7 with an EGFR/CEP7 ratio of <2 displaying high polysomy. Of these cases, 4 had insufficient clinicopathologic data to include in additional analysis, 15 were glioblastomas, 2 were IDH-mutant astrocytomas, and 1 was a high-grade glial neoplasm, NOS. Next-generation sequencing available on 3 cases demonstrated one with a TERT promoter mutation, TP53 mutations in all cases, and no EGFR mutations or amplifications, which most closely matched the nonamplified cases. The median overall survival times were 42.86, 66.07, and 41.14 weeks for amplified, highly polysomic, and nonamplified, respectively, and were not significantly different (p = 0.3410). High chromosome 7 polysomic gliomas are rare but our data suggest that they may be biologically similar to nonamplified gliomas.

FOXP3 promote the progression of glioblastoma via inhibiting ferroptosis mediated by linc00857/miR-1290/GPX4 axis.

The oncogenic properties of members belonging to the forkhead box (FOX) family have been extensively documented in different types of cancers. In this study, our objective was to investigate the impact of FOXP3 on glioblastoma multiforme (GBM) cells. By conducting a screen using a small hairpin RNA (shRNA) library, we discovered a significant association between FOXP3 and ferroptosis in GBM cells. Furthermore, we observed elevated levels of FOXP3 in both GBM tissues and cell lines, which correlated with a poorer prognosis. FOXP3 was found to promote the proliferation of GBM cells by inhibiting cell ferroptosis in vitro and in vivo. Mechanistically, FOXP3 not only directly upregulated the transcription of GPX4, but also attenuated the degradation of GPX4 mRNA through the linc00857/miR-1290 axis, thereby suppressing ferroptosis and promoting proliferation. Additionally, the FOXP3 inhibitor epirubicin exhibited the ability to impede proliferation and induce ferroptosis in GBM cells both in vitro and in vivo. In summary, our study provided evidences that FOXP3 facilitates the progression of glioblastoma by inhibiting ferroptosis via the linc00857/miR-1290/GPX4 axis, highlighting FOXP3 as a potential therapeutic target for GBM.

Identification of genetic modifiers enhancing B7-H3-targeting CAR T cell therapy against glioblastoma through large-scale CRISPRi screening.

BACKGROUND: Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with a poor prognosis. Current treatment options are limited and often ineffective. CAR T cell therapy has shown success in treating hematologic malignancies, and there is growing interest in its potential application in solid tumors, including GBM. However, current CAR T therapy lacks clinical efficacy against GBM due to tumor-related resistance mechanisms and CAR T cell deficiencies. Therefore, there is a need to improve CAR T cell therapy efficacy in GBM. METHODS: We conducted large-scale CRISPR interference (CRISPRi) screens in GBM cell line U87 MG cells co-cultured with B7-H3 targeting CAR T cells to identify genetic modifiers that can enhance CAR T cell-mediated tumor killing. Flow cytometry-based tumor killing assay and CAR T cell activation assay were performed to validate screening hits. Bioinformatic analyses on bulk and single-cell RNA sequencing data and the TCGA database were employed to elucidate the mechanism underlying enhanced CAR T efficacy upon knocking down the selected screening hits in U87 MG cells. RESULTS: We established B7-H3 as a targetable antigen for CAR T therapy in GBM. Through large-scale CRISPRi screening, we discovered genetic modifiers in GBM cells, including ARPC4, PI4KA, ATP6V1A, UBA1, and NDUFV1, that regulated the efficacy of CAR T cell-mediated tumor killing. Furthermore, we discovered that TNFSF15 was upregulated in both ARPC4 and NDUFV1 knockdown GBM cells and revealed an immunostimulatory role of TNFSF15 in modulating tumor-CAR T interaction to enhance CAR T cell efficacy. CONCLUSIONS: Our study highlights the power of CRISPR-based genetic screening in investigating tumor-CAR T interaction and identifies potential druggable targets in tumor cells that confer resistance to CAR T cell killing. Furthermore, we devised targeted strategies that synergize with CAR T therapy against GBM. These findings shed light on the development of novel combinatorial strategies for effective immunotherapy of GBM and other solid tumors.

Prognostic value of preoperative diffusion restriction in glioblastoma.

INTRODUCTION: Although glioblastoma (GBM) has a very poor prognosis, overall survival (OS) in treated patients shows great difference varying from few days to several months. Identifying factors explaining this difference would improve management of patient treatment. AIM: To determine the relevance of diffusion restriction in newly diagnosed treatment-naïve GBM patients. METHODS: Preoperative magnetic resonance scans of 33 patients with GBM were reviewed. Regions of interest including all the T2 hyperintense lesion were drawn on diffusion weighted B0 images and transferred to the apparent diffusion coefficient (ADC) map. For each patient, a histogram displaying the ADC values within in the regions of interest was generated. Volumetric parameters including tumor regions with restricted diffusion, parameters derived from histogram and mean ADC value of the tumor were calculated. Their relationship with OS was analyzed. RESULTS: Patients with mean ADC value < 1415x10-6 mm2/s had a significantly shorter OS (p=0.021). Among volumetric parameters, the percentage of volume within T2 lesion with a normalized ADC value <1.5 times that in white matter was significantly associated with OS (p=0.0045). Patients with a percentage>23.92% had a shorter OS. Among parameters derived from histogram, the 50th percentile showed a trend towards significance for OS (p=0.055) with patients living longer when having higher values of 50th percentile. A difference in OS was observed between patients according to ADC peak of histogram but this difference did not reach statistical significance (p=0.0959). CONCLUSION: Diffusion magnetic resonance imaging may provide useful information for predicting GBM prognosis.

Tumor associated microglia/macrophages utilize GPNMB to promote tumor growth and alter immune cell infiltration in glioma.

Tumor-associated microglia and blood-derived macrophages (TAMs) play a central role in modulating the immune suppressive microenvironment in glioma. Here, we show that GPNMB is predominantly expressed by TAMs in human glioblastoma multiforme and the murine RCAS-PDGFb high grade glioma model. Loss of GPNMB in the in vivo tumor microenvironment results in significantly smaller tumor volumes and generates a pro-inflammatory innate and adaptive immune cell microenvironment. The impact of host-derived GPNMB on tumor growth was confirmed in two distinct murine glioma cell lines in organotypic brain slices from GPNMB-KO and control mice. Using published data bases of human glioma, the elevated levels in TAMs could be confirmed and the GPNMB expression correlated with a poorer survival.

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm.

BACKGROUND AND OBJECTIVE: Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcome. METHODS: We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. Classification accuracy of each gene were compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity. RESULTS: WSO-SVM achieved 0.80 accuracy, 0.79 sensitivity, and 0.81 specificity for classifying EGFR; 0.71 accuracy, 0.70 sensitivity, and 0.72 specificity for classifying PDGFRA; 0.80 accuracy, 0.78 sensitivity, and 0.83 specificity for classifying PTEN; these results significantly outperformed the existing ML algorithms. Using SHAP, we found that the relative contributions of the five contrast images differ between genes, which are consistent with findings in the literature. The prediction maps revealed extensive intra-tumoral region-to-region heterogeneity within each individual tumor in terms of the alteration status of the three genes. CONCLUSIONS: This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.

Mesenchymal glioma stem cells trigger vasectasia-distinct neovascularization process stimulated by extracellular vesicles carrying EGFR.

Targeting neovascularization in glioblastoma (GBM) is hampered by poor understanding of the underlying mechanisms and unclear linkages to tumour molecular landscapes. Here we report that different molecular subtypes of human glioma stem cells (GSC) trigger distinct endothelial responses involving either angiogenic or circumferential vascular growth (vasectasia). The latter process is selectively triggered by mesenchymal (but not proneural) GSCs and is mediated by a subset of extracellular vesicles (EVs) able to transfer EGFR/EGFRvIII transcript to endothelial cells. Inhibition of the expression and phosphorylation of EGFR in endothelial cells, either pharmacologically (Dacomitinib) or genetically (gene editing), abolishes their EV responses in vitro and disrupts vasectasia in vivo. Therapeutic inhibition of EGFR markedly extends anticancer effects of VEGF blockade in mice, coupled with abrogation of vasectasia and prolonged survival. Thus, vasectasia driven by intercellular transfer of oncogenic EGFR may represent a new therapeutic target in a subset of GBMs.

Delineation of three-dimensional tumor margins based on normalized absolute difference mapping via volumetric optical coherence tomography.

The extent of surgical resection is an important prognostic factor in the treatment of patients with glioblastoma. Optical coherence tomography (OCT) imaging is one of the adjunctive methods available to achieve the maximal surgical resection. In this study, the tumor margins were visualized with the OCT image obtained from a murine glioma model. A commercialized human glioblastoma cell line (U-87) was employed to develop the orthotopic murine glioma model. A swept-source OCT (SS-OCT) system of 1300 nm was used for three-dimensional imaging. Based on the OCT intensity signal, which was obtained via accumulation of each A-scan data, an en-face optical attenuation coefficient (OAC) map was drawn. Due to the limited working distance of the focused beam, OAC values decrease with depth, and using the OAC difference in the superficial area was chosen to outline the tumor boundary, presenting a challenge in analyzing the tumor margin along the depth direction. To overcome this and enable three-dimensional tumor margin detection, we converted the en-face OAC map into an en-face difference map with x- and y-directions and computed the normalized absolute difference (NAD) at each depth to construct a volumetric NAD map, which was compared with the corresponding H&E-stained image. The proposed method successfully revealed the tumor margin along the peripheral boundaries as well as the margin depth. We believe this method can serve as a useful adjunct in glioma surgery, with further studies necessary for real-world practical applications.

Radio-anatomical evaluation of clinical and radiomic profile of multi-parametric magnetic resonance imaging of de novo glioblastoma multiforme.

BACKGROUND: Glioblastoma (GBM) is a fatal, fast-growing, and aggressive brain tumor arising from glial cells or their progenitors. It is a primary malignancy with a poor prognosis. The current study aims at evaluating the neuroradiological parameters of de novo GBM by analyzing the brain multi-parametric magnetic resonance imaging (mpMRI) scans acquired from a publicly available database analysis of the scans. METHODS: The dataset used was the mpMRI scans for de novo glioblastoma (GBM) patients from the University of Pennsylvania Health System, called the UPENN-GBM dataset. This was a collection from The Cancer Imaging Archive (TCIA), a part of the National Cancer Institute. The MRIs were reviewed by a single diagnostic radiologist, and the tumor parameters were recorded, wherein all recorded data was corroborated with the clinical findings. RESULTS: The study included a total of 58 subjects who were predominantly male (male:female ratio of 1.07:1). The mean age with SD was 58.49 (11.39) years. Mean survival days with SD were 347 (416.21) days. The left parietal lobe was the most commonly found tumor location with 11 (18.96%) patients. The mean intensity for T1, T2, and FLAIR with SD was 1.45E + 02 (20.42), 1.11E + 02 (17.61), and 141.64 (30.67), respectively (p = < 0.001). The tumor dimensions of anteroposterior, transverse, and craniocaudal gave a z-score (significance level = 0.05) of - 2.53 (p = 0.01), - 3.89 (p < 0.001), and 1.53 (p = 0.12), respectively. CONCLUSION: The current study takes a third-party database and reduces physician bias from interfering with study findings. Further prospective and retrospective studies are needed to provide conclusive data.

Targeting of REST with rationally-designed small molecule compounds exhibits synergetic therapeutic potential in human glioblastoma cells.

BACKGROUND: Glioblastoma (GBM) is an aggressive brain cancer associated with poor prognosis, intrinsic heterogeneity, plasticity, and therapy resistance. In some GBMs, cell proliferation is fueled by a transcriptional regulator, repressor element-1 silencing transcription factor (REST). RESULTS: Using CRISPR/Cas9, we identified GBM cell lines dependent on REST activity. We developed new small molecule inhibitory compounds targeting small C-terminal domain phosphatase 1 (SCP1) to reduce REST protein level and transcriptional activity in glioblastoma cells. Top leads of the series like GR-28 exhibit potent cytotoxicity, reduce REST protein level, and suppress its transcriptional activity. Upon the loss of REST protein, GBM cells can potentially compensate by rewiring fatty acid metabolism, enabling continued proliferation. Combining REST inhibition with the blockade of this compensatory adaptation using long-chain acyl-CoA synthetase inhibitor Triacsin C demonstrated substantial synergetic potential without inducing hepatotoxicity. CONCLUSIONS: Our results highlight the efficacy and selectivity of targeting REST alone or in combination as a therapeutic strategy to combat high-REST GBM.