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Cholesterol is an essential plasma membrane lipid for the maintenance of cellular homeostasis and cancer cell proliferation. Free cholesterol is harmful to cells; therefore, excessive free cholesterol must be quickly esterified by acetyl‐coenzyme A:cholesterol acetyltransferase (ACAT) and exported by scavenger receptor class B member I (SR‐BI) or ATP‐binding cassette protein A1 from specific cells such as macrophage foam cells, which contain cholesteryl ester‐derived vacuoles. Many vacuoles are present in the cytoplasm of Burkitt lymphoma cells. In this study, we observed that these vacuoles are often seen in high‐grade lymphomas. Cell culture study using lymphoma cell lines found that esterified cholesterol is the main component of these vacuoles and the expression of cholesterol metabolism‐related molecules was significantly upregulated in lymphoma cell lines, with SR‐BI and ACAT inhibitors (BLT‐1 and CI‐976, respectively) impeding lymphoma cell proliferation. Cytoplasmic free cholesterol was increased by ACAT and SR‐BI inhibitors, and the accumulation of free cholesterol induced lymphoma cell apoptosis by inducing endoplasmic reticulum stress. Furthermore, synergistic effects of SR‐BI and ACAT inhibitors were observed in a preclinical study. Treatment with SR‐BI inhibitor suppressed lymphoma progression in a tumor‐bearing mouse model, whereas ACAT inhibitor did not. Therefore, SR‐BI inhibitors are potential new antilymphoma therapeutics that target cholesterol metabolism. This study revealed that the main component of vacuoles seen in high‐grade lymphomas is esterified cholesterol. The expression of cholesterol metabolism‐related molecules such as scavenger receptor class B member I and acetyl‐coenzyme A:cholesterol acetyltransferase is significantly upregulated in lymphoma cells. Scavenger receptor class B member I inhibitor has potential as a new therapy for targeting the cholesterol metabolism pathway in lymphomas.

Glioblastoma is one of the most devastating human malignancies for which a novel efficient treatment is urgently required. This pre–clinical study shows that eribulin, a specific inhibitor of telomerase reverse transcriptase (TERT)‐RNA‐dependent RNA polymerase, is an effective anticancer agent against glioblastoma. Eribulin inhibited the growth of 4 TERT promoter mutation‐harboring glioblastoma cell lines in vitro at subnanomolar concentrations. In addition, it suppressed the growth of glioblastoma cells transplanted subcutaneously or intracerebrally into mice, and significantly prolonged the survival of mice harboring brain tumors at a clinically equivalent dose. A pharmacokinetics study showed that eribulin quickly penetrated brain tumors and remained at a high concentration even when it was washed away from plasma, kidney or liver 24 hours after intravenous injection. Moreover, a matrix‐assisted laser desorption/ionization mass spectrometry imaging analysis revealed that intraperitoneally injected eribulin penetrated the brain tumor and was distributed evenly within the tumor mass at 1 hour after the injection whereas only very low levels of eribulin were detected in surrounding normal brain. Eribulin is an FDA‐approved drug for refractory breast cancer and can be safely repositioned for treatment of glioblastoma patients. Thus, our results suggest that eribulin may serve as a novel therapeutic option for glioblastoma. Based on these data, an investigator‐initiated registration‐directed clinical trial to evaluate the safety and efficacy of eribulin in patients with recurrent GBM (UMIN000030359) has been initiated. Eribulin inhibited the growth of TERT promoter mutation‐harboring glioblastoma cell lines in vitro. In addition, it suppressed the growth of glioblastoma cells transplanted subcutaneously or intracerebrally into mice, and significantly prolonged the survival of mice harboring brain tumors at a clinically equivalent dose. Thus, our results suggest that eribulin may serve as a novel therapeutic option for glioblastoma.

Glioblastoma multiforme (GBM), a lethal brain tumor developing in the white matter of the adult brain, contains a small population of GBM stem cells (GSCs), which potentially cause chemotherapeutic resistance and tumor recurrence. However, the mechanisms underlying the pathogenesis and maintenance of GSCs remain largely unknown. A recent study reported that incorporation of ribosomes and ribosomal proteins into somatic cells promoted lineage trans‐differentiation toward multipotency. This study aimed to investigate the mechanism underlying stemness acquisition in GBM cells by focusing on 40S ribosomal protein S6 (RPS6). RPS6 was significantly upregulated in high‐grade glioma and localized at perivascular, perinecrotic, and border niches in GBM tissues. siRNA‐mediated RPS6 knock‐down significantly suppressed the characteristics of GSCs, including their tumorsphere potential and GSC marker expression; STAT3 was downregulated in GBM cells. RPS6 overexpression enhanced the tumorsphere potential of GSCs and these effects were attenuated by STAT3 inhibitor (AG490). Moreover, RPS6 expression was significantly correlated with SOX2 expression in different glioma grades. Immunohistochemistry data herein indicated that RPS6 was predominant in GSC niches, concurrent with the data from IVY GAP databases. Furthermore, RPS6 and other ribosomal proteins were upregulated in GSC‐predominant areas in this database. The present results indicate that, in GSC niches, ribosomal proteins play crucial roles in the development and maintenance of GSCs and are clinically associated with chemoradioresistance and GBM recurrence. We evaluated ribosomal protein S6 (RPS6) that has important roles in developing glioblastoma stem‐like cells. RPS6‐positive cells were highly expressed in glioblastoma stem‐like cell dominant areas. Also, we tested the RPS6 regulated stem cell properties of glioblastoma stem‐like cells. These findings are a break‐through in targeting therapy for ribosomal proteins to downregulate stem cell properties in glioblastoma.

Glioblastoma (GBM) involves disruptions in the blood–brain barrier (BBB) and alterations in the immune microenvironment, including the activation of glioma‐associated macrophages (GAMs). Vascular endothelial growth factor inhibitors, commonly used in recurrent GBM treatment, can influence these processes. This study investigates the relationship between BBB disruption and GAM activation, focusing on plasmalemma vesicle‐associated protein (PLVAP), a marker of BBB disruption, and α1‐acid glycoprotein (AGP), an inflammatory protein implicated in tumor progression. PLVAP expression was analyzed by immunohistochemistry (IHC) in human GBM samples to determine correlations with tumor grade, proliferation, and GAM activation. Pre‐ and post‐bevacizumab treatment GBM samples were compared to assess changes in BBB integrity and macrophage activity. AGP's role in GAM activation was studied through in vitro assays and glioma implantation in AGP knockout mice, with assessments of tumor growth and angiogenesis. Results showed elevated PLVAP expression in higher‐grade gliomas, correlating with increased tumor proliferation and GAM activation, particularly around PLVAP‐positive vessels. Bevacizumab treatment reduced PLVAP expression and macrophage activity. AGP localized to regions of BBB disruption, promoting macrophage‐mediated tumor growth in vitro. AGP knockout mice demonstrated reduced angiogenesis and prolonged survival. Spatial analysis revealed increased expression of macrophage‐inducing molecules near PLVAP‐positive vessels. These findings suggest PLVAP as a marker of BBB disruption and glioma malignancy. AGP, associated with BBB leakage, contributes to GAM activation and tumor progression, highlighting its potential as a therapeutic target for GBM. Plasmalemma vesicle‐associated protein (PLVAP) is a marker of BBB disruption and correlates with GBM malignancy and tumor progression. Bevacizumab treatment potentially suppressed protumor activation of macrophages and improve the GBM microenvironment. AGP leakage was shown in BBB disrupted area, and potentially induced protumor activation of macrophages which were associated to tumor growth and angiogenesis.

Primary central nervous system lymphoma (PCNSL) is a rare malignancy confined to the central nervous system (CNS), and majority of PCNSL is pathologically classified as diffuse large B-cell lymphoma (DLBCL). We have now performed whole-exome sequencing for 41 tumor tissues of DLBCL-type PCNSL and paired normal specimens and also RNA-sequencing for 30 tumors, revealing a very high frequency of nonsynonymous somatic mutations in PIM1 (100 %), BTG2 (92.7 %), and MYD88 (85.4 %). Many genes in the NF-κB pathway are concurrently mutated within the same tumors. Further, focal deletion or somatic mutations in the HLA genes are associated with poor prognosis. Copy number amplification and overexpression of genes at chromosome 7q35 were both found to predict short progression-free survival as well. Oncogenic mutations in GRB2 were also detected, the effects of which in cultured cells were attenuated by inhibitors of the downstream kinases MAP2K1 and MAP2K2. Individuals with tumors positive for MYD88 mutations also harbored the same mutations at a low frequency in peripheral blood mononuclear cells, suggesting that MYD88 mutation-positive precancerous cells originate outside of the CNS and develop into lymphoma after additional genetic hits that confer adaptation to the CNS environment.

Objectives To evaluate the image quality of deep learning–based reconstruction (DLR), model-based (MBIR), and hybrid iterative reconstruction (HIR) algorithms for lower-dose (LD) unenhanced head CT and compare it with those of standard-dose (STD) HIR images. Methods This retrospective study included 114 patients who underwent unenhanced head CT using the STD ( n  = 57) or LD ( n  = 57) protocol on a 320-row CT. STD images were reconstructed with HIR; LD images were reconstructed with HIR (LD-HIR), MBIR (LD-MBIR), and DLR (LD-DLR). The image noise, gray and white matter (GM-WM) contrast, and contrast-to-noise ratio (CNR) at the basal ganglia and posterior fossa levels were quantified. The noise magnitude, noise texture, GM-WM contrast, image sharpness, streak artifact, and subjective acceptability were independently scored by three radiologists (1 = worst, 5 = best). The lesion conspicuity of LD-HIR, LD-MBIR, and LD-DLR was ranked through side-by-side assessments (1 = worst, 3 = best). Reconstruction times of three algorithms were measured. Results The effective dose of LD was 25% lower than that of STD. Lower image noise, higher GM-WM contrast, and higher CNR were observed in LD-DLR and LD-MBIR than those in STD (all, p  ≤ 0.035). Compared with STD, the noise texture, image sharpness, and subjective acceptability were inferior for LD-MBIR and superior for LD-DLR (all, p  < 0.001). The lesion conspicuity of LD-DLR (2.9 ± 0.2) was higher than that of HIR (1.2 ± 0.3) and MBIR (1.8 ± 0.4) (all, p  < 0.001). Reconstruction times of HIR, MBIR, and DLR were 11 ± 1, 319 ± 17, and 24 ± 1 s, respectively. Conclusion DLR can enhance the image quality of head CT while preserving low radiation dose level and short reconstruction time. Key Points •  For unenhanced head CT, DLR reduced the image noise and improved the GM-WM contrast and lesion delineation without sacrificing the natural noise texture and image sharpness relative to HIR . •  The subjective and objective image quality of DLR was better than that of HIR even at 25% reduced dose without considerably increasing the image reconstruction times (24 s vs. 11 s) . •  Despite the strong noise reduction and improved GM-WM contrast performance, MBIR degraded the noise texture, sharpness, and subjective acceptance with prolonged reconstruction times relative to HIR, potentially hampering its feasibility .

Purpose The aim of this study is to assess the effect of super-resolution deep learning-based reconstruction (SR-DLR), which uses k-space properties, on image quality of intracranial time-of-flight (TOF) magnetic resonance angiography (MRA) at 3 T. Methods This retrospective study involved 35 patients who underwent intracranial TOF-MRA using a 3-T MRI system with SR-DLR based on k-space properties in October and November 2022. We reconstructed MRA with SR-DLR (matrix = 1008 × 1008) and MRA without SR-DLR (matrix = 336 × 336). We measured the signal-to-noise ratio (SNR), contrast, and contrast-to-noise ratio (CNR) in the basilar artery (BA) and the anterior cerebral artery (ACA) and the sharpness of the posterior cerebral artery (PCA) using the slope of the signal intensity profile curve at the half-peak points. Two radiologists evaluated image noise, artifacts, contrast, sharpness, and overall image quality of the two image types using a 4-point scale. We compared quantitative and qualitative scores between images with and without SR-DLR using the Wilcoxon signed-rank test. Results The SNRs, contrasts, and CNRs were all significantly higher in images with SR-DLR than those without SR-DLR ( p < 0.001). The slope was significantly greater in images with SR-DLR than those without SR-DLR ( p < 0.001). The qualitative scores in MRAs with SR-DLR were all significantly higher than MRAs without SR-DLR ( p < 0.001). Conclusion SR-DLR with k-space properties can offer the benefits of increased spatial resolution without the associated drawbacks of longer scan times and reduced SNR and CNR in intracranial MRA.

Indirect bypass using autologous tissue is effective in Moyamoya disease, especially among pediatric patients. This study aimed to evaluate the effectiveness of indirect bypass using DuraGen (absorbable artificial dura mater composed of collagen matrix), as a substitute for autologous tissue in a rat model of chronic cerebral hypoperfusion. Male Wistar rats were subjected to bilateral internal carotid artery occlusion and divided into three groups: a control group without bypass surgery, a group wherein indirect bypass was performed using the temporalis muscle (encephalo-myo-synangiosis [EMS] group), and a group wherein DuraGen was used (Dura group). The ratio of the number of vascular endothelial cells, detected by antibodies to CD31 and glucose transporter type 1 (Glut-1), on the operative side to that on the non-operative side was measured and compared between the three groups. The ratio of CD31-positive cells was 1.50 ± 0.13 and 1.92 ± 0.29 in the EMS and Dura groups, respectively, and that of Glut-1-positive cells was 1.32 ± 0.10 and 1.53 ± 0.18 in the EMS and Dura groups, respectively. No significant difference was observed in the ratio of vascular endothelial cells on the bypass side between the EMS and Dura groups. Indirect bypass with DuraGen resulted in an increased ratio of vascular endothelial cells, equivalent to that of an indirect bypass with the temporalis muscle in a rat model. Thus, in an actual indirect bypass for patients with Moyamoya disease, the use of DuraGen may produce the same angiogenesis as using autologous tissue.

Purpose The purpose of this study is to evaluate the influence of super-resolution deep learning-based reconstruction (SR-DLR), which utilizes k-space data, on the quality of images and the quantitation of the apparent diffusion coefficient (ADC) for diffusion-weighted images (DWI) in brain magnetic resonance imaging (MRI). Methods A retrospective analysis was performed on 34 patients who had undergone DWI using a 3 T MRI system with SR-DLR reconstruction based on k-space data in August 2022. DWI was reconstructed with SR-DLR (Matrix = 684 × 684) and without SR-DLR (Matrix = 228 × 228). Measurements were made of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) in white matter (WM) and grey matter (GM), and the full width at half maximum (FWHM) of the septum pellucidum. Two radiologists assessed image noise, contrast, artifacts, blur, and the overall quality of three image types using a four-point scale. Quantitative and qualitative scores between images with and without SR-DLR were compared using the Wilcoxon signed-rank test. Results Images with SR-DLR showed significantly higher SNRs and CNRs than those without SR-DLR ( p  < 0.001). No statistically significant variances were found in the apparent diffusion coefficients (ADCs) in WM and GM between images with and without SR-DLR (ADC in WM, p  = 0.945; ADC in GM, p  = 0.235). Moreover, the FWHM without SR-DLR was notably lower compared to that with SR-DLR ( p  < 0.001). Conclusion SR-DLR has the potential to augment the quality of DWI in DL MRI scans without significantly impacting ADC quantitation.

Purpose We aimed to evaluate the effect of deep learning-based reconstruction (DLR) on high-spatial-resolution three-dimensional T2-weighted fast asymmetric spin-echo (HR-3D T2-FASE) imaging in the preoperative evaluation of cerebellopontine angle (CPA) tumors. Methods This study included 13 consecutive patients who underwent preoperative HR-3D T2-FASE imaging using a 3 T MRI scanner. The reconstruction voxel size of HR-3D T2-FASE imaging was 0.23 × 0.23 × 0.5 mm. The contrast-to-noise ratios (CNRs) of the structures were compared between HR-3D T2-FASE images with and without DLR. The observers’ preferences based on four categories on the tumor side on HR-3D T2-FASE images were evaluated. The facial nerve in relation to the tumor on HR-3D T2-FASE images was assessed with reference to intraoperative findings. Results The mean CNR between the tumor and trigeminal nerve and between the cerebrospinal fluid and trigeminal nerve was significantly higher for DLR images than non-DLR-based images (14.3 ± 8.9 vs. 12.0 ± 7.6, and 66.4 ± 12.0 vs. 53.9 ± 8.5, P  < 0.001, respectively). The observer’s preference for the depiction and delineation of the tumor, cranial nerves, vessels, and location relation on DLR HR-3D T2FASE images was superior to that on non-DLR HR-3D T2FASE images in 7 (54%), 6 (46%), 6 (46%), and 6 (46%) of 13 cases, respectively. The facial nerves around the tumor on HR-3D T2-FASE images were visualized accurately in five (38%) cases with DLR and in four (31%) without DLR. Conclusion DLR HR-3D T2-FASE imaging is useful for the preoperative assessment of CPA tumors.