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Human cytomegalovirus (HCMV) infection is associated with human glioblastoma, the most common and aggressive primary brain tumor, but the underlying infection mechanism has not been fully demonstrated. Here, we show that EphA2 was upregulated in glioblastoma and correlated with the poor prognosis of the patients. EphA2 silencing inhibits, whereas overexpression promotes HCMV infection, establishing EphA2 as a crucial cell factor for HCMV infection of glioblastoma cells. Mechanistically, EphA2 binds to HCMV gH/gL complex to mediate membrane fusion. Importantly, the HCMV infection was inhibited by the treatment of inhibitor or antibody targeting EphA2 in glioblastoma cells. Furthermore, HCMV infection was also impaired in optimal glioblastoma organoids by EphA2 inhibitor. Taken together, we propose EphA2 as a crucial cell factor for HCMV infection in glioblastoma cells and a potential target for intervention., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Dong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: The aim of this study was to build a convolutional neural network (CNN)-based prediction model of glioblastoma (GBM) molecular subtype diagnosis and prognosis with multimodal features., Methods: In total, 222 GBM patients were included in the training set from Sun Yat-sen University Cancer Center (SYSUCC) and 107 GBM patients were included in the validation set from SYSUCC, Xuanwu Hospital Capital Medical University, and the First Hospital of Jilin University. The multimodal model was trained with MR images (pre- and postcontrast T1-weighted images and T2-weighted images), corresponding MRI impression, and clinical patient information. First, the original images were segmented using the Multimodal Brain Tumor Image Segmentation Benchmark toolkit. Convolutional features were extracted using 3D residual deep neural network (ResNet50) and convolutional 3D (C3D). Radiomic features were extracted using pyradiomics. Report texts were converted to word embedding using word2vec. These three types of features were then integrated to train neural networks. Accuracy, precision, recall, and F1-score were used to evaluate the model performance., Results: The C3D-based model yielded the highest accuracy of 91.11% in the prediction of IDH1 mutation status. Importantly, the addition of semantics improved precision by 11.21% and recall in MGMT promoter methylation status prediction by 14.28%. The areas under the receiver operating characteristic curves of the C3D-based model in the IDH1, ATRX, MGMT, and 1-year prognosis groups were 0.976, 0.953, 0.955, and 0.976, respectively. In external validation, the C3D-based model showed significant improvement in accuracy in the IDH1, ATRX, MGMT, and 1-year prognosis groups, which were 88.30%, 76.67%, 85.71%, and 85.71%, respectively (compared with 3D ResNet50: 83.51%, 66.67%, 82.14%, and 70.79%, respectively)., Conclusions: The authors propose a novel multimodal model integrating C3D, radiomics, and semantics, which had a great performance in predicting IDH1, ATRX, and MGMT molecular subtypes and the 1-year prognosis of GBM.

Foxp3 + regulatory T cells (Treg) play an important part in the glioma immunosuppressive microenvironment. This study analyzed the effect of Foxsp3 on the immune microenvironment and constructed a Foxp3-related immune prognostic signature (IPS)for predicting prognosis in glioblastoma multiforme (GBM). Immunohistochemistry (IHC) staining for Foxp3 was performed in 72 high-grade glioma specimens. RNA-seq data from 152 GBM samples were obtained from The Cancer Genome Atlas database (TCGA) and divided into two groups, Foxp3 High (Foxp3_H) and Foxp3 Low (Foxp3_L), based on Foxp3 expression. We systematically analyzed the influence of Foxp3 on the immune microenvironment. Least Absolute Shrinkage and Selection Operator (LASSO) Cox analysis was conducted for immune-related genes that were differentially expressed between Foxp3_H and Foxp3_L GBM patients. We found a differential expression of Foxp3 in high-grade glioma tissues. The presence of Foxp3 was significantly associated with poor OS. From the four-gene IPS developed, GBM patients were stratified into low-risk and high-risk groups in both the training set and validation sets. Furthermore, we developed a novel nomogram to evaluate the overall survival in GBM patients. This study offers innovative insights into the GBM immune microenvironment and these findings contribute to individualized treatment and improvement in the prognosis for GBM patients.

Background: Cerebrospinal fluid (CSF) has been demonstrated as a better source of circulating tumor DNA (ctDNA) than plasma for brain tumors. However, it is unclear whether whole exome sequencing (WES) is qualified for detection of ctDNA in CSF. The aim of this study was to determine if assessment of ctDNA in CSF by WES is a feasible approach to detect genomic alterations of glioblastoma., Methods: CSFs of ten glioblastoma patients were collected pre-operatively at the Department of Neurosurgery, Sun Yat-sen University Cancer Center. ctDNA in CSF and genome DNA in the resected tumor were extracted and subjected to WES. The identified glioblastoma-associated mutations from ctDNA in CSF and genome DNA in the resected tumor were compared., Results: Due to the ctDNA in CSF was unqualified for exome sequencing for one patient, nine patients were included into the final analysis. More glioblastoma-associated mutations tended to be detected in CSF compared with the corresponding tumor tissue samples (3.56 ± 0.75 vs. 2.22 ± 0.32, P = 0.097), while the statistical significance was limited by the small sample size. The average mutation frequencies were similar in CSF and tumor tissue samples (74.1% ± 6.0% vs. 73.8% ± 6.0%, P = 0.924). The R132H mutation of isocitrate dehydrogenase 1 and the G34V mutation of H3 histone, family 3A (H3F3A) which had been reported in the pathological diagnoses were also detected from ctDNA in CSF by WES. Patients who received temozolomide chemotherapy previously or those whose tumor involved subventricular zone tended to harbor more mutations in their CSF., Conclusion: Assessment of ctDNA in CSF by WES is a feasible approach to detect genomic alterations of glioblastoma, which may provide useful information for the decision of treatment strategy.

We aimed to develop a high-throughput deep DNA sequencing assay of cerebrospinal fluid (CSF) to identify clinically relevant oncogenic mutations that contribute to the development of glioblastoma (GBM) and serve as biomarkers to predict patients' responses to surgery. For this purpose, we recruited five patients diagnosed with highly suspicious GBM according to preoperative magnet resonance imaging. Subsequently, patients were histologically diagnosed with GBM. CSF was obtained through routine lumbar puncture, and plasma from peripheral blood was collected before surgery and 7 days after. Fresh tumor samples were collected using routine surgical procedures. Targeted deep sequencing was used to characterize the genomic landscape and identify mutational profile that differed between pre-surgical and post-surgical samples. Sequence analysis was designed to detect protein-coding exons, exon-intron boundaries, and the untranslated regions of 50 genes associated with cancers of the central nervous system. Circulating tumor DNAs (ctDNAs) were prepared from the CSF and plasma from peripheral blood. For comparison, DNA was isolated from fresh tumor tissues. Non-silent coding variants were detected in CSF and plasma ctDNAs, and the overall minor allele frequency (MAF) of the former corresponded to an earlier disease stage compared with that of plasma when the tumor burden was released (surgical removal). Gene mutation loads of GBMs significantly correlated with overall survival (OS, days) (Pearson correlation = -0.95, P = 0.01). We conclude that CSF ctDNAs better reflected the sequential mutational changes of driver genes compared with those of plasma ctDNAs. Deep sequencing of the CSF of patients with GBM may therefore serve as an alternative clinical assay to improve patients' outcomes., (Copyright © 2019 Elsevier Ltd. All rights reserved.)