A potassium-chloride co-transporter with altered genome architecture functions as a suppressor in glioma.

Gliomas, the most lethal tumours in brain, have a poor prognosis despite accepting standard treatment. Limited benefits from current therapies can be attributed to genetic, epigenetic and microenvironmental cues that affect cell programming and drive tumour heterogeneity. Through the analysis of Hi-C data, we identified a potassium-chloride co-transporter SLC12A5 associated with disrupted topologically associating domain which was downregulated in tumour tissues. Multiple independent glioma cohorts were included to analyse the characterization of SLC12A5 and found it was significantly associated with pathological features, prognostic value, genomic alterations, transcriptional landscape and drug response. We constructed two SLC12A5 overexpression cell lines to verify the function of SLC12A5 that suppressed tumour cell proliferation and migration in vitro. In addition, SLC12A5 was also positively associated with GABAA receptor activity and negatively associated with pro-tumour immune signatures and immunotherapy response. Collectively, our study provides a comprehensive characterization of SLC12A5 in glioma and supports SLC12A5 as a potential suppressor of disease progression.

A natural compound melatonin enhances the effects of Nimotuzumab via inhibiting EGFR in glioblastoma.

Sleep disorders are prevalent and debilitating symptoms in primary brain tumor patients, notably those receiving radiation therapy. Nevertheless, the relationship between sleep disorders, melatonin - a circadian rhythm regulatory hormone, and gliomas is underexplored. Melatonin exhibits various biological functions, one of them being anti-tumor activity. In the context of gliomas, often overexpressing EGFR, the humanized monoclonal antibody Nimotuzumab targets this marker. Our research discovered that variations in circadian rhythm significantly influence tumor growth in mice through impacting melatonin secretion. Harnessing proteogenomic, we identified that melatonin could inhibit the phosphorylation of EGFR and its downstream effectors, key elements in angiogenesis and tumor progression. Building on structural simulations, we propose that melatonin may amplify Nimotuzumab's anti-glioma efficacy by inhibiting EGFR TK dimerization. This proposition was validated in our in vitro and in vivo studies where melatonin synergistically augmented cytotoxicity and apoptosis in Nimotuzumab-treated glioma cells. Thus, melatonin shows promise as a beneficial addition to Nimotuzumab treatment in glioma patients.

Pan-cancer evaluation of regulated cell death to predict overall survival and immune checkpoint inhibitor response.

Regulated cell death (RCD) plays a pivotal role in various biological processes, including development, tissue homeostasis, and immune response. However, a comprehensive assessment of RCD status and its associated features at the pan-cancer level remains unexplored. Furthermore, despite significant advancements in immune checkpoint inhibitors (ICI), only a fraction of cancer patients currently benefit from treatments. Given the emerging evidence linking RCD and ICI efficacy, we hypothesize that the RCD status could serve as a promising biomarker for predicting the ICI response and overall survival (OS) in patients with malignant tumors. We defined the RCD levels as the RCD score, allowing us to delineate the RCD landscape across 30 cancer types, 29 normal tissues in bulk, and 2,573,921 cells from 82 scRNA-Seq datasets. By leveraging large-scale datasets, we aimed to establish the positive association of RCD with immunity and identify the RCD signature. Utilizing 7 machine-learning algorithms and 18 ICI cohorts, we developed an RCD signature (RCD.Sig) for predicting ICI response. Additionally, we employed 101 combinations of 10 machine-learning algorithms to construct a novel RCD survival-related signature (RCD.Sur.Sig) for predicting OS. Furthermore, we obtained CRISPR data to identify potential therapeutic targets. Our study presents an integrative framework for assessing RCD status and reveals a strong connection between RCD status and ICI effectiveness. Moreover, we establish two clinically applicable signatures and identify promising potential therapeutic targets for patients with tumors.

A designer peptide against the EAG2-Kvß2 potassium channel targets the interaction of cancer cells and neurons to treat glioblastoma.

Glioblastoma (GBM) is an incurable brain cancer that lacks effective therapies. Here we show that EAG2 and Kvß2, which are predominantly expressed by GBM cells at the tumor-brain interface, physically interact to form a potassium channel complex due to a GBM-enriched Kvß2 isoform. In GBM cells, EAG2 localizes at neuron-contacting regions in a Kvß2-dependent manner. Genetic knockdown of the EAG2-Kvß2 complex decreases calcium transients of GBM cells, suppresses tumor growth and invasion and extends the survival of tumor-bearing mice. We engineered a designer peptide to disrupt EAG2-Kvß2 interaction, thereby mitigating tumor growth in patient-derived xenograft and syngeneic mouse models across GBM subtypes without overt toxicity. Neurons upregulate chemoresistant genes in GBM cells in an EAG2-Kvß2-dependent manner. The designer peptide targets neuron-associated GBM cells and possesses robust efficacy in treating temozolomide-resistant GBM. Our findings may lead to the next-generation therapeutic agent to benefit patients with GBM.

Mood swings are causally associated with intracranial aneurysm subarachnoid hemorrhage: A Mendelian randomization study.

BACKGROUND: Mood swings have been observed in patients with intracranial aneurysm (IA), but it is still unknown whether mood swings can affect IA. AIM: To explore the causal association between mood swings or experiencing mood swings and IA through a two-sample Mendelian randomization (MR) study. METHODS: Summary-level statistics of mood swings, experiencing mood swings, IA, aneurysm-associated subarachnoid hemorrhage (aSAH), and non-ruptured IA (uIA) were collected from the genome-wide association study. Two-sample MR and various sensitivity analyses were employed to explore the causal association between mood swings or experiencing mood swings and IA, or aSAH, or uIA. The inverse-variance weighted method was used as the primary method. RESULTS: Genetically determined mood swings (odds ratio [OR] = 5.23, 95% confidence interval (95%CI): 1.65-16.64, p = .005) and experiencing mood swings (OR = 2.50, 95%CI: 1.37-4.57, p = .003) were causally associated with an increased risk of IA. Mood swings (OR = 5.67, 95%CI: 1.40-23.04, p = .015) and experiencing mood swings were causally associated with the risk of aSAH (OR = 2.91, 95%CI: 1.47-5.75, p = .002). Neither mood swings (OR = 1.95, 95%CI: .31-12.29, p = .478) nor experiencing mood swings (OR = 1.20, 95%CI: .48-3.03, p = .693) were associated with uIA. CONCLUSIONS: Mood swings and experiencing mood swings increased the risk of IA and aSAH incidence. These results suggest that alleviating mood swings may reduce IA rupture incidence and aSAH incidence.

Integration of single-cell regulon atlas and multi-omics data for prognostic stratification and personalized treatment prediction in human lung adenocarcinoma.

Transcriptional programs are often dysregulated in cancers. A comprehensive investigation of potential regulons is critical to the understanding of tumorigeneses. We first constructed the regulatory networks from single-cell RNA sequencing data in human lung adenocarcinoma (LUAD). We next introduce LPRI (Lung Cancer Prognostic Regulon Index), a precision oncology framework to identify new biomarkers associated with prognosis by leveraging the single cell regulon atlas and bulk RNA sequencing or microarray datasets. We confirmed that LPRI could be a robust biomarker to guide prognosis stratification across lung adenocarcinoma cohorts. Finally, a multi-omics data analysis to characterize molecular alterations associated with LPRI was performed from The Cancer Genome Atlas (TCGA) dataset. Our study provides a comprehensive chart of regulons in LUAD. Additionally, LPRI will be used to help prognostic prediction and developing personalized treatment for future studies.

Mechanical nanosurgery of chemoresistant glioblastoma using magnetically controlled carbon nanotubes.

Glioblastoma (GBM) is the most common and aggressive primary brain cancer. Despite multimodal treatment including surgery, radiotherapy, and chemotherapy, median patient survival has remained at ~15 months for decades. This situation demands an outside-the-box treatment approach. Using magnetic carbon nanotubes (mCNTs) and precision magnetic field control, we report a mechanical approach to treat chemoresistant GBM. We show that GBM cells internalize mCNTs, the mobilization of which by rotating magnetic field results in cell death. Spatiotemporally controlled mobilization of intratumorally delivered mCNTs suppresses GBM growth in vivo. Functionalization of mCNTs with anti-CD44 antibody, which recognizes GBM cell surface-enriched antigen CD44, increases mCNT recognition of cancer cells, prolongs mCNT enrichment within the tumor, and enhances therapeutic efficacy. Using mouse models of GBM with upfront or therapy-induced resistance to temozolomide, we show that mCNT treatment is effective in treating chemoresistant GBM. Together, we establish mCNT-based mechanical nanosurgery as a treatment option for GBM.

Functional characterization of TSPAN7 as a novel indicator for immunotherapy in glioma.

Glioma is the most common primary malignant tumor of the central nervous system in clinical practice. Most adult diffuse gliomas have poor efficacy after standard treatment, especially glioblastoma. With the in-depth understanding of brain immune microenvironment, immunotherapy as a new treatment has attracted much attention. In this study, through analyzing a large number of glioma cohorts, we reported that TSPAN7, a member of the tetraspanin family, decreased in high-grade gliomas and low expression was associated with poor prognosis in glioma patients. Meanwhile, the expression pattern of TSPAN7 was verified in glioma clinical samples and glioma cell lines by qPCR, Western Blotting and immunofluorescence. In addition, functional enrichment analysis showed that cell proliferation, EMT, angiogenesis, DNA repair and MAPK signaling pathways were activated in the TSPAN7 lower expression subgroup. Lentiviral plasmids were used to overexpress TSPAN7 in U87 and LN229 glioma cell lines to explore the anti-tumor role of TSPAN7 in glioma. Moreover, by analyzing the relationship between TSPAN7 expression and immune cell infiltration in multiple datasets, we found that TSPAN7 was significantly negatively correlated with the immune infiltration of tumor-related macrophages, especially M2-type macrophages. Further analysis of immune checkpoints showed that, the expression level of TSPAN7 was negatively correlated with the expression of PD-1, PD-L1 and CTLA-4. Using an independent anti-PD-1 immunotherapy cohorts of GBM, we demonstrated that TSPAN7 expression may had a synergistic effect with PD-L1 on the response to immunotherapy. Based on the above findings, we speculate that TSPAN7 can serve as a biomarker for prognosis and a potential immunotherapy target in glioma patients.

ESRG is critical to maintain the cell survival and self-renewal/pluripotency of hPSCs by collaborating with MCM2 to suppress p53 pathway.

The mechanisms of self-renewal and pluripotency maintenance of human pluripotent stem cells (hPSCs) have not been fully elucidated, especially for the role of those poorly characterized long noncoding RNAs (lncRNAs). ESRG is a lncRNA highly expressed in hPSCs, and its functional roles are being extensively explored in the field. Here, we identified that the transcription of ESRG can be directly regulated by OCT4, a key self-renewal factor in hPSCs. Knockdown of ESRG induces hPSC differentiation, cell cycle arrest, and apoptosis. ESRG binds to MCM2, a replication-licensing factor, to sustain its steady-state level and nuclear location, safeguarding error-free DNA replication. Further study showed that ESRG knockdown leads to MCM2 abnormalities, resulting in DNA damage and activation of the p53 pathway, ultimately impairs hPSC self-renewal and pluripotency, and induces cell apoptosis. In summary, our study suggests that ESRG, as a novel target of OCT4, plays an essential role in maintaining the cell survival and self-renewal/pluripotency of hPSCs in collaboration with MCM2 to suppress p53 signaling. These findings provide critical insights into the mechanisms underlying the maintenance of self-renewal and pluripotency in hPSCs by lncRNAs.

Transcription factor ZBTB42 is a novel prognostic factor associated with immune cell infiltration in glioma.

Background: ZBTB42 is a transcription factor that belongs to the ZBTB transcript factor family and plays an important role in skeletal muscle development. Dysregulation of ZBTB42 expression can lead to a variety of diseases. However, the function of ZBTB42 in glioma development has not been studied by now. Methods: We analyzed the expression of ZBTB42 in LGG and GBM via the The Cancer Genome Atlas CGA and Chinese Glioma Genome Atlas database. Gene Ontology, KEGG, and GSVA analyses were performed to illustrate ZBTB42-related pathways. ESTIMATE and CIBERSORT were applied to calculate the immune score and immune cell proportion in glioma. One-class logistic regression OCLR algorithm was used to study the stemness of glioma. Multivariate Cox analysis was employed to detect the prognostic value of five ZBTB42-related genes. Results: Our results show that ZBTB42 is highly expressed in glioma and may be a promising prognostic factor for Low Grade Glioma and GBM. In addition, ZBTB42 is related to immune cell infiltration and may play a role in the immune suppression microenvironment. What's more, ZBTB42 is correlated with stem cell markers and positively associated with glioma stemness. Finally, a five genes nomogram based on ZBTB42 was constructed and has an effective prognosis prediction ability. Conclusion: We identify that ZBTB42 is a prognostic biomarker for Low Grade Glioma and GBM and its function is related to the suppressive tumor microenvironment and stemness of glioma.

A neurodevelopmental epigenetic programme mediated by SMARCD3-DAB1-Reelin signalling is hijacked to promote medulloblastoma metastasis.

How abnormal neurodevelopment relates to the tumour aggressiveness of medulloblastoma (MB), the most common type of embryonal tumour, remains elusive. Here we uncover a neurodevelopmental epigenomic programme that is hijacked to induce MB metastatic dissemination. Unsupervised analyses of integrated publicly available datasets with our newly generated data reveal that SMARCD3 (also known as BAF60C) regulates Disabled 1 (DAB1)-mediated Reelin signalling in Purkinje cell migration and MB metastasis by orchestrating cis-regulatory elements at the DAB1 locus. We further identify that a core set of transcription factors, enhancer of zeste homologue 2 (EZH2) and nuclear factor I X (NFIX), coordinates with the cis-regulatory elements at the SMARCD3 locus to form a chromatin hub to control SMARCD3 expression in the developing cerebellum and in metastatic MB. Increased SMARCD3 expression activates Reelin-DAB1-mediated Src kinase signalling, which results in a MB response to Src inhibition. These data deepen our understanding of how neurodevelopmental programming influences disease progression and provide a potential therapeutic option for patients with MB.

Mechanosensitive brain tumor cells construct blood-tumor barrier to mask chemosensitivity.

Major obstacles in brain cancer treatment include the blood-tumor barrier (BTB), which limits the access of most therapeutic agents, and quiescent tumor cells, which resist conventional chemotherapy. Here, we show that Sox2+ tumor cells project cellular processes to ensheathe capillaries in mouse medulloblastoma (MB), a process that depends on the mechanosensitive ion channel Piezo2. MB develops a tissue stiffness gradient as a function of distance to capillaries. Sox2+ tumor cells perceive substrate stiffness to sustain local intracellular calcium, actomyosin tension, and adhesion to promote cellular process growth and cell surface sequestration of ß-catenin. Piezo2 knockout reverses WNT/ß-catenin signaling states between Sox2+ tumor cells and endothelial cells, compromises the BTB, reduces the quiescence of Sox2+ tumor cells, and markedly enhances the MB response to chemotherapy. Our study reveals that mechanosensitive tumor cells construct the BTB to mask tumor chemosensitivity. Targeting Piezo2 addresses the BTB and tumor quiescence properties that underlie treatment failures in brain cancer.

Identification of the novel prognostic biomarker, MLLT11, reveals its relationship with immune checkpoint markers in glioma.

Aim: This study aimed to explore the expression pattern of MLLT11 under different pathological features, evaluate its prognostic value for glioma patients, reveal the relationship between MLLT11 mRNA expression and immune cell infiltration in the tumor microenvironment (TME), and provide more evidence for the molecular diagnosis of glioma and immunotherapy. Methods: Using large-scale bioinformatic approach and RNA sequencing (RNA-seq) data from public databases The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and The Gene Expression Omnibus (GEO)), we investigated the relationship between MLLT11 mRNA levels and pathologic characteristics. The distribution in the different subtypes was observed based on Verhaak bulk and Neftel single-cell classification. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used for bioinformatic analysis. Kaplan-Meier survival analysis and Cox regression analysis were used for survival analysis. Correlation analyses were performed between MLLT11 expression and 22 immune cells and immune checkpoints in the TME. Results: We found that MLLT11 expression is decreased in high-grade glioma tissues; we further verified this result by RT-PCR, Western blotting, and immunohistochemistry using our clinical samples. According to the Verhaak classification, high MLLT11 expression is mostly clustered in pro-neutral (PN) and neutral (NE) subtypes, while in the Neftel classification, MLLT11 mainly clustered in neural progenitor-like (NPC-like) neoplastic cells. Survival analysis revealed that low levels of MLLT11 expression are associated with a poorer prognosis; MLLT11 was identified as an independent prognostic factor in multivariate Cox regression analyses. Functional enrichment analyses of MLLT11 with correlated expression indicated that low MLLT11 expression is associated with the biological process related to the extracellular matrix, and the high expression group is related to the synaptic structure. Correlation analyses suggest that declined MLLT11 expression is associated with increased macrophage infiltration in glioma, especially M2 macrophage, and verified by RT-PCR, Western blotting, and immunohistochemistry using our clinical glioma samples. MLLT11 had a highly negative correlation with immune checkpoint inhibitor (ICI) genes including PDCD1, PD-L1, TIM3(HAVCR2), and PD-L2 (PDCD1LG2). Conclusion: MLLT11 plays a crucial role in the progression of glioma and has the potential to be a new prognostic marker for glioma.

Recurrence- and Malignant Progression-Associated Biomarkers in Low-Grade Gliomas and Their Roles in Immunotherapy.

Despite a generally better prognosis than high-grade glioma (HGG), recurrence and malignant progression are the main causes for the poor prognosis and difficulties in the treatment of low-grade glioma (LGG). It is of great importance to learn about the risk factors and underlying mechanisms of LGG recurrence and progression. In this study, the transcriptome characteristics of four groups, namely, normal brain tissue and recurrent LGG (rLGG), normal brain tissue and secondary glioblastoma (sGBM), primary LGG (pLGG) and rLGG, and pLGG and sGBM, were compared using Chinese Glioma Genome Atlas (CGGA) and Genotype-Tissue Expression Project (GTEx) databases. In this study, 296 downregulated and 396 upregulated differentially expressed genes (DEGs) with high consensus were screened out. Univariate Cox regression analysis of data from The Cancer Genome Atlas (TCGA) yielded 86 prognostically relevant DEGs; a prognostic prediction model based on five key genes (HOXA1, KIF18A, FAM133A, HGF, and MN1) was established using the least absolute shrinkage and selection operator (LASSO) regression dimensionality reduction and multivariate Cox regression analysis. LGG was divided into high- and low-risk groups using this prediction model. Gene Set Enrichment Analysis (GSEA) revealed that signaling pathway differences in the high- and low-risk groups were mainly seen in tumor immune regulation and DNA damage-related cell cycle checkpoints. Furthermore, the infiltration of immune cells in the high- and low-risk groups was analyzed, which indicated a stronger infiltration of immune cells in the high-risk group than that in the low-risk group, suggesting that an immune microenvironment more conducive to tumor growth emerged due to the interaction between tumor and immune cells. The tumor mutational burden and tumor methylation burden in the high- and low-risk groups were also analyzed, which indicated higher gene mutation burden and lower DNA methylation level in the high-risk group, suggesting that with the accumulation of genomic mutations and epigenetic changes, tumor cells continued to evolve and led to the progression of LGG to HGG. Finally, the value of potential therapeutic targets for the five key genes was analyzed, and findings demonstrated that KIF18A was the gene most likely to be a potential therapeutic target. In conclusion, the prediction model based on these five key genes can better identify the high- and low-risk groups of LGG and lay a solid foundation for evaluating the risk of LGG recurrence and malignant progression.

Alterations in 3D chromatin organization contribute to tumorigenesis of EGFR-amplified glioblastoma.

Background: EGFR amplification and/or mutation are found in more than half of the cases with glioblastoma. Yet, the role of chromatin interactions and its regulation of gene expression in EGFR-amplified glioblastoma remains unclear. Methods: In this study, we explored alterations in 3D chromatin organization of EGFR-amplified glioblastoma and its subsequent impact by performing a comparative analysis of Hi-C, RNA-seq, and whole-genome sequencing (WGS) on EGFR-amplified glioblastoma-derived A172 and normal astrocytes (HA1800 cell line). Results: A172 cells showed an elevated chromatin relaxation, and unexpected entanglement of chromosome regions. A genome-wide landscape of switched compartments and differentially expressed genes between HA1800 and A172 cell lines demonstrated that compartment activation reshaped chromatin accessibility and activated tumorigenesis-related genes. Topological associating domain (TAD) analysis revealed that altered TAD domains in A172 also contribute to oncogene activation and tumor repressor deactivation. Interestingly, glioblastoma-derived A172 cells showed a different chromatin loop contact propensity. Genes in tumorigenesis-associated signaling pathways were significantly enriched at the anchor loci of altered chromatin loops. Oncogene activation and tumor repressor deactivation were associated with chromatin loop alteration. Structure variations (SVs) had a dramatic impact on the chromatin conformation of EGFR-amplified glioblastoma-derived tumor cells. Moreover, our results revealed that 7p11.2 duplication activated EGFR expression in EGFR-amplified glioblastoma via neo-TAD formation and novel enhancer-promoter interaction emergence between LINC01446 and EGFR. Conclusions: The disordered 3D genomic map and multi-omics data of EGFR-amplified glioblastoma provide a resource for future interrogation of the relationship between chromatin interactions and transcriptome in tumorigenesis.

Fatty acid oxidation fuels glioblastoma radioresistance with CD47-mediated immune evasion.

Glioblastoma multiforme (GBM) remains the top challenge to radiotherapy with only 25% one-year survival after diagnosis. Here, we reveal that co-enhancement of mitochondrial fatty acid oxidation (FAO) enzymes (CPT1A, CPT2 and ACAD9) and immune checkpoint CD47 is dominant in recurrent GBM patients with poor prognosis. A glycolysis-to-FAO metabolic rewiring is associated with CD47 anti-phagocytosis in radioresistant GBM cells and regrown GBM after radiation in syngeneic mice. Inhibition of FAO by CPT1 inhibitor etomoxir or CRISPR-generated CPT1A-/-, CPT2-/-, ACAD9-/- cells demonstrate that FAO-derived acetyl-CoA upregulates CD47 transcription via NF-κB/RelA acetylation. Blocking FAO impairs tumor growth and reduces CD47 anti-phagocytosis. Etomoxir combined with anti-CD47 antibody synergizes radiation control of regrown tumors with boosted macrophage phagocytosis. These results demonstrate that enhanced fat acid metabolism promotes aggressive growth of GBM with CD47-mediated immune evasion. The FAO-CD47 axis may be targeted to improve GBM control by eliminating the radioresistant phagocytosis-proofing tumor cells in GBM radioimmunotherapy.

Deep Learning Model for Intracranial Hemangiopericytoma and Meningioma Classification.

Background: Intracranial hemangiopericytoma/solitary fibrous tumor (SFT/HPC) is a rare type of neoplasm containing malignancies of infiltration, peritumoral edema, bleeding, or bone destruction. However, SFT/HPC has similar radiological characteristics as meningioma, which had different clinical managements and outcomes. This study aims to discriminate SFT/HPC and meningioma via deep learning approaches based on routine preoperative MRI. Methods: We enrolled 236 patients with histopathological diagnosis of SFT/HPC (n = 144) and meningioma (n = 122) from 2010 to 2020 in Xiangya Hospital. Radiological features were extracted manually, and a radiological diagnostic model was applied for classification. And a deep learning pretrained model ResNet-50 was adapted to train T1-contrast images for predicting tumor class. Deep learning model attention mechanism was visualized by class activation maps. Results: Our study reports that SFT/HPC was found to have more invasion to venous sinus (p = 0.001), more cystic components (p < 0.001), and more heterogeneous enhancement patterns (p < 0.001). Deep learning model achieved a high classification accuracy of 0.889 with receiver-operating characteristic curve area under the curve (AUC) of 0.91 in the validation set. Feature maps showed distinct clustering of SFT/HPC and meningioma in the training and test cohorts, respectively. And the attention of the deep learning model mainly focused on the tumor bulks that represented the solid texture features of both tumors for discrimination.

Immune Infiltration Associated MAN2B1 Is a Novel Prognostic Biomarker for Glioma.

Mannosidase Alpha Class 2B Member 1 (MAN2B1) gene encodes lysosomal alpha-d-mannosidase involved in the ordered degradation of N-linked glycoproteins. Alteration in MAN2B1 has been proved to be accountable for several diseases. However, the relationship between MAN2B1 and glioma malignancy remains unclear. In this study, RNA-seq data from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas datasets were analyzed to explore the correlation between MAN2B1 and clinicopathological features, prognosis, and somatic mutations in gliomas. We found that MAN2B1 was elevated in glioma and was correlated with malignant clinical and molecular features. Upregulated expression of MAN2B1 is prognostic for poor outcomes in glioma patients. Different frequencies of somatic mutations were found in gliomas between high and low MAN2B1 expression. Real-time quantitative polymerase chain reaction, western blot, and immunohistochemistry staining from glioma patient samples and cell lines were used to validate bioinformatic findings. Functional enrichment analysis showed that MAN2B1 was involved in immune and inflammation processes. Moreover, MAN2B1 expression was strongly correlated with M2 macrophages and weakly correlated with M1 macrophages. Further analysis confirmed that MAN2B1 was closely associated with the markers of M2 macrophages and tumor-associated macrophages. Taken together, MAN2B1 is a potential prognostic biomarker in glioma and associates with immune infiltration.

A novel co-targeting strategy of EGFR/SEC61G for multi-modality fluorescence/MR/photoacoustic imaging of glioblastoma.

Surgical resection is often the first choice and cornerstone therapy of glioblastoma; the degree of complete resection, as an important prognostic factor, is directly related to individuals' long-term outcomes. However, current imaging approaches, subjected to its single-function and poor targeting affinity, used to have disappointing performance on preoperative diagnosis and intraoperative positioning. Herein, we have designed a nanoparticle for triple-modality NIF/MR/photoacoustic imaging and brought in a dual-targeting strategy with co-expressed EGFR and SEC61G in glioblastoma. In comparison with the dual-negative nanocarrier, the EGFR/SEC61G biotargeting nanoprobe presented a significantly enhanced contrast and durability in vivo. Furthermore, we have evaluated the safety and biocompatibility using a CCK-8 assay ex vivo, which showed negligible toxicity. Therefore, the dual-target probes hold great potentials for a comprehensive preoperative plan and durable intraoperative navigation in glioblastoma.

Clinical characteristics, surgical management, and prognostic factors for supratentorial hemangioblastoma: A retrospective study.

Background: Supratentorial hemangioblastoma is an extremely rare neoplasm. The aim of this study is to delineate the clinical features among cystic and solid supratentorial hemangioblastoma patients and evaluate the risk factors for progression-free survival (PFS). Methods: We conducted a literature search in PubMed for histopathologically identified supratentorial hemangioblastoma between 1947 and 2021 and extracted and collected the clinical features of patients treated at our own institute. The rate of PFS was determined using Kaplan-Meier analysis. Differences in categorical factors, such as the location of tumor and diagnosis of von Hippel-Lindau disease, were analyzed using the Pearson χ 2 test. A Cox regression analysis was performed to evaluate the association between various variates and survival outcomes. Results: A total of 237 cases of supratentorial hemangioblastoma were identified from 169 studies. A survival analysis found that patients with cystic tumors had a significantly better prognosis than those with solid tumors (log-rank, p = 0.0122). Cox regression analysis suggested that cystic hemangioblastoma (hazard ratio (HR): 0.186, 95% CI: 0.043-0.803, p < 0.05) and gross total resection (GTR) (HR: 0.126, 95% CI: 0.049-0.323, p < 0.001) were significant predictors of longer survival (PFS) for supratentorial hemangioblastoma. Following an analysis of 13 supratentorial hemangioblastoma cases from our institute, we validated that cystic tumor had improved prognosis than solid tumor (log-rank, p = 0.0096) and GTR was superior to subtotal resection (log-rank, p = 0.0029). Conclusions: Cystic hemangioblastoma vs. solid hemangioblastoma may be two tumoral statuses with different clinical features, and a specific treatment strategy should be considered.