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PurposeCurrently, a range of electromagnetic therapies, including magnetic field therapy, micro-currents therapy, and tumor treating fields, are under investigation for their potential in central nervous system tumor research. Each of these electromagnetic therapies possesses distinct effects and limitations. Our focus is on overcoming these limitations by developing a novel electric field generator. This generator operates by producing alternating induced currents within the tumor area through electromagnetic induction.MethodsFinite element analysis was employed to calculate the distribution of electric fields. Cell viability was assessed using the CCK-8 assay. Tumor volumes and weights served as indicators to evaluate the effectiveness of TTIF. The in-vivo imaging system was utilized to confirm tumor growth in the brains of mice.ResultsTTIF significantly inhibited the proliferation of U87 cells both in vitro and in vivo.ConclusionTTIF significantly inhibited the proliferation of U87 cells both in vitro and in vivo. Consequently, TTIF emerges as a potential treatment option for patients with progressive or metastatic GBM.

Abstract Utrophin (UTRN), known as a tumor suppressor, potentially regulates tumor development and the immune microenvironment. However, its impact on breast cancer’s development and treatment remains unstudied. We conducted a thorough examination of UTRN using both bioinformatic and in vitro experiments in this study. We discovered UTRN expression decreased in breast cancer compared to standard samples. High UTRN expression correlated with better prognosis. Drug sensitivity tests and RT-qPCR assays revealed UTRN’s pivotal role in tamoxifen resistance. Furthermore, the Kruskal–Wallis rank test indicated UTRN’s potential as a valuable diagnostic biomarker for breast cancer and its utility in detecting T stage of breast cancer. Additionally, our results demonstrated UTRN’s close association with immune cells, inhibitors, stimulators, receptors, and chemokines in breast cancer (BRCA). This research provides a novel perspective on UTRN’s role in breast cancer’s prognostic and therapeutic value. Low UTRN expression may contribute to tamoxifen resistance and a poor prognosis. Specifically, UTRN can improve clinical decision-making and raise the diagnosis accuracy of breast cancer.

IntroductionGlioblastoma (GBM) presents significant challenges due to its malignancy and limited treatment options. Precision treatment requires subtyping patients based on prognosis. Disulfidptosis, a novel cell death mechanism, is linked to aberrant glucose metabolism and disulfide stress, particularly in tumors expressing high levels of SLC7A11. The exploration of disulfidptosis may provide a new perspective for precise diagnosis and treatment of glioblastoma.MethodsTranscriptome sequencing was conducted on samples from GBM patients treated at Tiantan Hospital (January 2022 - December 2023). Data from CGGA and TCGA databases were collected. Consensus clustering based on disulfidptosis features categorized GBM patients into two subtypes (DRGclusters). Tumor immune microenvironment, response to immunotherapy, and drug sensitivity were analyzed. An 8-gene disulfidptosis-based subtype predictor was developed using LASSO machine learning algorithm and validated on CGGA dataset.ResultsPatients in DRGcluster A exhibited improved overall survival (OS) compared to DRGcluster B. DRGcluster subtypes showed differences in tumor immune microenvironment and response to immunotherapy. The predictor effectively stratified patients into high and low-risk groups. Significant differences in IC50 values for chemotherapy and targeted therapy were observed between risk groups.DiscussionDisulfidptosis-based classification offers promise as a prognostic predictor for GBM. It provides insights into tumor immune microenvironment and response to therapy. The predictor aids in patient stratification and personalized treatment selection, potentially improving outcomes for GBM patients.

Abstract Gliomas refer to a group of complicated human brain tumors with a low 5‐year survival rate and limited therapeutic options. Extremely low‐frequency pulsed electromagnetic field (ELF‐PEMF) is a specific magnetic field featuring almost no side effects. However, the application of ELF‐PEMF in the treatment of gliomas is rare. This review summarizes five significant underlying mechanisms including calcium ions, autophagy, apoptosis, angiogenesis, and reactive oxygen species, and applications of ELF‐PEMF in glioma treatment from a clinical practice perspective. In addition, the prospects of ELF‐PEMF in combination with conventional therapy for the treatment of gliomas are reviewed. This review benefits any specialists, especially oncologists, interested in this new therapy because it can help treat patients with gliomas properly.

Glioblastoma is the most common and aggressive primary tumor in the central nervous system. There is no standard of care for patients with recurrent GBM. Honokiol is a pleiotropic lignan and has the potential to be a potent and safe anticancer agent in human GBM when it is encapsulated by liposomes. We report an efficient and safe response to three phases of treatment with liposomal honokiol in a patient with recurrent glioblastoma.

Medulloblastoma, a common pediatric malignant tumor, has been recognized to have four molecular subgroups [wingless (WNT), sonic hedgehog (SHH), group 3, group 4], which are defined by the characteristic gene transcriptomic and DNA methylomic profiles, and has distinct clinical features within each subgroup. The tumor immune microenvironment is integral in tumor initiation and progression and might be associated with therapeutic responses. However, to date, the immune infiltrative landscape of medulloblastoma has not yet been elucidated. Thus, we proposed MethylCIBERSORT to estimate the degree of immune cell infiltration and weighted correlation network analysis (WGCNA) to find modules of highly correlated genes. Synthesizing the hub genes in the protein–protein interaction (PPI) network and modules of the co-expression network, we identify three candidate biomarkers [GRB2-associated-binding protein 1 (GAB1), Abelson 1 (ABL1), and CXC motif chemokine receptor type 4 (CXCR4)] via the molecular profiles of medulloblastoma. Given this, we investigated the correlation between these three immune hub genes and immune checkpoint blockade response and the potential of drug prediction further. In addition, this study demonstrated a higher presence of endothelial cells and infiltrating immune cells in Group 3 tumor bulk. The above results will be conducive to better comprehending the immune-related pathogenesis and treatment of medulloblastoma.

Abstract Background Glioma is the most common primary brain tumor, occurring due to the carcinogenesis of glial cells in the brain and spinal cord. Many aspects of the mechanism of its tumorigenesis remain unknown. The relationship between viral infection and glioma is one of the most important research aspects in this field. Currently, there is a lack of systematic reviews and meta-analyses to evaluate the effect of viral infection on the prognosis of glioma patients. The purpose of this study was to evaluate the relationship between viral infection and the prognosis of glioma patients, aimed at evaluating the prognostic value of the detection of viral infection. Methods Through careful and comprehensive retrieval of results from the PubMed, Embase, and Cochrane databases, eligible articles were selected strictly according to the inclusion and exclusion criteria. The regional sources, detection methods, detection indicators, patient survival, and other data from the samples in the papers were extracted, and the integrated analysis was conducted using Stata 15.1. We conducted a subgroup analysis of the relationship between the degree of infection and prognosis in cytomegalovirus (CMV) patients. Results A total of 11 studies were included in the analysis. Among them, 7 studies involved the relationship between CMV infection and the prognosis of patients with glioma, 2 studies involved human papillomavirus (HPV), 2 studies involved human herpesvirus-6 (HHV-6), and one study involved simian virus 40 (SV40), woolly monkey sarcoma virus (WMSV) and human endogenous retrovirus K113 (HERV-K113). In the CMV study, the pooled Hazard ratio (HR) of Overall survival (OS) was 1.024 (CI: 0.698–1.501), with a P value of 0.905. The pooled HR of Progression free survival (PFS) was 1.067 (CI: 0.770–1.478), with a P value of 0.697. The pooled HR value of low-degree infection versus high-degree infection was 1.476 (CI: 0.799–2.727), with a P value of 0.213. In the HPV study, the pooled HR of OS was 1.467 (CI: 0.552–3.901), with a P value of 0.443. Conclusion CMV infection has no significant effect on the prognosis of glioma patients. Using the IEA as the detection index, the degree of CMV infection was found to have a significant impact on the prognosis of glioma patients; it was not found to possess a significant prognostic value after the integration of different indicators. Neither HPV nor HHV-6 infection has a significant effect on the prognosis of glioma patients. SV40 and WMSV infection are associated with poor prognosis in patients with low-grade glioma. Trial Registration This meta-analysis registered in https://www.crd.york.ac.uk/PROSPERO/ , PROSPERO ID: CRD42019127648 .

BackgroundDiagnosing primary central nervous system lymphoma (PCNSL) remains a challenge. MicroRNAs (miRNAs) are promising noninvasive markers for the identification of PCNSL. The present study aims to assess the diagnostic value of miRNAs for PCNSL patients as biomarkers.MethodsWe systematically searched PubMed, Embase, and the Cochrane library from inception to January 31, 2021. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), together with the summary receiver operator characteristic (SROC) curve, and the area under the SROC curve (AUC) value were used to estimate the overall diagnostic performance. We used Q statistic and I2 to test heterogeneity and used subgroup analyses to investigate the source of heterogeneity. The statistical analyses were independently performed by two investigators using Stata 14.0 and Revman 5.3.ResultsIn total, 11 studies from 6 records were included in the current meta-analysis with 281 PCNSL patients and 367 controls. Our statistical analysis demonstrated that the pooled sensitivity, specificity, PLR, NLR, DOR, and AUC were 0.91 (95% CI 0.84–0.95), 0.88 (95% CI 0.84–0.91), 7.48 (95% CI 5.71–9.78), 0.11 (95% CI 0.06–0.19), 70 (95% CI 35–142), and 0.90 (95% CI 0.87–0.92), respectively. The studies had substantial heterogeneity (I2 = 54%, 95% CI 0–100). Two subgroup analyses were conducted based on the type of specimen and miRNAs profiled.ConclusionsThis meta-analysis indicated that miRNAs were suitable as noninvasive diagnostic biomarkers for PCNSL with high accuracy. In addition, both cerebrospinal fluid-based and blood-based miRNAs assays for PCNSL detection were considered reliable for clinical application. MicroRNA-21 assays also seemed to be more accurate in the diagnosis of PCNSL. Good quality studies with large samples should be conducted to verify our results.

PurposeGlioma is a classical type of primary brain tumors that is most common seen in adults, and its high heterogeneity used to be a reference standard for subgroup classification. Glioma has been diagnosed based on histopathology, grade, and molecular markers including IDH mutation, chromosome 1p/19q loss, and H3K27M mutation. This subgroup classification cannot fully meet the current needs of clinicians and researchers. We, therefore, present a new subgroup classification for glioma based on the expression levels of Gβ and Gγ genes to complement studies on glioma and Gβγ subunits, and to support clinicians to assess a patient’s tumor status.MethodsGlioma samples retrieved from the CGGA database and the TCGA database. We clustered the gliomas into different groups by using expression values of Gβ and Gγ genes extracted from RNA sequencing data. The Kaplan–Meier method with a two-sided log-rank test was adopted to compare the OS of the patients between GNB2 group and non-GNB2 group. Univariate Cox regression analysis was referred to in order to investigate the prognostic role of each Gβ and Gγ genes. KEGG and ssGSEA analysis were applied to identify highly activated pathways. The “estimate” package, “GSVA” package, and the online analytical tools CIBERSORTx were employed to evaluate immune cell infiltration in glioma samples.ResultsThree subgroups were identified. Each subgroup had its own specific pathway activation pattern and other biological characteristics. High M2 cell infiltration was observed in the GNB2 subgroup. Different subgroups displayed different sensitivities to chemotherapeutics. GNB2 subgroup predicted poor survival in patients with gliomas, especially in patients with LGG with mutation IDH and non-codeleted 1p19q.ConclusionThe subgroup classification we proposed has great application value. It can be used to select chemotherapeutic drugs and the prognosis of patients with target gliomas. The unique relationships between subgroups and tumor-related pathways are worthy of further investigation to identify therapeutic Gβγ heterodimer targets.