CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2008-2012

Liposomes as versatile agents for the management of traumatic and nontraumatic central nervous system disorders: drug stability, targeting efficiency, and safety

Various nanoparticle-based drug delivery systems for the treatment of neurological disorders have been widely studied. However, their inability to cross the blood-brain barrier hampers the clinical translation of these therapeutic strategies. Liposomes are nanoparticles composed of lipid bilayers, which can effectively encapsulate drugs and improve drug delivery across the blood-brain barrier and into brain tissue through their targeting and permeability. Therefore, they can potentially treat traumatic and nontraumatic central nervous system diseases. In this review, we outlined the common properties and preparation methods of liposomes, including thin-film hydration, reverse-phase evaporation, solvent injection techniques, detergent removal methods, and microfluidics techniques. Afterwards, we comprehensively discussed the current applications of liposomes in central nervous system diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, traumatic brain injury, spinal cord injury, and brain tumors. Most studies related to liposomes are still in the laboratory stage and have not yet entered clinical trials. Additionally, their application as drug delivery systems in clinical practice faces challenges such as drug stability, targeting efficiency, and safety. Therefore, we proposed development strategies related to liposomes to further promote their development in neurological disease research.

The potential of mesenchymal stem cell coexpressing cytosine deaminase and secretory IL18-FC chimeric cytokine in suppressing glioblastoma recurrence

Glioblastoma multiforme (GBM) patients have a high recurrence rate of 90%, and the 5-year survival rate is only about 5%. Cytosine deaminase (CDA)/5-fluorocytosine (5-FC) gene therapy is a promising glioma treatment as 5-FC can cross the blood-brain barrier (BBB), while 5-fluorouracil (5-FU) cannot. Furthermore, 5-FU can assist reversing the immunological status of cold solid tumors. This study developed mesenchymal stem cells (MSCs) co-expressing yeast CDA and the secretory IL18-FC superkine to prevent recurrent tumor progression by simultaneously exerting cytotoxic effects and enhancing immune responses. IL18 was fused with Igk and IgG2a FC domains to enhance its secretion and serum half-life. The study confirmed the expression and activity of the CDA enzyme, as well as the expression, secretion, and activity of secretory IL18 and IL18-FC superkine, which were expressed by lentiviruses transduced-MSCs. In the transwell tumor-tropism assay, it was observed that the genetically modified MSCs retained their selective tumor-tropism ability following transduction. CDA-expressing MSCs, in the presence of 5-FC (200 µg/ml), induced cell cycle arrest and apoptosis in glioma cells through bystander effects in an indirect transwell co-culture system. They reduced the viability of the direct co-culture system when they constituted only 12.5 % of the cell population. The effectiveness of engineered MSCs in suppressing tumor progression was assessed by intracerebral administration of a lethal dose of GL261 cells combined in a ratio of 1:1 with MSCs expressing CDA, or CDA and sIL18, or CDA and sIL18-FC, into C57BL/6 mice. PET scan showed no conspicuous tumor mass in the MSC-CDA-sIL18-FC group that received 5-FC treatment. The pathological analysis showed that tumor progression suppressed in this group until 20th day after cell inoculation. Cytokine assessment showed that both interferon-gamma (IFN-γ) and interleukin-4 (IL-4) increased in the serum of MSC-CDA-sIL18 and MSC-CDA-sIL18-FC, treated with normal saline (NS) compared to those of the control group. The MSC-CDA-sIL18-FC group that received 5-FC treatment showed reduced serum levels of IL-6 and a considerably improved survival rate compared to the control group. Therefore, MSCs co-expressing yeast CDA and secretory IL18-FC, with tumor tropism capability, may serve as a supplementary approach to standard GBM treatment to effectively inhibit tumor progression and prevent recurrence.

Long chain capsaicin analogues synthetized by CALB-CLEAs show cytotoxicity on glioblastoma cell lines

Glioblastoma is one of the most lethal tumors, displaying striking cellular heterogeneity and drug resistance. The prognosis of patients suffering from glioblastoma after 5 years is only 5%. In the present work, capsaicin analogues bearing modifications on the acyl chain with long-chain fatty acids showed promising anti-tumoral activity by its cytotoxicity on U-87 and U-138 glioblastoma multiforme cells. The capsaicin analogues were enzymatically synthetized with cross-linked enzyme aggregates of lipase B from Candida antarctica (CALB). The catalytic performance of recombinant CALB-CLEAs was compared to their immobilized form on a hydrophobic support. After 72 h of reaction, the synthesis of capsaicin analogues from linoleic acid, docosahexaenoic acid, and punicic acid achieved a maximum conversion of 69.7, 8.3 and 30.3% with CALB-CLEAs, respectively. Similar values were obtained with commercial CALB, with conversion yields of 58.3, 24.2 and 22% for capsaicin analogues from linoleic acid, DHA and punicic acid, respectively. Olvanil and dohevanil had a significant cytotoxic effect on both U-87 and U-138 glioblastoma cells. Irrespective of the immobilization form, CALB is an efficient biocatalyst for the synthesis of anti-tumoral capsaicin derivatives. KEY POINTS: • This is the first report concerning the enzymatic synthesis of capsaicin analogues from docosahexaenoic acid and punicic acid with CALB-CLEAs. • The viability U-87 and U-138 glioblastoma cells was significantly affected after incubation with olvanil and dohevanil. • Capsaicin analogues from fatty acids obtained by CALB-CLEAs are promising candidates for therapeutic use as cytotoxic agents in glioblastoma cancer cells.

Multifaceted bioactivity of marine fungal derived secondary metabolite, xyloketal B -a review

Background

A growing number of findings have focused on the distinctive physiochemical characteristics that marine microorganisms have acquired as a result of their adaptation to the challenging conditions inherent in the marine environment. It has been established that the marine environment is a very rich source of bioactive substances with a variety of biological effects and structural diversity. A major discovery was the extraction of xyloketals from Xylaria sp. Numerous thorough studies have subsequently been carried out to determine the medicinal potential of these bioactive components. Xyloketals are thought to be a very promising and significant class of naturally occurring substances with a wide range of potent biological activities, such as radical scavenging, suppression of cell proliferation, reduction of neonatal hypoxic-ischemic brain injury, antioxidant activity, inhibition of acetylcholine esterase, inhibition of L-calcium channels, and others. Xyloketal B is one of the most potent molecules with significant therapeutic properties among the numerous variants discovered.

Conclusion

This review summarizes the structural characterization of all naturally occurring xyloketal compounds, especially the B derivative with an emphasis on their bioactivity and provides an outline of how xyloketals operate in diverse disease scenarios.

BMP4 and Temozolomide Synergize in the Majority of Patient-Derived Glioblastoma Cultures

One of the main causes of poor prognoses in patient with glioblastoma (GBM) is drug resistance to current standard treatment, which includes chemoradiation and adjuvant temozolomide (TMZ). In addition, the concept of cancer stem cells provides new insights into therapy resistance and management also in GBM and glioblastoma stem cell-like cells (GSCs), which might contribute to therapy resistance. Bone morphogenetic protein-4 (BMP4) stimulates astroglial differentiation of GSCs and thereby reduces their self-renewal capacity. Exposure of GSCs to BMP4 may also sensitize these cells to TMZ. A recent phase I trial has shown that local delivery of BMP4 is safe, but a large variation in survival is seen in these treated patients and in features of their cultured tumors. We wanted to combine TMZ and BMP4 (TMZ + BMP4) therapy and assess the inter-tumoral variability in response to TMZ + BMP4 in patient-derived GBM cultures. A phase II trial could then benefit a larger group of patients than those treated with BMP4 only. We first show that simultaneous treatment with TMZ + BMP4 is more effective than sequential treatment. Second, when applying our optimized treatment protocol, 70% of a total of 20 GBM cultures displayed TMZ + BMP4 synergy. This combination induces cellular apoptosis and does not inhibit cell proliferation. Comparative bulk RNA-sequencing indicates that treatment with TMZ + BMP4 eventually results in decreased MAPK signaling, in line with previous evidence that increased MAPK signaling is associated with resistance to TMZ. Based on these results, we advocate further clinical trial research to test patient benefit and validate pathophysiological hypothesis.

From promise to progress: the dynamic landscape of glioblastoma immunotherapy

Glioblastoma multiforme (GBM) is the most common CNS cancer, it has dismal survival rates despite several effective mediators: intensified cytotoxic therapy, chimeric antigen receptor (CAR)-T cell therapy, viral therapy, adoptive cell therapy, immune checkpoint blockade therapy, radiation therapy and vaccine therapy. This review examines the basic concepts underlying immune targeting and examines products such as checkpoint blockade drugs, CAR-T cells, oncolytic viruses, combinatory multimodal immunotherapy and cancer vaccines. New approaches to overcoming current constraints and challenges in GBM therapy are discussed, based on recent studies into these tactics, findings from ongoing clinical trials, as well as previous trial results.

Anatomical and subcortical invasiveness in diffuse low-grade astrocytomas differ between IDH status and provide prognostic information

Background

Diffuse astrocytomas preferentially infiltrate eloquent areas affecting the outcome. A preoperative understanding of isocitrate dehydrogenase (IDH) status may offer opportunities for specific targeted therapies impacting treatment management. The aim of this study was to analyze clinical, topographical, radiological in WHO 2 astrocytomas with different IDH status and the long-term patient's outcome.

Methods

A series of confirmed WHO 2 astrocytoma patients (between 2005 and 2015) were retrospectively analyzed. MRI sequences (FLAIR) were used for tumor volume segmentation and to create a frequency map of their locations into the Montreal Neurological Institute (MNI) space. The Brain-Grid (BG) system (standardized radiological tool of intersected lines according to anatomical landmarks) was used as an overlay for infiltration analysis of each tumor. Long-term follow-up was used to perform a survival analysis.

Results

Forty patients with confirmed IDH status (26 IDH-mutant, IDHm/14 IDH-wild type, IDHwt) according to WHO 2021 classification were included with a mean follow-up of 7.8 years. IDHm astrocytomas displayed a lower number of BG-voxels (P < 0.05) and were preferentially located in the anterior insular region. IDHwt group displayed a posterior insular and peritrigonal location. IDHwt group displayed a shorter OS compared with IDHm (P < 0.05), with the infiltration of 7 or more BG-voxels as an independent factor predicting a shorter OS.

Conclusions

IDHm and IDHwt astrocytomas differed in preferential location, number of BG-voxels and OS at long follow-up time. The number of BG-voxels affected the OS in IDHwt was possibly reflecting higher tumor invasiveness. We encourage the systematic use of alternative observational tools, such as gradient maps and the Brain-Grid analysis, to better detect differences of tumor invasiveness in diffuse low-grade gliomas subtypes.

National Trends and Factors Associated with Voluntary Refusal of Glioblastoma Treatment: A Retrospective Review of the National Cancer Database

OBJECTIVE

Adherence to combinatorial treatments are important predictors of improved long-term outcomes for patients with glioblastoma (GB); however, factors associated with refusal of surgery, chemotherapy, or radiotherapy (RT) by patients with GB have not been studied.

METHODS

The National Cancer Database was queried from 2004 to 2018 to identify patients with a primary diagnosis of GB who underwent surgical resection alone or followed by either RT or chemotherapy. Adult patients who voluntarily rejected a physician's recommendations for 1 or more treatment were selected. Multivariable regression was used to identify factors associated with rejection of surgical resection, chemotherapy, and RT. Patients receiving treatment were 3:1 propensity score matched to those rejecting treatment and median overall survival (OS) was compared.

RESULTS

58,788 patients were included in the analysis. Factors associated with voluntary refusal of GB treatment included: old age, nonprivate insurance, female sex, Black race, comorbidities, treatment at a nonacademic facility, and living 55+ miles away from a treatment facility (P < 0.05). On propensity matched analysis, refusal of surgery conferred a 4 month decrease in OS (P < 0.001), RT an 8 month decrease in OS (P < 0.001), and chemotherapy a 7 month decrease in OS (P < 0.001).

CONCLUSIONS

In patients with GB, age, sex, race, nonprivate insurance, medical comorbidities, distance from treatment facility, and geographic location were associated with refusal of surgery, postsurgical RT, and chemotherapy. In addition, treatment refusal had a significant impact on OS length.

Current advance of nanotechnology in diagnosis and treatment for malignant tumors

Cancer remains a significant risk to human health. Nanomedicine is a new multidisciplinary field that is garnering a lot of interest and investigation. Nanomedicine shows great potential for cancer diagnosis and treatment. Specifically engineered nanoparticles can be employed as contrast agents in cancer diagnostics to enable high sensitivity and high-resolution tumor detection by imaging examinations. Novel approaches for tumor labeling and detection are also made possible by the use of nanoprobes and nanobiosensors. The achievement of targeted medication delivery in cancer therapy can be accomplished through the rational design and manufacture of nanodrug carriers. Nanoparticles have the capability to effectively transport medications or gene fragments to tumor tissues via passive or active targeting processes, thus enhancing treatment outcomes while minimizing harm to healthy tissues. Simultaneously, nanoparticles can be employed in the context of radiation sensitization and photothermal therapy to enhance the therapeutic efficacy of malignant tumors. This review presents a literature overview and summary of how nanotechnology is used in the diagnosis and treatment of malignant tumors. According to oncological diseases originating from different systems of the body and combining the pathophysiological features of cancers at different sites, we review the most recent developments in nanotechnology applications. Finally, we briefly discuss the prospects and challenges of nanotechnology in cancer.

Looking backward toward the future: A bibliometric analysis of the last 40 years of meningioma global outcomes

This study is the first comprehensive bibliometric analysis about meningioma to date. The aim of this study is to identify the most influential publications in this field through citation and co-citation analysis, to examine international collaborations, to identify the conceptual framework of the subject and emerging trending topics through keyword analysis, and to identify the most productive countries, authors and journals. 9619 articles on meningioma published between 1980 and 2023 were downloaded from the Web of Science (WoS) database and statistically analyzed. In this study, various bibliometric techniques were utilized, including trend keyword analysis, thematic evolution analysis, factor analysis, conceptual structure analysis, citation and co-citation analyses. Bibliometric network visualization maps were created to identify trend topics, citation analysis and cross-country collaborations. The Exponential Smoothing estimator was used to predict article productivity in the coming years. The first 3 countries that contributed the most to the literature were respectively; USA (2664, 27.7%), Japan (972, 10.1%), Germany (943, 9.8%). The first three most productive journals were respectively; Journal of Neurosurgery (number of article = 496), World Neurosurgery (399), Acta Neurochirurgica (378). The most productive author was Mcdermott MW (number of article = 88) and the most active institution was the University of California System (number of article = 470). In addition to high-grade meningiomas, the most studied topics from past to present have been magnetic resonance imaging, recurrence, radiation therapy, and skull base. As a result of the analyses to determine trend topics, the subjects studied in recent years were diagnostic and imaging methods, surgical and treatment methods, prognosis and survival, epidemiology and quality of life, and with the advancement of technology, machine learning and prediction models. Scientific collaboration was seen primarily in articles from western countries, especially the USA, European countries, and Canada. However, there was also a not insignificant effect in developing countries such as China, India, and Turkey.

Dual targeting of histone deacetylases and MYC as potential treatment strategy for H3-K27M pediatric gliomas

Diffuse midline gliomas (DMGs) are aggressive and fatal pediatric tumors of the central nervous system that are highly resistant to treatments. Lysine to methionine substitution of residue 27 on histone H3 (H3-K27M) is a driver mutation in DMGs, reshaping the epigenetic landscape of these cells to promote tumorigenesis. H3-K27M gliomas are characterized by deregulation of histone acetylation and methylation pathways, as well as the oncogenic MYC pathway. In search of effective treatment, we examined the therapeutic potential of dual targeting of histone deacetylases (HDACs) and MYC in these tumors. Treatment of H3-K27M patient-derived cells with Sulfopin, an inhibitor shown to block MYC-driven tumors in vivo, in combination with the HDAC inhibitor Vorinostat, resulted in substantial decrease in cell viability. Moreover, transcriptome and epigenome profiling revealed synergistic effect of this drug combination in downregulation of prominent oncogenic pathways such as mTOR. Finally, in vivo studies of patient-derived orthotopic xenograft models showed significant tumor growth reduction in mice treated with the drug combination. These results highlight the combined treatment with PIN1 and HDAC inhibitors as a promising therapeutic approach for these aggressive tumors.

Machine-Learning and Radiomics-Based Preoperative Prediction of Ki-67 Expression in Glioma Using MRI Data

BACKGROUND

Gliomas are the most common primary brain tumours and constitute approximately half of all malignant glioblastomas. Unfortunately, patients diagnosed with malignant glioblastomas typically survive for less than a year. In light of this circumstance, genotyping is an effective means of categorising gliomas. The Ki67 proliferation index, a widely used marker of cellular proliferation in clinical contexts, has demonstrated potential for predicting tumour classification and prognosis. In particular, magnetic resonance imaging (MRI) plays a vital role in the diagnosis of brain tumours. Using MRI to extract glioma-related features and construct a machine learning model offers a viable avenue to classify and predict the level of Ki67 expression.

METHODS

This study retrospectively collected MRI data and postoperative immunohistochemical results from 613 glioma patients from the First Affliated Hospital of Nanjing Medical University. Subsequently, we performed registration and skull stripping on the four MRI modalities: T1-weighted (T1), T2-weighted (T2), T1-weighted with contrast enhancement (T1CE), and Fluid Attenuated Inversion Recovery (FLAIR). Each modality's segmentation yielded three distinct tumour regions. Following segmentation, a comprehensive set of features encompassing texture, first-order, and shape attributes were extracted from these delineated regions. Feature selection was conducted using the least absolute shrinkage and selection operator (LASSO) algorithm with subsequent sorting to identify the most important features. These selected features were further analysed using correlation analysis to finalise the selection for machine learning model development. Eight models: logistic regression (LR), naive bayes, decision tree, gradient boosting tree, and support vector classification (SVM), random forest (RF), XGBoost, and LightGBM were used to objectively classify Ki67 expression.

RESULTS

In total, 613 patients were enroled in the study, and 24,455 radiomic features were extracted from each patient's MRI. These features were eventually reduced to 36 after LASSO screening, RF importance ranking, and correlation analysis. Among all the tested machine learning models, LR and linear SVM exhibited superior performance. LR achieved the highest area under the curve score of 0.912 ± 0.036, while linear SVM obtained the top accuracy with a score of 0.884 ± 0.031.

CONCLUSION

This study introduced a novel approach for classifying Ki67 expression levels using MRI, which has been proven to be highly effective. With the LR model at its core, our method demonstrated its potential in signalling a promising avenue for future research. This innovative approach of predicting Ki67 expression based on MRI features not only enhances our understanding of cell activity but also represents a significant leap forward in brain glioma research. This underscores the potential of integrating machine learning with medical imaging to aid in the diagnosis and prognosis of complex diseases.

ZBTB20 suppresses tumor growth in glioblastoma through activating the TET1/FAS/caspase‑3 pathway

Zinc finger and BTB domain containing 20 (ZBTB20) is a key transcription repressor that regulates multiple physiological and pathophysiological processes. Thus far, the role of ZBTB20 in glioblastoma (GBM), a World Health Organization grade IV glioma, remains unclear. In the present study, the expression profile data of ZBTB20 in GBM tissues from public databases was analyzed. It was found that ZBTB20 expression in GBM tissues was significantly lower than that measured in lower grade glioma tissues. Furthermore, patients with GBM with lower ZBTB20 expression were associated with a shorter overall survival time. Gain- and loss-of-function experiments in GBM cells were also performed. The results demonstrated that ZBTB20 overexpression decreased GBM cell proliferation, while ZBTB20 knockdown significantly enhanced it. Cell cycle analysis showed the ZBTB20 overexpression may have inhibited proliferation through cell cycle arrest at the G2/M phase, while ZBTB20 knockdown increased the percentages of cells in both the S phase and G2/M phase. Ten-eleven translocation 1 (TET1) is an important tumor suppressor involved in the formation of various types of tumor, and it was upregulated in ZBTB20-overexpressing GBM cells. It was further demonstrated that ZBTB20 activated the TET1/FAS/caspase-3 pathway. The results of the present study therefore indicated the potential role of ZBTB20 as a tumor suppressor and therapeutic target for GBM.

Development of Predicting Nomograms for Diffuse Astrocytoma and Anaplastic Astrocytoma: A Study Based on the Surveillance, Epidemiology, and End Results Database

BACKGROUND

Astrocytoma is a type of adult-type diffuse gliomas that includes diffuse astrocytoma (DA) and anaplastic astrocytoma (AA). However, comprehensive investigations into the risk assessment and prognosis of DA and AA using population-based studies remain noticeably scarce.

METHODS

In this study, we developed 2 predictive nomograms to evaluate the susceptibility and prognosis associated with DA and AA. The study cohort comprised 3837 individuals diagnosed with DA or AA between 2010 and 2019 selected from the Surveillance, Epidemiology, and End Results (SEER) database. Independent predictors were identified and used to construct the nomograms for overall death and cancer-specific death rates. The performance of the models was assessed using C-index, calibration curves, and receiver operating characteristic curve, and the clinical applicability was evaluated using decision curve analysis.

RESULTS

The receiver operating characteristic curves in this study show excellent clinical applicability and predictive power. Notably, the area under the curves of the training and verification queues was higher than 0.80, thereby cementing the models' precision. Additionally, the calibration plots demonstrate that the anticipated mortality rates strikingly match the measured values. This alignment of figures is sustained in the validation cohort. Furthermore, the decision curve analysis corroborates the models' translational potential, reinforcing their relevance within real-world clinical settings.

CONCLUSIONS

The presented nomograms have not only exhibited good predictive performance but also showcased pragmatic clinical utility in prognosticating patient outcomes. Significantly, this will undoubtedly serve as a valuable asset for oncologists, facilitating informed treatment decisions and meticulous follow-up planning.

Circulating Liquid Biopsy Biomarkers in Glioblastoma: Advances and Challenges

Gliomas, particularly glioblastoma (GBM), represent the most prevalent and aggressive tumors of the central nervous system (CNS). Despite recent treatment advancements, patient survival rates remain low. The diagnosis of GBM traditionally relies on neuroimaging methods such as magnetic resonance imaging (MRI) or computed tomography (CT) scans and postoperative confirmation via histopathological and molecular analysis. Imaging techniques struggle to differentiate between tumor progression and treatment-related changes, leading to potential misinterpretation and treatment delays. Similarly, tissue biopsies, while informative, are invasive and not suitable for monitoring ongoing treatments. These challenges have led to the emergence of liquid biopsy, particularly through blood samples, as a promising alternative for GBM diagnosis and monitoring. Presently, blood and cerebrospinal fluid (CSF) sampling offers a minimally invasive means of obtaining tumor-related information to guide therapy. The idea that blood or any biofluid tests can be used to screen many cancer types has huge potential. Tumors release various components into the bloodstream or other biofluids, including cell-free nucleic acids such as microRNAs (miRNAs), circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), proteins, extracellular vesicles (EVs) or exosomes, metabolites, and other factors. These factors have been shown to cross the blood-brain barrier (BBB), presenting an opportunity for the minimally invasive monitoring of GBM as well as for the real-time assessment of distinct genetic, epigenetic, transcriptomic, proteomic, and metabolomic changes associated with brain tumors. Despite their potential, the clinical utility of liquid biopsy-based circulating biomarkers is somewhat constrained by limitations such as the absence of standardized methodologies for blood or CSF collection, analyte extraction, analysis methods, and small cohort sizes. Additionally, tissue biopsies offer more precise insights into tumor morphology and the microenvironment. Therefore, the objective of a liquid biopsy should be to complement and enhance the diagnostic accuracy and monitoring of GBM patients by providing additional information alongside traditional tissue biopsies. Moreover, utilizing a combination of diverse biomarker types may enhance clinical effectiveness compared to solely relying on one biomarker category, potentially improving diagnostic sensitivity and specificity and addressing some of the existing limitations associated with liquid biomarkers for GBM. This review presents an overview of the latest research on circulating biomarkers found in GBM blood or CSF samples, discusses their potential as diagnostic, predictive, and prognostic indicators, and discusses associated challenges and future perspectives.

Endothelial cell ferroptosis influences IDH wild-type glioblastoma growth in recurrent glioblastoma multiforme patients

Glioblastomas are known for their poor clinical prognosis, with recurrent tumors often exhibiting greater invasiveness and faster growth rates compared to primary tumors. To understand the intratumoral changes driving this phenomenon, we employed single-cell sequencing to analyze the differences between two pairs of primary and recurrent glioblastomas. Our findings revealed an upregulation of ferroptosis in endothelial cells within recurrent tumors, identified by the significant overexpression of the NOX4 gene. Further analysis indicated that knocking down NOX4 in endothelial cells reduced the activity of the ferroptosis pathway. Utilizing conditioned media from endothelial cells with lower ferroptosis activity, we observed a decrease in the growth rate of glioblastoma cells. These results highlighted the complex role of ferroptosis within tumors and suggested that targeting ferroptosis in the treatment of glioblastomas requires careful consideration of its effects on endothelial cells, as it may otherwise produce counterproductive outcomes.

The efficacy and adverse events of bevacizumab combined with temozolomide in the treatment of glioma: a systemic review and meta-analysis of randomized controlled trials

Objectives

To assess the efficacy and adverse events of bevacizumab (BEV) combined with temozolomide (TMZ) in the treatment of glioma.

Materials and methods

Randomized controlled trials (RCT) involving BEV combined with TMZ in the treatment of glioma were searched using PubMed, Embase and Cochrane library, and a comprehensive meta-analysis was conducted. The primary outcomes were overall survival time (OS) and progression-free survival time (PFS), and the secondary outcome was adverse events. Researchers conducted literature screening, data extraction and quality assessment according to inclusion and exclusion criteria. RevMan 5.3 software was used for meta-analysis.

Results

A total of 8 prospective RCTs of 3,039 cases were included in the meta-analysis. Meta-analysis showed that compared with TMZ alone, BEV combined with TMZ could significantly improve PFS, OS and complete remission rate (CR). A total of 6 studies reported related adverse events, mainly including thrombocytopenia, neutropenia, leukopenia, anemia and fatigue. Combination therapy may have more adverse events but no serious consequences.

Conclusion

The combination of BEV and TMZ had a better therapeutic effect on glioblastoma, significantly prolonged the survival time of patients and improved the quality of life. However, some patients are afflicted with the adverse events of combination therapy, and subsequent studies should continue to conduct larger, multi-center RCTs to confirm the findings and explore in depth how to minimize and manage adverse events effectively.

Nomogram of magnetic resonance imaging (MRI) histogram analysis to predict telomerase reverse transcriptase promoter mutation status in glioblastoma

Background

Telomerase reverse transcriptase promoter (pTERT) status is a strong biomarker to diagnose and predict the prognosis of glioblastoma (GBM). In this study, we explored the predictive value of preoperative magnetic resonance imaging (MRI) histogram analysis in the form of nomogram for evaluating pTERT mutation status in GBM.

Methods

The clinical and imaging data of 181 patients with GBM at our hospital between November 2018 and April 2023 were retrospectively assessed. We used the molecular sequencing results to classify the datasets into pTERT mutations (C228T and C250T) and pTERT-wildtype groups. FireVoxel software was used to extract preoperative T1-weighted contrast-enhanced (T1C) histogram parameters of GBM patients. The T1C histogram parameters were compared between groups. Univariate and multivariate logistic regression analyses were used to construct the nomogram, and the predictive efficacy of model was evaluated using calibration and decision curves. Receiver operating characteristic curve was used to assess model performance.

Results

Patient age and percentage of unenhanced tumor area showed statistically significant differences between the pTERT mutation and pTERT-wildtype groups (P<0.001). Among the T1C histogram features, the maximum, standard deviation (SD), variance, coefficient of variation (CV), skewness, 5th, 10th, 25th, 95th and 99th percentiles were statistically significantly different between groups (P=0.000-0.040). Multivariate logistic regression analysis showed that age, percentage of unenhanced tumor area, SD and CV were independent risk factors for predicting pTERT mutation status in GBM patients. The logistic regression model based on these four features showed a better sample predictive performance, and the area under the curve (AUC) [95% confidence interval (CI)], accuracy, sensitivity, specificity were 0.842 (0.767-0.917), 0.796, 0.820, and 0.729, respectively. There were no significant differences in the T1C histogram parameters between the C228T and C250T groups (P=0.055-0.854).

Conclusions

T1C histogram parameters can be used to evaluate pTERT mutations status in GBM. A nomogram based on conventional MRI features and T1C histogram parameters is a reliable tool for the pTERT mutation status, allowing for non-invasive radiological prediction before surgery.

Prediction of O(6)-methylguanine-DNA methyltransferase promoter methylation status in IDH-wildtype glioblastoma using MRI histogram analysis

To evaluate the utility of magnetic resonance imaging (MRI) histogram parameters in predicting O(6)-methylguanine-DNA methyltransferase promoter (pMGMT) methylation status in IDH-wildtype glioblastoma (GBM). From November 2021 to July 2023, forty-six IDH-wildtype GBM patients with known pMGMT methylation status (25 unmethylated and 21 methylated) were enrolled in this retrospective study. Conventional MRI signs (including location, across the midline, margin, necrosis/cystic changes, hemorrhage, and enhancement pattern) were assessed and recorded. Histogram parameters were extracted and calculated by Firevoxel software based on contrast-enhanced T1-weighted images (CET1). Differences and diagnostic performance of conventional MRI signs and histogram parameters between the pMGMT-unmethylated and pMGMT-methylated groups were analyzed and compared. No differences were observed in the conventional MRI signs between pMGMT-unmethylated and pMGMT-methylated groups (all p > 0.05). Compared with the pMGMT-methylated group, pMGMT-unmethylated showed a higher minimum, mean, Perc.01, Perc.05, Perc.10, Perc.25, Perc.50, and coefficient of variation (CV) (all p < 0.05). Among all significant CET1 histogram parameters, minimum achieved the best distinguishing performance, with an area under the curve of 0.836. CET1 histogram parameters could provide additional value in predicting pMGMT methylation status in patients with IDH-wildtype GBM, with minimum being the most promising parameter.

Evaluating synthetic neuroimaging data augmentation for automatic brain tumour segmentation with a deep fully-convolutional network

Gliomas observed in medical images require expert neuro-radiologist evaluation for treatment planning and monitoring, motivating development of intelligent systems capable of automating aspects of tumour evaluation. Deep learning models for automatic image segmentation rely on the amount and quality of training data. In this study we developed a neuroimaging synthesis technique to augment data for training fully-convolutional networks (U-nets) to perform automatic glioma segmentation. We used StyleGAN2-ada to simultaneously generate fluid-attenuated inversion recovery (FLAIR) magnetic resonance images and corresponding glioma segmentation masks. Synthetic data were successively added to real training data (n = 2751) in fourteen rounds of 1000 and used to train U-nets that were evaluated on held-out validation (n = 590) and test sets (n = 588). U-nets were trained with and without geometric augmentation (translation, zoom and shear), and Dice coefficients were computed to evaluate segmentation performance. We also monitored the number of training iterations before stopping, total training time, and time per iteration to evaluate computational costs associated with training each U-net. Synthetic data augmentation yielded marginal improvements in Dice coefficients (validation set +0.0409, test set +0.0355), whereas geometric augmentation improved generalization (standard deviation between training, validation and test set performances of 0.01 with, and 0.04 without geometric augmentation). Based on the modest performance gains for automatic glioma segmentation we find it hard to justify the computational expense of developing a synthetic image generation pipeline. Future work may seek to optimize the efficiency of synthetic data generation for augmentation of neuroimaging data.

Concurrence of craniopharyngioma and meningioma: a case report and systematic review of the literature

Craniopharyngioma (CPG) is a benign epithelial tumor that originates from Rathke's pouch. Meningiomas (MNG) are neoplasms of meningothelial cell. The patient is a 42-year-old female who presented with left-sided temporal headaches and visual acuity impairment. Neurological examination revealed bilateral peripheral visual field defects. Imaging of the brain showed a hypointense solid-cystic sellar lesion with suprasellar extension without calcification which enhanced with contrast. Also present was a second, contrast-enhancing extra axial lesion overlying the olfactory groove. The patient had no history of tumor surgery or radiation therapy. Both of the lesions were operated for resection and post operation status was uneventful. This study reports non-radiation related co-occurrence of a craniopharyngioma (CPG) and a meningioma (MNG). We reviewed published articles between 1966 and 2020, and found that although MNGs are the most commonly occurring brain tumors, the occurrence of MNG and CPG together with no relation to radiation is relatively rare, reported only 7 times in living patients. By analyzing the data and keeping in mind that there is no proven common genetic background and risk factor between them, their co-occurrence, shows the importance of further investigation to clear any possible relationship between the two other than mere coincidence.

Social impairment in survivors of pediatric brain tumors via reduced social attention and emotion-specific facial expression recognition

BACKGROUND/OBJECTIVES

Survivors of pediatric brain tumors (SPBT) experience significant social challenges, including fewer friends and greater isolation than peers. Difficulties in face processing and visual social attention have been implicated in these outcomes. This study evaluated facial expression recognition (FER), social attention, and their associations with social impairments in SPBT.

METHODS

SPBT (N = 54; ages 7-16) at least 2 years post treatment completed a measure of FER, while parents completed measures of social impairment. A subset (N = 30) completed a social attention assessment that recorded eye gaze patterns while watching videos depicting pairs of children engaged in joint play. Social Prioritization scores were calculated, with higher scores indicating more face looking. Correlations and regression analyses evaluated associations between variables, while a path analysis modeling tool (PROCESS) evaluated the indirect effects of Social Prioritization on social impairments through emotion-specific FER.

RESULTS

Poorer recognition of angry and sad facial expressions was significantly correlated with greater social impairment. Social Prioritization was positively correlated with angry FER but no other emotions. Social Prioritization had significant indirect effects on social impairments through angry FER.

CONCLUSION

Findings suggest interventions aimed at improving recognition of specific emotions may mitigate social impairments in SPBT. Further, reduced social attention (i.e., diminished face looking) could be a factor in reduced face processing ability, which may result in social impairments. Longitudinal research is needed to elucidate temporal associations between social attention, face processing, and social impairments.

Recent Update on PET/CT Radiotracers for Imaging Cerebral Glioma

Positron emission tomography/computed tomography (PET/CT) has dramatically altered the landscape of noninvasive glioma evaluation, offering complementary insights to those gained through magnetic resonance imaging (MRI). PET/CT scans enable a multifaceted analysis of glioma biology, supporting clinical applications from grading and differential diagnosis to mapping the full extent of tumors and planning subsequent treatments and evaluations. With a broad array of specialized radiotracers, researchers and clinicians can now probe various biological characteristics of gliomas, such as glucose utilization, cellular proliferation, oxygen deficiency, amino acid trafficking, and reactive astrogliosis. This review aims to provide a recent update on the application of versatile PET/CT radiotracers in glioma research and clinical practice.

Real-world cost- effectiveness analysis: Tumor Treating Fields for newly diagnosed glioblastoma in China

BACKGROUND

Glioblastoma (GBM) stands as the most aggressive and prevalent primary brain malignancy. Tumor Treating Fields (TTFields), an innovative therapy complementing chemotherapy for GBM treatment, which can significantly enhance overall survival, disease progression-free survival, and patient's quality of life. However, there is a dearth of health economics evaluation on TTFields therapy both domestically and internationally.

OBJECTIVE

The study aims to assess the cost-effectiveness of TTFields + temozolomide (TMZ) in comparison to TMZ alone for newly diagnosed GBM patients. The intent is to provide robust economic evidence to serve as a foundation for policymaking and decision-making processes in GBM treatment.

METHODS

We estimated outcomes for newly diagnosed GBM patients over a lifetime horizon using a partitioned survival model with three states: Progression-Free Survival, Progression Disease, and Death. The survival model was derived from a real-world study in China, with long-term survival data drawn from GBM epidemiology literature. Adverse event rates were sourced from the EF-14 trial data. Cost data, validated by expert consultation, was obtained from public literature and databases. Utility values were extracted from published literature. Using Microsoft Excel, we calculated expected costs and quality-adjusted life years (QALYs) over 15 years from a health system perspective. The willingness-to-pay threshold was set at three times the Chinese per capita Gross Domestic Product (GDP) in 2022, amounting to CN¥242,928 (US$37,655) /QALY. A 5% discount rate was applied to costs and utilities. Results underwent analysis through single factor and probability sensitivity analyses.

RESULTS

TTFields + TMZ demonstrated a mean increase in cost by CN¥389,326 (US$57,859) and an increase of 2.46 QALYs compared to TMZ alone. The incremental cost-effectiveness ratio (ICER) was CN¥157,979 (US$23,474) per QALY gained. The model exhibited heightened sensitivity to changes in the discount rate. Probability sensitivity analysis indicates that, under the existing threshold, the probability of TTFields + TMZ being economical is 95.60%.

CONCLUSIONS

This cost-effectiveness analysis affirms that incorporating TTFields into TMZ treatment proves to be cost-effective, given a threshold three times the Chinese per capita GDP.

Discovery of Novel Small-Molecule-Based Potential PD-L1/EGFR Dual Inhibitors with High Druggability for Glioblastoma Immunotherapy

Based on the close relationship between programmed death protein ligand 1 (PD-L1) and epidermal growth factor receptor (EGFR) in glioblastoma (GBM), we designed and synthesized a series of small molecules as potential dual inhibitors of EGFR and PD-L1. Among them, compound EP26 exhibited the highest inhibitory activity against EGFR (IC50 = 37.5 nM) and PD-1/PD-L1 interaction (IC50 = 1.77 μM). In addition, EP26 displayed superior in vitro antiproliferative activities and in vitro immunomodulatory effects by promoting U87MG cell death in a U87MG/Jurkat cell coculture model. Furthermore, EP26 possessed favorable pharmacokinetic properties (F = 22%) and inhibited tumor growth (TGI = 92.0%) in a GBM mouse model more effectively than Gefitinib (77.2%) and NP19 (82.8%). Moreover, EP26 increased CD4+ cells and CD8+ cells in tumor microenvironment. Collectively, these results suggest that EP26 represents the first small-molecule-based PD-L1/EGFR dual inhibitor deserving further investigation as an immunomodulating agent for cancer treatment.

Novel cancer-fighting role of ticagrelor inhibits GTSE1-induced EMT by regulating PI3K/Akt/NF-κB signaling pathway in malignant glioma

Background

Glioma is the most common malignant brain tumor of the central nervous system. Despite of the improvement of therapeutic strategy, the prognosis of malignant glioma patients underwent by STUPP strategy is still unexpected. Previous studies have suggested that ticagrelor exerted chemotherapeutic effects by inhibition of epithelial-mesenchymal transition (EMT) in various diseases including tumors. However, whether ticagrelor can exhibit the antitumor efficiency in glioma by affecting the EMT process is still unclear. In this study, we investigated the cancer-fighting role of ticagrelor and demonstrated its chemotherapeutic mechanism in glioma.

Materials and methods

The MTT assay was performed to detect the cytotoxicity of ticagrelor in glioma cells. We evaluated the expression of Ki67 in glioma cells by immunofluorescence assay after ticagrelor treatment. We conducted wound healing assay and transwell assay to determine the effects of ticagrelor on the migration and invasion of glioma cells. RNA-seq analysis was conducted to examine potential target genes and alternative signaling pathways for ticagrelor treatment. The expression levels of key EMT -related proteins were examined by Western blot experiment.

Results

Ticagrelor inhibited the proliferation, migration and invasion of glioma cells with a favorable toxicity profile in vitro. Ticagrelor downregulated the expression of GTSE1 in glioma cells. RNA-seq analysis explored that GTSE1 acted as the potential target gene for ticagrelor treatment. Upregulation of GTSE1 antagonized the inhibitory effect of ticagrelor on the invasion of glioma and EMT progression by regulation of PI3K/Akt/NF-κB signaling pathway. And ticagrelor also exhibited the similar chemotherapeutic effect of glioma in vivo.

Conclusions

Ticagrelor as a potential chemotherapeutic option induced the inhibition of the GTSE1-induced EMT progression by regulation of PI3K/AKT/NF-κB signaling pathway.

Glioma-derived exosome Lncrna Agap2-As1 promotes glioma proliferation and metastasis by mediating Tgf-β1 secretion of myeloid-derived suppressor cells

Background

Glioma (GBM) is the most prevalent malignancy worldwide with high morbidity and mortality. Exosome-mediated transfer of long noncoding RNA (lncRNA) has been reported to be associated with human cancers, containing GBM. Meanwhile, myeloid-derived suppressor cells (MDSCs) play a vital role in mediating the immunosuppressive environments in GBM.

Objectives

This study is designed to explore the role and mechanism of exosomal (Exo) lncRNA AGAP2-AS1 on the MDSC pathway in GBM.

Methods

AGAP2-AS1, microRNA-486-3p (miR-486-3p), and Transforming growth factor beta-1 (TGF-β1) levels were detected by real-time quantitative polymerase chain reaction (RT-qPCR). Cell proliferation, apoptosis, migration, and invasion were detected by 5-ethynyl-2'-deoxyuridine (EdU), flow cytometry, and Transwell assays. E-cadherin, Vimentin, CD9, CD81, and TGF-β1 protein levels were examined using Western blot. Exosomes were detected by a transmission electron microscope (TEM). Binding between miR-486-3p and AGAP2-AS1 or TGF-β1 was predicted by LncBase or TargetScan and then verified using a dual-luciferase reporter assay.

Results

AGAP2-AS1 was highly expressed in GBM tissues and cells. Functionally, AGAP2-AS1 absence or TGF-β1 knockdown repressed tumor cell growth and metastasis. Furthermore, Exo-AGAP2-AS1 from GBM cells regulated TGF-β1 expression via sponging miR-486-3p in MDSCs. Exo-AGAP2-AS1 upregulation facilitated GBM cell growth and metastasis via the MDSC pathway.

Conclusion

Exo-AGAP2-AS1 boosted GBM cell development partly by regulating the MDSC pathway, hinting at a promising therapeutic target for GBM treatment.

Profiling of Tumor-Infiltrating Immune Cells and Their Impact on Survival in Glioblastoma Patients Undergoing Immunotherapy with Dendritic Cells

Glioblastomas (GBM) are the most common primary malignant brain tumors, comprising 2% of all cancers in adults. Their location and cellular and molecular heterogeneity, along with their highly infiltrative nature, make their treatment challenging. Recently, our research group reported promising results from a prospective phase II clinical trial involving allogeneic vaccination with dendritic cells (DCs). To date, six out of the thirty-seven reported cases remain alive without tumor recurrence. In this study, we focused on the characterization of infiltrating immune cells observed at the time of surgical resection. An analytical model employing a neural network-based predictive algorithm was used to ascertain the potential prognostic implications of immunological variables on patients' overall survival. Counterintuitively, immune phenotyping of tumor-associated macrophages (TAMs) has revealed the extracellular marker PD-L1 to be a positive predictor of overall survival. In contrast, the elevated expression of CD86 within this cellular subset emerged as a negative prognostic indicator. Fundamentally, the neural network algorithm outlined here allows a prediction of the responsiveness of patients undergoing dendritic cell vaccination in terms of overall survival based on clinical parameters and the profile of infiltrated TAMs observed at the time of tumor excision.

Recent advances in targeted drug delivery for the treatment of glioblastoma

Glioblastoma multiforme (GBM) is one of the highly malignant brain tumors characterized by significant morbidity and mortality. Despite the recent advancements in the treatment of GBM, major challenges persist in achieving controlled drug delivery to tumors. The management of GBM poses considerable difficulties primarily due to unresolved issues in the blood-brain barrier (BBB)/blood-brain tumor barrier (BBTB) and GBM microenvironment. These factors limit the uptake of anti-cancer drugs by the tumor, thus limiting the therapeutic options. Current breakthroughs in nanotechnology provide new prospects concerning unconventional drug delivery approaches for GBM treatment. Specifically, swimming nanorobots show great potential in active targeted delivery, owing to their autonomous propulsion and improved navigation capacities across biological barriers, which further facilitate the development of GBM-targeted strategies. This review presents an overview of technological progress in different drug administration methods for GBM. Additionally, the limitations in clinical translation and future research prospects in this field are also discussed. This review aims to provide a comprehensive guideline for researchers and offer perspectives on further development of new drug delivery therapies to combat GBM.

Microglia and macrophages in glioblastoma: landscapes and treatment directions

Glioblastoma is the most common primary malignant tumour of the central nervous system and remains uniformly and rapidly fatal. The tumour-associated macrophage (TAM) compartment comprises brain-resident microglia and bone marrow-derived macrophages (BMDMs) recruited from the periphery. Immune-suppressive and tumour-supportive TAM cell states predominate in glioblastoma, and immunotherapies, which have achieved striking success in other solid tumours have consistently failed to improve survival in this 'immune-cold' niche context. Hypoxic and necrotic regions in the tumour core are found to enrich, especially in anti-inflammatory and immune-suppressive TAM cell states. Microglia predominate at the invasive tumour margin and express pro-inflammatory and interferon TAM cell signatures. Depletion of TAMs, or repolarisation towards a pro-inflammatory state, are appealing therapeutic strategies and will depend on effective understanding and classification of TAM cell ontogeny and state based on new single-cell and spatial multi-omic in situ profiling. Here, we explore the application of these datasets to expand and refine TAM characterisation, to inform improved modelling approaches, and ultimately underpin the effective manipulation of function.

Triggering receptor expressed on myeloid cells 2 (TREM2) regulates phagocytosis in glioblastoma

BACKGROUND

Glioblastomas (GBMs) are central nervous system tumors that resist standard-of-care interventions and even immune checkpoint blockade. Myeloid cells in the tumor microenvironment can contribute to GBM progression; therefore, emerging immunotherapeutic approaches include reprogramming these cells to achieve desirable antitumor activity. Triggering receptor expressed on myeloid cells 2 (TREM2) is a myeloid signaling regulator that has been implicated in a variety of cancers and neurological diseases with contrasting functions, but its role in GBM immunopathology and progression is still under investigation.

METHODS

Our reverse translational investigations leveraged single-cell RNA sequencing and cytometry of human gliomas to characterize TREM2 expression across myeloid subpopulations. Using 2 distinct murine glioma models, we examined the role of Trem2 on tumor progression and immune modulation of myeloid cells. Furthermore, we designed a method of tracking phagocytosis of glioma cells in vivo and employed in vitro assays to mechanistically understand the influence of TREM2 signaling on tumor uptake.

RESULTS

We discovered that TREM2 expression does not correlate with immunosuppressive pathways, but rather showed strong a positive association with the canonical phagocytosis markers lysozyme (LYZ) and macrophage scavenger receptor (CD163) in gliomas. While Trem2 deficiency was found to be dispensable for gliomagenesis, Trem2+ myeloid cells display enhanced tumor uptake compared to Trem2- cells. Mechanistically, we demonstrate that TREM2 mediates phagocytosis via Syk signaling.

CONCLUSIONS

These results indicate that TREM2 is not associated with immunosuppression in gliomas. Instead, TREM2 is an important regulator of phagocytosis that may be exploited as a potential therapeutic strategy for brain tumors.

Noninvasive Isocitrate Dehydrogenase 1 Status Prediction in Grade II/III Glioma Based on Magnetic Resonance Images: A Transfer Learning Strategy

OBJECTIVE

The aim of this study was to evaluate transfer learning combined with various convolutional neural networks (TL-CNNs) in predicting isocitrate dehydrogenase 1 ( IDH1 ) status of grade II/III gliomas.

METHODS

Grade II/III glioma patients diagnosed at the Tangdu Hospital (August 2009 to May 2017) were retrospectively enrolled, including 54 patients with IDH1 mutant and 56 patients with wild-type IDH1 . Convolutional neural networks, AlexNet, GoogLeNet, ResNet, and VGGNet were fine-tuned with T2-weighted imaging (T2WI), fluid attenuation inversion recovery (FLAIR), and contrast-enhanced T1-weighted imaging (T1CE) images. The single-modal networks were integrated with averaged sigmoid probabilities, logistic regression, and support vector machine. FLAIR-T1CE-fusion (FC-fusion), T2WI-T1CE-fusion (TC-fusion), and FLAIR-T2WI-T1CE-fusion (FTC-fusion) were used for fine-tuning TL-CNNs.

RESULTS

IDH1 -mutant prediction accuracies using AlexNet, GoogLeNet, ResNet, and VGGNet achieved 70.0% (AUC = 0.660), 65.0% (AUC = 0.600), 70.0% (AUC = 0.700), and 80.0% (AUC = 0.730) for T2WI images, 70.0% (AUC = 0.660), 70.0% (AUC = 0.620), 70.0% (AUC = 0.710), and 80.0% (AUC = 0.720) for FLAIR images, and 73.7% (AUC = 0.744), 73.7% (AUC = 0.656), 73.7% (AUC = 0.633), and 73.7% (AUC = 0.700) for T1CE images, respectively. The highest AUC (0.800) was achieved using VGGNet and FC-fusion images.

CONCLUSIONS

TL-CNNs (especially VGGNet) had a potential predictive value for IDH1 -mutant status of grade II/III gliomas.

Identifying key factors for predicting O6-Methylguanine-DNA methyltransferase status in adult patients with diffuse glioma: a multimodal analysis of demographics, radiomics, and MRI by variable Vision Transformer

PURPOSE

This study aimed to perform multimodal analysis by vision transformer (vViT) in predicting O6-methylguanine-DNA methyl transferase (MGMT) promoter status among adult patients with diffuse glioma using demographics (sex and age), radiomic features, and MRI.

METHODS

The training and test datasets contained 122 patients with 1,570 images and 30 patients with 484 images, respectively. The radiomic features were extracted from enhancing tumors (ET), necrotic tumor cores (NCR), and the peritumoral edematous/infiltrated tissues (ED) using contrast-enhanced T1-weighted images (CE-T1WI) and T2-weighted images (T2WI). The vViT had 9 sectors; 1 demographic sector, 6 radiomic sectors (CE-T1WI ET, CE-T1WI NCR, CE-T1WI ED, T2WI ET, T2WI NCR, and T2WI ED), 2 image sectors (CE-T1WI, and T2WI). Accuracy and area under the curve of receiver-operating characteristics (AUC-ROC) were calculated for the test dataset. The performance of vViT was compared with AlexNet, GoogleNet, VGG16, and ResNet by McNemar and Delong test. Permutation importance (PI) analysis with the Mann-Whitney U test was performed.

RESULTS

The accuracy was 0.833 (95% confidence interval [95%CI]: 0.714-0.877) and the area under the curve of receiver-operating characteristics was 0.840 (0.650-0.995) in the patient-based analysis. The vViT had higher accuracy than VGG16 and ResNet, and had higher AUC-ROC than GoogleNet (p<0.05). The ED radiomic features extracted from the T2-weighted image demonstrated the highest importance (PI=0.239, 95%CI: 0.237-0.240) among all other sectors (p<0.0001).

CONCLUSION

The vViT is a competent deep learning model in predicting MGMT status. The ED radiomic features of the T2-weighted image demonstrated the most dominant contribution.

A Rare Presentation of Primary Frontotemporal Cerebral Lymphoma: A Case Report

Primary central nervous system (CNS) lymphoma is a rare and aggressive form of extranodal non-Hodgkin's lymphoma, limited to the brain, eyes, spinal cord, or leptomeninges without systemic involvement. This group of malignant tumors is characterized by a particular diagnostic, therapeutic, and evolutionary profile compared to other types of non-Hodgkin's lymphomas. We report a case of a young patient treated in our university hospital center for primary cerebral lymphoma who benefited from primary chemotherapy and then consolidation radiotherapy with good disease control and good tolerance.

Epidemiology and Management Trends of Neuro-Oncology in Nigeria: A Systematic Review and Pooled Analysis

OBJECTIVE

Access to neuro-oncologic care in Nigeria has grown exponentially since the first reported cases in the mid-1960s. In this systematic review and pooled analysis, we characterize the growth of neurosurgical oncology in Nigeria and build a reference paper to direct efforts to expand this field.

METHODS

We performed an initial literature search of several article databases and gray literature sources. We included and subsequently screened articles published between 1962 and 2021. Several variables were extracted from each study, including the affiliated hospital, the number of patients treated, patient sex, tumor pathology, the types of imaging modalities used for diagnosis, and the interventions used for each individual. Change in these variables was assessed using Chi-squared independence tests and univariate linear regression when appropriate.

RESULTS

A total of 147 studies were identified, corresponding to 5,760 patients. Over 4000 cases were reported in the past 2 decades from 21 different Nigerian institutions. The types of tumors reported have increased over time, with increasingly more patients being evaluated via computed tomography (CT) and magnetic resonance imaging (MRI). There is also a prevalent use of radiotherapy, though chemotherapy remains an underreported treatment modality.

CONCLUSIONS

This study highlights key trends regarding the prevalence and management of neuro-oncologic pathologies within Nigeria. Further studies are needed to continue to learn and guide the future growth of this field in Nigeria.

A Retrospective Study to Evaluate Discrepancies in Urban Versus Rural Mortality Due to Brain Cancer in the United States

INTRODUCTION

The study aims to examine the disparities in mortality rates attributed to brain cancer between urban and rural areas over a 22-year period, totaling 315,538 deaths. This investigation serves as a crucial step in identifying areas within healthcare that require improvement. By pinpointing the variations in mortality rates between urban and rural settings, healthcare authorities can strategically implement necessary interventions.

METHODOLOGY

A retrospective study was conducted by analyzing the death certificate available on the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database from 1999 to 2020 to evaluate the mortality rate trends of brain cancer ( International Classification of Diseases (ICD)-10 C71.0-71.9).The data was grouped based on rural and urban death rates according to the 2013 urbanization classification and the variables that were used were age, gender and race. Data was analyzed using Microsoft Excel and R Studio 4.3.1. Significant associations between demographic variables and mortality rates were identified via Binomial tests.

RESULTS

From 1999 to 2020, urban areas recorded 259,402 deaths attributed to brain cancer, compared to 56,136 deaths in rural areas, indicating a higher mortality rate in urban settings. The mortality rate in both rural and urban areas exhibited an upward trend, except for a slight drop in 2010. The mortality rates were significantly higher in rural areas compared to urban areas for age groups 55-64 years and 65-74 years, males and caucasians.

CONCLUSIONS

Our research underscores the differences in death rates from brain cancer between urban and rural areas, specifically among individuals aged 55-64 and 65-74, males and those of caucasian ethnicity. Future research must adopt a multifaceted approach, integrating more recent datasets and embracing a finer granularity of individual-level information. Moreover, there is a pressing need to explore the interplay of various factors such as access to healthcare, treatment modalities, genetic predispositions, and socioeconomic determinants on mortality outcomes.

Evolution of Surgical Management of Pineal Region Tumors in the Pediatric Population: A 17-Year Experience at a Single Institution

INTRODUCTION

Pineal region tumors have historically been challenging to treat. Advances in surgical techniques have led to significant changes in care and outcomes for these patients, and this is well demonstrated by our single institution's experience over a 17-year-period in which the evolution of diagnosis, treatment, and outcomes of pineal tumors in pediatric patients will be outlined.

METHODS

We retrospectively collected data on all pediatric patients with pineal region lesions treated with surgery at Children's National Hospital (CNH) from 2005 to 2021. Variables analyzed included presenting symptoms, presence of hydrocephalus, diagnostic and surgical approach, pathology, and adverse events, among others. IRB approval was obtained (IRB: STUDY00000009), and consent was waived due to minimal risk to patients included.

RESULTS

A total of 43 pediatric patients with pineal region tumors were treated during a 17-year period. Most tumors in our series were germinomas (n = 13, 29.5%) followed by pineoblastomas (n = 10, 22.7%). Twenty seven of the 43 patients (62.8%) in our series received a biopsy to establish diagnosis, and 44.4% went on to have surgery for resection. The most common open approach was posterior interhemispheric (PIH, transcallosal) - used for 59.3% of the patients. Gross total resection was achieved in 50%; recurrence occurred in 20.9% and mortality in 11% over a median follow-up of 47 months. Endoscopic third ventriculostomy (ETV) was employed to treat hydrocephalus in 26 of the 38 patients (68.4%) and was significantly more likely to be performed from 2011 to 2021. Most (73%) of the patients who received an ETV also underwent a concurrent endoscopic biopsy. No difference was found in recurrence rate or mortality in patients who underwent resection compared to those who did not, but complications were more frequent with resection. There was disagreement between frozen and final pathology in 18.4% of biopsies.

CONCLUSION

This series describes the evolution of surgical approaches and outcomes over a 17-year-period at a single institution. Complication rates were higher with open resection, reinforcing the safety of pursuing endoscopic biopsy as an initial approach. The most significant changes occurred in the preferential use of ETVs over ventriculoperitoneal shunts. Though there has been a significant evolution in our understanding of and treatment for these tumors, in our series, the outcomes for these patients have not significantly changed over that time.

Analysis and prediction of central nervous system tumor burden in China during 1990-2030

Central nervous system (CNS) tumors, due to their unique locations, pose a serious threat to human health and present challenges to modern medicine. These tumors exhibit notable epidemiological characteristics across various ethnicities, regions, and age groups. This study investigated the trend of disease burden of CNS tumors in China from 1990-2019 and predicted the incidence and death rate from 2020-2030. Employing data from the 2019 Global Burden of Disease (GBD) database, we utilized key indicators to scrutinize the disease burden associated with CNS tumors in China. The analysis employed the Joinpoint model to track the trend in disease burden, calculating both the annual percentage change (APC) and average annual percentage change (AAPC). Additionally, the Matlab software facilitated the creation of a gray model to forecast the incidence and death rate of CNS tumors in China spanning from 2020 to 2030." In 2019, the age-standardized incidence rate, prevalence rate, death rate, and disability-adjusted life years (DALYs) associated with CNS tumors in China were among the high level in the world. The standardized prevalence rate and DALYs of CNS tumors in China residents showed a stable fluctuation trend with age; however, age-standardized death and incidence rate demonstrated a generally upward trend with age. In China, the age-standardized prevalence and incidence rate of males were lower than those for female residents, while the age-standardized death rate and DALYs among males surpassed those of females. From 1990-2019, the age-standardized prevalence and incidence rate of CNS tumors in China exhibited an increasing trend. The age-standardized death rate and DALYs showed a contrasting trend. According to the gray model's prediction, incidence rate of CNS tumors would continue rising while the death rate is expected to decline in China from 2020-2023. The burden of CNS tumors in China has shown an upward trajectory, posing significant challenges to their treatment. It is necessary to pay attention to tertiary prevention, start from the perspective of high-risk groups and high-risk factors to reduce the burden of disease, and achieve "early detection, early diagnosis, and early treatment".

Automatic Brain Tissue and Lesion Segmentation and Multi-Parametric Mapping of Contrast-Enhancing Gliomas without the Injection of Contrast Agents: A Preliminary Study

This study aimed to develop a rapid, 1 mm3 isotropic resolution, whole-brain MRI technique for automatic lesion segmentation and multi-parametric mapping without using contrast by continuously applying balanced steady-state free precession with inversion pulses throughout incomplete inversion recovery in a single 6 min scan. Modified k-means clustering was performed for automatic brain tissue and lesion segmentation using distinct signal evolutions that contained mixed T1/T2/magnetization transfer properties. Multi-compartment modeling was used to derive quantitative multi-parametric maps for tissue characterization. Fourteen patients with contrast-enhancing gliomas were scanned with this sequence prior to the injection of a contrast agent, and their segmented lesions were compared to conventionally defined manual segmentations of T2-hyperintense and contrast-enhancing lesions. Simultaneous T1, T2, and macromolecular proton fraction maps were generated and compared to conventional 2D T1 and T2 mapping and myelination water fraction mapping acquired with MAGiC. The lesion volumes defined with the new method were comparable to the manual segmentations (r = 0.70, p < 0.01; t-test p > 0.05). The T1, T2, and macromolecular proton fraction mapping values of the whole brain were comparable to the reference values and could distinguish different brain tissues and lesion types (p < 0.05), including infiltrating tumor regions within the T2-lesion. Highly efficient, whole-brain, multi-contrast imaging facilitated automatic lesion segmentation and quantitative multi-parametric mapping without contrast, highlighting its potential value in the clinic when gadolinium is contraindicated.

Dual-space disentangled-multimodal network (DDM-net) for glioma diagnosis and prognosis with incomplete pathology and genomic data

Objective. Effective fusion of histology slides and molecular profiles from genomic data has shown great potential in the diagnosis and prognosis of gliomas. However, it remains challenging to explicitly utilize the consistent-complementary information among different modalities and create comprehensive representations of patients. Additionally, existing researches mainly focus on complete multi-modality data and usually fail to construct robust models for incomplete samples.Approach. In this paper, we propose adual-space disentangled-multimodal network (DDM-net)for glioma diagnosis and prognosis. DDM-net disentangles the latent features generated by two separate variational autoencoders (VAEs) into common and specific components through a dual-space disentangled approach, facilitating the construction of comprehensive representations of patients. More importantly, DDM-net imputes the unavailable modality in the latent feature space, making it robust to incomplete samples.Main results. We evaluated our approach on the TCGA-GBMLGG dataset for glioma grading and survival analysis tasks. Experimental results demonstrate that the proposed method achieves superior performance compared to state-of-the-art methods, with a competitive AUC of 0.952 and a C-index of 0.768.Significance. The proposed model may help the clinical understanding of gliomas and can serve as an effective fusion model with multimodal data. Additionally, it is capable of handling incomplete samples, making it less constrained by clinical limitations.

CBX7 reprograms metabolic flux to protect against meningioma progression by modulating the USP44/c-MYC/LDHA axis

Meningioma is one of the most common primary neoplasms in the central nervous system, but no specific molecularly targeted therapy has been approved for the clinical treatment of aggressive meningiomas. There is hence an urgent demand to decrypt the biological and molecular landscape of malignant meningioma. Here, through the in-silica prescreening and 10-year follow-up studies of 445 meningioma patients, we uncovered that CBX7 expression progressively decreases with malignancy grade and neoplasia stage in meningioma, and a high CBX7 expression level predicts a favorable prognosis in meningioma patients. CBX7 restoration significantly induces cell cycle arrest and inhibits meningioma cell proliferation. iTRAQ-based proteomics analysis indicated that CBX7 restoration triggers the metabolic shift from glycolysis to oxidative phosphorylation. The mechanistic study demonstrated that CBX7 promotes the proteasome-dependent degradation of c-MYC protein by transcriptionally inhibiting the expression of a c-MYC deubiquitinase, USP44, consequently attenuates c-MYC-mediated transactivation of LDHA transcripts, and further inhibits glycolysis and subsequent cell proliferation. More importantly, the functional role of CBX7 was further confirmed in subcutaneous and orthotopic meningioma xenograft mouse models and meningioma patients. Altogether, our results shed light on the critical role of CBX7 in meningioma malignancy progression and identify the CBX7/USP44/c-MYC/LDHA axis as a promising therapeutic target against meningioma progression.

Investigation of the status of immune checkpoint molecules (PD-L1 and PD-1) in meningiomas by immunohistochemistry

Background/aim

Meningiomas are the most common primary brain tumors of the central nervous system. Immunotherapy is a promising treatment method applied in many types of cancer. There is no standard and effective medical treatment to reduce recurrence and mortality in cases of incomplete resection of meningiomas and in high-grade cases. In order to investigate medical treatments in addition to surgery and radiotherapy, in this study, the status of immune checkpoint molecules (PD-L1/PD-1), which are the target of immunotherapy, in meningiomas was investigated.

Materials and methods

Four hundred two cases of meningioma diagnosed between 2007 and 2020 at our institution were used. New blocks were prepared from the appropriate blocks of the cases using the tissue microarray method. Sections obtained from these blocks were immunohistochemically stained with PD-1 and PD-L1 antibodies. Obtained data were interpreted with statistical analysis.

Results

Expression of PD-L1 was observed in 28.4% of meningiomas. Staining rates are higher in high-grade tumors. The staining rate of PD-L1 in the tumor increased significantly with pattern loss. PD-L1 expression in immune cells is 19.9%. Immune cell expression and the number of expressing immune cells correlate with spontaneous necrosis. Immune cell expression and the number of expressing immune cells are increased in high-grade meningiomas. PD-1 expression in immune cells is 9.0%, and this correlates with brain invasion.

Conclusions

With these data, it was observed that the expression of immune checkpoint molecules PD-L1 and PD-1 increased especially in high-grade meningiomas. It may be the subject of research that these molecules may be targets of immunotherapy in the treatment of meningiomas.

Grading of Gliomas by Contrast-Enhanced CT Radiomics Features

Background

Gliomas, as Central Nervous System (CNS) tumors, are greatly common with 80% of malignancy. Treatment methods for gliomas, such as surgery, radiation therapy, and chemotherapy depend on the grade, size, location, and the patient's age.

Objective

This study aimed to quantify glioma based on the radiomics analysis and classify its grade into High-grade Glioma (HGG) or Low-grade Glioma (LGG) by various machine-learning methods using contrast-enhanced brain Computerized Tomography (CT) scans.

Material and Methods

This retrospective study involved acquiring and segmenting data, selecting and extracting features, classifying, analyzing, and evaluating classifiers. The study included a total of 62 patients (31 with LGG and 31 with HGG). The tumors were segmented by an experienced CT-scan technologist with 3D slicer software. A total of 14 shape features, 18 histogram-based features, and 75 texture-based features were computed. The Area Under the Curve (AUC) and Receiver Operating Characteristic Curve (ROC) were used to evaluate and compare classification models.

Results

A total of 13 out of 107 features were selected to differentiate between LGGs and HGGs and to perform various classifier algorithms with different cross-validations. The best classifier algorithm was linear-discriminant with 93.5% accuracy, 96.77% sensitivity, 90.3% specificity, and 0.98% AUC in the differentiation of LGGs and HGGs.

Conclusion

The proposed method can identify LGG and HGG with 93.5% accuracy, 96.77% sensitivity, 90.3% specificity, and 0.98% AUC, leading to the best treatment for glioma patients by using CT scans based on radiomics analysis.

Development of a rapid and comprehensive genomic profiling test supporting diagnosis and research for gliomas

A prompt and reliable molecular diagnosis for brain tumors has become crucial in precision medicine. While Comprehensive Genomic Profiling (CGP) has become feasible, there remains room for enhancement in brain tumor diagnosis due to the partial lack of essential genes and limitations in broad copy number analysis. In addition, the long turnaround time of commercially available CGPs poses an additional obstacle to the timely implementation of results in clinics. To address these challenges, we developed a CGP encompassing 113 genes, genome-wide copy number changes, and MGMT promoter methylation. Our CGP incorporates not only diagnostic genes but also supplementary genes valuable for research. Our CGP enables us to simultaneous identification of mutations, gene fusions, focal and broad copy number alterations, and MGMT promoter methylation status, with results delivered within a minimum of 4 days. Validation of our CGP, through comparisons with whole-genome sequencing, RNA sequencing, and pyrosequencing, has certified its accuracy and reliability. We applied our CGP for 23 consecutive cases of intracranial mass lesions, which demonstrated its efficacy in aiding diagnosis and prognostication. Our CGP offers a comprehensive and rapid molecular profiling for gliomas, which could potentially apply to clinical practices and research primarily in the field of brain tumors.

Integrative analysis of metabolism subtypes and identification of prognostic metabolism-related genes for glioblastoma

Increasing evidence has demonstrated that cancer cell metabolism is a critical factor in tumor development and progression; however, its role in glioblastoma (GBM) remains limited. In the present study, we classified GBM into three metabolism subtypes (MC1, MC2, and MC3) through cluster analysis of 153 GBM samples from the RNA-sequencing data of The Cancer Genome Atlas (TCGA) based on 2752 metabolism-related genes (MRGs). We further explored the prognostic value, metabolic signatures, immune infiltration, and immunotherapy sensitivity of the three metabolism subtypes. Moreover, the metabolism scoring model was established to quantify the different metabolic characteristics of the patients. Results showed that MC3, which is associated with a favorable survival outcome, had higher proportions of isocitrate dehydrogenase (IDH) mutations and lower tumor purity and proliferation. The MC1 subtype, which is associated with the worst prognosis, shows a higher number of segments and homologous recombination defects and significantly lower mRNA expression-based stemness index (mRNAsi) and epigenetic-regulation-based mRNAsi. The MC2 subtype has the highest T-cell exclusion score, indicating a high likelihood of immune escape. The results were validated using an independent dataset. Five MRGs (ACSL1, NDUFA2, CYP1B1, SLC11A1, and COX6B1) correlated with survival outcomes were identified based on metabolism-related co-expression module analysis. Laboratory-based validation tests further showed the expression of these MRGs in GBM tissues and how their expression influences cell function. The results provide a reference for developing clinical management approaches and treatments for GBM.

vNARs as Neutralizing Intracellular Therapeutic Agents: Glioblastoma as a Target

Glioblastoma is the most prevalent and fatal form of primary brain tumors. New targeted therapeutic strategies for this type of tumor are imperative given the dire prognosis for glioblastoma patients and the poor results of current multimodal therapy. Previously reported drawbacks of antibody-based therapeutics include the inability to translocate across the blood-brain barrier and reach intracellular targets due to their molecular weight. These disadvantages translate into poor target neutralization and cancer maintenance. Unlike conventional antibodies, vNARs can permeate tissues and recognize conformational or cryptic epitopes due to their stability, CDR3 amino acid sequence, and smaller molecular weight. Thus, vNARs represent a potential antibody format to use as intrabodies or soluble immunocarriers. This review comprehensively summarizes key intracellular pathways in glioblastoma cells that induce proliferation, progression, and cancer survival to determine a new potential targeted glioblastoma therapy based on previously reported vNARs. The results seek to support the next application of vNARs as single-domain antibody drug-conjugated therapies, which could overcome the disadvantages of conventional monoclonal antibodies and provide an innovative approach for glioblastoma treatment.

Multiple surgical resections for progressive IDH wildtype glioblastoma-is it beneficial?

PURPOSE

The role of repeat resection for recurrent glioblastoma (rGB) remains equivocal. This study aims to assess the overall survival and complications rates of single or repeat resection for rGB.

METHODS

A single-centre retrospective review of all patients with IDH-wildtype glioblastoma managed surgically, between January 2014 and January 2022, was carried out. Patient survival and factors influencing prognosis were analysed, using Kaplan-Meier and Cox regression methods.

RESULTS

Four hundred thirty-two patients were included, of whom 329 underwent single resection, 83 had two resections and 20 patients underwent three resections. Median OS (mOS) in the cohort who underwent a single operation was 13.7 months (95% CI: 12.7-14.7 months). The mOS was observed to be extended in patients who underwent second or third-time resection, at 22.9 months and 44.7 months respectively (p < 0.001). On second operation achieving > 95% resection or residual tumour volume of < 2.25 cc was significantly associated with prolonged survival. There was no significant difference in overall complication rates between primary versus second (p = 0.973) or third-time resections (p = 0.312). The use of diffusion tensor imaging (DTI) guided resection was associated with reduced post-operative neurological deficit (RR 0.37, p = 0.002), as was use of intraoperative ultrasound (iUSS) (RR 0.45, p = 0.04).

CONCLUSIONS

This study demonstrates potential prolongation of survival for rGB patients undergoing repeat resection, without significant increase in complication rates with repeat resections. Achieving a more complete repeat resection improved survival. Moreover, the use of intraoperative imaging adjuncts can maximise tumour resection, whilst minimising the risk of neurological deficit.