Diagnostic, therapeutic, and prognostic implications of the 2021 World Health Organization classification of tumors of the central nervous system

DENDRITIC CELLS IN GLIOBLASTOMA TREATMENT: A MODERN VIEW OF THE PROBLEM AND OWN EXPERIENCE

Glioblastoma (GBM) is the most aggressive primary malignant brain tumor in adults. The improvement of the efficacy of GBM treatment is an urgent problem encouraging the development of novel therapeutic strategies, in particular, immunotherapeutic modalities. With more understanding of the intimate interrelationships between the immune system and the mechanisms involved in cancer origin and progression, the skepticism related to the relevance of the immunotherapeutic approaches in the treatment of brain tumors is gradually decreasing. The review discloses the modern concepts on the association between CNS and the immune system. For a long time, CNS was considered as the immunoprivileged site that prevents the effects of immunotherapy in the treatment of brain tumors. Nowadays, these views are reconsidered, which opens the way to the use of immunotherapeutic approaches in GBM treatment. The results of the recent clinical trials on immunotherapy as a supplement to the conventional GBM treatment are considered. Vaccines based on the dendritic cell (DC) technology are regarded as the most promising for this purpose. The preliminary results of the Ukrainian clinical study are also presented and discussed. The results of the international clinical trials as well as our own experience give evidence of the relevance for using DC vaccines in the complex treatment of GBM, which is supported by the increased survival of patients and the safety of vaccine application. It is of high importance that GBM patients with the most unfavorable prognosis can benefit from DC vaccines as a component of the complex treatment. The prospects for immunotherapy in neurooncology are discussed.

Tumor Multiregional Mean Apparent Propagator (MAP) Features in Evaluating Gliomas-A Comparative Study With Diffusion Kurtosis Imaging (DKI)

BACKGROUND

Glioma classification affects treatment and prognosis. Reliable imaging methods for preoperatively evaluating gliomas are essential.

PURPOSE

To evaluate tumor multiregional mean apparent propagator (MAP) features in glioma diagnosis and to compare those with diffusion-kurtosis imaging (DKI).

STUDY TYPE

Retrospective study.

SUBJECTS

70 untreated glioma patients (31 LGGs (low-grade gliomas), 34 women; mean age, 47 ± 12 years, training (60%, n = 42) and testing cohorts (40%, n = 28)).

FIELD STRENGTH/SEQUENCE

3-T, diffusion-MRI using q-space Cartesian grid sampling with 11 different b-values.

ASSESSMENT

Tumor multiregional MAP (mean squared displacement (MSD); q-space inverse variance (QIV); non-Gaussianity (NG); axial/radial non-Gaussianity (NGAx, NGRad); return-to-origin/axis/plane probability (RTOP, RTAP, and RTPP)); and DKI metrics (axial/mean/radial kurtosis (AK, MK, and RK)) on tumor parenchyma (TP) and peritumoral areas (PT) in histopathologically gliomas grading and genotyping were assessed.

STATISTICAL TESTS

Mann-Whitney U; Kruskal-Wallis; Benjamini-Hochberg; Bonferroni-correction; receiver operating curve (ROC) and area under curve (AUC); DeLong's test; Random Forest (RF). P value<0.05 was considered statistically significant after multiple comparisons correction.

RESULTS

Compared with LGGs, MSD, and QIV were significantly lower in TP, whereas NG, NGAx, NGRad, RTOP, RTAP, RTPP, and DKI metrics were significantly higher in HGGs (high-grade gliomas) (P ≤ 0.007), as well as in isocitrate-dehydrogenase (IDH)-mutated than IDH-wildtype gliomas (P ≤ 0.039). These trends were reversed for PT (tumor grades, P ≤ 0.011; IDH-mutation status, P ≤ 0.012). ROC analysis showed that, in TP, DKI metrics performed best in TP (AUC 0.83), whereas in PT, RTPP performed best (AUC 0.77) in glioma grading. AK performed best in TP (AUC 0.77), whereas MSD and RTPP performed best in PT (AUC 0.73) in IDH genotyping. Further RF analysis with DKI and MAP demonstrated good performance in grading (AUC 0.91, Accuracy 82%) and IDH genotyping (AUC 0.87, Accuracy 79%).

DATA CONCLUSION

Tumor multiregional MAP features could effectively evaluate gliomas. The performance of MAP may be similar to DKI in TP, while in PT, MAP may outperform DKI.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

Childhood and Adolescent Central Nervous System Tumours in Spain: Incidence and Survival over 20 Years: A Historical Baseline for Current Assessment

BACKGROUND

Central nervous system (CNS) neoplasms are highly frequent solid tumours in children and adolescents. While some studies have shown a rise in their incidence in Europe, others have not. Survival remains limited. We addressed two questions about these tumours in Spain: (1) Is incidence increasing? and (2) Has survival improved?

METHODS

This population-based study included 1635 children and 328 adolescents from 11 population-based cancer registries with International Classification of Childhood Cancer Group III tumours, incident in 1983-2007. Age-specific and age-standardised (world population) incidence rates (ASRws) were calculated. Incidence time trends were characterised using annual percent change (APC) obtained with Joinpoint. Cases from 1991 to 2005 (1171) were included in Kaplan-Meier survival analyses, and the results were evaluated with log-rank and log-rank for trend tests. Children's survival was age-standardised using: (1) the age distribution of cases and the corresponding trends assessed with Joinpoint; and (2) European weights for comparison with Europe.

RESULTS

ASRw 1983-2007: children: 32.7 cases/106; adolescents: 23.5 cases/106. The overall incidence of all tumours increased across 1983-2007 in children and adolescents. Considering change points, the APCs were: (1) children: 1983-1993, 4.3%^ (1.1; 7.7); 1993-2007, -0.2% (-1.9; 1.6); (2) adolescents: 1983-2004: 2.9%^ (0.9; 4.9); 2004-2007: -7.7% (-40; 41.9). For malignant tumours, the trends were not significant. 5-year survival was 65% (1991-2005), with no significant trends (except for non-malignant tumours).

CONCLUSIONS

CNS tumour incidence in Spain was found to be similar to that in Europe. Rises in incidence may be mostly attributable to changes in the registration of non-malignant tumours. The overall malignant CNS tumour trend was compatible with reports for Southern Europe. Survival was lower than in Europe, without improvement over time. We provide a baseline for assessing current paediatric oncology achievements and incidence in respect of childhood and adolescent CNS tumours.

Artificial intelligence in neuro-oncology

Artificial intelligence (AI) describes the application of computer algorithms to the solution of problems that have traditionally required human intelligence. Although formal work in AI has been slowly advancing for almost 70 years, developments in the last decade, and particularly in the last year, have led to an explosion of AI applications in multiple fields. Neuro-oncology has not escaped this trend. Given the expected integration of AI-based methods to neuro-oncology practice over the coming years, we set to provide an overview of existing technologies as they are applied to the neuropathology and neuroradiology of brain tumors. We highlight current benefits and limitations of these technologies and offer recommendations on how to appraise novel AI-tools as they undergo consideration for integration into clinical workflows.

Histone demethylase KDM4B accelerates the progression of glioblastoma via the epigenetic regulation of MYC stability

BACKGROUND

Glioblastoma (GBM) is the most malignant and invasive human brain tumor. Histone demethylase 4B (KDM4B) is abnormally expressed in GBM, but the molecular mechanisms by which KDM4B affects the malignant tumor progression are not well defined.

METHODS

GBM cell lines and xenograft tumor samples were subjected to quantitative PCR (qPCR), Western blot, immunohistochemical staining (IHC), as well as ubiquitination, immunoprecipitation (IP), and chromatin immunoprecipitation (ChIP) assays to investigate the role of KDM4B in the progression of GBM.

RESULTS

Here, we report that KDM4B is an epigenetic activator of GBM progression. Abnormal expression of KDM4B is correlated with a poor prognosis in GBM patients. In GBM cell lines, KDM4B silencing significantly inhibited cell survival, proliferation, migration, and invasion, indicating that KDM4B is essential for the anchorage-independent growth and tumorigenic activity of GBM cells. Mechanistically, KDM4B silencing led to downregulation of the oncoprotein MYC and suppressed the expression of cell cycle proteins and epithelial-to-mesenchymal transition (EMT)-related proteins. Furthermore, we found that KDM4B regulates MYC stability through the E3 ligase complex SCFFBXL3+CRY2 and epigenetically activates the transcription of CCNB1 by removing the repressive chromatin mark histone H3 lysine 9 trimethylation (H3K9me3). Finally, we provide evidence that KDM4B epigenetically activates the transcription of miR-181d-5p, which enhances MYC stability.

CONCLUSIONS

Our study has uncovered a KDM4B-dependent epigenetic mechanism in the control of tumor progression, providing a rationale for utilizing KDM4B as a promising therapeutic target for the treatment of MYC-amplified GBM.

Low-Grade Gliomas: Histological Subtypes, Molecular Mechanisms, and Treatment Strategies

Low-Grade Gliomas (LGGs) represent a diverse group of brain tumors originating from glial cells, characterized by their unique histopathological and molecular features. This article offers a comprehensive exploration of LGGs, shedding light on their subtypes, histological and molecular aspects. By delving into the World Health Organization's grading system, 5th edition, various specificities were added due to an in-depth understanding of emerging laboratory techniques, especially genomic analysis. Moreover, treatment modalities are extensively discussed. The degree of surgical resection should always be considered according to postoperative quality of life and cognitive status. Adjuvant therapies focused on chemotherapy and radiotherapy depend on tumor grading and invasiveness. In the current literature, emerging targeted molecular therapies are well discussed due to their succinctly therapeutic effect; in our article, those therapies are summarized based on posttreatment results and possible adverse effects. This review serves as a valuable resource for clinicians, researchers, and medical professionals aiming to deepen their knowledge on LGGs and enhance patient care.

Aquaporin 1 overexpression may enhance glioma tumorigenesis by interacting with the transcriptional regulation networks of Foxo4, Maz, and E2F families

BACKGROUND

The glioblastoma has served as a valuable experimental model system for investigating the growth and invasive properties of glioblastoma. Aquaporin-1 (AQP1) in facilitating cell migration and potentially contributing to tumor progression. In this study, we analyzed the role of AQP1 overexpression in glioblastoma and elucidated the main mechanisms involved.

METHODS

AQP1 overexpression recombinant vector was introduced into C6 rat glioma cells to construct an AQP1 overexpression C6 cell line, and its effect on cell viability and migration ability was detected by MTT and Transwell. RNA was extracted by Trizol method for gene sequencing and transcriptomics analysis, and the differentially expressed genes (DEGs) were enriched for up- and downregulated genes by Principal component analysis (PCA), and the molecular mechanism of AQP1 overexpression was analyzed in comparison with the control group using the NCBI GEO database. Statistical analysis was performed using Mann-Whitney paired two tailed t test.

RESULTS

The cell viability of AQP1-transfected cell lines increased by 23% and the mean distance traveled increased by 67% compared with the control group. Quantitative analysis of gene expression showed that there were 12,121 genes with an average transcripts per million (TPM) value greater than 1. DEGs accounted for 13% of the genes expressed, with the highest correlation with upregulated genes being FOXO4 and MAZ, and the highest with downregulated genes being E2F TFs.

CONCLUSIONS

AQP1 may be implicated in glioma formation by interacting with the transcriptional regulation networks involving the FOXO4, MAZ, and E2F1/2. These findings shed light on the potential significance of AQP1 in glioma pathogenesis and warrant further investigations to unravel the underlying molecular mechanisms.

MRI radiomics model for predicting TERT promoter mutation status in glioblastoma

BACKGROUND AND PURPOSE

The presence of TERT promoter mutations has been associated with worse prognosis and resistance to therapy for patients with glioblastoma (GBM). This study aimed to determine whether the combination model of different feature selections and classification algorithms based on multiparameter MRI can be used to predict TERT subtype in GBM patients.

METHODS

A total of 143 patients were included in our retrospective study, and 2553 features were obtained. The datasets were randomly divided into training and test sets in a ratio of 7:3. The synthetic minority oversampling technique was used to achieve data balance. The Pearson correlation coefficients were used for dimension reduction. Three feature selections and five classification algorithms were used to model the selected features. Finally, 10-fold cross validation was applied to the training dataset.

RESULTS

A model with eight features generated by recursive feature elimination (RFE) and linear discriminant analysis (LDA) showed the greatest diagnostic performance (area under the curve values for the training, validation, and testing sets: 0.983, 0.964, and 0.926, respectively), followed by relief and random forest (RF), analysis of variance and RF. Furthermore, the relief was the optimal feature selection for separately evaluating those five classification algorithms, and RF was the most preferable algorithm for separately assessing the three feature selectors. ADC entropy was the parameter that made the greatest contribution to the discrimination of TERT mutations.

CONCLUSIONS

Radiomics model generated by RFE and LDA mainly based on ADC entropy showed good performance in predicting TERT promoter mutations in GBM.

Knockdown of SLC39A14 inhibits glioma progression by promoting erastin-induced ferroptosis SLC39A14 knockdown inhibits glioma progression

BACKGROUND

Ferroptosis is a newly classified form of regulated cell death with implications in various tumor progression pathways. However, the roles and mechanisms of ferroptosis-related genes in glioma remain unclear.

METHODS

Bioinformatics analysis was employed to identify differentially expressed ferroptosis-related genes in glioma. The expression levels of hub genes were assessed using real-time reverse transcriptase-polymerase chain reaction (RT-qPCR). To explore the role of SLC39A14 in glioma, a series of in vitro assays were conducted, including cell counting kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU), flow cytometry, wound healing, and Transwell assays. Enzyme-linked immunosorbent assay (ELISA) was utilized to measure the levels of indicators associated with ferroptosis. Hematoxylin-eosin (HE) and immunohistochemistry (IHC) staining were performed to illustrate the clinicopathological features of the mouse transplantation tumor model. Additionally, Western blot analysis was used to assess the expression of the cGMP-PKG pathway-related proteins.

RESULTS

Seven ferroptosis-related hub genes, namely SLC39A14, WWTR1, STEAP3, NOTCH2, IREB2, HIF1A, and FANCD2, were identified, all of which were highly expressed in glioma. Knockdown of SLC39A14 inhibited glioma cell proliferation, migration, and invasion, while promoting apoptosis. Moreover, SLC39A14 knockdown also facilitated erastin-induced ferroptosis, leading to the suppression of mouse transplantation tumor growth. Mechanistically, SLC39A14 knockdown inhibited the cGMP-PKG signaling pathway activation.

CONCLUSION

Silencing SLC39A14 inhibits ferroptosis and tumor progression, potentially involving the regulation of the cGMP-PKG signaling pathway.

Unveiling a Biomarker Signature of Meningioma: The Need for a Panel of Genomic, Epigenetic, Proteomic, and RNA Biomarkers to Advance Diagnosis and Prognosis

Meningiomas are the most prevalent primary intracranial tumors. The majority are benign but can undergo dedifferentiation into advanced grades classified by World Health Organization (WHO) into Grades 1 to 3. Meningiomas' tremendous variability in tumor behavior and slow growth rates complicate their diagnosis and treatment. A deeper comprehension of the molecular pathways and cellular microenvironment factors implicated in meningioma survival and pathology is needed. This review summarizes the known genetic and epigenetic aberrations involved in meningiomas, with a focus on neurofibromatosis type 2 (NF2) and non-NF2 mutations. Novel potential biomarkers for meningioma diagnosis and prognosis are also discussed, including epigenetic-, RNA-, metabolomics-, and protein-based markers. Finally, the landscape of available meningioma-specific animal models is overviewed. Use of these animal models can enable planning of adjuvant treatment, potentially assisting in pre-operative and post-operative decision making. Discovery of novel biomarkers will allow, in combination with WHO grading, more precise meningioma grading, including meningioma identification, subtype determination, and prediction of metastasis, recurrence, and response to therapy. Moreover, these biomarkers may be exploited in the development of personalized targeted therapies that can distinguish between the 15 diverse meningioma subtypes.

Predictors for delayed awakening in adult glioma patients receiving awake craniotomy under monitored anesthesia care

PURPOSE

Delayed awakening after anesthetic discontinuation during awake craniotomy is associated with somnolence during functional brain mapping. However, predictors of delayed awakening in patients receiving monitored anesthesia care for awake craniotomy are unknown.

METHODS

This retrospective cohort study analyzed 117 adult patients with supratentorial glioma in or near eloquent areas who received monitored anesthesia care for awake craniotomy between July 2020 and January 2023 at Linkou Chang Gung Memorial Hospital. These patients were divided into two groups according to their time to awakening (ability to speak their names) after propofol cessation: longer or shorter than 20 min (median duration). Because propofol was solely used anesthetic from skin incision to dural opening, parameters in Schnider model for propofol target-controlled infusion, such as age, sex, and BMI, were adjusted or propensity-matched to compare their anesthetic, surgical, and histopathological profiles.

RESULTS

After propensity-matched comparisons of age and BMI, significant predictors of delayed awakening included IDH1 wild-type tumors and repeated craniotomies. Subgroup analysis revealed that older age and larger T2 volume were predictors in patients undergoing the first craniotomy, while lower preoperative Karnofsky performance scale scores and depression were predictors in repeated craniotomy cases. Delayed awakening was also associated with somnolence and a lower gross total resection rate.

CONCLUSION

Our retrospective analysis of patients receiving monitored anesthesia care for awake craniotomy revealed that delayed awakening after propofol discontinuation occurred more often in patients with IDH1 wild-type tumors and repeated craniotomies. Also, delayed awakening was associated with somnolence during functional mapping and a lower gross total resection rate.

Cancer vaccine strategies for the treatment of diffusely infiltrating gliomas

Diffusely infiltrating gliomas - including glioblastoma (GBM), isocitrate dehydrogenase (IDH) mutant gliomas, and histone 3 (H3) altered gliomas - are primary brain tumors with an invariably fatal outcome. Despite advances in the understanding of their biology, standard, targeted and immune checkpoint inhibitor immunotherapies have proven ineffective in arresting their inexorable progression and associated morbidity and mortality. Recognizing the unique aspects of the immunogenicity of cancer cells, the last decade has seen the development and evaluation of vaccine-based therapies for the treatment of solid tumors, including gliomas. Here we review the current vaccine strategies for the treatment of GBM, IDH-mutant gliomas and diffuse midline glioma H3 K27M-altered. We discuss potential benefits and challenges of vaccine therapies in these specific patient populations.

GPR37 expression as a prognostic marker in gliomas: a bioinformatics-based analysis

BACKGROUND

Gliomas are the most frequently diagnosed primary brain tumors, and are associated with multiple molecular aberrations during their development and progression. GPR37 is an orphan G protein-coupled receptor (GPCR) that is implicated in different physiological pathways in the brain, and has been linked to various malignancies. The aim of this study was to explore the relationship between GPR37 gene expression and the clinicopathological factors, patient prognosis, tumor-infiltrating immune cell signature GSEA and methylation levels in glioma.

METHODS

We explored the diagnostic value, clinical relevance, and molecular function of GPR37 in glioma using TCGA, STRING, cBioPortal, Tumor Immunity Estimation Resource (TIMER) database and MethSurv databases. Besides, the "ssGSEA" algorithm was conducted to estimate immune cells infiltration abundance, with 'ggplot2' package visualizing the results. Immunohistochemical staining of clinical samples were used to verify the speculations of bioinformatics analysis.

RESULTS

GPR37 expression was significantly higher in the glioma tissues compared to the normal brain tissues, and was linked to poor prognosis. Functional annotation of GPR37 showed enrichment of ether lipid metabolism, fat digestion and absorption, and histidine metabolism. In addition, GSEA showed that GPR37 was positively correlated to the positive regulation of macrophage derived foam cell differentiation, negative regulation of T cell receptor signaling pathway, neuroactive ligand receptor interaction, calcium signaling pathway, and negatively associated with immunoglobulin complex, immunoglobulin complex circulating, ribosome and spliceosome mediated by circulating immunoglobulin etc. TIMER2.0 and ssGSEA showed that GPR37 expression was significantly associated with the infiltration of T cells, CD8 T cell, eosinophils, macrophages, neutrophils, NK CD56dim cells, NK cells, plasmacytoid DCs (pDCs), T helper cells and T effector memory (Tem) cells. In addition, high GPR37 expression was positively correlated with increased infiltration of M2 macrophages, which in turn was associated with poor prognosis. Furthermore, GPR37 was positively correlated with various immune checkpoints (ICPs). Finally, hypomethylation of the GPR37 promoter was associated with its high expression levels and poor prognosis in glioma.

CONCLUSION

GPR37 had diagnostic and prognostic value in glioma. The possible biological mechanisms of GPR37 provide novel insights into the clinical diagnosis and treatment of glioma.

Multiple ossified intracranial and spinal meningiomas: a rare case report and literature review

Ossified intracranial meningiomas (OIM) and ossified spinal meningiomas (OSM) are rare neoplasms of mesenchymal origin that predominantly manifest in the spinal cord and infrequently in the cranial region, accounting for ~0. 7-5.5% of all meningiomas. It is extremely rare to have multiple intracranial and spinal lesions accompanied by ossification. Herein, we report this rare case for the first time. A 34-year-old woman presented with paresthesia and limb weakness in the right lower limb and gradually worsened. Approximately half a year later, she could only walk with crutches. Magnetic resonance imaging of the brain and spinal cord showed multiple meningiomas, and histopathological examination confirmed multiple OIM and OSM (WHO grade 1). Multiple OIM and OSM are extremely rare with diverse imaging features, and it is easily confused with other tumors. Histopathological examination is the final diagnostic method.

ARPC5 acts as a potential prognostic biomarker that is associated with cell proliferation, migration and immune infiltrate in gliomas

BACKGROUND

Gliomas are the most common malignant brain tumors, with powerful invasiveness and an undesirable prognosis. Actin related protein 2/3 complex subunit 5 (ARPC5) encodes a component of the Arp2/3 protein complex, which plays a significant role in regulating the actin cytoskeleton. However, the prognostic values and biological functions of ARPC5 in gliomas remain unclear.

METHODS

Based on the TCGA, GEO, HPA, and UALCAN database, we determined the expression of ARPC5 in glioma. The results were verified by immunohistochemistry and Western blot analysis of glioma samples. Moreover, Kaplan-Meier curves, ROC curves, Cox regression analyses, and prognostic nomograms were used to observe the correlation between the ARPC5 expression and the prognosis of glioma patients. GO and KEGG enrichment analyses were conducted to identify immune-related pathways involved with the differential expression of ARPC5. Subsequently, the TCGA database was used to estimate the relationship between ARPC5 expression and immunity-related indexes, such as immune scores, infiltrating immune cells, and TMB. The TCIA database was used to assess the correlation between ARPC5 with immunotherapy. The association between ARPC5 and T cells marker CD3 was also evaluated through immunohistochemistry methods. The correlation between ARPC5 and T cell, as well as the prognosis of patients, was also evaluated using immunological methods. Moreover, the effect of ARPC5 on the biological characteristics of LN229 and U251 cells was determined by MTT, clone formation, and transwell migration assay.

RESULTS

The high degree of ARPC5 was correlated with worse prognosis and unfavorable clinical characteristics of glioma patients. In the analysis of GO and KEGG, it is shown that ARPC5 was strongly correlated with multiple immune-related signaling pathways. The single-cell analysis revealed that ARPC5 expression was increased in astrocytes, monocytes and T cells. In addition, ARPC5 expression was strongly associated with immune scores, infiltrating immune cells, TMB, MSI, immune biomarkers, and immunotherapy. In experimental analysis, we found that ARPC5 was significantly overexpressed in gliomas and closely correlated with patient prognosis and CD3 expression. Functionally, the knockout of ARPC5 significantly reduced the proliferation and invasion of LN229 and U251 cells.

CONCLUSIONS

Our study revealed that the high expression level of ARPC5 may serve as a promising prognostic biomarker and be associated with tumor immunity in glioma.

Meningioma: A Biography-Tumor Forever Tied to the Origins and "Soul of Neurosurgery"

Meningiomas are neoplasms derived from the arachnoid cap cells of the leptomeninges and are the most common intracranial tumor. In the present historical vignette, the evolution of the management and diagnosis of meningioma is described. We begin with studies of skulls from the prehistoric record, such as the Steinheim skull, which demonstrate morphologic changes (e.g., hyperostosis) now known to occur with meningioma growth. We then continue with the earliest formal descriptions of meningiomas, including that by Platter, who published the first report of meningioma, along with early histopathologic descriptions by Cushing, who divined the cytological origins of the tumor and was the first to use the term meningioma. We conclude with a description of current management of meningiomas and potential avenues for further discovery. This article is effectively a lifetime biography of a tumor known and loved by neurosurgeons, the simple and yet complex meningioma.

Disease-Based Prognostication: Neuro-Oncology

Primary malignant and non-malignant brain and other central nervous system (CNS) tumors, while relatively rare, are a disproportionate source of morbidity and mortality. Here we provide a brief overview of approaches to modeling important clinical outcomes, such as overall survival, that are critical for clinical care. Because there are a large number of histologically distinct types of primary malignant and non-malignant brain and other CNS tumors, this chapter will provide an overview of prognostication considerations on the most common primary non-malignant brain tumor, meningioma, and the most common primary malignant brain tumor, glioblastoma. In addition, information on nomograms and how they can be used as individualized prognostication tools by clinicians to counsel patients and their families regarding treatment, follow-up, and prognosis is described. The current state of nomograms for meningiomas and glioblastomas are also provided.

Initial Treatment of IDH-Wildtype Glioblastoma in Adults Older Than 70 Years

The incidence of glioblastoma, the most common malignant primary brain tumour in adults, increases after the age of 40 and peaks in adults aged 75-84 years. Initial management involves maximising surgical resection while preserving neurologic function. IDH mutations and MGMT promoter methylation should be checked in tumour samples. Radiation and temozolomide constitute initial treatment for newly diagnosed glioblastoma patients with good functional status. It is suggested that patients who have received concurrent and adjuvant temozolomide treatment should undergo six cycles of adjuvant monthly temozolomide, as opposed to a more extended treatment regimen. Low-intensity alternating electric field therapy improved survival in a large randomised trial. We provide a detailed review, providing the latest treatment viewpoint for IDH-wildtype glioblastoma and including the current situation of immunotherapy. The treatment ideas and methods reviewed here would be of help to physicians when they encounter patients with this kind of IDH-wildtype glioblastoma in clinical practice.

The evaluation of six genes combined value in glioma diagnosis and prognosis

PURPOSE

Glioma is the most common and fatal type of brain tumour. Owing to its aggressiveness and lethality, early diagnosis and prediction of patient survival are very important. This study aimed to identify key genes and biomarkers for glioma that can guide clinicians in making rapid diagnosis and prognostication.

METHODS

Data mining of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Repository of Molecular Brain Neoplasia Data, and Genotype-Tissue Expression Project brain expression data revealed significantly differentially expressed genes (DEGs), and the risk scores of individual patients were calculated. WGCNA was utilized to screen for genes most related to clinical diagnosis. Prognostic genes associated with glioma were selected via combining the LASSO regression with univariate and multivariate Cox regression and protein-protein interaction network analyses. Then, a nomogram was constructed. And CGGA dataset was utilized to validated. The protein expression levels of the signature were detected using the human protein atlas. Drug response prediction was carried out using the package "pRRophetic".

RESULTS

A six-gene signature (KLF6, CHI3L1, SERPINE1, ANGPT2, TGFBR1, and PTX3) was identified and used to stratify patients into low- and high-risk groups. Survival, ROC curve, and Cox analyses clarified that the six hub genes were a favourable independent prognostic factor for patients with glioma. A nomogram was set up by integrating clinical parameters with risk signatures, showing high precision for predicting 2-, 3-, 4-, 5-years survival. In addition, the expression of most genes was consistent with protein expression. Furthermore, the sensitivity to the top ten drugs in the GDSC database of the high-risk group was significantly higher than the low-risk group.

CONCLUSION

Based on genetic profiles and clinicopathological features, including age, grade, isocitrate dehydrogenase mutation status, we constructed a comprehensive prognostic model for patients with glioma. These signatures can be regarded as biomarkers to predict the prognosis of gliomas, possibly providing more therapeutic strategies for future clinical research.

Clinicopathological significance of concurrent ErbB receptor expression in human meningioma

In general, human meningiomas grow slowly and have a favourable prognosis; however, some are prone to recur despite their benign histology. Therefore, knowledge of their tumour biology is essential to determine objective biomarkers that can identify cases with an increased risk for recurrence and to generate effective treatment options. Thus, studies on the epidermal growth factor receptor (EGFR) family, comprising ErbB1/EGFR, ErbB2/HER2, ErbB3/HER3 and ErbB4/HER4, are important. We have recently published papers on the expression of each of these receptor proteins in human meningiomas. The present study aimed to assess the clinicopathological significance of their concurrent expression. A total of 185 grade 1 and 2 meningiomas with robust clinical data underwent immunohistochemical analyses with antibodies against the aforementioned receptors. All meningiomas exhibited upregulation of these receptor proteins relative to normal meninges. In addition, the expression of phosphorylated/activated ErbB1/EGFR1 and phosphorylated/activated ErbB2/HER2 was significantly associated with histological malignancy grade and prognosis, respectively. The concurrent upregulation of ErbB receptors in human meningioma supports their fundamental role in the tumourigenesis of these tumours, and they could thus be exploited in diagnostics, prognosis, and ultimately, in targeted clinical interventions.

Multi-parameter MRI based radiomics nomogram for predicting telomerase reverse transcriptase promoter mutation and prognosis in glioblastoma

Objective

To investigate the clinical utility of multi-parameter MRI-based radiomics nomogram for predicting telomerase reverse transcriptase (TERT) promoter mutation status and prognosis in adult glioblastoma (GBM).

Methods

We retrospectively analyzed MRI and pathological data of 152 GBM patients. A total of 2,832 radiomics features were extracted and filtered from preoperative MRI images. A radiomics nomogram was created on the basis of radiomics signature (rad-score) and clinical traits. The performance of the nomogram in TERT mutation identification was assessed using receiver operating characteristic (ROC) curve, calibration curves, and clinical decision curves. Pathologically confirmed TERT mutations and risk score-based TERT mutations were employed to assess patient prognosis, respectively.

Results

The random forest (RF) algorithm outperformed the other two algorithms, yielding the best diagnostic efficacy in differentiating TERT mutations, with area under the curve (AUC) values of 0.892 (95% CI: 0.828-0.956) and 0.824 (95% CI: 0.677-0.971) in the training set and validation sets, respectively. Furthermore, the predictive power of the radiomics nomogram constructed with the rad-score and clinical variables reached 0.916 (95%CI: 0.864, 0.968) in the training set and 0.880 (95%CI: 0.743, 1) in the validation set. Calibration curve and decision curve analysis findings further uphold the clinical application value of the radiomics nomogram. The overall survival of the high-risk subgroup was significantly shorter than that of the low-risk subgroup, which was consistent with the results of the pathologically confirmed TERT mutation group.

Conclusion

The radiomics nomogram could non-invasively provide promising insights for predicting TERT mutations and prognosis in GBM patients with excellent identification and calibration abilities.

Exploration of the radiosensitivity-related prognostic risk signature in patients with glioma: evidence from microarray data

BACKGROUND

Gene expression signatures can be used as prognostic biomarkers in various types of cancers. We aim to develop a gene signature for predicting the response to radiotherapy in glioma patients.

METHODS

Radio-sensitive and radio-resistant glioma cell lines (M059J and M059K) were subjected to microarray analysis to screen for differentially expressed mRNAs. Additionally, we obtained 169 glioblastomas (GBM) samples and 5 normal samples from The Cancer Genome Atlas (TCGA) database, as well as 80 GBM samples and 4 normal samples from the GSE7696 set. The "DESeq2" R package was employed to identify differentially expressed genes (DEGs) between the normal brain samples and GBM samples. Combining the prognostic-related molecules identified from the TCGA, we developed a radiosensitivity-related prognostic risk signature (RRPRS) in the training set, which includes 152 patients with glioblastoma. Subsequently, we validated the reliability of the RRPRS in a validation set containing 616 patients with glioma from the TCGA database, as well as an internal validation set consisting of 31 glioblastoma patients from the Nanfang Hospital, Southern Medical University.

RESULTS

Based on the microarray and LASSO COX regression analysis, we developed a nine-gene radiosensitivity-related prognostic risk signature. Patients with glioma were divided into high- or low-risk groups based on the median risk score. The Kaplan-Meier survival analysis showed that the progression-free survival (PFS) of the high-risk group was significantly shorter. The signature accurately predicted PFS as assessed by time-dependent receiver operating characteristic curve (ROC) analyses. Stratified analysis demonstrated that the signature is specific to predict the outcome of patients who were treated using radiotherapy. Univariate and multivariate Cox regression analysis revealed that the predictor was an independent predictor for the prognosis of patients with glioma. The prognostic nomograms accompanied by calibration curves displayed the 1-, 2-, and 3-year PFS and OS in patients with glioma.

CONCLUSION

Our study established a new nine-gene radiosensitivity-related prognostic risk signature that can predict the prognosis of patients with glioma who received radiotherapy. The nomogram showed great potential to predict the prognosis of patients with glioma treated using radiotherapy.

Cell-Free miRNAs as Non-Invasive Biomarkers in Brain Tumors

Diagnosing brain tumors, especially malignant variants, such as glioblastoma, medulloblastoma, or brain metastasis, presents a considerable obstacle, while current treatment methods often yield unsatisfactory results. The monitoring of individuals with brain neoplasms becomes burdensome due to the intricate tumor nature and associated risks of tissue biopsies, compounded by the restricted accuracy and sensitivity of presently available non-invasive diagnostic techniques. The uncertainties surrounding diagnosis and the tumor's reaction to treatment can lead to delays in critical determinations that profoundly influence the prognosis of the disease. Consequently, there exists a pressing necessity to formulate and validate dependable, minimally invasive biomarkers that can effectively diagnose and predict brain tumors. Cell-free microRNAs (miRNAs), which remain stable and detectable in human bodily fluids, such as blood and cerebrospinal fluid (CSF), have emerged as potential indicators for a range of ailments, brain tumors included. Numerous investigations have showcased the viability of profiling cell-free miRNA expression in both CSF and blood samples obtained from patients with brain tumors. Distinct miRNAs demonstrate varying expression patterns within CSF and blood. While cell-free microRNAs in the blood exhibit potential in diagnosing, prognosticating, and monitoring treatment across diverse tumor types, they fall short in effectively diagnosing brain tumors. Conversely, the cell-free miRNA profile within CSF demonstrates high potential in delivering precise and specific evaluations of brain tumors.

Actionable molecular alterations in newly diagnosed and recurrent IDH1/2 wild-type glioblastoma patients and therapeutic implications: a large mono-institutional experience using extensive next-generation sequencing analysis

BACKGROUND

Next-generation sequencing (NGS) panels enable the identification of alterations in cancer-related genes. This may guide a molecularly targeted strategy for the treatment of glioblastoma (GBM).

MATERIAL AND METHODS

We retrospectively analysed data obtained using FoundationOne®CDx in a large cohort of IDH1/2 wild-type GBM. We aimed to 1) identify potentially actionable molecular alterations at diagnosis and/or recurrence based on ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) defined categories of targetability, 2) understand the clinical implications of NGS in terms of access to and activity of targeted therapies.

RESULTS

In 442 samples, an NGS profile was available in 98.2%. The median time from diagnosis to NGS profiling was 7.4 months (interquartile range (IQR): 3.4-13.2). Although about half of the patients had at least one actionable molecular alteration, only 3.4% of them were classified as ESCAT IB-IC and 6.7% as ESCAT IIB. Only 36 patients (10.5%) received personalised treatment in clinical trials or as off-label/compassionate use from second-line (median line 3). Most patients did not receive targeted therapy due to clinical deterioration/death (49.6%). Patients treated with dabrafenib/trametinib (9 patients) had the highest disease control rate of 77% and an objective response rate of 22%, with a median progression-free survival (PFS) of 5.2 months. No complete/partial responses were seen with the other regimens. 4/9 (44.4%) patients on anti-BRAF/anti-MEK, 2/4 patients (50%) on erdafitinib and 1/1 patient on capmatinib had a PFS ratio > 1.3. One recurrent GBM patient with ROS1-GOCP fusion maintained a complete response for 11.3 months on entrectinib.

CONCLUSIONS

Our study demonstrated the feasibility of NGS in GBM samples. As the number of clinically relevant targets was limited and only a small group of GBM patients were treated with targeted therapy, NGS testing should be performed in the context of clinical trials. Our results support the activity of anti-BRAF/anti-MEK, while for the other agents prospective study results are needed to draw solid conclusions.

NeuroD4 converts glioblastoma cells into neuron-like cells through the SLC7A11-GSH-GPX4 antioxidant axis

Cell fate and proliferation ability can be transformed through reprogramming technology. Reprogramming glioblastoma cells into neuron-like cells holds great promise for glioblastoma treatment, as it induces their terminal differentiation. NeuroD4 (Neuronal Differentiation 4) is a crucial transcription factor in neuronal development and has the potential to convert astrocytes into functional neurons. In this study, we exclusively employed NeuroD4 to reprogram glioblastoma cells into neuron-like cells. In vivo, the reprogrammed glioblastoma cells demonstrated terminal differentiation, inhibited proliferation, and exited the cell cycle. Additionally, NeuroD4 virus-infected xenografts exhibited smaller sizes compared to the GFP group, and tumor-bearing mice in the GFP+NeuroD4 group experienced prolonged survival. Mechanistically, NeuroD4 overexpression significantly reduced the expression of SLC7A11 and Glutathione peroxidase 4 (GPX4). The ferroptosis inhibitor ferrostatin-1 effectively blocked the NeuroD4-mediated process of neuron reprogramming in glioblastoma. To summarize, our study demonstrates that NeuroD4 overexpression can reprogram glioblastoma cells into neuron-like cells through the SLC7A11-GSH-GPX4 signaling pathway, thus offering a potential novel therapeutic approach for glioblastoma.

Atypical radiological aspect of meningioma: Web-like enhancement

Meningiomas are the most common extra-axial neoplasmof the central nervous system (CNS). There are a number of characteristic imaging features of meningiomas on magnetic resonance imaging (MRI) that allow an accurate diagnosis, however there are a number of atypical features that may be diagnostically challenging. Furthermore, a number of other neoplastic and non-neoplastic conditions may mimic meningiomas. This case highlights the importance of careful analysis of imaging findings and the need for consideration of all possible diagnoses, including rare or atypical presentations of common neoplasms such as meningiomas. Early detection and accurate diagnosis are crucial in determining the appropriate management and improving the outcomes for patients with intracranial tumors.

Discrimination Between Glioblastoma and Solitary Brain Metastasis Using Conventional MRI and Diffusion-Weighted Imaging Based on a Deep Learning Algorithm

This study aims to develop and validate a deep learning (DL) model to differentiate glioblastoma from single brain metastasis (BM) using conventional MRI combined with diffusion-weighted imaging (DWI). Preoperative conventional MRI and DWI of 202 patients with solitary brain tumor (104 glioblastoma and 98 BM) were retrospectively obtained between February 2016 and September 2022. The data were divided into training and validation sets in a 7:3 ratio. An additional 32 patients (19 glioblastoma and 13 BM) from a different hospital were considered testing set. Single-MRI-sequence DL models were developed using the 3D residual network-18 architecture in tumoral (T model) and tumoral + peritumoral regions (T&P model). Furthermore, the combination model based on conventional MRI and DWI was developed. The area under the receiver operating characteristic curve (AUC) was used to assess the classification performance. The attention area of the model was visualized as a heatmap by gradient-weighted class activation mapping technique. For the single-MRI-sequence DL model, the T2WI sequence achieved the highest AUC in the validation set with either T models (0.889) or T&P models (0.934). In the combination models of the T&P model, the model of DWI combined with T2WI and contrast-enhanced T1WI showed increased AUC of 0.949 and 0.930 compared with that of single-MRI sequences in the validation set, respectively. And the highest AUC (0.956) was achieved by combined contrast-enhanced T1WI, T2WI, and DWI. In the heatmap, the central region of the tumoral was hotter and received more attention than other areas and was more important for differentiating glioblastoma from BM. A conventional MRI-based DL model could differentiate glioblastoma from solitary BM, and the combination models improved classification performance.

The role of radiation therapy and systemic treatments in meningioma: The present and the future

Meningiomas are the most prevalent tumors of the central nervous system. Their standard treatment is surgery, which can be curative. Adjuvant radiotherapy treatment is reserved for newly diagnosed cases of grade II and grade III meningiomas in cases of recurrent disease or when surgery is not radical or feasible. However, around 20% of these patients cannot undergo further surgical and/or radiotherapy treatment. Systemic oncological therapy can find its place in this setting. Several tyrosine kinase inhibitors have been tested (gefitinib, erlotinib, sunitinib) with unsatisfactory or negative results. Bevacizumab has shown encouraging results in these settings of patients. Immunotherapy with immune checkpoint inhibitors has reported interesting results with modest objective response rates. Several ongoing studies are assessing different target therapies and multimodal therapies; the results are to be disclosed. Not only a better understanding of the molecular characteristics in meningiomas has allowed the gathering of more information regarding pathogenesis and prognosis, but in addition, the availability of new target therapy, immunotherapy, and biological drugs has widened the scope of potentially effective treatments in this patient population. The aim of this review was to explore the radiotherapy and systemic treatments of meningioma with an analysis of ongoing trials and future therapeutic perspectives.

Imaging-Based Versus Pathologic Survival Stratifications of Diffuse Glioma According to the 2021 WHO Classification System

OBJECTIVE

Imaging-based survival stratification of patients with gliomas is important for their management, and the 2021 WHO classification system must be clinically tested. The aim of this study was to compare integrative imaging- and pathology-based methods for survival stratification of patients with diffuse glioma.

MATERIALS AND METHODS

This study included diffuse glioma cases from The Cancer Genome Atlas (training set: 141 patients) and Asan Medical Center (validation set: 131 patients). Two neuroradiologists analyzed presurgical CT and MRI to assign gliomas to five imaging-based risk subgroups (1 to 5) according to well-known imaging phenotypes (e.g., T2/FLAIR mismatch) and recategorized them into three imaging-based risk groups, according to the 2021 WHO classification: group 1 (corresponding to risk subgroup 1, indicating oligodendroglioma, isocitrate dehydrogenase [IDH]-mutant, and 1p19q-co-deleted), group 2 (risk subgroups 2 and 3, indicating astrocytoma, IDH-mutant), and group 3 (risk subgroups 4 and 5, indicating glioblastoma, IDHwt). The progression-free survival (PFS) and overall survival (OS) were estimated for each imaging risk group, subgroup, and pathological diagnosis. Time-dependent area-under-the receiver operating characteristic analysis (AUC) was used to compare the performance between imaging-based and pathology-based survival model.

RESULTS

Both OS and PFS were stratified according to the five imaging-based risk subgroups (P < 0.001) and three imaging-based risk groups (P < 0.001). The three imaging-based groups showed high performance in predicting PFS at one-year (AUC, 0.787) and five-years (AUC, 0.823), which was similar to that of the pathology-based prediction of PFS (AUC of 0.785 and 0.837). Combined with clinical predictors, the performance of the imaging-based survival model for 1- and 3-year PFS (AUC 0.813 and 0.921) was similar to that of the pathology-based survival model (AUC 0.839 and 0.889).

CONCLUSION

Imaging-based survival stratification according to the 2021 WHO classification demonstrated a performance similar to that of pathology-based survival stratification, especially in predicting PFS.

Glioblastoma with a primitive neuronal component: A case report

The present study describes a rare case of glioblastoma with a primitive neuronal component (GBM-PNC), and provides an in-depth analysis of the clinical, pathological and differential diagnostic findings. A comprehensive literature review was conducted to enhance the understanding of GBM-PNC, revealing its distinct characteristics and prognostic implications. A 57-year-old woman presented with acute onset headache, nausea and vomiting, leading to the identification of an intracranial mass through magnetic resonance imaging. Surgical resection revealed the coexistence of a glial component and a PNC within the tumor. Immunohistochemical analysis detected the expression of glial fibrillary acidic protein in the glial component and synaptin in the PNC. The pathological diagnosis confirmed the presence of GBM-PNC. Gene detection analysis revealed no mutations in isocitrate dehydrogenase (IDH)1 and IDH2, and neurotrophic tyrosine kinase receptor-1 (NTRK1), NTRK2 and NTRK3 genes. GBM-PNC is characterized by a propensity for recurrence and metastasis, with a low 5-year survival rate. The present case report highlights the importance of accurate diagnosis and comprehensive characterization of GBM-PNC to guide treatment decisions and improve patient outcomes.

PRO Hair Safe Study: The Patient's Perspective on the Effects of Scalp Cooling on Hair Preservation

Purpose

Alopecia has been reported a distressing side-effect of chemotherapy for breast cancer patients (BCP) that is highly relevant for quality of life during treatment. For the prevention of chemotherapy-induced alopecia, scalp cooling (SC) has been reported to be an effective and safe intervention. However, data on the patient's perspective on effectiveness and applicability of SC in a clinical routine setting are scarce. In this comparative study, we aimed at a longitudinal assessment of patient-reported outcome (PRO) data on the effect of SC on alopecia and its effect on symptoms and functional health when applied in clinical routine in BCP receiving taxane or anthracycline-based chemotherapy.

Patients and Methods

Study participants were allocated either to the intervention group receiving SC or to the control group based on patient preference (non-randomized study). All patients completed PRO-measures on hair preservation (EORTC Item Library items on hair loss), symptom and functional health measures (EORTC QLQ-C30 and -BR23) and the Body Image Scale (BIS). Outcomes were assessed at chemotherapy start (baseline), mid-chemotherapy, last chemotherapy cycle, 3 months follow-up and 6-9 months follow-up.

Results

Overall, we included 113 patients: 75 patients underwent SC (mean age = 51.3 years, 52.7% premenopausal); 38 patients standard care (mean age = 55.6 years, 39.5% premenopausal). A total of 53 patients (70.7%) discontinued SC, with 39 patients (73.5%) stating alopecia as the primary reason. On average, BCP stayed on treatment with the cooling cap for 40.2% of the duration of their chemotherapy (SD 25.3%). In an intention-to-treat analysis, we found no difference between the SC group and the control group with regard to their patient-reported hair loss (p=0.831) across the observation period, overall QOL (p=0.627), emotional functioning (p=0.737), social functioning (p=0.635) and body image (p=0.463) did not differ between groups.

Conclusion

We found a high rate of SC-decliners and no beneficial effects of SC for patient-reported hair loss, symptoms and functional health. The efficacy and tolerability of SC applied in a clinical routine setting hence appeared to be limited. The further determination and up-front definition of criteria prognostic for effectiveness of SC may be helpful to identify patient subgroups that may experience a treatment benefit.

Efficacy and safety of innate and adaptive immunotherapy combined with standard of care in high-grade gliomas: a systematic review and meta-analysis

Background

Malignant glioma is the most common intracranial malignant tumor with the highest mortality. In the era of immunotherapy, it is important to determine what type of immunotherapy provides the best chance of survival.

Method

Here, the efficacy and safety of immunotherapy in high-grade glioma (HGG) were evaluated by systematic review and meta-analysis. The differences between various types of immunotherapy were explored. Retrieved hits were screened for inclusion in 2,317 articles. We extracted the overall survival (OS) and progression-free survival (PFS) hazard ratios (HRs) as two key outcomes for examining the efficacy of immunotherapy. We also analyzed data on the reported corresponding adverse events to assess the safety of immunotherapy. This study was registered with PROSPERO (CRD42019112356).

Results

We included a total of 1,271 patients, of which 524 received a combination of immunotherapy and standard of care (SOC), while 747 received SOC alone. We found that immunotherapy extended the OS (HR = 0.74; 95% confidence interval [CI], 0.56-0.99; Z = -2.00, P = 0.0458 < 0.05) and PFS (HR = 0.67; 95% CI, 0.45-0.99; Z = -1.99, P = 0.0466 < 0.05), although certain adverse events occurred (proportion = 0.0773, 95% CI, 0.0589-0.1014). Our data have demonstrated the efficacy of the dendritic cell (DC) vaccine in prolonging the OS (HR = 0.38; 95% CI, 0.21-0.68; Z = -3.23; P = 0.0012 < 0.05) of glioma patients. Oncolytic viral therapy (VT) only extended patient survival in a subgroup analysis (HR = 0.60; 95% CI, 0.45-0.80; Z = -3.53; P = 0.0004 < 0.05). By contrast, immunopotentiation (IP) did not prolong OS (HR = 0.69; 95% CI, 0.50-0.96; Z = -2.23; P = 0.0256).

Conclusion

Thus, DC vaccination significantly prolonged the OS of HGG patients, however, the efficacy of VT and IP should be explored in further studies. All the therapeutic schemes evaluated were associated with certain side effects.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=112356.

Medical Management of Meningiomas

Meningiomas represent the most common type of benign tumor of the extra-axial compartment. Although most meningiomas are benign World Health Organization (WHO) grade 1 lesions, the increasingly prevalent of WHO grade 2 lesion and occasional grade 3 lesions show worsened recurrence rates and morbidity. Multiple medical treatments have been evaluated but show limited efficacy. We review the status of medical management in meningiomas, highlighting successes and failures of various treatment options. We also explore newer studies evaluating the use of immunotherapy in management.

NUDT21 alters glioma migration through differential alternative polyadenylation of LAMC1

PURPOSE

Gliomas and their surrounding microenvironment constantly interact to promote tumorigenicity, yet the underlying posttranscriptional regulatory mechanisms that govern this interplay are poorly understood.

METHODS

Utilizing our established PAC-seq approach and PolyAMiner bioinformatic analysis pipeline, we deciphered the NUDT21-mediated differential APA dynamics in glioma cells.

RESULTS

We identified LAMC1 as a critical NUDT21 alternative polyadenylation (APA) target, common in several core glioma-driving signaling pathways. qRT-PCR analysis confirmed that NUDT21-knockdown in glioma cells results in the preferred usage of the proximal polyA signal (PAS) of LAMC1. Functional studies revealed that NUDT21-knockdown-induced 3'UTR shortening of LAMC1 is sufficient to cause translational gain, as LAMC1 protein is upregulated in these cells compared to their respective controls. We demonstrate that 3'UTR shortening of LAMC1 after NUDT21 knockdown removes binding sites for miR-124/506, thereby relieving potent miRNA-based repression of LAMC1 expression. Remarkably, we report that the knockdown of NUDT21 significantly promoted glioma cell migration and that co-depletion of LAMC1 with NUDT21 abolished this effect. Lastly, we observed that LAMC1 3'UTR shortening predicts poor prognosis of low-grade glioma patients from The Cancer Genome Atlas.

CONCLUSION

This study identifies NUDT21 as a core alternative polyadenylation factor that regulates the tumor microenvironment through differential APA and loss of miR-124/506 inhibition of LAMC1. Knockdown of NUDT21 in GBM cells mediates 3'UTR shortening of LAMC1, contributing to an increase in LAMC1, increased glioma cell migration/invasion, and a poor prognosis.

Insights into the Role of LncRNAs and miRNAs in Glioma Progression and Their Potential as Novel Therapeutic Targets

Accumulating evidence supports that both long non-coding and micro RNAs (lncRNAs and miRNAs) are implicated in glioma tumorigenesis and progression. Poor outcome of gliomas has been linked to late-stage diagnosis and mostly ineffectiveness of conventional treatment due to low knowledge about the early stage of gliomas, which are not possible to observe with conventional diagnostic approaches. The past few years witnessed a revolutionary advance in biotechnology and neuroscience with the understanding of tumor-related molecules, including non-coding RNAs that are involved in the angiogenesis and progression of glioma cells and thus are used as prognostic biomarkers as well as novel therapeutic targets. The emerging research on lncRNAs and miRNAs highlights their crucial role in glioma progression, offering new insights into the disease. These non-coding RNAs hold significant potential as novel therapeutic targets, paving the way for innovative treatment approaches against glioma. This review encompasses a comprehensive discussion about the role of lncRNAs and miRNAs in gene regulation that is responsible for the promotion or the inhibition of glioma progression and collects the existing links between these key cancer-related molecules.

Prediction of IDH1 gene mutation by a nomogram based on multiparametric and multiregional MR images

OBJECTIVE

To investigate the value of a nomogram based on multiparametric and multiregional MR images to predict Isocitrate Dehydrogenase-1 (IDH1) gene mutations in glioma.

DATA AND METHODS

The authors performed a retrospective analysis of 110 MR images of surgically confirmed pathological gliomas; 33 patients with IDH1 gene Mutation (IDH1-M) and 77 patients with Wild-type IDH1 (IDH1-W) were divided into training and validation sets in a 7:3 ratio. The clinical features were statistically analyzed using SPSS and R software. Three glioma regions (rCET, rE, rNEC) were outlined using ITK-SNAP software and projected to four conventional sequences (T1, T2, Flair, T1C) for feature extraction using AI-Kit software. The extracted features were screened using R software. A logistic regression model was established, and a nomogram was generated using the selected clinical features. Eight models were developed based on different sequences and ROIs, and Receiver Operating Characteristic (ROC) curves were used to evaluate the predictive efficacy. Decision curve analysis was performed to assess the clinical usefulness.

RESULTS

Age was selected with Radscore to construct the nomogram. The Model 1 AUC values based on four sequences and three ROIs were the highest in these models, at 0.93 and 0.89, respectively. Decision curve analysis indicated that the net benefit of model 1 was higher than that of the other models for most Pt-values.

CONCLUSION

A nomogram based on multiparametric and multiregional MR images can predict the mutation status of the IDH1 gene accurately.

The role of lysosomal peptidases in glioma immune escape: underlying mechanisms and therapeutic strategies

Glioblastoma is the most common primary malignant tumor of the central nervous system, which has the characteristics of strong invasion, frequent recurrence, and rapid progression. These characteristics are inseparable from the evasion of glioma cells from immune killing, which makes immune escape a great obstacle to the treatment of glioma, and studies have confirmed that glioma patients with immune escape tend to have poor prognosis. The lysosomal peptidase lysosome family plays an important role in the immune escape process of glioma, which mainly includes aspartic acid cathepsin, serine cathepsin, asparagine endopeptidases, and cysteine cathepsins. Among them, the cysteine cathepsin family plays a prominent role in the immune escape of glioma. Numerous studies have confirmed that glioma immune escape mediated by lysosomal peptidases has something to do with autophagy, cell signaling pathways, immune cells, cytokines, and other mechanisms, especially lysosome organization. The relationship between protease and autophagy is more complicated, and the current research is neither complete nor in-depth. Therefore, this article reviews how lysosomal peptidases mediate the immune escape of glioma through the above mechanisms and explores the possibility of lysosomal peptidases as a target of glioma immunotherapy.

FDX1 serves as a prognostic biomarker and promotes glioma progression by regulating the immune response

The present study investigates the prognostic value of the FDX1 gene and its association with immune infiltration in gliomas. Gene expression profiles and corresponding clinical parameters of glioma patients were obtained from the Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. In vitro experiments were also performed to validate its impact on malignant phenotypes of glioma cells. Kaplan-Meier analysis demonstrated that high FDX1 expression was associated with poor prognosis in glioma. Function and pathway enrichment for FDX1 predominantly demonstrated immunomodulatory function. In addition, the high-FDX1 expression group had higher Estimation of Stromal and Immune cells in malignant tumor tissues using Expression data, stromal, and immune scores (p<0.001). On evaluation of immunotherapy response, TIDE and dysfunction scores were higher in the low-FDX1 group, while the exclusion score demonstrated an opposite trend. In vitro tests showed that FDX1 silencing-induced inhibition of cell invasion and migration inactivated the nucleotide oligomerization domain (NOD)-like receptor signaling pathway by regulating PD-L1 expression. Notably, NOD1 expression was reversed in FDX1-knockdown cells after treatment with NOD1 agonists. In conclusion, FDX1 may play an important role in the diagnosis and treatment of gliomas. Regulating its expression may therefore help improve immunotherapy for these tumors.

Predicting Histopathological Grading of Adult Gliomas Based On Preoperative Conventional Multimodal MRI Radiomics: A Machine Learning Model

PURPOSE

The accurate preoperative histopathological grade diagnosis of adult gliomas is of great significance for the formulation of a surgical plan and the implementation of a subsequent treatment. The aim of this study is to establish a predictive model for classifying adult gliomas into grades 2-4 based on preoperative conventional multimodal MRI radiomics.

PATIENTS AND METHODS

Patients with pathologically confirmed gliomas at Huashan Hospital, Fudan University, between February 2017 and July 2019 were retrospectively analyzed. Two regions of interest (ROIs), called the maximum anomaly region (ROI1) and the tumor region (ROI2), were delineated on the patients' preoperative MRIs utilizing the tool ITK-SNAP, and Pyradiomics 3.0 was applied to execute feature extraction. Feature selection was performed utilizing a least absolute shrinkage and selection operator (LASSO) filter. Six classifiers, including Gaussian naive Bayes (GNB), random forest (RF), K-nearest neighbor (KNN), support vector machine (SVM) with a linear kernel, adaptive boosting (AB), and multilayer perceptron (MLP) were used to establish predictive models, and the predictive performance of the six classifiers was evaluated through five-fold cross-validation. The performance of the predictive models was evaluated using the AUC and other metrics. After that, the model with the best predictive performance was tested using the external data from The Cancer Imaging Archive (TCIA).

RESULTS

According to the inclusion and exclusion criteria, 240 patients with gliomas were identified for inclusion in the study, including 106 grade 2, 68 grade 3, and 66 grade 4 gliomas. A total of 150 features was selected, and the MLP classifier had the best predictive performance among the six classifiers based on T2-FLAIR (mean AUC of 0.80 ± 0.07). The SVM classifier had the best predictive performance among the six classifiers based on DWI (mean AUC of 0.84 ± 0.05); the SVM classifier had the best predictive performance among the six classifiers based on CE-T1WI (mean AUC of 0.85 ± 0.06). Among the six classifiers, based on ROI1, the MLP classifier had the best prediction performance (mean AUC of 0.78 ± 0.07); among the six classifiers, based on ROI2, the SVM classifier had the best prediction performance (mean AUC of 0.82 ± 0.07). Among the six classifiers, based on the multimodal MRI of all the ROIs, the SVM classifier had the best prediction performance (average AUC of 0.85 ± 0.04). The SVM classifier, based on the multimodal MRI of all the ROIs, achieved an AUC of 0.81 using the external data from TCIA.

CONCLUSIONS

The prediction model, based on preoperative conventional multimodal MRI radiomics, established in this study can conveniently, accurately, and noninvasively classify adult gliomas into grades 2-4, providing certain assistance for the precise diagnosis and treatment of patients and optimizing their clinical management.

A prognostic model based on the Augmin family genes for LGG patients

Gliomas are the most prevalent primary tumors in the central nervous system. Despite some breakthroughs in the treatment of glioma in recent years, survival rates remain low. Although genes of the Augmin family play a key role in microtubule nucleation, the role they play in gliomas is unclear. Transcriptome data were extracted from UCSC XENA and GTEx for low-grade glioma (LGG) and normal tissues, respectively. The protein interaction network associated with Augmin family genes was established using STRING and GeneMANIA databases. Enrichment analysis of gene-related functions and pathways was used to explore potential biological pathways and TIMER to assess immune cell infiltration. Regression analysis and Kaplan-Meier analysis were used to look at the clinical characteristics of the Augmin family genes and the association with the prognosis of patients with glioma. The results showed that the mRNA expression of Augmin family genes was significantly elevated in LGG tissues, except for HAUS7. Immunoregulation, cell cycle, apoptosis and other signaling pathways may be involved in the development and progression of LGG. Except for HAUS4 and HAUS7, the expression of all genes was positively correlated with immune cell infiltration. High expression of HAUS1, HAUS3, HAUS5, HAUS7, HAUS8 and low expression of HAUS4, HAUS6 in LGG was associated with poor prognosis. The risk models constructed based on the pivotal genes HAUS2, HAUS4 and HAUS8 were validated by nomogram and confirmed to be clinically useful for predicting the prognosis of LGG.

Spotlights on adult patients with pediatric-type diffuse gliomas in accordance with the 2021 WHO classification of CNS tumors

Introduction

The fifth edition of the World Health Organization (WHO) classification of central nervous system (CNS) tumors released in 2021 formally defines pediatric-type diffuse gliomas. However, there is still little understanding of pediatric-type diffuse gliomas, and even less attention has been paid to adult patients. Therefore, this study describes the clinical radiological, survival, and molecular features of adult patients with pediatric-type glioma.

Methods

Adult patients who underwent surgery from January 2011 to January 2022, classified as pediatric-type glioma, were included in this study. Clinical, radiological, histopathological, molecular pathological, and survival data were collected for analysis.

Results

Among 596 adult patients, 20 patients with pediatric-type glioma were screened, including 6 with diffuse astrocytoma, MYB- or MYBL1-altered, 2 with diffuse midline glioma, H3 K27-altered, and 12 with diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype. Pediatric high-grade glioma (pHGG) frequently showed tumor enhancement, peritumoral edema, and intratumoral necrosis. Adult patients with pHGG showed a longer life expectancy than adult patients with glioblastoma. Common molecular alterations included chromosome alterations and CDKN2A/B, PIK3CA, and PTEN, while altered KMT5B and MET were found to affect the overall survival.

Conclusion

Our study demonstrated adult patients with pediatric-type glioma. Notably, our research aims to expand the current understanding of adult patients with pediatric-type diffuse gliomas. Furthermore, personalized therapies consisting of targeted molecular inhibitors for MET and VEGFA may exhibit beneficial effects in the corresponding population.

Combination of multi-modal MRI radiomics and liquid biopsy technique for preoperatively non-invasive diagnosis of glioma based on deep learning: protocol for a double-center, ambispective, diagnostical observational study

Background

2021 World Health Organization (WHO) Central Nervous System (CNS) tumor classification increasingly emphasizes the important role of molecular markers in glioma diagnoses. Preoperatively non-invasive "integrated diagnosis" will bring great benefits to the treatment and prognosis of these patients with special tumor locations that cannot receive craniotomy or needle biopsy. Magnetic resonance imaging (MRI) radiomics and liquid biopsy (LB) have great potential for non-invasive diagnosis of molecular markers and grading since they are both easy to perform. This study aims to build a novel multi-task deep learning (DL) radiomic model to achieve preoperative non-invasive "integrated diagnosis" of glioma based on the 2021 WHO-CNS classification and explore whether the DL model with LB parameters can improve the performance of glioma diagnosis.

Methods

This is a double-center, ambispective, diagnostical observational study. One public database named the 2019 Brain Tumor Segmentation challenge dataset (BraTS) and two original datasets, including the Second Affiliated Hospital of Nanchang University, and Renmin Hospital of Wuhan University, will be used to develop the multi-task DL radiomic model. As one of the LB techniques, circulating tumor cell (CTC) parameters will be additionally applied in the DL radiomic model for assisting the "integrated diagnosis" of glioma. The segmentation model will be evaluated with the Dice index, and the performance of the DL model for WHO grading and all molecular subtype will be evaluated with the indicators of accuracy, precision, and recall.

Discussion

Simply relying on radiomics features to find the correlation with the molecular subtypes of gliomas can no longer meet the need for "precisely integrated prediction." CTC features are a promising biomarker that may provide new directions in the exploration of "precision integrated prediction" based on the radiomics, and this is the first original study that combination of radiomics and LB technology for glioma diagnosis. We firmly believe that this innovative work will surely lay a good foundation for the "precisely integrated prediction" of glioma and point out further directions for future research.

Clinical trail registration

This study was registered on ClinicalTrails.gov on 09/10/2022 with Identifier NCT05536024.

Risk of cardiac-related death in astrocytoma patients treated with chemotherapy: A competing risk analysis using the SEER database

Purpose

To explore the impact of chemotherapy on the risk of cardiac-related death in astrocytoma patients.

Methods

We retrospectively evaluated astrocytoma patients diagnosed between 1,975 and 2016 in the Surveillance, Epidemiology, and End Results (SEER) database. Using Cox proportional hazards models, we compared the risks of cardiac-related death between a chemotherapy group and non-chemotherapy group. Competing-risks regression analyses were used to evaluate the difference in cardiac-related death. Also, propensity score matching (PSM) was employed to reduce confounding bias. The robustness of these findings was evaluated by sensitivity analysis, and E values were calculated.

Results

A total of 14,834 patients diagnosed with astrocytoma were included. Chemotherapy (HR = 0.625, 95%CI: 0.444-0.881) was associated with cardiac-related death in univariate Cox regression analysis. Chemotherapy was an independent prognostic factor for a lower risk of cardiac-related death before (HR = 0.579, 95%CI: 0.409-0.82, P = 0.002) and after PSM (HR = 0.550, 95%CI: 0.367-0.823 P = 0.004). Sensitivity analysis determined that the E-value of chemotherapy was 2.848 and 3.038 before and after PSM.

Conclusions

Chemotherapy did not increase the risk of cardiac-related death in astrocytoma patients. This study highlights that cardio-oncology teams should provide comprehensive care and long-term monitoring for cancer patients, especially those with an increased risk of cardiovascular disease.

Review of meningioma diagnosis and management

Meningiomas are the most common intracranial tumors in adult patients. Although the majority of meningiomas are diagnosed as benign, approximately 20% of cases are high-grade tumors that require significant clinical treatment. The gold standard for grading central nervous system tumors comes from the World Health Organization Classification of Tumors of the central nervous system. Treatment options also depend on the location, imaging, and histopathological features of the tumor. This review will cover diagnostic strategies for meningiomas, including 2021 updates to the World Health Organization's grading of meningiomas. Meningioma treatment plans are variable and highly dependent on tumor grading. This review will also update the reader on developments in the treatment of meningiomas, including surgery, radiation therapy and monoclonal antibody treatment.

Hypermethylation of HIC2 is a potential prognostic biomarker and tumor suppressor of glioma based on bioinformatics analysis and experiments

INTRODUCTION

Glioma is the most common primary tumor in the central nervous system, and prognostic biomarkers are still lacking. HIC ZBTB transcriptional repressor 2 (HIC2) is a hypermethylated gene that plays an important functional role in cardiac development. However, the actual role of HIC2 in glioma progression remains unclear. This study aimed to investigate the function of HIC2 and whether it could be a prognostic biomarker in glioma.

METHODS

The DNA methylation and mRNA expression profiles of HIC2 were downloaded from public databases. The prognostic prediction ability and mechanism research of HIC2 were evaluated.

RESULTS

We found that HIC2 was hypermethylated and expressed at low levels in glioma samples. Hypermethylation and low expression of HIC2 predicted poor prognosis. Multivariate Cox regression analysis suggested that HIC2 was an independent prognostic factor for gliomas. Co-IP assays demonstrated that HIC2 interacts with RNF44, and dual-luciferase reporter assays and ChIP assays revealed that HIC2 transcriptionally inhibits PTPRN2 expression.

CONCLUSIONS

Our findings suggest that HIC2 represents a tumor suppressor gene and prognostic biomarker for glioma progression and that overexpression of HIC2 inhibits the proliferation of glioma in vitro and in vivo by interacting with RNF44 and PTPRN2.

Exosomes; multifaceted nanoplatform for targeting brain cancers

At the moment, anaplastic changes within the brain are challenging due to the complexity of neural tissue, leading to the inefficiency of therapeutic protocols. The existence of a cellular interface, namely the blood-brain barrier (BBB), restricts the entry of several macromolecules and therapeutic agents into the brain. To date, several nano-based platforms have been used in laboratory settings and in vivo conditions to overcome the barrier properties of BBB. Exosomes (Exos) are one-of-a-kind of extracellular vesicles with specific cargo to modulate cell bioactivities in a paracrine manner. Regarding unique physicochemical properties and easy access to various biofluids, Exos provide a favorable platform for drug delivery and therapeutic purposes. Emerging data have indicated that Exos enable brain penetration of selective cargos such as bioactive factors and chemotherapeutic compounds. Along with these statements, the application of smart delivery approaches can increase delivery efficiency and thus therapeutic outcomes. Here, we highlighted the recent advances in the application of Exos in the context of brain tumors.

Recapitulating the Key Advances in the Diagnosis and Prognosis of High-Grade Gliomas: Second Half of 2021 Update

High-grade gliomas (World Health Organization grades III and IV) are the most frequent and fatal brain tumors, with median overall survivals of 24–72 and 14–16 months, respectively. We reviewed the progress in the diagnosis and prognosis of high-grade gliomas published in the second half of 2021. A literature search was performed in PubMed using the general terms “radio* and gliom*” and a time limit from 1 July 2021 to 31 December 2021. Important advances were provided in both imaging and non-imaging diagnoses of these hard-to-treat cancers. Our prognostic capacity also increased during the second half of 2021. This review article demonstrates slow, but steady improvements, both scientifically and technically, which express an increased chance that patients with high-grade gliomas may be correctly diagnosed without invasive procedures. The prognosis of those patients strictly depends on the final results of that complex diagnostic process, with widely varying survival rates.

Clinical updates on gliomas and implications of the 5th edition of the WHO classification of central nervous system tumors

Background

The 5th edition of the World Health Organization (WHO) classification of central nervous system tumors incorporated specific molecular alterations into the categorization of gliomas. The major revision of the classification scheme effectuates significant changes in the diagnosis and management of glioma. This study aimed to depict the clinical, molecular, and prognostic characteristics of glioma and its subtypes according to the current WHO classification.

Methods

Patients who underwent surgery for glioma at Peking Union Medical College Hospital during 11 years were re-examined for tumor genetic alterations using next-generation sequencing, polymerase chain reaction-based assay, and fluorescence in situ hybridization methods and enrolled in the analysis.

Results

The enrolled 452 gliomas were reclassified into adult-type diffuse glioma (ntotal=373; astrocytoma, n=78; oligodendroglioma, n=104; glioblastoma, n=191), pediatric-type diffuse glioma (ntotal=23; low-grade, n=8; high-grade, n=15), circumscribed astrocytic glioma (n=20), and glioneuronal and neuronal tumor (n=36). The composition, definition, and incidence of adult- and pediatric-type gliomas changed significantly between the 4th and the 5th editions of the classification. The clinical, radiological, molecular, and survival characteristics of each subtype of glioma were identified. Alterations in CDK4/6, CIC, FGFR2/3/4, FUBP1, KIT, MET, NF1, PEG3, RB1, and NTRK2 were additional factors correlated with the survival of different subtypes of gliomas.

Conclusions

The updated WHO classification based on histology and molecular alterations has updated our understanding of the clinical, radiological, molecular, survival, and prognostic characteristics of varied subtypes of gliomas and provided accurate guidance for diagnosis and potential prognosis for patients.