Glioma.

Gliomas are primary brain tumours that are thought to develop from neural stem or progenitor cells that carry tumour-initiating genetic alterations. Based on microscopic appearance and molecular characteristics, they are classified according to the WHO classification of central nervous system (CNS) tumours and graded into CNS WHO grades 1-4 from a low to high grade of malignancy. Diffusely infiltrating gliomas in adults comprise three tumour types with distinct natural course of disease, response to treatment and outcome: isocitrate dehydrogenase (IDH)-mutant and 1p/19q-codeleted oligodendrogliomas with the best prognosis; IDH-mutant astrocytomas with intermediate outcome; and IDH-wild-type glioblastomas with poor prognosis. Pilocytic astrocytoma is the most common glioma in children and is characterized by circumscribed growth, frequent BRAF alterations and favourable prognosis. Diffuse gliomas in children are divided into clinically indolent low-grade tumours and high-grade tumours with aggressive behaviour, with histone 3 K27-altered diffuse midline glioma being the leading cause of glioma-related death in children. Ependymal tumours are subdivided into biologically and prognostically distinct types on the basis of histology, molecular biomarkers and location. Although surgery, radiotherapy and alkylating agent chemotherapy are the mainstay of glioma treatment, individually tailored strategies based on tumour-intrinsic dominant signalling pathways have improved outcome in subsets of patients.

The Clinical Utility of a Tiered Approach to Pediatric Glioma Molecular Characterization for Resource-Limited Settings.

PURPOSE: Molecular characterization is key to optimally diagnose and manage cancer. The complexity and cost of routine genomic analysis have unfortunately limited its use and denied many patients access to precision medicine. A possible solution is to rationalize use-creating a tiered approach to testing which uses inexpensive techniques for most patients and limits expensive testing to patients with the highest needs. Here, we tested the utility of this approach to molecularly characterize pediatric glioma in a cost- and time-sensitive manner. METHODS: We used a tiered testing pipeline of immunohistochemistry (IHC), customized fusion panels or fluorescence in situ hybridization (FISH), and targeted RNA sequencing in pediatric gliomas. Two distinct diagnostic algorithms were used for low- and high-grade gliomas (LGGs and HGGs). The percentage of driver alterations identified, associated testing costs, and turnaround time (TAT) are reported. RESULTS: The tiered approach successfully characterized 96% (95 of 99) of gliomas. For 82 LGGs, IHC, targeted fusion panel or FISH, and targeted RNA sequencing solved 35% (29 of 82), 29% (24 of 82), and 30% (25 of 82) of cases, respectively. A total of 64% (53 of 82) of samples were characterized without targeted RNA sequencing. Of 17 HGG samples, 13 were characterized by IHC and four were characterized by targeted RNA sequencing. The average cost per sample was more affordable when using the tiered approach as compared with up-front targeted RNA sequencing in LGG ($405 US dollars [USD] v $745 USD) and HGGs ($282 USD v $745 USD). The average TAT per sample was also shorter using the tiered approach (10 days for LGG, 5 days for HGG v 14 days for targeted RNA sequencing). CONCLUSION: Our tiered approach molecularly characterized 96% of samples in a cost- and time-sensitive manner. Such an approach may be feasible in neuro-oncology centers worldwide, particularly in resource-limited settings.

The diagnostic challenge of lack of choline level elevation on 1H-MR spectroscopy in grade II-III gliomas.

The accurate diagnosis of brain tumour is very important in modern neuro-oncology medicine. Magnetic resonance spectroscopy (MRS) is supposed to be a promising tool for detecting cancerous lesions. However, the interpretation of MRS data is complicated by the fact that not all cancerous lesions exhibit elevated choline (Cho) levels. The main goal of our study was to investigate the lack of Cho lesion /Cho ref elevation in the population of grade II-III gliomas. 89 cases of gliomas grade II and III were used for the retrospective analysis - glioma (astrocytoma or oligodendroglioma) grade II (74 out of 89 cases [83%]) and III (15 out of 89 cases [17%]) underwent conventional MRI extended by MRS before treatment. Histopathological diagnosis was obtained either by biopsy or surgical resection. Gliomas were classified to the group of no-choline elevation when the ratio of choline measured within the tumour (Cho lesion ) to choline from NABT (Cho ref ) were equal to or lower than 1. Significant differences were observed between ratios of Cho lesion /Cr lesion calculated for no-choline elevation and glial tumour groups as well as in the NAA lesion /Cr lesion ratio between the no-choline elevation group and glial tumour group. With consistent data concerning choline level elevation and slightly lower NAA value, the Cho lesion /NAA lesion ratio is significantly higher in the WHO II glial tumour group compared to the no-choline elevation cases ( p < 0.000). In the current study the results demonstrated possibility of lack of choline elevation in patients with grade II-III gliomas, so it is important to remember that the lack of elevated choline levels does not exclude neoplastic lesion.

Dual-ligand Eu-MOF/CuS@Au Heterostructure Array-based ECL Sensor for MiRNA-128 Detection in Glioblastoma Tissues.

In this work, the dual-ligand lanthanide metal-organic framework (MOF)-based electrochemiluminescence (ECL) sensor was constructed for the detection of miRNA-128 in glioblastoma (GBM) diagnosis. The luminescent Eu-MOF (EuBBN) was synthesized with terephthalic acid (BDC) and 2-amino terephthalic acid (BDC-NH2) as dual-ligand. Due to the antenna effect, EuBBN with conjugated-π structure exhibited strong luminescent signal and high quantum efficiency, which can be employed as ECL nanoprobe. Furthermore, the novel plasmonic CuS@Au heterostructure array has been prepared. The localized surface plasmon resonance coupling effect of the CuS@Au heterostructure array can amplify the ECL signal of EuBBN significantly. The EuBBN/CuS@Au heterostructure array-based sensing system has been prepared for the detection of miRNA-128 with a wide linear range from 1 fM to 1 nM and a detection limit of 0.24 fM. Finally, miRNA-128 in the clinic GBM tissue sample has been analysis for the distinguish of tumor grade successfully. The results demonstrated that the dual-ligand MOF/CuS@Au heterostructure array-based ECL sensor can provide important support for the development of GBM diagnosis.

Evaluation of the clinical use of MGMT methylation in extracellular vesicle-based liquid biopsy as a tool for glioblastoma patient management.

Glioblastoma (GB) is a devastating tumor of the central nervous system characterized by a poor prognosis. One of the best-established predictive biomarker in IDH-wildtype GB is O6-methylguanine-DNA methyltransferase (MGMT) methylation (mMGMT), which is associated with improved treatment response and survival. However, current efforts to monitor GB patients through mMGMT detection have proven unsuccessful. Small extracellular vesicles (sEVs) hold potential as a key element that could revolutionize clinical practice by offering new possibilities for liquid biopsy. This study aimed to determine the utility of sEV-based liquid biopsy as a predictive biomarker and disease monitoring tool in patients with IDH-wildtype GB. Our findings show consistent results with tissue-based analysis, achieving a remarkable sensitivity of 85.7% for detecting mMGMT in liquid biopsy, the highest reported to date. Moreover, we suggested that liquid biopsy assessment of sEV-DNA could be a powerful tool for monitoring disease progression in IDH-wildtype GB patients. This study highlights the critical significance of overcoming molecular underdetection, which can lead to missed treatment opportunities and misdiagnoses, possibly resulting in ineffective therapies. The outcomes of our research significantly contribute to the field of sEV-DNA-based liquid biopsy, providing valuable insights into tumor tissue heterogeneity and establishing it as a promising tool for detecting GB biomarkers. These results have substantial implications for advancing predictive and therapeutic approaches in the context of GB and warrant further exploration and validation in clinical settings.

Pediatric high grade gliomas: A comprehensive histopathological, immunohistochemical and molecular integrated approach in routine practice.

Pediatric high grade gliomas have undergone remarkable changes in recent time with discovery of new molecular pathways. They have been added separately in current WHO 2021 blue book. All the entities show characteristic morphology and immunohistochemistry. Methylation data correctly identifies these entities into particular group of clusters. The pediatric group high grade glioma comprises- Diffuse midline glioma, H3K27-altered; Diffuse hemispheric glioma, H3G34-mutant; Diffuse pediatric-type high-grade glioma, H3-wild type & IDH-wild type; Infant hemispheric glioma and Epithelioid glioblastoma/Grade 3 pleomorphic xanthoastrocytoma and very rare IDH-mutant astrocytoma. However it is not always feasible to perform these molecular tests where cost-effective diagnosis is a major concern. Here we discuss the major entities with their characteristic histopathology, immunohistochemistry and molecular findings that may help to reach to suggest the diagnosis and help the clinician for appropriate treatment strategies. We have also made a simple algorithmic flow chart integrated with histopathology, immunohistochemistry and molecular characteristics for better understanding.

Diagnostic and Prognostic Value of Circulating DNA Fragments in Glioblastoma Multiforme Patients.

Novel blood-circulating molecules, as potential biomarkers for glioblastoma multiforme (GBM) diagnosis and monitoring, are attracting particular attention due to limitations of imaging modalities and invasive tissue biopsy procedures. This study aims to assess the diagnostic and prognostic values of circulating cell-free DNA (cfDNA) in relation to inflammatory status in GBM patients and to determine the concentration and average size of DNA fragments typical of tumour-derived DNA fractions. Preoperative plasma samples from 40 patients (GBM 65.0 ± 11.3 years) and 40 healthy controls (HC 70.4 ± 5.4 years) were compared. The cfDNA concentrations and lengths were measured using the electrophoresis platform, and inflammatory indices (NLR, PLR, LMR, and SII) were calculated from complete blood cell analysis. More fragmented cfDNA and 4-fold higher 50-700 bp cfDNA concentrations were detected in GBM patients than in healthy controls. The average cfDNA size in the GBM group was significantly longer (median 336 bp) than in the HC group (median 271 bp). Optimal threshold values were 1265 pg/µL for 50-700 bp cfDNA (AUC = 0.857) and 290 bp for average cfDNA size (AUC = 0.814). A Kaplan-Meier survival curves analysis also demonstrated a higher mortality risk in the GBM group with a cut-off >303 bp cfDNA. This study is the first to have revealed glioblastoma association with high levels of cfDNA > 1000 pg/µL of 50-700 bp in length, which can be aggravated by immunoinflammatory reactivity.

Automatic brain-tumor diagnosis using cascaded deep convolutional neural networks with symmetric U-Net and asymmetric residual-blocks.

The use of various kinds of magnetic resonance imaging (MRI) techniques for examining brain tissue has increased significantly in recent years, and manual investigation of each of the resulting images can be a time-consuming task. This paper presents an automatic brain-tumor diagnosis system that uses a CNN for detection, classification, and segmentation of glioblastomas; the latter stage seeks to segment tumors inside glioma MRI images. The structure of the developed multi-unit system consists of two stages. The first stage is responsible for tumor detection and classification by categorizing brain MRI images into normal, high-grade glioma (glioblastoma), and low-grade glioma. The uniqueness of the proposed network lies in its use of different levels of features, including local and global paths. The second stage is responsible for tumor segmentation, and skip connections and residual units are used during this step. Using 1800 images extracted from the BraTS 2017 dataset, the detection and classification stage was found to achieve a maximum accuracy of 99%. The segmentation stage was then evaluated using the Dice score, specificity, and sensitivity. The results showed that the suggested deep-learning-based system ranks highest among a variety of different strategies reported in the literature.

Potential Diagnostic and Clinical Significance of Selected Genetic Alterations in Glioblastoma.

Glioblastoma is currently considered the most common and, unfortunately, also the most aggressive primary brain tumor, with the highest morbidity and mortality rates. The average survival of patients diagnosed with glioblastoma is 14 months, and only 2% of patients survive 3 years after surgery. Based on our clinical experience and knowledge from extensive clinical studies, survival is mainly related to the molecular biological properties of glioblastoma, which are of interest to the general medical community. Our study examined a total of 71 retrospective studies published from 2016 through 2022 and available on PubMed that deal with mutations of selected genes in the pathophysiology of GBM. In conclusion, we can find other mutations within a given gene group that have different effects on the prognosis and quality of survival of a patient with glioblastoma. These mutations, together with the associated mutations of other genes, as well as intratumoral heterogeneity itself, offer enormous potential for further clinical research and possible application in therapeutic practice.

Pediatric-Like Brain Tumors in Adults.

Pediatric brain tumors are different to those found in adults in pathological type, anatomical site, molecular signature, and probable tumor drivers. Although these tumors usually occur in childhood, they also rarely present in adult patients, either as a de novo diagnosis or as a delayed recurrence of a pediatric tumor in the setting of a patient that has transitioned into adult services.Due to the rarity of pediatric-like tumors in adults, the literature on these tumor types in adults is often limited to small case series, and treatment decisions are often based on the management plans taken from pediatric studies. However, the biology of these tumors is often different from the same tumors found in children. Likewise, adult patients are often unable to tolerate the side effects of the aggressive treatments used in children-for which there is little or no evidence of efficacy in adults. In this chapter, we review the literature and summarize the clinical, pathological, molecular profile, and response to treatment for the following pediatric tumor types-medulloblastoma, ependymoma, craniopharyngioma, pilocytic astrocytoma, subependymal giant cell astrocytoma, germ cell tumors, choroid plexus tumors, midline glioma, and pleomorphic xanthoastrocytoma-with emphasis on the differences to the adult population.

Headache in Brain Tumors.

The prevalence of brain tumors in patients with headache is very low; however, 48% to 71% of patients with brain tumors experience headache. The clinical presentation of headache in brain tumors varies according to age; intracranial pressure; tumor location, type, and progression; headache history; and treatment. Brain tumor-associated headaches can be caused by local and distant traction on pain-sensitive cranial structures, mass effect caused by the enlarging tumor and cerebral edema, infarction, hemorrhage, hydrocephalus, and tumor secretion. This article reviews the current findings related to epidemiologic details, clinical manifestations, mechanisms, diagnostic approaches, and management of headache in association with brain tumors.

Chat-GPT on brain tumors: An examination of Artificial Intelligence/Machine Learning's ability to provide diagnoses and treatment plans for example neuro-oncology cases.

OBJECTIVE: Assess the capabilities of ChatGPT-3.5 and 4 to provide accurate diagnoses, treatment options, and treatment plans for brain tumors in example neuro-oncology cases. METHODS: ChatGPT-3.5 and 4 were provided with twenty example neuro-oncology cases of brain tumors, all selected from medical textbooks. The artificial intelligence programs were asked to give a diagnosis, treatment option, and treatment plan for each of these twenty example cases. Team members first determined in which cases ChatGPT-3.5 and 4 provided the correct diagnosis or treatment plan. Twenty neurosurgeons from the researchers' institution then independently rated the diagnoses, treatment options, and treatment plans provided by both artificial intelligence programs for each of the twenty example cases, on a scale of one to ten, with ten being the highest score. To determine whether the difference between the scores of ChatGPT-3.5 and 4 was statistically significant, a paired t-test was conducted for the average scores given to the programs for each example case. RESULTS: In the initial analysis of correct responses, ChatGPT-4 had an accuracy of 85% for its diagnoses of example brain tumors and an accuracy of 75% for its provided treatment plans, while ChatGPT-3.5 only had an accuracy of 65% and 10%, respectively. The average scores given by the twenty independent neurosurgeons to ChatGPT-4 for its accuracy of diagnosis, provided treatment options, and provided treatment plan were 8.3, 8.4, and 8.5 out of 10, respectively, while ChatGPT-3.5's average scores for these categories of assessment were 5.9, 5.7, and 5.7. These differences in average score are statistically significant on a paired t-test, with a p-value of less than 0.001 for each difference. CONCLUSIONS: ChatGPT-4 demonstrates great promise as a diagnostic tool for brain tumors in neuro-oncology, as attested to by the program's performance in this study and its assessment by surveyed neurosurgeon reviewers.

Intraoperative Touch Imprint Cytology of Brain Neoplasms: A Useful High-Diagnostic Tool in 93 Consecutive Cases; Differential Diagnoses, Pitfalls, and Traps.

Introduction: Intraoperative cytological examination of central nervous system (CNS) lesions was first introduced in 1920 by Eisenhardt and Cushing for rapid evaluation of neurosurgical specimens and to guide surgical treatment. It is recognized that this method not only confirms the adequacy of biopsy in CNS samples but also indicates the presence and preliminary diagnosis of lesional tissue. Methods: A total of 93 patients who underwent touch imprint cytology (TIC) for CNS tumors or lesions between 2018 and 2023 were included in the study. All cases were correlated with the final histopathological diagnosis, and pitfalls and difficulties encountered with discrepancies were noted. Result: The most common primary CNS tumors were gliomas and meningiomas, while secondary (metastatic) tumors were predominantly lung, breast, and gastrointestinal system carcinomas. Sensitivity, specificity, positive predictive value, and negative predictive value for diagnosis with TIC were 94.1%, 100%, and 61.5%, respectively. Final histopathological diagnosis by TIC was made in 88 cases (94.6%) and the discrepancy was found in 5 cases (5.37%). Three of the five discrepancies (3.2%) were haematolymphoid malignancies (two lymphomas and one plasma cell neoplasia), one glioblastoma, and one hemangioblastoma case. Conclusion: TIC is a fast, safe, and inexpensive diagnostic tool used during intraoperative neuropathology consultation. Awareness of the pitfalls of using this method during intraoperative consultation will enable high-diagnostic accuracy.

Advancing glioblastoma treatment by targeting metabolism.

Alterations in cellular metabolism are important hallmarks of glioblastoma(GBM). Metabolic reprogramming is a critical feature as it meets the higher nutritional demand of tumor cells, including proliferation, growth, and survival. Many genes, proteins, and metabolites associated with GBM metabolism reprogramming have been found to be aberrantly expressed, which may provide potential targets for cancer treatment. Therefore, it is becoming increasingly important to explore the role of internal and external factors in metabolic regulation in order to identify more precise therapeutic targets and diagnostic markers for GBM. In this review, we define the metabolic characteristics of GBM, investigate metabolic specificities such as targetable vulnerabilities and therapeutic resistance, as well as present current efforts to target GBM metabolism to improve the standard of care.

A fast transition: A case study of patients' experiences during the diagnostic and surgical treatment phase of an accelerated brain cancer pathway.

BACKGROUND: Patients receiving a brain cancer diagnosis may face cognitive decline and a poor prognosis. In addition, they suffer from a high symptom burden in a complex cancer pathway. The aim of this study was to investigate the early hospital experiences of brain tumour patients during the diagnostic and surgical treatment phase. METHODS: A descriptive longitudinal single-case study design was used, and data were analysed via systematic text condensation. RESULTS: The patients' experiences of being diagnosed with and treated for brain cancer were interpreted in terms of the central theme: a fast transition into an unknown journey. This theme consisted of the following subthemes: emotionally overwhelmed, putting life on hold and an unfamiliar dependency. CONCLUSIONS: Patients diagnosed with brain cancer struggle with overwhelming emotions due to this sudden life-threatening diagnosis, their fear of brain surgery and their progressing dependence. Patients did not voice their feelings, fears or needs, so these may easily be overlooked and unmet. A proactive and continuous care approach throughout the diagnostic phase is needed to support these patients.

A Validated Highly Sensitive Microsatellite Instability Assay Accurately Identifies Individuals Harboring Biallelic Germline PMS2 Pathogenic Variants in Constitutional Mismatch Repair Deficiency.

BACKGROUND: Constitutional mismatch repair deficiency (CMMRD) is a rare and extraordinarily penetrant childhood-onset cancer predisposition syndrome. Genetic diagnosis is often hampered by the identification of mismatch repair (MMR) variants of unknown significance and difficulties in PMS2 analysis, the most frequently mutated gene in CMMRD. We present the validation of a robust functional tool for CMMRD diagnosis and the characterization of microsatellite instability (MSI) patterns in blood and tumors. METHODS: The highly sensitive assessment of MSI (hs-MSI) was tested on a blinded cohort of 66 blood samples and 24 CMMRD tumor samples. Hs-MSI scores were compared with low-pass genomic instability scores (LOGIC/MMRDness). The correlation of hs-MSI scores in blood with age of cancer onset and the distribution of insertion-deletion (indel) variants in microsatellites were analyzed in a series of 169 individuals (n = 68 CMMRD, n = 124 non-CMMRD). RESULTS: Hs-MSI achieved high accuracy in the identification of CMMRD in blood (sensitivity 98.5% and specificity 100%) and detected MSI in CMMRD-associated tumors. Hs-MSI had a strong positive correlation with whole low-pass genomic instability LOGIC scores (r = 0.89, P = 2.2e-15 in blood and r = 0.82, P = 7e-3 in tumors). Indel distribution identified PMS2 pathogenic variant (PV) carriers from other biallelic MMR gene PV carriers with an accuracy of 0.997. Higher hs-MSI scores correlated with younger age at diagnosis of the first tumor (r = -0.43, P = 0.011). CONCLUSIONS: Our study confirms the accuracy of the hs-MSI assay as ancillary testing for CMMRD diagnosis, which can also characterize MSI patterns in CMMRD-associated cancers. Hs-MSI is a powerful tool to pinpoint PMS2 as the affected germline gene and thus potentially personalize cancer risk.

Real-time glioblastoma tumor microenvironment assessment by SpiderMass for improved patient management.

Glioblastoma is a highly heterogeneous and infiltrative form of brain cancer associated with a poor outcome and limited therapeutic effectiveness. The extent of the surgery is related to survival. Reaching an accurate diagnosis and prognosis assessment by the time of the initial surgery is therefore paramount in the management of glioblastoma. To this end, we are studying the performance of SpiderMass, an ambient ionization mass spectrometry technology that can be used in vivo without invasiveness, coupled to our recently established artificial intelligence pipeline. We demonstrate that we can both stratify isocitrate dehydrogenase (IDH)-wild-type glioblastoma patients into molecular sub-groups and achieve an accurate diagnosis with over 90% accuracy after cross-validation. Interestingly, the developed method offers the same accuracy for prognosis. In addition, we are testing the potential of an immunoscoring strategy based on SpiderMass fingerprints, showing the association between prognosis and immune cell infiltration, to predict patient outcome.