DNA methylation-based classification of central nervous system tumours

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Deep learning-assisted flavonoid-based fluorescent sensor array for the nondestructive detection of meat freshness

Gas sensors containing indicators have been widely used in meat freshness testing. However, concerns about the toxicity of indicators have prevented their commercialization. Here, we prepared three fluorescent sensors by complexing each flavonoid (fisetin, puerarin, daidzein) with a flexible film, forming a fluorescent sensor array. The fluorescent sensor array was used as a freshness indication label for packaged meat. Then, the images of the indication labels on the packaged meat under different freshness levels were collected by smartphones. A deep convolutional neural network (DCNN) model was built using the collected indicator label images and freshness labels as the dataset. Finally, the model was used to detect the freshness of meat samples, and the overall accuracy of the prediction model was as high as 97.1%. Unlike the TVB-N measurement, this method provides a nondestructive, real-time measurement of meat freshness.

The heterogeneous sensitivity of pediatric brain tumors to different oncolytic viruses is predicted by unique gene expression profiles

Despite decades of research, the prognosis of high-grade pediatric brain tumors (PBTs) remains dismal; however, recent cases of favorable clinical responses were documented in clinical trials using oncolytic viruses (OVs). In the current study, we employed four different species of OVs: adenovirus Delta24-RGD, herpes simplex virus rQNestin34.5v1, reovirus R124, and the non-virulent Newcastle disease virus rNDV-F0-GFP against three entities of PBTs (high-grade gliomas, atypical teratoid/rhabdoid tumors, and ependymomas) to determine their in vitro efficacy. These four OVs were screened on 14 patient-derived PBT cell cultures and the degree of oncolysis was assessed using an ATP-based assay. Subsequently, the observed viral efficacies were correlated to whole transcriptome data and Gene Ontology analysis was performed. Although no significant tumor type-specific OV efficacy was observed, the analysis revealed the intrinsic biological processes that associated with OV efficacy. The predictive power of the identified expression profiles was further validated in vitro by screening additional PBTs. In summary, our results demonstrate OV susceptibility of multiple patient-derived PBT entities and the ability to predict in vitro responses to OVs using unique expression profiles. Such profiles may hold promise for future OV preselection with effective oncolytic potency in a specific tumor, therewith potentially improving OV responses.

The Significance of BRAF Mutation in the Epithelioid Glioblastoma Subtype: A Systematic Literature Review and a Case Report with a Unique Intraventricular Topography

Epithelioid glioblastoma (E-GBM) is an exceedingly rare subtype of isocitrate dehydrogenase (IDH)-wildtype glioblastoma, first included in the WHO 2016 classification and characterized by a dominant population of epithelioid cells. Its histological and molecular defining features remain troublesome. The significance of BRAF mutations to pathological diagnosis and surgical outcome has drawn increasing attention given their promising potential for future adjuvant therapies. Herein, we describe a unique case of an E-GBM in the atrium of the left lateral ventricle and comprehensively analyze the importance of BRAF status in a cohort of 211 E-GBMs from the literature. Our patient was a 40-year-old man with occipital pain. His brain MRI revealed a large intraventricular tumor at the same location as a signal change found 10 years earlier with no additional follow-up. He underwent gross total tumor removal followed by conventional adjuvant treatment. Histopathological diagnosis was consistent with IDH-wildtype E-GBM WHO grade 4 with pleomorphic xanthoastrocytoma-like areas. BRAF p.V600 mutation was demonstrated in the tumoral genetic study. In the cohort analyzed, male patients predominated (63%), the median age was 32 years old, and the 5-year survival rate following diagnosis was 4.2%. BRAF mutations were found in 60.3% of the tumors overall, with this rate increasing to 78.3% in young adults (19-49 years, P < .001). Presence of BRAF mutations associated with tumor progression (P = .001), the event usually leading to death (P < .001). In conclusion, our study supports the importance of genetic BRAF p.V600 mutation analysis because its presence not only points to an E-GBM diagnosis but may also promote tumor progression.

Artificial intelligence in histopathological image analysis of central nervous system tumours: A systematic review

The convergence of digital pathology and artificial intelligence could assist histopathology image analysis by providing tools for rapid, automated morphological analysis. This systematic review explores the use of artificial intelligence for histopathological image analysis of digitised central nervous system (CNS) tumour slides. Comprehensive searches were conducted across EMBASE, Medline and the Cochrane Library up to June 2023 using relevant keywords. Sixty-eight suitable studies were identified and qualitatively analysed. The risk of bias was evaluated using the Prediction model Risk of Bias Assessment Tool (PROBAST) criteria. All the studies were retrospective and preclinical. Gliomas were the most frequently analysed tumour type. The majority of studies used convolutional neural networks or support vector machines, and the most common goal of the model was for tumour classification and/or grading from haematoxylin and eosin-stained slides. The majority of studies were conducted when legacy World Health Organisation (WHO) classifications were in place, which at the time relied predominantly on histological (morphological) features but have since been superseded by molecular advances. Overall, there was a high risk of bias in all studies analysed. Persistent issues included inadequate transparency in reporting the number of patients and/or images within the model development and testing cohorts, absence of external validation, and insufficient recognition of batch effects in multi-institutional datasets. Based on these findings, we outline practical recommendations for future work including a framework for clinical implementation, in particular, better informing the artificial intelligence community of the needs of the neuropathologist.

Microarray-Based DNA Methylation Profiling: Validation Considerations for Clinical Testing

Microarray-based methylation profiling has emerged as a valuable tool for refining diagnoses and revealing novel tumor subtypes, particularly in central nervous system tumors. Despite the increasing adoption of this technique in clinical genomic laboratories, no technical standards have been published in establishing minimum criteria for test validation. A working group with experience and expertise in DNA-based methylation profiling tests on central nervous system tumors collaborated to develop practical discussion points and focus on important considerations for validating this test in clinical laboratory settings. The experience in validating this methodology in a clinical setting is summarized. Specifically, the advantages and challenges associated with utilizing an in-house classifier compared with a third-party classifier are highlighted. Additionally, experiences in demonstrating the assay's sensitivity and specificity, establishing minimum sample criteria, and implementing quality control metrics are described. As methylation profiling for tumor classification expands to other tumor types and continues to evolve for various other applications, the critical considerations described here are expected to serve as a guidance for future efforts in establishing professional guidelines for this assay.

Aberrant DNA methylation distorts developmental trajectories in atypical teratoid/rhabdoid tumors

Atypical teratoid/rhabdoid tumors (AT/RTs) are pediatric brain tumors known for their aggressiveness and aberrant but still unresolved epigenetic regulation. To better understand their malignancy, we investigated how AT/RT-specific DNA hypermethylation was associated with gene expression and altered transcription factor binding and how it is linked to upstream regulation. Medulloblastomas, choroid plexus tumors, pluripotent stem cells, and fetal brain were used as references. A part of the genomic regions, which were hypermethylated in AT/RTs similarly as in pluripotent stem cells and demethylated in the fetal brain, were targeted by neural transcriptional regulators. AT/RT-unique DNA hypermethylation was associated with polycomb repressive complex 2 and linked to suppressed genes with a role in neural development and tumorigenesis. Activity of the several NEUROG/NEUROD pioneer factors, which are unable to bind to methylated DNA, was compromised via the suppressed expression or DNA hypermethylation of their target sites, which was also experimentally validated for NEUROD1 in medulloblastomas and AT/RT samples. These results highlight and characterize the role of DNA hypermethylation in AT/RT malignancy and halted neural cell differentiation.

Proteomic insights into paediatric cancer: Unravelling molecular signatures and therapeutic opportunities

Survival rates in some paediatric cancers have improved greatly over recent decades, in part due to the identification of diagnostic, prognostic and predictive molecular signatures, and the development of risk-directed therapies. However, other paediatric cancers have proved difficult to treat, and there is an urgent need to identify novel biomarkers that reveal therapeutic opportunities. The proteome is the total set of expressed proteins present in a cell or tissue at a point in time, and is vastly more dynamic than the genome. Proteomics holds significant promise for cancer research, as proteins are ultimately responsible for cellular phenotype and are the target of most anticancer drugs. Here, we review the discoveries, opportunities and challenges of proteomic analyses in paediatric cancer, with a focus on mass spectrometry (MS)-based approaches. Accelerating incorporation of proteomics into paediatric precision medicine has the potential to improve survival and quality of life for children with cancer.

High-throughput molecular assays for inclusion in personalised oncology trials - State-of-the-art and beyond

In the last decades, the development of high-throughput molecular assays has revolutionised cancer diagnostics, paving the way for the concept of personalised cancer medicine. This progress has been driven by the introduction of such technologies through biomarker-driven oncology trials. In this review, strengths and limitations of various state-of-the-art sequencing technologies, including gene panel sequencing (DNA and RNA), whole-exome/whole-genome sequencing and whole-transcriptome sequencing, are explored, focusing on their ability to identify clinically relevant biomarkers with diagnostic, prognostic and/or predictive impact. This includes the need to assess complex biomarkers, for example microsatellite instability, tumour mutation burden and homologous recombination deficiency, to identify patients suitable for specific therapies, including immunotherapy. Furthermore, the crucial role of biomarker analysis and multidisciplinary molecular tumour boards in selecting patients for trial inclusion is discussed in relation to various trial concepts, including drug repurposing. Recognising that today's exploratory techniques will evolve into tomorrow's routine diagnostics and clinical study inclusion assays, the importance of emerging technologies for multimodal diagnostics, such as proteomics and in vivo drug sensitivity testing, is also discussed. In addition, key regulatory aspects and the importance of patient engagement in all phases of a clinical trial are described. Finally, we propose a set of recommendations for consideration when planning a new precision cancer medicine trial.

Clinical Course after Carmustine Wafer Implantation for Newly Diagnosed Adult-type Diffuse Gliomas; A controlled propensity matched analysis of a single center cohort

PURPOSE

It remains unclear whether combining carmustine wafer (CW) implantation with the standard treatment for adult-type diffuse gliomas is safe and has a prognostic impact. This study aimed to investigate the prognostic value and safety of CW implantation.

METHODS

Adult patients with IDH-wild-type and -mutant gliomas, grades 3-4 treated with surgical resection, radiotherapy, and temozolomide chemotherapy between 2013 and 2023 were surveyed. CWs were implanted except in cases of intraoperative wide ventricle opening or marked preoperative brain swelling. For survival analyses, a case-matched dataset based on propensity score matching (PSM), including multiple factors (patient background, diagnosis, and extent of resection) was generated. Progression-free survival (PFS), overall survival (OS), and frequency of complications of CW implantation (brain edema, infection, and cerebrospinal fluid leakage) were compared between the CW and non-use groups.

RESULTS

In total, 127 patients (75 in the CW use group and 52 in the non-use group) were enrolled. Regardless of stratification, no significant differences in PFS and OS were observed between the CW use and non-use groups. The frequency of postoperative brain edema was significantly higher in the CW use group than in the non-use group. An adjusted dataset containing 41 patients in the CW use and nonuse groups was generated. Even after PSM, CW implantation had no prognostic effect.

CONCLUSIONS

CW implantation with standard treatment demonstrated little beneficial effect for the present strategy of CW use.

Ganglioglioma with anaplastic/high-grade transformation: Histopathologic, molecular, and epigenetic characterization of 3 cases

Ganglioglioma (GG) with anaplasia (anaplastic ganglioglioma) is a rare and controversial diagnosis. When present, anaplasia involves the glial component of the tumor, either at presentation or at recurrence. To date, most published cases lack molecular characterization. We describe the histologic and molecular features of 3 patients presenting with BRAF p. V600E-mutant GG (CNS WHO grade 1) with high-grade glial transformation at recurrence. The tumors occurred in pediatric patients (age 9-16 years) with time to recurrence from 20 months to 7 years. At presentation, each tumor was low-grade, with a BRAFV600E-positive ganglion cell component and a glial component resembling pleomorphic xanthoastrocytoma (PXA) or fibrillary astrocytoma. At recurrence, tumors resembled anaplastic PXA or high-grade astrocytomas without neuronal differentiation. CDKN2A homozygous deletion (HD) was absent in all primary tumors. At recurrence, 2 cases acquired CDKN2A HD; the third case showed loss of p16 and MTAP immunoexpression, but no CDKN2A/B HD or mutation was identified. By DNA methylation profiling, all primary and recurrent tumors either grouped or definitely matched to different methylation classes. Our findings indicate that malignant progression of the glial component can occur in GG and suggest that CDKN2A/B inactivation plays a significant role in this process.

Rapid DNA methylation-based classification of pediatric brain tumors from ultrasonic aspirate specimens

BACKGROUND

Although cavitating ultrasonic aspirators are commonly used in neurosurgical procedures, the suitability of ultrasonic aspirator-derived tumor material for diagnostic procedures is still controversial. Here, we explore the feasibility of using ultrasonic aspirator-resected tumor tissue to classify otherwise discarded sample material by fast DNA methylation-based analysis using low pass nanopore whole genome sequencing.

METHODS

Ultrasonic aspirator-derived specimens from pediatric patients undergoing brain tumor resection were subjected to low-pass nanopore whole genome sequencing. DNA methylation-based classification using a neural network classifier and copy number variation analysis were performed. Tumor purity was estimated from copy number profiles. Results were compared to microarray (EPIC)-based routine neuropathological histomorphological and molecular evaluation.

RESULTS

19 samples with confirmed neuropathological diagnosis were evaluated. All samples were successfully sequenced and passed quality control for further analysis. DNA and sequencing characteristics from ultrasonic aspirator-derived specimens were comparable to routinely processed tumor tissue. Classification of both methods was concordant regarding methylation class in 17/19 (89%) cases. Application of a platform-specific threshold for nanopore-based classification ensured a specificity of 100%, whereas sensitivity was 79%. Copy number variation profiles were generated for all cases and matched EPIC results in 18/19 (95%) samples, even allowing the identification of diagnostically or therapeutically relevant genomic alterations.

CONCLUSION

Methylation-based classification of pediatric CNS tumors based on ultrasonic aspirator-reduced and otherwise discarded tissue is feasible using time- and cost-efficient nanopore sequencing.

Phase I Trial of GD2.CART Cells Augmented With Constitutive Interleukin-7 Receptor for Treatment of High-Grade Pediatric CNS Tumors

PURPOSE

T cells modified with chimeric antigen receptors (CARTs) have demonstrated efficacy for hematologic malignancies; however, benefit for patients with CNS tumors has been limited. To enhance T cell activity against GD2+ CNS malignancies, we modified GD2-directed CART cells (GD2.CARTs) with a constitutively active interleukin (IL)-7 receptor (C7R-GD2.CARTs).

METHODS

Patients age 1-21 years with H3K27-altered diffuse midline glioma (DMG) or other recurrent GD2-expressing CNS tumors were eligible for this phase I trial (ClinicalTrials.gov identifier: NCT04099797). All subjects received standard-of-care adjuvant radiation therapy or chemotherapy before study enrollment. The first treatment cohort received GD2.CARTs alone (1 × 107 cells/m2), and subsequent cohorts received C7R-GD2.CARTs at two dose levels (1 × 107 cells/m2; 3 × 107 cells/m2). Standard lymphodepletion with cyclophosphamide and fludarabine was included at all dose levels.

RESULTS

Eleven patients (age 4-18 years) received therapy without dose-limiting toxicity. The GD2.CART cohort did not experience toxicity, but had disease progression after brief improvement of residual neurologic deficits (≤3 weeks). The C7R-GD2.CART cohort developed grade 1 tumor inflammation-associated neurotoxicity in seven of eight (88%) cases, controllable with anakinra. Cytokine release syndrome was observed in six of eight (75%, grade 1 in all but one patient) and associated with increased circulating IL-6 and IP-10 (P < .05). Patients receiving C7R-GD2.CARTs experienced temporary improvement from baseline neurologic deficits (range, 2 to >12 months), and seven of eight (88%) remained eligible for additional treatment cycles (range 2-4 cycles). Partial responses by iRANO criteria were observed in two of seven (29%) patients with DMG treated by C7R-GD2.CARTs.

CONCLUSION

Intravenous GD2.CARTs with and without C7R were well tolerated. Patients treated with C7R-GD2.CARTs exhibited transient improvement of neurologic deficits and increased circulating cytokines/chemokines. Treatment with C7R-GD2.CARTs represents a novel approach warranting further investigation for children with these incurable CNS cancers.

Glial and glioneuronal tumors: Navigating the complexity of evolving concepts and new classification

The World Health Organization (WHO) published the 5th edition classification of tumors of central nervous system in 2021, commonly abbreviated as WHO CNS5, which became the new standard for brain tumor diagnosis and therapy. This edition dramatically impacted tumor diagnostics. In short it introduced new tumors, changed the names of previously recognized tumors, and modified the working definition of previously known tumors. The new system appears complex due to the integration of morphological and multiple molecular criteria. The most radical changes occurred in the field of glial and glioneuronal tumors, which constitutes the lengthy first chapter of this new edition. Herein we present an illustrative outline of the evolving concepts of glial and glioneuronal tumors. We also attempt to explain the rationales behind this substantial change in tumor classification and the challenges to update and integrate it into clinical practice. We aim to present a concise and precise roadmap to aid navigation through the intricate conceptual framework of glial and glioneuronal tumors in the context of WHO CNS5.

Prediction of DNA methylation-based tumor types from histopathology in central nervous system tumors with deep learning

Precision in the diagnosis of diverse central nervous system (CNS) tumor types is crucial for optimal treatment. DNA methylation profiles, which capture the methylation status of thousands of individual CpG sites, are state-of-the-art data-driven means to enhance diagnostic accuracy but are also time consuming and not widely available. Here, to address these limitations, we developed Deep lEarning from histoPathoLOgy and methYlation (DEPLOY), a deep learning model that classifies CNS tumors to ten major categories from histopathology. DEPLOY integrates three distinct components: the first classifies CNS tumors directly from slide images ('direct model'), the second initially generates predictions for DNA methylation beta values, which are subsequently used for tumor classification ('indirect model'), and the third classifies tumor types directly from routinely available patient demographics. First, we find that DEPLOY accurately predicts beta values from histopathology images. Second, using a ten-class model trained on an internal dataset of 1,796 patients, we predict the tumor categories in three independent external test datasets including 2,156 patients, achieving an overall accuracy of 95% and balanced accuracy of 91% on samples that are predicted with high confidence. These results showcase the potential future use of DEPLOY to assist pathologists in diagnosing CNS tumors within a clinically relevant short time frame.

A prognostic neural epigenetic signature in high-grade glioma

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is limited. We present an epigenetically defined neural signature of glioblastoma that independently predicts patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals a high abundance of malignant stemcell-like cells in high-neural glioblastoma, primarily of the neural lineage. These cells are further classified as neural-progenitor-cell-like, astrocyte-like and oligodendrocyte-progenitor-like, alongside oligodendrocytes and excitatory neurons. In line with these findings, high-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature is associated with decreased overall and progression-free survival. High-neural tumors also exhibit increased functional connectivity in magnetencephalography and resting-state magnet resonance imaging and can be detected via DNA analytes and brain-derived neurotrophic factor in patients' plasma. The prognostic importance of the neural signature was further validated in patients diagnosed with diffuse midline glioma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant. High-neural gliomas likely require a maximized surgical resection approach for improved outcomes.

Response Rate and Molecular Correlates to Encorafenib and Binimetinib in BRAF-V600E Mutant High-Grade Glioma

PURPOSE

Although fewer than 5% of high-grade gliomas (HGG) are BRAF-V600E mutated, these tumors are notable as BRAF-targeted therapy shows efficacy for some populations. The purpose of this study was to evaluate response to the combination of encorafenib with binimetinib in adults with recurrent BRAF-V600-mutated HGG.

PATIENTS AND METHODS

In this phase 2, open-label, Adult Brain Tumor Consortium (ABTC) trial (NCT03973918), encorafenib and binimetinib were administered at their FDA-approved doses continuously in 28-day cycles. Eligible patients were required to have HGG or glioblastoma with a BRAF-V600E alteration that was recurrent following at least one line of therapy, including radiotherapy.

RESULTS

Five patients enrolled between January 2020 and administrative termination in November 2021 (due to closure of the ABTC). Enrolled patients received treatment for 2 to 40 months; currently one patient remains on treatment. Centrally determined radiographic response rate was 60%, with one complete response and two partial responses. Methylation profiling revealed that all tumors cluster most closely with anaplastic pleomorphic xanthoastrocytoma (PXA). Transcriptional profile for MAPK-response signature was similar across all tumors at baseline and did not correlate with response in this small population. Circulating tumor DNA measured in plasma samples before treatment, during response, and upon progression showed feasibility of detection for the BRAF-V600E alteration. No new safety signal was detected.

CONCLUSIONS

Encorafenib and binimetinib exhibit positive tumor responses in patients with recurrent BRAF-V600E mutant HGG in this small series, warranting therapeutic consideration. Although toxicity remains a concern for BRAF-targeted therapies, no new safety signal was observed in these patients.

Grading of glioma tumors using digital holographic microscopy

Gliomas are the most common type of cerebral tumors; they occur with increasing incidence in the last decade and have a high rate of mortality. For efficient treatment, fast accurate diagnostic and grading of tumors are imperative. Presently, the grading of tumors is established by histopathological evaluation, which is a time-consuming procedure and relies on the pathologists' experience. Here we propose a supervised machine learning procedure for tumor grading which uses quantitative phase images of unstained tissue samples acquired by digital holographic microscopy. The algorithm is using an extensive set of statistical and texture parameters computed from these images. The procedure has been able to classify six classes of images (normal tissue and five glioma subtypes) and to distinguish between gliomas types from grades II to IV (with the highest sensitivity and specificity for grade II astrocytoma and grade III oligodendroglioma and very good scores in recognizing grade III anaplastic astrocytoma and grade IV glioblastoma). The procedure bolsters clinical diagnostic accuracy, offering a swift and reliable means of tumor characterization and grading, ultimately the enhancing treatment decision-making process.

A common tumour in a rare location: a single centre case series of cerebellar glioblastoma

Although glioblastoma is the commonest primary brain tumour in adults, its location in the cerebellum is extremely rare. We present thirteen cases (3 female, 10 male; median age at presentation 56 [age range 21-77]) of surgically managed, histologically confirmed, primary cerebellar glioblastoma (cGB) over a 17 year period (2005-2022). Pre-operative radiological diagnosis was challenging given cGB rarity, although MRI demonstrated ring enhancement in all cases. Surgical management included posterior fossa craniectomy and debulking in 11 cases and burr hole biopsy in two. CSF diversion was necessary in four cases. No evidence of IDH or ATRX gene mutations was found when tested. Survival ranged from 1 to 22 months after diagnosis (mean 10.9 months). We also seek to understand why glioblastoma is rare in this location and discuss potential reasons for this. We hypothesise that increasing anatomical distance from germinal regions and decreased local endogenous neural stem cell activity (which has been associated with glioblastoma) may explain why glioblastoma is rare in the cerebellum. We hereby seek to add to the limited literature on cGB as this is the largest UK cGB series to date.

Construction and Application of Nanozyme Sensor Arrays

Compared with traditional "lock-key mode" biosensors, a sensor array consists of a series of sensing elements based on intermolecular interactions (typically hydrogen bonds, van der Waals forces, and electrostatic interactions). At the same time, sensor arrays also have the advantages of fast response, high sensitivity, low energy consumption, low cost, rich output signals, and imageability, which have attracted widespread attention from researchers. Nanozymes are nanomaterials which own enzyme-like properties. Because of the adjustable activity, high stability, and cost effectiveness of nanozymes, they are potential candidates for construction of sensor arrays to output different signals from analytes through the chemoresponse of colorants, which solves the shortcomings of traditional sensors that they cannot support multiple detection and lack universality. Recently, a sensor array based on nanozymes as nonspecific recognition receptors has attracted much more attention from researchers and has been applied to precise recognition of proteins, bacteria, and heavy metals. In this perspective, attention is given to nanozymes and the regulation of their enzyme-like activity. Particularly, the building principles and methods for sensor arrays based on nanozymes are analyzed, and the applications are summarized. Finally, the approaches to overcome the challenges and perspectives are also presented and analyzed for facilitating further research and development of nanozyme sensor arrays. This perspective should be helpful for gaining insight into research ideas within the field of nanozyme sensor arrays.

Comprehensive molecular characterization of long-term glioblastoma survivors

Fewer than 5% glioblastoma (GBM) patients survive over five years and are termed long-term survivors (LTS), yet their molecular background is unclear. The present cohort included 72 isocitrate dehydrogenase (IDH)-wildtype GBM patients, consisting of 35 LTS and 37 short-term survivors (STS), and we employed whole exome sequencing, RNA-seq and DNA methylation array to delineate this largest LTS cohort to date. Although LTS and STS demonstrated analogous clinical characters and classical GBM biomarkers, CASC5 (P = 0.002) and SPEN (P = 0.013) mutations were enriched in LTS, whereas gene-to-gene fusions were concentrated in STS (P = 0.007). Importantly, LTS exhibited higher tumor mutation burden (P < 0.001) and copy number (CN) increase (P = 0.013), but lower mutant-allele tumor heterogeneity score (P < 0.001) and CN decrease (P = 0.026). Additionally, LTS demonstrated hypermethylated genome (P < 0.001) relative to STS. Differentially expressed and methylated genes both enriched in olfactory transduction. Further, analysis of the tumor microenvironment revealed higher infiltration of M1 macrophages (P = 0.043), B cells (P = 0.016), class-switched memory B cells (P = 0.002), central memory CD4+ T cells (P = 0.031) and CD4+ Th1 cells (P = 0.005) in LTS. We also separately analyzed a subset of patients who were methylation class-defined GBM, contributing 70.8% of the entire cohort, and obtained similar results relative to prior analyses. Finally, we demonstrated that LTS and STS could be distinguished using a subset of molecular features. Taken together, the present study delineated unique molecular attributes of LTS GBM.

Pervasive structural heterogeneity rewires glioblastoma chromosomes to sustain patient-specific transcriptional programs

Glioblastoma multiforme (GBM) encompasses brain malignancies marked by phenotypic and transcriptional heterogeneity thought to render these tumors aggressive, resistant to therapy, and inevitably recurrent. However, little is known about how the spatial organization of GBM genomes underlies this heterogeneity and its effects. Here, we compile a cohort of 28 patient-derived glioblastoma stem cell-like lines (GSCs) known to reflect the properties of their tumor-of-origin; six of these were primary-relapse tumor pairs from the same patient. We generate and analyze 5 kbp-resolution chromosome conformation capture (Hi-C) data from all GSCs to systematically map thousands of standalone and complex structural variants (SVs) and the multitude of neoloops arising as a result. By combining Hi-C, histone modification, and gene expression data with chromatin folding simulations, we explain how the pervasive, uneven, and idiosyncratic occurrence of neoloops sustains tumor-specific transcriptional programs via the formation of new enhancer-promoter contacts. We also show how even moderately recurrent neoloops can relate to patient-specific vulnerabilities. Together, our data provide a resource for dissecting GBM biology and heterogeneity, as well as for informing therapeutic approaches.

Clinical implications of DNA methylation-based integrated classification of histologically defined grade 2 meningiomas

The combination of DNA methylation analysis with histopathological and genetic features allows for a more accurate risk stratification and classification of meningiomas. Nevertheless, the implications of this classification for patients with grade 2 meningiomas, a particularly heterogeneous tumor entity, are only partially understood. We correlate the outcomes of histopathologically confirmed grade 2 meningioma with an integrated molecular-morphologic risk stratification and determine its clinical implications. Grade 2 meningioma patients treated at our institution were re-classified using an integrated risk stratification involving DNA methylation array-based data, copy number assessment and TERT promoter mutation analyses. Grade 2 meningioma cases according to the WHO 2021 criteria treated between 2007 and 2021 (n = 100) were retrospectively analyzed. The median clinical and radiographic follow-up periods were 59.8 and 54.4 months. A total of 38 recurrences and 17 deaths were observed. The local control rates of the entire cohort after 2-, 4-, and 6-years were 84.3%, 68.5%, and 50.8%, with a median local control time of 77.2 months. The distribution of the integrated risk groups were as follows: 31 low, 54 intermediate, and 15 high risk cases. In the multivariable Cox regression analysis, integrated risk groups were significantly associated with the risk of local recurrence (hazard ratio (HR) intermediate: 9.91, HR high-risk: 7.29, p < 0.01). Gross total resections decreased the risk of local tumor progression (HR gross total resection: 0.19, p < 0.01). The comparison of 1p status and integrated risk groups (low vs. intermediate/high) revealed nearly identical local control rates within their respective subgroups. In summary, only around 50% of WHO 2021 grade 2 meningiomas have an intermediate risk profile. Integrated molecular risk stratification is crucial to guide the management of patients with grade 2 tumors and should be routinely applied to avoid over- and undertreatment, especially concerning the use of adjuvant radiotherapy.

Integrated proteomics spotlight the proteasome as a therapeutic vulnerability in embryonal tumors with multilayered rosettes

BACKGROUND

Embryonal tumors with multilayered rosettes (ETMR) are rare malignant embryonal brain tumors. The prognosis of ETMR is poor and novel therapeutic approaches are desperately needed. Comprehension of ETMR tumor biology is currently based on only few previous molecular studies, which mainly focused on the analyses of nucleic acids. In this study, we explored integrated ETMR proteomics.

METHODS

Using mass spectrometry, proteome data were acquired from 16 ETMR and the ETMR cell line BT183. Proteome data were integrated with case-matched global DNA methylation data, publicly available transcriptome data, and proteome data of further embryonal and pediatric brain tumors.

RESULTS

Proteome-based cluster analyses grouped ETMR samples according to histomorphology, separating neuropil-rich tumors with neuronal signatures from primitive tumors with signatures relating to stemness and chromosome organization. Integrated proteomics showcased that ETMR and BT183 cells harbor proteasome regulatory proteins in abundance, implicating their strong dependency on the proteasome machinery to safeguard proteostasis. Indeed, in vitro assays using BT183 highlighted that ETMR tumor cells are highly vulnerable toward treatment with the CNS penetrant proteasome inhibitor Marizomib.

CONCLUSIONS

In summary, histomorphology stipulates the proteome signatures of ETMR, and proteasome regulatory proteins are pervasively abundant in these tumors. As validated in vitro, proteasome inhibition poses a promising therapeutic option in ETMR.

DistSNE: Distributed computing and online visualization of DNA methylation-based central nervous system tumor classification

The current state-of-the-art analysis of central nervous system (CNS) tumors through DNA methylation profiling relies on the tumor classifier developed by Capper and colleagues, which centrally harnesses DNA methylation data provided by users. Here, we present a distributed-computing-based approach for CNS tumor classification that achieves a comparable performance to centralized systems while safeguarding privacy. We utilize the t-distributed neighborhood embedding (t-SNE) model for dimensionality reduction and visualization of tumor classification results in two-dimensional graphs in a distributed approach across multiple sites (DistSNE). DistSNE provides an intuitive web interface (https://gin-tsne.med.uni-giessen.de) for user-friendly local data management and federated methylome-based tumor classification calculations for multiple collaborators in a DataSHIELD environment. The freely accessible web interface supports convenient data upload, result review, and summary report generation. Importantly, increasing sample size as achieved through distributed access to additional datasets allows DistSNE to improve cluster analysis and enhance predictive power. Collectively, DistSNE enables a simple and fast classification of CNS tumors using large-scale methylation data from distributed sources, while maintaining the privacy and allowing easy and flexible network expansion to other institutes. This approach holds great potential for advancing human brain tumor classification and fostering collaborative precision medicine in neuro-oncology.

Diffeomorphic Counterfactuals With Generative Models

Counterfactuals can explain classification decisions of neural networks in a human interpretable way. We propose a simple but effective method to generate such counterfactuals. More specifically, we perform a suitable diffeomorphic coordinate transformation and then perform gradient ascent in these coordinates to find counterfactuals which are classified with great confidence as a specified target class. We propose two methods to leverage generative models to construct such suitable coordinate systems that are either exactly or approximately diffeomorphic. We analyze the generation process theoretically using Riemannian differential geometry and validate the quality of the generated counterfactuals using various qualitative and quantitative measures.

Imaging of supratentorial intraventricular masses in children:a pictorial review- part 1

PURPOSE

This article is the first in a two-part series designed to provide a comprehensive overview of the range of supratentorial intraventricular masses observed in children. Our primary objective is to discuss the diverse types of intraventricular masses that originate not only from cells within the choroid plexus but also from other sources.

METHODS

In this article, we review relevant epidemiological data, the current genetics/molecular classification as outlined in the fifth edition of the World Health Organization's Classification of tumours of the Central Nervous System and noteworthy imaging findings. We conduct an exhaustive analysis of primary choroid plexus tumours as well as other conditions such as choroid plexus hyperplasia, choroid plexus cyst, choroid plexus xanthogranuloma, atypical teratoid rhabdoid tumour, meningioma, arteriovenous malformation and metastasis.

RESULTS

We comprehensively evaluated each supratentorial intraventricular mass, providing an in-depth analysis of their unique clinical and histological characteristics. The fifth edition of the World Health Organization Classification of Tumours of the Central Nervous System introduces major modifications. These important changes could potentially have a profound impact on the management strategies and subsequent outcomes of these tumours.

CONCLUSION

Intraventricular masses in children can arise from various sources. Surgical intervention is key for certain supratentorial intraventricular masses in paediatric patients, with preoperative neuroimaging essential to decide the best treatment approach, surgical or otherwise, as some cases may not require surgery.

Singular Value Decomposition-Based Penalized Multinomial Regression for Classifying Imbalanced Medulloblastoma Subgroups Using Methylation Data

Medulloblastoma (MB) is a molecularly heterogeneous brain malignancy with large differences in clinical presentation. According to genomic studies, there are at least four distinct molecular subgroups of MB: sonic hedgehog (SHH), wingless/INT (WNT), Group 3, and Group 4. The treatment and outcomes depend on appropriate classification. It is difficult for the classification algorithms to identify these subgroups from an imbalanced MB genomic data set, where the distribution of samples among the MB subgroups may not be equal. To overcome this problem, we used singular value decomposition (SVD) and group lasso techniques to find DNA methylation probe features that maximize the separation between the different imbalanced MB subgroups. We used multinomial regression as a classification method to classify the four different molecular subgroups of MB using the reduced DNA methylation data. Coordinate descent is used to solve our loss function associated with the group lasso, which promotes sparsity. By using SVD, we were able to reduce the 321,174 probe features to just 200 features. Less than 40 features were successfully selected after applying the group lasso, which we then used as predictors for our classification models. Our proposed method achieved an average overall accuracy of 99% based on fivefold cross-validation technique. Our approach produces improved classification performance compared with the state-of-the-art methods for classifying MB molecular subgroups.

Two novel tumours with NTRK2 fusion in the methylation class of extraventricular neurocytomas, including one intraventricular

We report here about two novel tumours classified as extraventricular neurocytomas (EVN) using DNA-methylation profiling, associated with NTRK2 fusions instead of the usual FGFR1 alterations so far attributed to this tumoural entity. We present the second detailed case of an intraventricular presentation in the MC EVN. Our findings broaden the spectrum of MC EVN and have implications in terms of diagnosis, therapy and terminology.

Genome-wide DNA methylation-analysis of blastic plasmacytoid dendritic cell neoplasm identifies distinct molecular features

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) constitutes a rare and aggressive malignancy originating from plasmacytoid dendritic cells (pDCs) with a primarily cutaneous tropism followed by dissemination to the bone marrow and other organs. We conducted a genome-wide analysis of the tumor methylome in an extended cohort of 45 BPDCN patients supplemented by WES and RNA-seq as well as ATAC-seq on selected cases. We determined the BPDCN DNA methylation profile and observed a dramatic loss of DNA methylation during malignant transformation from early and mature DCs towards BPDCN. DNA methylation profiles further differentiate between BPDCN, AML, CMML, and T-ALL exhibiting the most striking global demethylation, mitotic stress, and merely localized DNA hypermethylation in BPDCN resulting in pronounced inactivation of tumor suppressor genes by comparison. DNA methylation-based analysis of the tumor microenvironment by MethylCIBERSORT yielded two, prognostically relevant clusters (IC1 and IC2) with specific cellular composition and mutational spectra. Further, the transcriptional subgroups of BPDCN (C1 and C2) differ by DNA methylation signatures in interleukin/inflammatory signaling genes but also by higher transcription factor activity of JAK-STAT and NFkB signaling in C2 in contrast to an EZH2 dependence in C1-BPDCN. Our integrative characterization of BPDCN offers novel molecular insights and potential diagnostic applications.

Implications of DNA Methylation Classification in Diagnosing Ependymoma

BACKGROUND

Ependymoma is a central nervous system (CNS) tumor that arises from the ependymal cells of the brain's ventricles and spinal cord. The histopathology of ependymomas is indistinguishable regardless of the site of origin, and the prognosis varies. Recent studies have revealed that the development site and prognosis reflect the genetic background. In this study, we used genome-wide DNA methylation array analysis to investigate the epigenetic background of ependymomas from different locations treated at our hospital.

METHODS

Four cases of posterior fossa ependymomas and 11 cases of spinal ependymomas were analyzed.

RESULTS

DNA methylation profiling using the DKFZ methylation classifier showed that the methylation diagnoses of the 2 cases differed from the histopathological diagnoses, and 2 cases could not be classified. Tumor that spread from the brain to the spinal cord was molecularly distinguishable from other primary spinal tumors.

CONCLUSIONS

Although adding DNA methylation classification to conventional diagnostic methods may be helpful, the diagnosis in some cases remains undetermined. This may affect decision-making regarding treatment strategies and follow-up. Further investigations are required to improve the diagnostic accuracy of these tumors.

Consensus guideline for the diagnosis and management of pituitary adenomas in childhood and adolescence: Part 1, general recommendations

Tumours of the anterior part of the pituitary gland represent just 1% of all childhood (aged <15 years) intracranial neoplasms, yet they can confer high morbidity and little evidence and guidance is in place for their management. Between 2014 and 2022, a multidisciplinary expert group systematically developed the first comprehensive clinical practice consensus guideline for children and young people under the age 19 years (hereafter referred to as CYP) presenting with a suspected pituitary adenoma to inform specialist care and improve health outcomes. Through robust literature searches and a Delphi consensus exercise with an international Delphi consensus panel of experts, the available scientific evidence and expert opinions were consolidated into 74 recommendations. Part 1 of this consensus guideline includes 17 pragmatic management recommendations related to clinical care, neuroimaging, visual assessment, histopathology, genetics, pituitary surgery and radiotherapy. While in many aspects the care for CYP is similar to that of adults, key differences exist, particularly in aetiology and presentation. CYP with suspected pituitary adenomas require careful clinical examination, appropriate hormonal work-up, dedicated pituitary imaging and visual assessment. Consideration should be given to the potential for syndromic disease and genetic assessment. Multidisciplinary discussion at both the local and national levels can be key for management. Surgery should be performed in specialist centres. The collection of outcome data on novel modalities of medical treatment, surgical intervention and radiotherapy is essential for optimal future treatment.

Comprehensive clinicopathological, molecular, and methylation analysis of mesenchymal tumors with NTRK and other kinase gene aberrations

Alterations in kinase genes such as NTRK1/2/3, RET, and BRAF underlie infantile fibrosarcoma (IFS), the emerging entity 'NTRK-rearranged spindle cell neoplasms' included in the latest WHO classification, and a growing set of tumors with overlapping clinical and pathological features. In this study, we conducted a comprehensive clinicopathological and molecular analysis of 22 cases of IFS and other kinase gene-altered spindle cell neoplasms affecting both pediatric and adult patients. Follow-up periods for 16 patients ranged in length from 10 to 130 months (mean 38 months). Six patients were treated with targeted therapy, achieving a partial or complete response in five cases. Overall, three cases recurred and one metastasized. Eight patients were free of disease, five were alive with disease, and two patients died. All cases showed previously reported morphological patterns. Based on the cellularity and level of atypia, cases were divided into three morphological grade groups. S100 protein and CD34 were at least focally positive in 12/22 and 14/22 cases, respectively. Novel PWWP2A::RET, NUMA1::RET, ITSN1::RAF1, and CAPZA2::MET fusions, which we report herein in mesenchymal tumors for the first time, were detected by RNA sequencing. Additionally, the first uterine case with BRAF and EGFR mutations and CD34 and S100 co-expression is described. DNA sequencing performed in 13 cases uncovered very rare additional genetic aberrations. The CNV profiles showed that high-grade tumors demonstrate a significantly higher percentage of copy number gains and losses across the genome compared with low- and intermediate-grade tumors. Unsupervised clustering of the tumors' methylation profiles revealed that in 8/9 cases, the methylation profiles clustered with the IFS methylation class, irrespective of their clinicopathological or molecular features. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Epigenetic regulation of tumor-immune symbiosis in glioma

Glioma is a type of aggressive and incurable brain tumor. Patients with glioma are highly resistant to all types of therapies, including immunotherapies. Epigenetic reprogramming is a key molecular hallmark in tumors across cancer types, including glioma. Mounting evidence highlights a pivotal role of epigenetic regulation in shaping tumor biology and therapeutic responses through mechanisms involving both glioma cells and immune cells, as well as their symbiotic interactions in the tumor microenvironment (TME). In this review, we discuss the molecular mechanisms of epigenetic regulation that impacts glioma cell biology and tumor immunity in both a cell-autonomous and non-cell-autonomous manner. Moreover, we provide an overview of potential therapeutic approaches that can disrupt epigenetic-regulated tumor-immune symbiosis in the glioma TME.

Availability and utilization of molecular testing for primary central nervous system tumors among US hospitals

Advanced molecular testing has increasingly become an integral component for accurate diagnosis of central nervous system (CNS) tumors. We sought to establish the current state of molecular testing availability and approaches for the diagnosis of CNS tumors in US hospitals that conduct high volumes of CNS tumor resections. We distributed a 16-item survey inquiring about molecular testing approaches for CNS tumors to 115 neuropathologists at US hospitals with neurosurgery residency programs. Thirty-five neuropathologists (30.4%) responded to the survey, all of whom indicated their institutions perform molecular testing on CNS tumor tissue. The most commonly offered tests were MGMT methylation profiling and next-generation sequencing. Fourteen respondents (40%) indicated that their institution is able to test for and report all of the molecular alterations included in our survey. Nine (25.7%) respondents indicated that molecular testing is performed as standard of care for all patients with resected CNS tumors. Our results suggest that even in academic hospitals with a high volume of CNS tumor resections, molecular testing for these tumors is limited. Continued initiatives are necessary to expand the availability of molecular testing for CNS tumors to ensure diagnostic accuracy and guide targeted therapy.

Associations in cell type-specific hydroxymethylation and transcriptional alterations of pediatric central nervous system tumors

Although intratumoral heterogeneity has been established in pediatric central nervous system tumors, epigenomic alterations at the cell type level have largely remained unresolved. To identify cell type-specific alterations to cytosine modifications in pediatric central nervous system tumors, we utilize a multi-omic approach that integrated bulk DNA cytosine modification data (methylation and hydroxymethylation) with both bulk and single-cell RNA-sequencing data. We demonstrate a large reduction in the scope of significantly differentially modified cytosines in tumors when accounting for tumor cell type composition. In the progenitor-like cell types of tumors, we identify a preponderance differential Cytosine-phosphate-Guanine site hydroxymethylation rather than methylation. Genes with differential hydroxymethylation, like histone deacetylase 4 and insulin-like growth factor 1 receptor, are associated with cell type-specific changes in gene expression in tumors. Our results highlight the importance of epigenomic alterations in the progenitor-like cell types and its role in cell type-specific transcriptional regulation in pediatric central nervous system tumors.

Clinicopathological and molecular landscape of 5-year IDH-wild-type glioblastoma survivors: A multicentric retrospective study

Five-year glioblastoma (GBM) survivors (LTS) are the minority of the isocitrate dehydrogenase (IDH)-wild-type GBM patients, and their molecular fingerprint is still largely unexplored. This multicenter retrospective study analyzed a large LTS-GBM cohort from nine Italian institutions and molecularly characterized a subgroup of patients by mutation, DNA methylation (DNAm) and copy number variation (CNV) profiling, comparing it to standard survival GBM. Mutation scan allowed the identification of pathogenic variants in most cases, showing a similar mutational spectrum in both groups, and highlighted TP53 as the most commonly mutated gene in the LTS group. We confirmed DNAm as a valuable tool for GBM classification with a diagnostic refinement by using brain tumor classifier v12.5. LTS were more heterogeneous with more cases classified as diffuse pediatric high-grade glioma subtypes and having peculiar CNVs. We observed a global higher methylation in CpG islands and in gene promoters of LTS with methylation levels of distinct gene promoters correlating with prognosis.

Low-input and single-cell methods for Infinium DNA methylation BeadChips

The Infinium BeadChip is the most widely used DNA methylome assay technology for population-scale epigenome profiling. However, the standard workflow requires over 200 ng of input DNA, hindering its application to small cell-number samples, such as primordial germ cells. We developed experimental and analysis workflows to extend this technology to suboptimal input DNA conditions, including ultra-low input down to single cells. DNA preamplification significantly enhanced detection rates to over 50% in five-cell samples and ∼25% in single cells. Enzymatic conversion also substantially improved data quality. Computationally, we developed a method to model the background signal's influence on the DNA methylation level readings. The modified detection P-value calculation achieved higher sensitivities for low-input datasets and was validated in over 100 000 public diverse methylome profiles. We employed the optimized workflow to query the demethylation dynamics in mouse primordial germ cells available at low cell numbers. Our data revealed nuanced chromatin states, sex disparities, and the role of DNA methylation in transposable element regulation during germ cell development. Collectively, we present comprehensive experimental and computational solutions to extend this widely used methylation assay technology to applications with limited DNA.

DNA Methylation Profiles Are Stable in H3 K27M-Mutant Diffuse Midline Glioma Neurosphere Cell Lines

Diffuse midline gliomas are among the deadliest human cancers and have had little progress in treatment in the last 50 years. Cell cultures of these tumors have been developed recently, but the degree to which such cultures retain the characteristics of the source tumors is unknown. DNA methylation profiling offers a powerful tool to look at genome-wide epigenetic changes that are biologically meaningful and can help assess the similarity of cultured tumor cells to their in vivo progenitors. Paraffinized diagnostic tissue from three diffuse intrinsic pontine gliomas with H3 K27M mutations was compared with subsequent passages of neurosphere cell cultures from those tumors. Each cell line was passaged 3-4 times and analyzed with DNA methylation arrays and standard algorithms that provided a comparison of diagnostic classification and cluster analysis. All samples tested maintained high classifier scores and clustered within the reference group of H3 K27M-mutant diffuse midline gliomas. There was a gain of 1q in all cell lines, with two cell lines initially manifesting the gain of 1q only during culture. In vitro cell cultures of H3 K27M-mutant gliomas maintain high degrees of similarity in DNA methylation profiles to their source tumor, confirming their fidelity even with some chromosomal changes.

Multi-Omics Integration for Liver Cancer Using Regression Analysis

Genetic biomarkers have played a pivotal role in the classification, prognostication, and guidance of clinical cancer therapies. Large-scale and multi-dimensional analyses of entire cancer genomes, as exemplified by projects like The Cancer Genome Atlas (TCGA), have yielded an extensive repository of data that holds the potential to unveil the underlying biology of these malignancies. Mutations stand out as the principal catalysts of cellular transformation. Nonetheless, other global genomic processes, such as alterations in gene expression and chromosomal re-arrangements, also play crucial roles in conferring cellular immortality. The incorporation of multi-omics data specific to cancer has demonstrated the capacity to enhance our comprehension of the molecular mechanisms underpinning carcinogenesis. This report elucidates how the integration of comprehensive data on methylation, gene expression, and copy number variations can effectively facilitate the unsupervised clustering of cancer samples. We have identified regressors that can effectively classify tumor and normal samples with an optimal integration of RNA sequencing, DNA methylation, and copy number variation while also achieving significant p-values. Further, these regressors were trained using linear and logistic regression with k-means clustering. For comparison, we employed autoencoder- and stacking-based omics integration and computed silhouette scores to evaluate the clusters. The proof of concept is illustrated using liver cancer data. Our analysis serves to underscore the feasibility of unsupervised cancer classification by considering genetic markers beyond mutations, thereby emphasizing the clinical relevance of additional global cellular parameters that contribute to the transformative process in cells. This work is clinically relevant because changes in gene expression and genomic re-arrangements have been shown to be signatures of cellular transformation across cancers, as well as in liver cancers.

Glioma Stem Cells-Features for New Therapy Design

On a molecular level, glioma is very diverse and presents a whole spectrum of specific genetic and epigenetic alterations. The tumors are unfortunately resistant to available therapies and the survival rate is low. The explanation of significant intra- and inter-tumor heterogeneity and the infiltrative capability of gliomas, as well as its resistance to therapy, recurrence and aggressive behavior, lies in a small subset of tumor-initiating cells that behave like stem cells and are known as glioma cancer stem cells (GCSCs). They are responsible for tumor plasticity and are influenced by genetic drivers. Additionally, GCSCs also display greater migratory abilities. A great effort is under way in order to find ways to eliminate or neutralize GCSCs. Many different treatment strategies are currently being explored, including modulation of the tumor microenvironment, posttranscriptional regulation, epigenetic modulation and immunotherapy.

A case of myxopapillary ependymoma with predominant giant cell morphology: A rare entity with comprehensive genomic profiling and review of literature

In the evolving landscape of ependymoma classification, which integrates histological, molecular, and anatomical context, we detail a rare case divergent from the usual histopathological spectrum. We present the case of a 37-year-old man with symptomatic spinal cord compression at the L3-L4 level. Neuroradiological evaluation revealed an intradural, encapsulated mass. Histologically, the tumor displayed atypical features: bizarre pleomorphic giant cells, intranuclear inclusions, mitotic activity, and a profusion of eosinophilic cytoplasm with hyalinized vessels, deviating from the characteristic perivascular pseudorosettes or myxopapillary patterns. Immunohistochemical staining bolstered this divergence, marking the tumor cells positive for glial fibrillary acidic protein and epithelial membrane antigen with a characteristic ring-like pattern, and CD99 but negative for Olig-2. These markers, alongside methylation profiling, facilitated its classification as a myxopapillary ependymoma (MPE), despite the atypical histologic features. This profile underscores the necessity of a multifaceted diagnostic process, especially when histological presentation is uncommon, confirming the critical role of immunohistochemistry and molecular diagnostics in classifying morphologically ambiguous ependymomas and exemplifying the histological diversity within MPEs.

Diffuse hemispheric glioma with H3 p.K28M (K27M) mutation: Unusual non-midline presentation of diffuse midline glioma, H3 K27M-altered?

Diffuse midline glioma, H3 K27-altered (DMG-H3 K27) is an aggressive group of diffuse gliomas that predominantly occurs in pediatric patients, involves midline structures, and displays loss of H3 p.K28me3 (K27me3) expression by immunohistochemistry and characteristic genetic/epigenetic profile. Rare examples of a diffuse glioma with an H3 p.K28M (K27M) mutation and without involvement of the midline structures, so-called "diffuse hemispheric glioma with H3 p.K28M (K27M) mutation" (DHG-H3 K27), have been reported. Herein, we describe 2 additional cases of radiologically confirmed DHG-H3 K27 and summarize previously reported cases. We performed histological, immunohistochemical, molecular, and DNA methylation analysis and provided clinical follow-up in both cases. Overall, DHG-H3 K27 is an unusual group of diffuse gliomas that shows similar clinical, histopathological, genomic, and epigenetic features to DMG-H3 K27 as well as enrichment for activating alterations in MAPK pathway genes. These findings suggest that DHG-H3 K27 is closely related to DMG-H3 K27 and may represent an unusual presentation of DMG-H3 K27 without apparent midline involvement and with frequent MAPK pathway activation. Detailed reports of additional cases with clinical follow-up will be important to expand our understanding of this unusual group of diffuse gliomas and to better define the clinical outcome and how to classify DHG-H3 K27.

Evaluating cell culture reliability in pediatric brain tumor primary cells through DNA methylation profiling

In vitro models of pediatric brain tumors (pBT) are instrumental for better understanding the mechanisms contributing to oncogenesis and testing new therapies; thus, ideally, they should recapitulate the original tumor. We applied DNA methylation (DNAm) and copy number variation (CNV) profiling to characterize 241 pBT samples, including 155 tumors and 86 pBT-derived cell cultures, considering serum vs serum-free conditions, late vs early passages, and dimensionality (2D vs 3D cultures). We performed a t-SNE classification and identified differentially methylated regions in tumors compared to cell models. Early cell cultures recapitulate the original tumor, but serum media and 2D culturing were demonstrated to significantly contribute to the divergence of DNAm profiles from the parental ones. All divergent cells clustered together acquiring a common deregulated epigenetic signature suggesting a shared selective pressure. We identified a set of hypomethylated genes shared among unfaithful cells converging on response to growth factors and migration pathways, such as signaling cascade activation, tissue organization, and cellular migration. In conclusion, DNAm and CNV are informative tools that should be used to assess the recapitulation of pBT-cells from parental tumors.

Haploinsufficiency of phosphodiesterase 10A activates PI3K/AKT signaling independent of PTEN to induce an aggressive glioma phenotype

Glioblastoma is universally fatal and characterized by frequent chromosomal copy number alterations harboring oncogenes and tumor suppressors. In this study, we analyzed exome-wide human glioblastoma copy number data and found that cytoband 6q27 is an independent poor prognostic marker in multiple data sets. We then combined CRISPR-Cas9 data, human spatial transcriptomic data, and human and mouse RNA sequencing data to nominate PDE10A as a potential haploinsufficient tumor suppressor in the 6q27 region. Mouse glioblastoma modeling using the RCAS/tv-a system confirmed that Pde10a suppression induced an aggressive glioma phenotype in vivo and resistance to temozolomide and radiation therapy in vitro. Cell culture analysis showed that decreased Pde10a expression led to increased PI3K/AKT signaling in a Pten-independent manner, a response blocked by selective PI3K inhibitors. Single-nucleus RNA sequencing from our mouse gliomas in vivo, in combination with cell culture validation, further showed that Pde10a suppression was associated with a proneural-to-mesenchymal transition that exhibited increased cell adhesion and decreased cell migration. Our results indicate that glioblastoma patients harboring PDE10A loss have worse outcomes and potentially increased sensitivity to PI3K inhibition.

Exploring TSPAN4 promoter methylation as a diagnostic biomarker for tuberculosis

Background

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a persistent infectious disease threatening human health. The existing diagnostic methods still have significant shortcomings, including a low positivity rate in pathogen-based diagnoses and the inability of immunological diagnostics to detect active TB. Hence, it is urgent to develop new techniques to detect TB more accurate and earlier. This research aims to scrutinize and authenticate DNA methylation markers suitable for tuberculosis diagnosis. Concurrently, Providing a new approach for tuberculosis diagnosis.

Methods

Blood samples from patients with newly diagnosed tuberculosis and healthy controls (HC) were utilized in this study. Examining methylation microarray data from 40 whole blood samples (22TB + 18HC), we employed two procedures: signature gene methylated position analysis and signature region methylated position analysis to pinpoint distinctive methylated positions. Based on the screening results, diagnostic classifiers are constructed through machine learning, and validation was conducted through pyrosequencing in a separate queue (22TB + 18HC). Culminating in the development of a new tuberculosis diagnostic method via quantitative real-time methylation specific PCR (qMSP).

Results

The combination of the two procedures revealed a total of 10 methylated positions, all of which were located in the promoter region. These 10 signature methylated positions facilitated the construction of a diagnostic classifier, exhibiting robust diagnostic accuracy in both cross-validation and external test sets. The LDA model demonstrated the best classification performance, achieving an AUC of 0.83, specificity of 0.8, and sensitivity of 0.86 on the external test set. Furthermore, the validation of signature methylated positions through pyrosequencing demonstrated high agreement with screening outcomes. Additionally, qMSP detection of 2 potential hypomethylated positions (cg04552852 and cg12464638) exhibited promising results, yielding an AUC of 0.794, specificity of 0.720, and sensitivity of 0.816.

Conclusion

Our study demonstrates that the validated signature methylated positions through pyrosequencing emerge as plausible biomarkers for tuberculosis diagnosis. The specific methylation markers in the TSPAN4 gene, identified in whole blood samples, hold promise for improving tuberculosis diagnosis. This approach could significantly enhance diagnostic accuracy and speed, offering a new avenue for early detection and treatment.

Pediatric-type high-grade gliomas with PDGFRA amplification in adult patients with Li-Fraumeni syndrome: clinical and molecular characterization of three cases

Li-Fraumeni syndrome (LFS) is an autosomal dominant tumor predisposition syndrome caused by heterozygous germline mutations or deletions in the TP53 tumor suppressor gene. Central nervous system tumors, such as choroid plexus tumors, medulloblastomas, and diffuse gliomas, are frequently found in patients with LFS. Although molecular profiles of diffuse gliomas that develop in pediatric patients with LFS have been elucidated, those in adults are limited. Recently, diffuse gliomas have been divided into pediatric- and adult-type gliomas, based on their distinct molecular profiles. In the present study, we investigated the molecular profiles of high-grade gliomas in three adults with LFS. These tumors revealed characteristic histopathological findings of high-grade glioma or glioblastoma and harbored wild-type IDH1/2 according to whole exome sequencing (WES). However, these tumors did not exhibit the key molecular alterations of glioblastoma, IDH-wildtype such as TERT promoter mutation, EGFR amplification, or chromosome 7 gain and 10 loss. Although WES revealed no other characteristic gene mutations or copy number alterations in high-grade gliomas, such as those in histone H3 genes, PDGFRA amplification was found in all three cases together with uniparental disomy of chromosome 17p, where the TP53 gene is located. DNA methylation analyses revealed that all tumors exhibited DNA methylation profiles similar to those of pediatric-type high-grade glioma H3-wildtype and IDH-wildtype (pHGG H3-/IDH-wt), RTK1 subtype. These data suggest that high-grade gliomas developed in adult patients with LFS may be involved in pHGG H3-/IDH-wt. PDGFRA and homozygous alterations in TP53 may play pivotal roles in the development of this type of glioma in adult patients with LFS.