Daniel J. Brat’s research while affiliated with Northwestern University and other places

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Publications (182)


Fig. 1 | Classifier performance. a t-SNE plot of classifier classes using 3690 training samples and 10,000 methylation probes. Class abbreviations can be found in Supplementary Table 3. b Receiver operating characteristic (ROC) curve for all 2633 validation samples. c ROC curve for all 319 metastatic validation samples.
Fig. 2 | Overall survival of selected TUO classes. Analyses for other TCGA projects and TUO classes can be found in Supplementary Fig. 3. a Splitting TCGA project Colon Adenocarcinoma (COAD) into classes Cecum (CEC) and Colon (COLON). b Splitting TCGA project Esophageal Carcinoma (ESCA) into classes Esophageal adenocarcinoma (ESO_ADC) and Esophageal squamous cell carcinoma (ESO_SCC). c Splitting TCGA project Pancreatic Adenocarcinoma (PAAD) into classes Pancreas (PANC) and Pancreas group 3 (PANC3). d Splitting TCGA project Sarcoma (SARC) into classes Soft tissue main (SOFT), Retroperitoneum (RTPT), Non-uterine leiomyosarcoma (LMS), and Uterine leiomyosarcoma (ULMS).
Fig. 5 | Clinical case #2. a Hematoxylin and Eosin stained section of the duodenal biopsy. Normal surface epithelium with underlying large atypical cells with poor architecture. b t-SNE visualization of the specimen compared to TUO classifier training samples. c Zoomed in t-SNE plot showing how the case clusters within breast group 2. d Random Forest classification of the sample reported in the patient medical record.
Samples used in study
Accurate identification of primary site in tumors of unknown origin (TUO) using DNA methylation
  • Article
  • Full-text available

January 2025

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11 Reads

npj Precision Oncology

Drew Duckett

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Erica R. Vormittag-Nocito

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Pouya Jamshidi

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[...]

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Tumors of unknown origin (TUO) generally result in poor patient survival and are clinically difficult to address. Identification of the site of origin in TUO patients is paramount to their improved treatment and survival but is difficult to obtain with current methods. Here, we develop a random forest machine learning TUO methylation classifier using a large number of primary and metastatic tumor samples. Our classifier achieves high accuracy in primary site identification when applied to both publicly available and internal validation samples, with 97% of samples classified correctly and 85% receiving high probability scores (≥0.9). Moreover, by employing pathologist expertise and t-SNE visualization, the TUO classifier can assign samples to 46 different sites of origin/disease classes. This strategy also revealed multiple classes of yet unknown significance for future exploration. Overall, the presented TUO classifier represents a significant step forward in the diagnosis of TUO tumors.

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Molecular Testing for the World Health Organization Classification of Central Nervous System Tumors: A Review

December 2024

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80 Reads

JAMA Oncology

Importance Molecular techniques, including next-generation sequencing, genomic copy number profiling, fusion transcript detection, and genomic DNA methylation arrays, are now indispensable tools for the workup of central nervous system (CNS) tumors. Yet there remains a great deal of heterogeneity in using such biomarker testing across institutions and hospital systems. This is in large part because there is a persistent reluctance among third-party payers to cover molecular testing. The objective of this Review is to describe why comprehensive molecular biomarker testing is now required for the accurate diagnosis and grading and prognostication of CNS tumors and, in so doing, to justify more widespread use by clinicians and coverage by third-party payers. Observations The 5th edition of the World Health Organization (WHO) classification system for CNS tumors incorporates specific molecular signatures into the essential diagnostic criteria for most tumor entities. Many CNS tumor types cannot be reliably diagnosed according to current WHO guidelines without molecular testing. The National Comprehensive Cancer Network also incorporates molecular testing into their guidelines for CNS tumors. Both sets of guidelines are maximally effective if they are implemented routinely for all patients with CNS tumors. Moreover, the cost of these tests is less than 5% of the overall average cost of caring for patients with CNS tumors and consistently improves management. This includes more accurate diagnosis and prognostication, clinical trial eligibility, and prediction of response to specific treatments. Each major group of CNS tumors in the WHO classification is evaluated and how molecular diagnostics enhances patient care is described. Conclusions and Relevance Routine advanced multidimensional molecular profiling is now required to provide optimal standard of care for patients with CNS tumors.


Progression-Free Survival (PFS) in (A) the overall cohort. (B) Comparison of gross-total resection (GTR) and subtotal resection (STR) shows that receiving STR is associated with shorter PFS. (C) However, among patients who received GTR, there was no difference in whether the resection was Simpson grade I or II. (D) Tumor location, defined as anterior, posterior, or lateral was not associated with PFS. Lastly, (E) methylation cluster did not have a statistically significant impact on PFS during the duration of follow-up available in the combined institutional and GSE212449 cohorts
Spinal Meningioma Methylation Clustering from institutional and GSE212449 datasets. (A) PAM clustering of samples revealed three stable clusters amongst 1000 bootstrap iterations. (B) Significant difference is evident between mean methylation levels in each cluster (**** = p <.0001, Wilcoxon-sum), with cluster 1 showing hypermethylation, cluster 2 showing intermediate methylation, and cluster 3 showing relatively low methylation levels. Horizontal lines represent the median and interquartile range. (C) Heatmap of the most variable probes (n = 1468) for each sample separated by cluster. Copy number gains and losses are shown for chromosomal arms previously associated with clinical outcome (1q, 14q, 9p, 6p, 1p, 22q). In addition, cohort origin, WHO grade, recurrence, histology, AKT1 and NF2 mutational status, and methylation array type are listed
Analysis of differentially methylated positions (DMPs) specific to cluster 1. (A) Cluster-specific DMPs separated by direction of change in methylation levels for each spinal meningioma cluster. (B) Top 5 transcription factors for hypermethylated cluster 1 specific DMPs. (C) Top 5 hypermethylated and hypomethylated genes enriched for cluster 1 specific DMPs. (D) Select Reactome pathways based on enrichment for hypermethylated cluster 1 specific DMPs, specifically highlighting the top two enriched terms for histone, HOX-, and PRC2 related terms
Evaluating immune enrichment in SM clusters via pairwise comparisons of A) Leukocyte fractions, B) average LYVE1 β value, C) average CD3E β value, and average CCL21 β value for each cluster. Horizontal lines represent the median and interquartile range. ns = Not significant. * = p <.05, ** = p <.01, and *** = p <.001
Clinical and methylomic features of spinal meningiomas

September 2024

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46 Reads

Journal of Neuro-Oncology

Purpose The objective of our study was to analyze methylomic and clinical features of a cohort of spinal meningiomas (SMs) resected at our institution. Methods This is a retrospective study of patients undergoing SM resection at our institution between 2010 and 2023. Clinical and radiographic characteristics were reviewed and analyzed with standard statistical methods. A Partitioning Around Medoids approach was used to cluster SMs with methylation data in a combined cohort from our institution and a publicly available dataset by methylation profiles. Clinical variables and pathway analyses were compared for the resulting clusters. Results Sixty-five SMs were resected in 53 patients with median radiographic follow-up of 34 months. Forty-six (87%) patients were female. The median age at surgery was 65 years and median tumor diameter was 1.9 cm. The five-year progression-free survival rate was 90%, with subtotal resection being associated with recurrence or progression (p = .017). SMs clustered into hypermethylation, intermediate methylation, and hypomethylation subgroups. Tumors in the hypermethylated subgroup were associated with higher WHO grade (p = .046) and higher risk histological subtypes (p <.001), while tumors in the hypomethylated subgroup were least likely to present with copy-number loss in chromosome 22q (p <.0001). SMs classified as immune-enriched under a previously developed intracranial meningioma classifier did not have increased leukocyte fractions or hypomethylation of genes typically hypomethylated in immune-enriched tumors. Conclusion SMs are more benign than their intracranial counterparts, and gross-total resection results in long term PFS. Methylation profiling identifies subgroups with differences in clinical variables.


cIMPACT-NOW Update 8: Clarifications on molecular risk parameters and recommendations for WHO grading of meningiomas

August 2024

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98 Reads

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8 Citations

Neuro-Oncology

Meningiomas are the most frequent primary intracranial tumors. Hence, they constitute a major share of diagnostic specimens in neuropathology practice. The 2021 WHO Classification of Central Nervous System Tumors (“CNS5”) has introduced the first molecular grading parameters for meningioma with oncogenic variants in the TERT promoter and homozygous deletion of CDKN2A/B as markers for CNS WHO grade 3. However, after publication of the new classification volume, clarifications were requested, not only on novel but also on long-standing questions in meningioma grading that were beyond the scope of the WHO “blue book”. In addition, more recent research into possible new molecular grading parameters could not yet be implemented in the 2021 classification but constitute a compelling body of literature. Hence, the cIMPACT-NOW Steering Committee convened a working group to provide such clarification and assess the evidence of possible novel molecular criteria. As a result, this cIMPACT-NOW update provides guidance for more standardized morphological evaluation and interpretation, most prominently pertaining to brain invasion, identifies scenarios in which advanced molecular testing is recommended, proposes to assign CNS WHO grade 2 for cases with CNS WHO grade 1 morphology but chromosomal arm 1p deletion in combination with 22q deletion and/or NF2 oncogenic variants, and discusses areas in which the current evidence is not yet sufficient to result in new recommendations.




Figure 2. Original representative images of the spatial and cellular localization of CD47/SIRPα expression. (a) A newly diagnosed glioblastoma specimen resected as a lobectomy in continuity with the adjacent infiltrating brain was analyzed using automated sequential multiplex immunofluorescence (n = 2) as previously described [21-23]. SIRPα (yellow; Cell Signaling, clone D613M, dilution 1/100) is expressed at the leading edge. CD47 (red; Novus Bio, clone B6H12.2, dilution 1/100) is
Glioblastoma Phagocytic Cell Death: Balancing the Opportunities for Therapeutic Manipulation

May 2024

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43 Reads

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3 Citations

Cells

Macrophages and microglia are professional phagocytes that sense and migrate toward “eat-me” signals. The role of phagocytic cells is to maintain homeostasis by engulfing senescent or apoptotic cells, debris, and abnormally aggregated macromolecules. Usually, dying cells send out “find-me” signals, facilitating the recruitment of phagocytes. Healthy cells can also promote or inhibit the phagocytosis phenomenon of macrophages and microglia by tuning the balance between “eat-me” and “don’t-eat-me” signals at different stages in their lifespan, while the “don’t-eat-me” signals are often hijacked by tumor cells as a mechanism of immune evasion. Using a combination of bioinformatic analysis and spatial profiling, we delineate the balance of the “don’t-eat-me” CD47/SIRPα and “eat-me” CALR/STC1 ligand–receptor interactions to guide therapeutic strategies that are being developed for glioblastoma sequestered in the central nervous system (CNS).


High-risk meningioma features.
Timeline of prognostic advances in meningiomas. Progressive molecular and histological characterization has led to refinement in the clinical treatment of meningiomas, including improvement in prognostic accuracy and selection of appropriate therapeutic interventions. The past thirty-five years have been marked by rapid molecular advances (inset panel), including high-throughput sequencing and genome-wide epigenetic studies.
Progressive advancement in clinical management of meningiomas. In most clinical settings, the current management of meningiomas is determined by histopathological markers and the extent of surgical resection. Emerging diagnostics include the consideration of copy number events and advanced molecular profiling. As our understanding of meningioma biology matures, the emergence of consensus-integrated paradigms will guide the selection of adjuvant therapies and the need for more frequent follow-up and imaging.
Case examples demonstrating how molecular profiling can inform care. T1 post-contrast MRI from two WHO grade 2 meningiomas (A,B) who both presented with a seizure and underwent gross total resection (C,D). The patient on the left had a hypermitotic methylation profile and chromosome losses at 1p, 6, 14, haplo-insufficiency of CDKN2A, and 22q, making it a Driver et al. integrated grade 3 tumor, with a high Chen et al. gene expression risk score. He underwent 59.4 Gy adjuvant radiotherapy and had an in-field recurrence (E) at 15 months post-operative. The patient on the right also had a WHO grade 2 meningioma that had an immune-enriched methylation profile and chromosome 8 loss with haplo-insufficiency of chromosome 22, making it a Driver et al. integrated grade 1 tumor [86], and had a low Chen et al. gene expression risk score [126]. She was observed given the favorable molecular profile without adjuvant radiotherapy and had no recurrence at 2 years post-operative (F).
The Evolving Classification of Meningiomas: Integration of Molecular Discoveries to Inform Patient Care

April 2024

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101 Reads

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2 Citations

Simple Summary Meningiomas are the most common intracranial tumors, and significant advances have been made in our understanding of the biology that leads to meningioma growth and aggressiveness. This review summarizes molecular advances and the historical contexts that led to them. Abstract Meningioma classification and treatment have evolved over the past eight decades. Since Bailey, Cushing, and Eisenhart’s description of meningiomas in the 1920s and 1930s, there have been continual advances in clinical stratification by histopathology, radiography and, most recently, molecular profiling, to improve prognostication and predict response to therapy. Precise and accurate classification is essential to optimizing management for patients with meningioma, which involves surveillance imaging, surgery, primary or adjuvant radiotherapy, and consideration for clinical trials. Currently, the World Health Organization (WHO) grade, extent of resection (EOR), and patient characteristics are used to guide management. While these have demonstrated reliability, a substantial number of seemingly benign lesions recur, suggesting opportunities for improvement of risk stratification. Furthermore, the role of adjuvant radiotherapy for grade 1 and 2 meningioma remains controversial. Over the last decade, numerous studies investigating the molecular drivers of clinical aggressiveness have been reported, with the identification of molecular markers that carry clinical implications as well as biomarkers of radiotherapy response. Here, we review the historical context of current practices, highlight recent molecular discoveries, and discuss the challenges of translating these findings into clinical practice.


(A) Chord plot depicting NAB2::STAT6 fusion breakpoints identified within the cohort. (B) Swimmer's plots (all patients) depicting patient adverse events by fusion type. The dashed lines highlight the time between the original diagnosis and the time when the specimen was reviewed.
(A) t‐Distributed stochastic neighbor embedding (t‐SNE) plot demonstrating three distinct methylation clusters including Cluster 1 (gold; n = 38), Cluster 2 (green; n = 22), Cluster 3 (orange; n = 20). (B) Swimmer's plots depicting patient adverse events throughout disease course by methylation cluster and fusion type. The dashed lines highlight the time between the original diagnosis and the time when the specimen was reviewed.
(A) Kaplan–Meier curves for metastasis‐free survival and overall survival amongst all patients from time of diagnosis by dichotomized fusion type (A, B; n = 99) and methylation clusters (C, D; n = 79). Kaplan–Meier curves for metastasis‐free survival and overall survival for patients in which the primary resection specimen was available (n = 88) by WHO (E, F).
(A, B) Kaplan–Meier curves for disease‐specific survival (A) and overall survival (B) of dichotomized NAB2::STAT6 fusion type, limited to cases in which the primary resection was available for review (n = 74) from time of surgery.
NAB2::STAT6 fusions and genome‐wide DNA methylation profiling: Predictors of patient outcomes in meningeal solitary fibrous tumors

March 2024

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40 Reads

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2 Citations

Meningeal solitary fibrous tumors (SFT) are rare and have a high frequency of local recurrence and distant metastasis. In a cohort of 126 patients (57 female, 69 male; mean age at surgery 53.0 years) with pathologically confirmed meningeal SFTs with extended clinical follow‐up (median 9.9 years; range 15 days–43 years), we performed extensive molecular characterization including genome‐wide DNA methylation profiling (n = 80) and targeted TERT promoter mutation testing (n = 98). Associations were examined with NAB2::STAT6 fusion status (n = 101 cases; 51 = ex5‐7::ex16‐17, 26 = ex4::ex2‐3; 12 = ex2‐3::exANY/other and 12 = no fusion) and placed in the context of 2021 Central Nervous System (CNS) WHO grade. NAB2::STAT6 fusion breakpoints (fusion type) were significantly associated with metastasis‐free survival (MFS) (p = 0.03) and, on multivariate analysis, disease‐specific survival (DSS) when adjusting for CNS WHO grade (p = 0.03). DNA methylation profiling revealed three distinct clusters: Cluster 1 (n = 38), Cluster 2 (n = 22), and Cluster 3 (n = 20). Methylation clusters were significantly associated with fusion type (p < 0.001), with Cluster 2 harboring ex4::ex2‐3 fusion in 16 (of 20; 80.0%), nearly all TERT promoter mutations (7 of 8; 87.5%), and predominantly an “SFT” histologic phenotype (15 of 22; 68.2%). Clusters 1 and 3 were less distinct, both dominated by tumors having ex5‐7::ex16‐17 fusion (respectively, 25 of 33; 75.8%, and 12 of 18; 66.7%) and with variable histological phenotypes. Methylation clusters were significantly associated with MFS (p = 0.027), but not overall survival (OS). In summary, NAB2::STAT6 fusion type was significantly associated with MFS and DSS, suggesting that tumors with an ex5::ex16‐17 fusion may have inferior patient outcomes. Methylation clusters were significantly associated with fusion type, TERT promoter mutation status, histologic phenotype, and MFS.


Integrated Proteogenomics Uncover Mechanisms of Glioblastoma Evolution, Pointing to Novel Therapeutic Targets

February 2024

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26 Reads

Cancer Research

Nearly all glioblastoma (GBM) patients relapse following standard treatment and eventually succumb to disease. While large scale, integrated multi-omic studies have tremendously advanced the understanding of primary GBM at the cellular and molecular level, the post-therapeutic trajectory and biological properties of recurrent GBM remain poorly understood. This knowledge gap was addressed in a recent Cancer Cell article in which Kim and colleagues report on a highly integrative proteogenomic analysis performed on 123 matched primary and recurrent GBMs that uncovered a dramatic evolutionary shift from a proliferative state at initial diagnosis to the activation of neuronal and synaptogenic pathways at recurrence following therapy. Neuronal transition was characterized by post-translational activation of WNT/PCP signaling and BRAF kinase, while many canonical oncogenic pathways, and EGFR in particular, were downregulated. Parallel multi-omics analyses of patient-derived xenograft (PDX) models corroborated this evolutionary trajectory, allowing in vivo experiments for translational significance. Notably, targeting BRAF kinase disrupted both the neuronal transition and migration capabilities of recurrent gliomas, which were key characteristics of post-treatment progression. Furthermore, combining BRAF inhibitor vemurafenib with temozolomide (TMZ) prolonged survival in PDX models. Overall, the results reveal novel biological mechanisms of GBM evolution and therapy resistance, and suggest promising therapeutic intervention.


Citations (71)


... Furthermore, the study of the cancer methylome also reflects additional somatic alterations 10 such as IDH mutation, which induces DNA hypermethylation, leads to the "glioma CpG island methylator phenotype" (G-CIMP) 11,12 . These epigenetic profiles have already been shown to be effective for subclassifying CNS tumors like ependymomas, CNS embryonal tumors and meningiomas 13,14 . ...

Reference:

Diagnostic impact of DNA methylation classification in adult and pediatric CNS tumors
cIMPACT-NOW Update 8: Clarifications on molecular risk parameters and recommendations for WHO grading of meningiomas
  • Citing Article
  • August 2024

Neuro-Oncology

... Some of these roles include: transmitting inflammatory signals, inducing immune responses, transferring genetic material, and regulating cell growth and proliferation [46,47]. For example, apoptotic bodies can carry "eat-me" signals on their surface, which help phagocytic cells identify and eliminate them [48]. Additionally, these bodies can transfer their antigens to antigen-presenting cells (APCs), thereby stimulating an immune response. ...

Glioblastoma Phagocytic Cell Death: Balancing the Opportunities for Therapeutic Manipulation

Cells

... MEN classification underwent significant changes in 2004-2007 (e.g. WHO defined the histological features for atypia) and this may have contributed to the trend we report 56 . Furthermore, exposure to ionizing radiation has been recognized as an environmental risk factor for both GB and MEN 25,57 . ...

The Evolving Classification of Meningiomas: Integration of Molecular Discoveries to Inform Patient Care

... These processes collectively facilitate the polarization of macrophages towards an M2-like phenotype. Moreover, TAMs supply creatine to tumors, helping them to withstand hypoxia-induced stress and facilitating glioblastoma progression (Rashidi et al. 2024). In glioblastoma, TAMs produce large amounts of polyamines to buffer the low intracellular pH, enabling their survival in the harsh acidic environment of solid tumors. ...

Myeloid cell-derived creatine in the hypoxic niche promotes glioblastoma growth
  • Citing Article
  • December 2023

Cell Metabolism

... The commercial tissue microarray (TMA) chip (code: D078Pa01) containing 39 cases of pancreatic cancer and matched adjacent pancreatic tissues was purchased from Bioaitech Company in China [33]. Initially, a preliminary experiment was conducted to determine the appropriate antibodies and their dilutions, followed by performing the standard IHC protocol. ...

ATXN3 deubiquitinates YAP1 to promote tumor growth
  • Citing Article
  • September 2023

American Journal of Cancer Research

... Several examples exist for the power of such approaches [44,71]. Recently, a proposal has been made for comprehensive tissue sampling by an international consensus [35]. At present, this may be considered a step back, but the present evolution of signatures, specifically the NAM, needs to be validated for consistency and correlation with clinical parameters such as anatomical location and zones of infiltration and imaging characteristics. ...

A framework for standardised tissue sampling and processing during resection of diffuse intracranial glioma: joint recommendations from four RANO groups
  • Citing Article
  • November 2023

The Lancet Oncology

... Xenograft cells (1×10 6 ) were incubated with fluorochromeconjugated antibodies for 15-30 min at 4 • C in 100 µL of Hanks' balanced saline solution (HBSS) containing 2 % FBS and 5-20 µL of each undiluted antibody as we described previously [26][27][28][29][30]. After washing three times in HBSS, cells were suspended in HBSS supplemented with 5 % FBS and subsequently analyzed with a LSR II (Becton Dickinson). ...

Targeting GBM with an Oncolytic Picornavirus SVV-001 alone and in combination with fractionated Radiation in a Novel Panel of Orthotopic PDX models

Journal of Translational Medicine

... Disialoganglioside (GD2) is a cell surface glycosphingolipid that has been identified as an attractive target for CAR-T cell therapy due to its high expression in several cancers, including neuroblastoma [11,20,24] and GBM [20,25]. A novel virus-free manufactured anti-GD2 CAR-T cell product has demonstrated encouraging results against neuroblastoma in 2D in vitro assays and in vivo studies [24], and against GBM in 2D label-free in vitro assays [26]. Despite these findings, there remains an opportunity to incorporate additional in vitro assays to understand and potentially predict the in vivo behavior of a solid tumor and immune cell interactions in 3D. ...

Label-free in vitro assays predict the potency of anti-disialoganglioside chimeric antigen receptor T-cell products

Cytotherapy

... PD-1 and its ligand PD-L1 have been shown to delay neutrophil apoptosis 58 , which may be related to our inverse risk association with neutrophils in IDH mut tumors. PD-1/PD-L1 check point inhibitors have been of interest as a potential glioma therapeutic, however most trials have focused on glioblastoma tumors (IDH wt according to WHO 2021) with limited success 59 . Our results suggest that the success of anti-PD-1/PD-L1 therapy may vary by IDH status and germline predisposition. ...

Immune checkpoint blockade in glioblastoma: from tumor heterogeneity to personalized treatment

The Journal of clinical investigation

... TP53 is a well-known tumor suppressor gene [53] that is frequently mutated in H3.3-G34R/V mutant gliomas [4,54]. TP53 mutations were incorporated into many of the models generated to study H3.3-G34R/V mutant gliomas [48,[55][56][57][58]. Its specific role in the gliomagenesis of pediatric DHG is not understood, but p53 is a well-known tumor suppressor that is commonly mutated in cancers. ...

Novel genetically engineered H3.3G34R model reveals cooperation with ATRX loss in upregulation of Hoxa cluster genes and promotion of neuronal lineage

Neuro-Oncology Advances