Papillary tumor of the pineal region: analysis of DNA methylation profiles and clinical outcomes in 76 cases.

Papillary tumor of the pineal region (PTPR) is an uncommon tumor of the pineal region with distinctive histopathologic and molecular characteristics. Experience is limited with respect to its molecular heterogeneity and clinical characteristics. Here, we describe 39 new cases and combine these with 37 previously published cases for a cohort of 76 PTPR's, all confirmed by methylation profiling. As previously reported, two main methylation groups were identified (PTPR-A and PTPR-B). In our analysis we extended the subtyping into three subtypes: PTPR-A, PTPR-B1 and PTPR-B2 supported by DNA methylation profile and genomic copy number variations. Frequent loss of chromosome 3 or 14 was found in PTPR-B1 tumors but not in PTPR-B2. Examination of clinical outcome showed that nearly half (14/30, 47%) of examined patients experienced tumor progression with significant difference among the subtypes (p value = 0.046). Our analysis extends the understanding of this uncommon but distinct neuroepithelial tumor by describing its molecular heterogeneity and clinical outcomes, including its tendency towards tumor recurrence.

Genetic and epigenetic instability as an underlying driver of progression and aggressive behavior in IDH-mutant astrocytoma.

In recent years, the classification of adult-type diffuse gliomas has undergone a revolution, wherein specific molecular features now represent defining diagnostic criteria of IDH-wild-type glioblastomas, IDH-mutant astrocytomas, and IDH-mutant 1p/19q-codeleted oligodendrogliomas. With the introduction of the 2021 WHO CNS classification, additional molecular alterations are now integrated into the grading of these tumors, given equal weight to traditional histologic features. However, there remains a great deal of heterogeneity in patient outcome even within these established tumor subclassifications that is unexplained by currently codified molecular alterations, particularly in the IDH-mutant astrocytoma category. There is also significant intercellular genetic and epigenetic heterogeneity and plasticity with resulting phenotypic heterogeneity, making these tumors remarkably adaptable and robust, and presenting a significant barrier to the design of effective therapeutics. Herein, we review the mechanisms and consequences of genetic and epigenetic instability, including chromosomal instability (CIN), microsatellite instability (MSI)/mismatch repair (MMR) deficits, and epigenetic instability, in the underlying biology, tumorigenesis, and progression of IDH-mutant astrocytomas. We also discuss the contribution of recent high-resolution transcriptomics studies toward defining tumor heterogeneity with single-cell resolution. While intratumoral heterogeneity is a well-known feature of diffuse gliomas, the contribution of these various processes has only recently been considered as a potential driver of tumor aggressiveness. CIN has an independent, adverse effect on patient survival, similar to the effect of histologic grade and homozygous CDKN2A deletion, while MMR mutation is only associated with poor overall survival in univariate analysis but is highly correlated with higher histologic/molecular grade and other aggressive features. These forms of genomic instability, which may significantly affect the natural progression of these tumors, response to therapy, and ultimately clinical outcome for patients, are potentially measurable features which could aid in diagnosis, grading, prognosis, and development of personalized therapeutics.

Two-Stage Training Framework Using Multicontrast MRI Radiomics for IDH Mutation Status Prediction in Glioma.

Purpose To develop a radiomics framework for preoperative MRI-based prediction of isocitrate dehydrogenase (IDH) mutation status, a crucial glioma prognostic indicator. Materials and Methods Radiomics features (shape, first-order statistics, and texture) were extracted from the whole tumor or the combination of nonenhancing, necrosis, and edema regions. Segmentation masks were obtained via the federated tumor segmentation tool or the original data source. Boruta, a wrapper-based feature selection algorithm, identified relevant features. Addressing the imbalance between mutated and wild-type cases, multiple prediction models were trained on balanced data subsets using random forest or XGBoost and assembled to build the final classifier. The framework was evaluated using retrospective MRI scans from three public datasets (The Cancer Imaging Archive [TCIA, 227 patients], the University of California San Francisco Preoperative Diffuse Glioma MRI dataset [UCSF, 495 patients], and the Erasmus Glioma Database [EGD, 456 patients]) and internal datasets collected from the University of Texas Southwestern Medical Center (UTSW, 356 patients), New York University (NYU, 136 patients), and University of Wisconsin-Madison (UWM, 174 patients). TCIA and UTSW served as separate training sets, while the remaining data constituted the test set (1617 or 1488 testing cases, respectively). Results The best performing models trained on the TCIA dataset achieved area under the receiver operating characteristic curve (AUC) values of 0.89 for UTSW, 0.86 for NYU, 0.93 for UWM, 0.94 for UCSF, and 0.88 for EGD test sets. The best performing models trained on the UTSW dataset achieved slightly higher AUCs: 0.92 for TCIA, 0.88 for NYU, 0.96 for UWM, 0.93 for UCSF, and 0.90 for EGD. Conclusion This MRI radiomics-based framework shows promise for accurate preoperative prediction of IDH mutation status in patients with glioma. Keywords: Glioma, Isocitrate Dehydrogenase Mutation, IDH Mutation, Radiomics, MRI Supplemental material is available for this article. Published under a CC BY 4.0 license. See also commentary by Moassefi and Erickson in this issue.

Synthesizing 3D Multi-Contrast Brain Tumor MRIs Using Tumor Mask Conditioning.

Data scarcity and data imbalance are two major challenges in training deep learning models on medical images, such as brain tumor MRI data. The recent advancements in generative artificial intelligence have opened new possibilities for synthetically generating MRI data, including brain tumor MRI scans. This approach can be a potential solution to mitigate the data scarcity problem and enhance training data availability. This work focused on adapting the 2D latent diffusion models to generate 3D multi-contrast brain tumor MRI data with a tumor mask as the condition. The framework comprises two components: a 3D autoencoder model for perceptual compression and a conditional 3D Diffusion Probabilistic Model (DPM) for generating high-quality and diverse multi-contrast brain tumor MRI samples, guided by a conditional tumor mask. Unlike existing works that focused on generating either 2D multi-contrast or 3D single-contrast MRI samples, our models generate multi-contrast 3D MRI samples. We also integrated a conditional module within the UNet backbone of the DPM to capture the semantic class-dependent data distribution driven by the provided tumor mask to generate MRI brain tumor samples based on a specific brain tumor mask. We trained our models using two brain tumor datasets: The Cancer Genome Atlas (TCGA) public dataset and an internal dataset from the University of Texas Southwestern Medical Center (UTSW). The models were able to generate high-quality 3D multi-contrast brain tumor MRI samples with the tumor location aligned by the input condition mask. The quality of the generated images was evaluated using the Fréchet Inception Distance (FID) score. This work has the potential to mitigate the scarcity of brain tumor data and improve the performance of deep learning models involving brain tumor MRI data.

First reported Rhodotorula mucilaginosa brain abscess: Found as coinfection in woman with common variable immune deficiency.

Rhodotorula is a rare pathogen seen in the immunocompromised host; while cases of Rhodotorula meningitis have been reported, there are no published cases of Rhodotorula brain abscess. We describe the diagnosis and management of a woman with common variable immune deficiency presenting with concomitant Rhodotorula and Nocardia brain abscesses.

MRI-Based Deep Learning Method for Classification of IDH Mutation Status.

Isocitrate dehydrogenase (IDH) mutation status has emerged as an important prognostic marker in gliomas. This study sought to develop deep learning networks for non-invasive IDH classification using T2w MR images while comparing their performance to a multi-contrast network. Methods: Multi-contrast brain tumor MRI and genomic data were obtained from The Cancer Imaging Archive (TCIA) and The Erasmus Glioma Database (EGD). Two separate 2D networks were developed using nnU-Net, a T2w-image-only network (T2-net) and a multi-contrast network (MC-net). Each network was separately trained using TCIA (227 subjects) or TCIA + EGD data (683 subjects combined). The networks were trained to classify IDH mutation status and implement single-label tumor segmentation simultaneously. The trained networks were tested on over 1100 held-out datasets including 360 cases from UT Southwestern Medical Center, 136 cases from New York University, 175 cases from the University of Wisconsin-Madison, 456 cases from EGD (for the TCIA-trained network), and 495 cases from the University of California, San Francisco public database. A receiver operating characteristic curve (ROC) was drawn to calculate the AUC value to determine classifier performance. Results: T2-net trained on TCIA and TCIA + EGD datasets achieved an overall accuracy of 85.4% and 87.6% with AUCs of 0.86 and 0.89, respectively. MC-net trained on TCIA and TCIA + EGD datasets achieved an overall accuracy of 91.0% and 92.8% with AUCs of 0.94 and 0.96, respectively. We developed reliable, high-performing deep learning algorithms for IDH classification using both a T2-image-only and a multi-contrast approach. The networks were tested on more than 1100 subjects from diverse databases, making this the largest study on image-based IDH classification to date.

Cervical intradural traumatic neuroma without history of trauma: illustrative case.

BACKGROUND: Traumatic neuroma typically refers to a reactive process in the injured peripheral nerve, characterized by an excessive growth of axons, Schwann cells, and fibroblasts at the proximal end of the nerve after its interruption. The authors report a case of a traumatic neuroma in the cervical nerve root in a patient with no history of trauma. OBSERVATIONS: The patient presented with sensation loss in the right-hand ulnar distribution, right flank around the T4-11 region, and right small toe along with motor power weakness over the right upper and lower extremity. Magnetic resonance imaging revealed an intradural extramedullary mass lesion with extension along the C7 nerve root. Histological examination showed traumatic neuroma. A total resection of the lesion along with the resolution of sensory and motor deficits was achieved directly after surgery. LESSONS: Traumatic neuroma should always be kept in the armamentarium for diagnosis of an intradural nerve sheath tumor.

Mismatch repair protein mutations in isocitrate dehydrogenase (IDH)-mutant astrocytoma and IDH-wild-type glioblastoma.

Background: Mutations in mismatch repair (MMR) genes (MSH2, MSH6, MLH1, and PMS2) are associated with microsatellite instability and a hypermutator phenotype in numerous systemic cancers, and germline MMR mutations have been implicated in multi-organ tumor syndromes. In gliomas, MMR mutations can function as an adaptive response to alkylating chemotherapy, although there are well-documented cases of germline and sporadic mutations, with detrimental effects on patient survival. Methods: The clinical, pathologic, and molecular features of 18 IDH-mutant astrocytomas and 20 IDH-wild-type glioblastomas with MMR mutations in the primary tumor were analyzed in comparison to 361 IDH-mutant and 906 IDH-wild-type tumors without MMR mutations. In addition, 12 IDH-mutant astrocytomas and 18 IDH-wild-type glioblastomas that developed MMR mutations between initial presentation and tumor recurrence were analyzed in comparison to 50 IDH-mutant and 104 IDH-wild-type cases that remained MMR-wild-type at recurrence. Results: In both IDH-mutant astrocytoma and IDH-wild-type glioblastoma cohorts, the presence of MMR mutation in primary tumors was associated with significantly higher tumor mutation burden (TMB) (P < .0001); however, MMR mutations only resulted in worse overall survival in the IDH-mutant astrocytomas (P = .0069). In addition, gain of MMR mutation between the primary and recurrent surgical specimen occurred more frequently with temozolomide therapy (P = .0073), and resulted in a substantial increase in TMB (P < .0001), higher grade (P = .0119), and worse post-recurrence survival (P = .0022) in the IDH-mutant astrocytoma cohort. Conclusions: These results suggest that whether present initially or in response to therapy, MMR mutations significantly affect TMB but appear to only influence the clinical outcome in IDH-mutant astrocytoma subsets.

Case report: Two sisters with a germline CHEK2 variant and distinct endocrine neoplasias.

Genetic testing has become the standard of care for many disease states. As a result, physicians treating patients who have tumors often rely on germline genetic testing results for making clinical decisions. Cases of two sisters carrying a germline CHEK2 variant are highlighted whereby possible other genetic drivers were discovered on tumor analysis. CHEK2 (also referred to as CHK2) loss of function has been firmly associated with breast cancer development. In this case report, two siblings with a germline CHEK2 mutation also had distinct endocrine tumors. Pituitary adenoma and pancreatic neuroendocrine tumor (PNET) was found in the first sibling and pheochromocytoma (PCC) discovered in the second sibling. Although pituitary adenomas, PNETs, and PCC have been associated with NF1 gene mutations, the second sister with a PCC did have proven germline CHEK2 with a pathogenic somatic NF1 mutation. We highlight the clinical point that unless the tumor is sequenced, the real driver mutation that is causing the patient's tumor may remain unknown.

Chromosomal instability in adult-type diffuse gliomas.

Chromosomal instability (CIN) is a fundamental property of cancer and a key underlying mechanism of tumorigenesis and malignant progression, and has been documented in a wide variety of cancers, including colorectal carcinoma with mutations in genes such as APC. Recent reports have demonstrated that CIN, driven in part by mutations in genes maintaining overall genomic stability, is found in subsets of adult-type diffusely infiltrating gliomas of all histologic and molecular grades, with resulting elevated overall copy number burden, chromothripsis, and poor clinical outcome. Still, relatively few studies have examined the effect of this process, due in part to the difficulty of routinely measuring CIN clinically. Herein, we review the underlying mechanisms of CIN, the relationship between chromosomal instability and malignancy, the prognostic significance and treatment potential in various cancers, systemic disease, and more specifically, in diffusely infiltrating glioma subtypes. While still in the early stages of discovery compared to other solid tumor types in which CIN is a known driver of malignancy, the presence of CIN as an early factor in gliomas may in part explain the ability of these tumors to develop resistance to standard therapy, while also providing a potential molecular target for future therapies.

EGFR ligand shifts the role of EGFR from oncogene to tumour suppressor in EGFR-amplified glioblastoma by suppressing invasion through BIN3 upregulation.

The epidermal growth factor receptor (EGFR) is a prime oncogene that is frequently amplified in glioblastomas. Here we demonstrate a new tumour-suppressive function of EGFR in EGFR-amplified glioblastomas regulated by EGFR ligands. Constitutive EGFR signalling promotes invasion via activation of a TAB1-TAK1-NF-κB-EMP1 pathway, resulting in large tumours and decreased survival in orthotopic models. Ligand-activated EGFR promotes proliferation and surprisingly suppresses invasion by upregulating BIN3, which inhibits a DOCK7-regulated Rho GTPase pathway, resulting in small hyperproliferating non-invasive tumours and improved survival. Data from The Cancer Genome Atlas reveal that in EGFR-amplified glioblastomas, a low level of EGFR ligands confers a worse prognosis, whereas a high level of EGFR ligands confers an improved prognosis. Thus, increased EGFR ligand levels shift the role of EGFR from oncogene to tumour suppressor in EGFR-amplified glioblastomas by suppressing invasion. The tumour-suppressive function of EGFR can be activated therapeutically using tofacitinib, which suppresses invasion by increasing EGFR ligand levels and upregulating BIN3.

Semi-Automated Computational Assessment of Cancer Organoid Viability Using Rapid Live-Cell Microscopy.

The creation of patient-derived cancer organoids represents a key advance in preclinical modeling and has recently been applied to a variety of human solid tumor types. However, conventional methods used to assess in vivo tumor tissue treatment response are poorly suited for the evaluation of cancer organoids because they are time-intensive and involve tissue destruction. To address this issue, we established a suite of 3-dimensional patient-derived glioma organoids, treated them with chemoradiotherapy, stained organoids with non-toxic cell dyes, and imaged them using a rapid laser scanning confocal microscopy method termed "Apex Imaging." We then developed and tested a fragmentation algorithm to quantify heterogeneity in the topography of the organoids as a potential surrogate marker of viability. This algorithm, SSDquant, provides a 3-dimensional visual representation of the organoid surface and a numerical measurement of the sum-squared distance (SSD) from the derived mass center of the organoid. We tested whether SSD scores correlate with traditional immunohistochemistry-derived cell viability markers (cellularity and cleaved caspase 3 expression) and observed statistically significant associations between them using linear regression analysis. Our work describes a quantitative, non-invasive approach for the serial measurement of patient-derived cancer organoid viability, thus opening new avenues for the application of these models to studies of cancer biology and therapy.

Targeting BCAT1 Combined with α-Ketoglutarate Triggers Metabolic Synthetic Lethality in Glioblastoma.

Branched-chain amino acid transaminase 1 (BCAT1) is upregulated selectively in human isocitrate dehydrogenase (IDH) wildtype (WT) but not mutant glioblastoma multiforme (GBM) and promotes IDHWT GBM growth. Through a metabolic synthetic lethal screen, we report here that α-ketoglutarate (AKG) kills IDHWT GBM cells when BCAT1 protein is lost, which is reversed by reexpression of BCAT1 or supplementation with branched-chain α-ketoacids (BCKA), downstream metabolic products of BCAT1. In patient-derived IDHWT GBM tumors in vitro and in vivo, cotreatment of BCAT1 inhibitor gabapentin and AKG resulted in synthetic lethality. However, AKG failed to evoke a synthetic lethal effect with loss of BCAT2, BCKDHA, or GPT2 in IDHWT GBM cells. Mechanistically, loss of BCAT1 increased the NAD+/NADH ratio but impaired oxidative phosphorylation, mTORC1 activity, and nucleotide biosynthesis. These metabolic alterations were synergistically augmented by AKG treatment, thereby causing mitochondrial dysfunction and depletion of cellular building blocks, including ATP, nucleotides, and proteins. Partial restoration of ATP, nucleotides, proteins, and mTORC1 activity by BCKA supplementation prevented IDHWT GBM cell death conferred by the combination of BCAT1 loss and AKG. These findings define a targetable metabolic vulnerability in the most common subset of GBM that is currently incurable. SIGNIFICANCE: Metabolic synthetic lethal screening in IDHWT glioblastoma defines a vulnerability to ΑΚG following BCAT1 loss, uncovering a therapeutic strategy to improve glioblastoma treatment. See related commentary by Meurs and Nagrath, p. 2354.

Imaging characteristics of 4th ventricle subependymoma.

PURPOSE: Subependymomas located within the 4th ventricle are rare, and the literature describing imaging characteristics is sparse. Here, we describe the clinical and radiological characteristics of 29 patients with 4th ventricle subependymoma. METHODS: This is a retrospective multi-center study performed after Institutional Review Board (IRB) approval. Patients diagnosed with suspected 4th ventricle subependymoma were identified. A review of clinical, radiology, and pathology reports along with magnetic resonance imaging (MRI) images was performed. RESULTS: Twenty-nine patients, including 6 females, were identified. Eighteen patients underwent surgery with histopathological confirmation of subependymoma. The median age at diagnosis was 52 years. Median tumor volume for the operative cohort was 9.87 cm3, while for the non-operative cohort, it was 0.96 cm3. Thirteen patients in the operative group exhibited symptoms at diagnosis. For the total cohort, the majority of subependymomas (n = 22) were isointense on T1, hyperintense (n = 22) on T2, and enhanced (n = 24). All tumors were located just below the body of the 4th ventricle, terminating near the level of the obex. Fourteen cases demonstrated extension of tumor into foramen of Magendie or Luschka. CONCLUSION: To the best of our knowledge, this is the largest collection of 4th ventricular subependymomas with imaging findings reported to date. All patients in this cohort had tumors originating between the bottom of the body of the 4th ventricle and the obex. This uniform and specific site of origin aids with imaging diagnosis and may infer possible theories of origin.

Epigenetic and genomic profiling of chordoid meningioma: implications for clinical management.

Chordoid meningioma is a morphological variant of meningioma designated as WHO grade 2. However, the recurrence rates varied widely in different case series, and to date, a unifying molecular genetic signature has not been identified. Among 1897 meningiomas resected at our institution, we identified 12 primary chordoid meningiomas from 12 patients. Histologically, all 12 cases had predominant (> 50%) chordoid morphology. Ten were otherwise grade 1, and two were also atypical. We performed DNA global methylation profile, copy number variation analysis, and targeted next-generation sequencing on 11 chordoid meningiomas, and compared to those of 51 non-chordoid, mostly high grade meningiomas. The chordoid meningiomas demonstrated a unique methylation profile in tSNE, UMAP, and hierarchical heatmap clustering analyses of the most differentially methylated CpGs. The most common copy number variation in chordoid meningioma was loss of 1p (7/11, 64%). Three chordoid meningiomas had 2p loss, which was significantly higher than the non-chordoid control cohort (27% vs 7.2%, p = 0.035). 22q loss was only seen in the two cases with additional atypical histological features. Chordoid meningiomas were enriched in mutations in chromatin remodeling genes EP400 (8/11,73%) KMT2C (4/11, 36%) and KMT2D (4/11, 36%), and showed low or absent NF2, TERT, SMO, and AKT1 mutations. Prognosis wise, only one case recurred. This case had atypical histology and high-grade molecular features including truncating NF2 mutation, 1p, 8p, 10, 14, 22q loss, and homozygous deletion of CDKN2A/B. Progression free survival of chordoid, otherwise grade 1 meningioma was comparable to non-chordoid WHO grade 1 meningioma (p = 0.75), and significantly better than chordoid WHO grade 2 meningioma (p = 0.019). Conclusion: the chordoid histology alone may not justify a universal WHO grade 2 designation. Screening for additional atypical histological or molecular genetic features is recommended.

Global DNA methylation profiling reveals chromosomal instability in IDH-mutant astrocytomas.

Diffusely infiltrating gliomas are among the most common central nervous system tumors in adults. Over the past decade, the subcategorization of these tumors has changed to include both traditional histologic features and more recently identified molecular factors. However, one molecular feature that has yet to be integrated is the presence/absence of chromosomal instability (CIN). Herein, we use global methylation profiling to evaluate a reference cohort of IDH-mutant astrocytomas with and without prior evidence of CIN (n = 42), and apply the resulting methylation-based characteristics to a larger test cohort of publicly-available IDH-mutant astrocytomas (n = 245). We demonstrate that IDH-mutant astrocytomas with evidence of CIN cluster separately from their chromosomally-stable counterparts. CIN cases were associated with higher initial histologic grade, altered expression patterns of genes related to CIN in other cancers, elevated initial total copy number burden, and significantly worse progression-free and overall survival. In addition, in a grade-for-grade analysis, patients with CIN-positive WHO grade 2 and 3 tumors had significantly worse survival. These results suggest that global methylation profiling can be used to discriminate between chromosomally stable and unstable IDH-mutant astrocytomas, and may therefore provide a reliable and cost-effective method for identifying gliomas with chromosomal instability and resultant poor clinical outcome.

Distant Pituitary Adenoma Spread: A Systematic Review and Report of 2 Cases.

BACKGROUND: Distant spread of pituitary adenoma outside the sellar/suprasellar region is classified as pituitary carcinoma. Cerebrospinal fluid (CSF)-born spread of pituitary adenoma can occur after tumor cell spillage into the CSF space after surgery, irradiation, or apoplexy and is not necessarily related to intrinsic tumor biology. OBJECTIVE: To systematically review the literature and describe the clinical characteristics and treatment strategies of patients with pituitary carcinomas. We further present 2 cases from our institution. METHODS: A single-center retrospective review of patients with pituitary adenoma spread to distant intracranial locations between 2000 and 2020 was performed. Electronic databases were searched from their inception to May 25, 2021, and studies describing patients with pituitary spread to distant locations were included. RESULTS: Of 1210 pituitary adenoma cases reviewed, 2 (0.16%) showed tumor spread to distant locations. We found 134 additional cases (from 108 published articles) resulting in a total of 136 cases (61.9% were male). The time to tumor spread ranged between 0 and 516 months (median: 96 months). The follow-up duration ranged between 0 and 240 months (median: 11.5 months). All but 2 patients (98.5%) underwent surgical resection before adenoma spread. The 2 exceptions included a patient with evidence of an apoplectic event on autopsy and another patient with leptomeningeal pituitary spread but an unclear history of apoplexy. Elevated tumor markers were not linked to poor outcomes. CONCLUSION: Distant spread of pituitary adenoma may occur after surgery, irradiation, or apoplexy. It is not necessarily associated with a malignant clinical course.

Establishment of patient-derived organoid models of lower-grade glioma.

BACKGROUND: Historically, creating patient-derived models of lower-grade glioma (LGG) has been challenging, contributing to few experimental platforms that support laboratory-based investigations of this disease. Although organoid modeling approaches have recently been employed to create in vitro models of high-grade glioma (HGG), it is unknown whether this approach can be successfully applied to LGG. METHODS: In this study, we developed an optimized protocol for the establishment of organoids from LGG primary tissue samples by utilizing physiologic (5%) oxygenation conditions and employed it to produce the first known suite of these models. To assess their fidelity, we surveyed key biological features of patient-derived organoids using metabolic, genomic, histologic, and lineage marker gene expression assays. RESULTS: Organoid models were created with a success rate of 91% (n = 20/22) from primary tumor samples across glioma histological subtypes and tumor grades (WHO Grades 1-4), and a success rate of 87% (13/15) for WHO Grade 1-3 tumors. Patient-derived organoids recapitulated stemness, proliferative, and tumor-stromal composition profiles of their respective parental tumor specimens. Cytoarchitectural, mutational, and metabolic traits of parental tumors were also conserved. Importantly, LGG organoids were maintained in vitro for weeks to months and reanimated after biobanking without loss of integrity. CONCLUSIONS: We report an efficient method for producing faithful in vitro models of LGG. New experimental platforms generated through this approach are well positioned to support preclinical studies of this disease, particularly those related to tumor immunology, tumor-stroma interactions, identification of novel drug targets, and personalized assessments of treatment response profiles.

The efficacy of immunohistochemistry in the diagnosis of molecular genetic alterations in central nervous system gliomas: Next-generation sequencing of 212 mutations in 112 patients.

Identification of molecular genetic alterations has become an important part of diagnosis and care of patients with brain tumors. Comparisons of immunohistochemistry (IHC) with DNA sequencing techniques have suggested that IHC is useful for identifying surrogates of mutations in gliomas; however, studies of the efficacy are relatively few. Our aim was to compare IHC in our neuropathology laboratory with a commercially available next-generation sequencing (NGS) platform, Tempus xT. We studied 212 immunohistochemically stained sections of gliomas to identify mutations of isocitrate dehydrogenase (IDH), p53, BRAF, the α-thalassemia/mental retardation syndrome X-linked protein (ATRX), and histone H3. Tempus xT NGS confirmed the IHC diagnosis of IDH1/R132H in 102 of 102 patients (100%), BRAF/V600E in 14 of 14 (100%) patients and H3/K27M in 10 of 10 (100%) patients. For p53, NGS confirmed the IHC diagnosis of mutation in 47 of 53 (87%) patients. For 6 patients, IHC was interpreted as wild-type while NGS indicated a mutation. NGS confirmed the IHC diagnosis of ATRX mutation in 29 of 31 (94%) patients. In 1 patient, IHC predicted a mutation that was not confirmed by NGS, and in another, IHC predicted wild-type, but NGS showed mutant. In 2 other patients, IHC diagnosis of ATRX mutation was equivocal; 1 was mutant and 1 was wild-type by NGS. Our single-center study suggests that IHC for IDH1/R132H, BRAF/V600E, and H3/K27M is highly reliable and may be used confidently in clinical practice. IHC for p53 and ATRX mutations is often reliable but possibly problematic, and genetic studies may be necessary to determine astrocytic or oligodendroglial differentiation.