Central neurocytoma exhibits radial glial cell signatures with FGFR3 hypomethylation and overexpression.

We explored the genomic events underlying central neurocytoma (CN), a rare neoplasm of the central nervous system, via multiomics approaches, including whole-exome sequencing, bulk and single-nuclei RNA sequencing, and methylation sequencing. We identified FGFR3 hypomethylation leading to FGFR3 overexpression as a major event in the ontogeny of CN that affects crucial downstream events, such as aberrant PI3K-AKT activity and neuronal development pathways. Furthermore, we found similarities between CN and radial glial cells based on analyses of gene markers and CN tumor cells and postulate that CN tumorigenesis is due to dysregulation of radial glial cell differentiation into neurons. Our data demonstrate the potential role of FGFR3 as one of the leading drivers of tumorigenesis in CN.

ELAVL2 loss promotes aggressive mesenchymal transition in glioblastoma.

Glioblastoma (GBM), the most lethal primary brain cancer, exhibits intratumoral heterogeneity and molecular plasticity, posing challenges for effective treatment. Despite this, the regulatory mechanisms underlying such plasticity, particularly mesenchymal (MES) transition, remain poorly understood. In this study, we elucidate the role of the RNA-binding protein ELAVL2 in regulating aggressive MES transformation in GBM. We found that ELAVL2 is most frequently deleted in GBM compared to other cancers and associated with distinct clinical and molecular features. Transcriptomic analysis revealed that ELAVL2-mediated alterations correspond to specific GBM subtype signatures. Notably, ELAVL2 expression negatively correlated with epithelial-to-mesenchymal transition (EMT)-related genes, and its loss promoted MES process and chemo-resistance in GBM cells, whereas ELAVL2 overexpression exerted the opposite effect. Further investigation via tissue microarray analysis demonstrated that high ELAVL2 protein expression confers a favorable survival outcome in GBM patients. Mechanistically, ELAVL2 was shown to directly bind to the transcripts of EMT-inhibitory molecules, SH3GL3 and DNM3, modulating their mRNA stability, potentially through an m6A-dependent mechanism. In summary, our findings identify ELAVL2 as a critical tumor suppressor and mRNA stabilizer that regulates MES transition in GBM, underscoring its role in transcriptomic plasticity and glioma progression.

An Autopsy-proven Case-based Review of Autoimmune Encephalitis.

Autoimmune encephalitis (AIE) is a type of immunoreactive encephalitic disorder and is recognized as the most prevalent noninfectious encephalitis. Nevertheless, the rarity of definitive AIE diagnosis through biopsy or autopsy represents a significant hurdle to understanding and managing the disease. In this article, we present the pathological findings of AIE and review the literature based on a distinct case of AIE presenting as CD8+ T-lymphocyte predominant encephalitis. We describe the clinical progression, diagnostic imaging, laboratory data, and autopsy findings of an 80-year-old deceased male patient. The patient was diagnosed with pulmonary tuberculosis 6 months before death and received appropriate medications. A week before admission to the hospital, the patient manifested symptoms such as a tendency to sleep, decreased appetite, and confusion. Although the patient temporally improved with medication including correction of hyponatremia, the patient progressed rapidly and died in 6 weeks. The brain tissue revealed lymphocytic infiltration in the gray and white matter, leptomeninges, and perivascular infiltration with a predominance of CD8+ T lymphocytes, suggesting a case of AIE. There was no detectable evidence of viral infection or underlying neoplasm. The autopsy revealed that this patient also had Alzheimer's disease, atherosclerosis, arteriolosclerosis, and aging-related tau astrogliopathy. This report emphasizes the pivotal role of pathological examination in the diagnosis of AIE, especially when serological autoantibody testing is not available or when a patient is suspected of having multiple diseases.

PANCDR: precise medicine prediction using an adversarial network for cancer drug response.

Pharmacogenomics aims to provide personalized therapy to patients based on their genetic variability. However, accurate prediction of cancer drug response (CDR) is challenging due to genetic heterogeneity. Since clinical data are limited, most studies predicting drug response use preclinical data to train models. However, such models might not be generalizable to external clinical data due to differences between the preclinical and clinical datasets. In this study, a Precision Medicine Prediction using an Adversarial Network for Cancer Drug Response (PANCDR) model is proposed. PANCDR consists of two sub-models, an adversarial model and a CDR prediction model. The adversarial model reduces the gap between the preclinical and clinical datasets, while the CDR prediction model extracts features and predicts responses. PANCDR was trained using both preclinical data and unlabeled clinical data. Subsequently, it was tested on external clinical data, including The Cancer Genome Atlas and brain tumor patients. PANCDR outperformed other machine learning models in predicting external test data. Our results demonstrate the robustness of PANCDR and its potential in precision medicine by recommending patient-specific drug candidates. The PANCDR codes and data are available at https://github.com/DMCB-GIST/PANCDR.

Fetal Lung Interstitial Tumor: A Comprehensive Case Study with an Emphasis on Next-Generation Sequencing.

Fetal lung interstitial tumor (FLIT), which is characterized by immature interstitial cells resembling the fetal lung parenchyma of 20 to 24 weeks of gestation, is a rare respiratory neoplasm. This study presents the first reported FLIT in Korea. It also aims to refine the diagnostic method of FLIT and increase the accuracy of prognostic assessment by using next-generation sequencing to check for anaplastic lymphoma receptor tyrosine kinase (anaplastic lymphoma kinase) gene rearrangement. Although the initial prognosis for FLIT has been promising since its first report in 2010, certain pathological features are associated with poorer outcomes. Therefore, achieving an accurate diagnosis of FLIT is crucial for avoiding unnecessary treatments beyond surgical resection.

Intramedullary spinal capillary hemangioma with secondary neurulation defect in children.

Intramedullary spinal capillary hemangioma is a rare occurrence in pediatric patients, and only limited cases have been reported. This study presents the first two cases of spinal capillary hemangioma co-present with retained medullary cord and one case of spinal capillary hemangioma with lumbosacral lipomatous malformation. Previous literature on ten patients with this pathology was reviewed. We speculated pathogenesis, imaging features, and histopathologic findings of the disease.

Added value of dynamic contrast-enhanced MR imaging in deep learning-based prediction of local recurrence in grade 4 adult-type diffuse gliomas patients.

Local recurrences in patients with grade 4 adult-type diffuse gliomas mostly occur within residual non-enhancing T2 hyperintensity areas after surgical resection. Unfortunately, it is challenging to distinguish non-enhancing tumors from edema in the non-enhancing T2 hyperintensity areas using conventional MRI alone. Quantitative DCE MRI parameters such as Ktrans and Ve convey permeability information of glioblastomas that cannot be provided by conventional MRI. We used the publicly available nnU-Net to train a deep learning model that incorporated both conventional and DCE MRI to detect the subtle difference in vessel leakiness due to neoangiogenesis between the non-recurrence area and the local recurrence area, which contains a higher proportion of high-grade glioma cells. We found that the addition of Ve doubled the sensitivity while nonsignificantly decreasing the specificity for prediction of local recurrence in glioblastomas, which implies that the combined model may result in fewer missed cases of local recurrence. The deep learning model predictive of local recurrence may enable risk-adapted radiotherapy planning in patients with grade 4 adult-type diffuse gliomas.

Integrated drug response prediction models pinpoint repurposed drugs with effectiveness against rhabdomyosarcoma.

Targeted therapies for inhibiting the growth of cancer cells or inducing apoptosis are urgently needed for effective rhabdomyosarcoma (RMS) treatment. However, identifying cancer-targeting compounds with few side effects, among the many potential compounds, is expensive and time-consuming. A computational approach to reduce the number of potential candidate drugs can facilitate the discovery of attractive lead compounds. To address this and obtain reliable predictions of novel cell-line-specific drugs, we apply prediction models that have the potential to improve drug discovery approaches for RMS treatment. The results of two prediction models were ensemble and validated via in vitro experiments. The computational models were trained using data extracted from the Genomics of Drug Sensitivity in Cancer database and tested on two RMS cell lines to select potential RMS drug candidates. Among 235 candidate drugs, 22 were selected following the result of the computational approach, and three candidate drugs were identified (NSC207895, vorinostat, and belinostat) that showed selective effectiveness in RMS cell lines in vitro via the induction of apoptosis. Our in vitro experiments have demonstrated that our proposed methods can effectively identify and repurpose drugs for treating RMS.

Added prognostic value of 3D deep learning-derived features from preoperative MRI for adult-type diffuse gliomas.

BACKGROUND: To investigate the prognostic value of spatial features from whole-brain MRI using a three-dimensional (3D) convolutional neural network for adult-type diffuse gliomas. METHODS: In a retrospective, multicenter study, 1925 diffuse glioma patients were enrolled from 5 datasets: SNUH (n = 708), UPenn (n = 425), UCSF (n = 500), TCGA (n = 160), and Severance (n = 132). The SNUH and Severance datasets served as external test sets. Precontrast and postcontrast 3D T1-weighted, T2-weighted, and T2-FLAIR images were processed as multichannel 3D images. A 3D-adapted SE-ResNeXt model was trained to predict overall survival. The prognostic value of the deep learning-based prognostic index (DPI), a spatial feature-derived quantitative score, and established prognostic markers were evaluated using Cox regression. Model evaluation was performed using the concordance index (C-index) and Brier score. RESULTS: The MRI-only median DPI survival prediction model achieved C-indices of 0.709 and 0.677 (BS = 0.142 and 0.215) and survival differences (P < 0.001 and P = 0.002; log-rank test) for the SNUH and Severance datasets, respectively. Multivariate Cox analysis revealed DPI as a significant prognostic factor, independent of clinical and molecular genetic variables: hazard ratio = 0.032 and 0.036 (P < 0.001 and P = 0.004) for the SNUH and Severance datasets, respectively. Multimodal prediction models achieved higher C-indices than models using only clinical and molecular genetic variables: 0.783 vs. 0.774, P = 0.001, SNUH; 0.766 vs. 0.748, P = 0.023, Severance. CONCLUSIONS: The global morphologic feature derived from 3D CNN models using whole-brain MRI has independent prognostic value for diffuse gliomas. Combining clinical, molecular genetic, and imaging data yields the best performance.

Fibrous hamartoma of infancy of the spinal cord resembling conus and filum, with a coexisting sacral dimple.

Fibrous hamartoma of infancy (FHI) is a rare benign soft tissue lesion of infants and young children. It usually occurs within the first 2 years of life at the superficial layer of the axilla, trunk, upper arm, and external genitalia. FHI in the central nervous system (CNS) is extremely rare. So far, only two spinal cord FHI cases have been reported. We present a case of a 1-month-old girl who presented with a skin dimple in the coccygeal area. Her MRI showed a substantial intramedullary mass in the thoracolumbar area with a sacral soft tissue mass and a track between the skin lesion to the coccygeal tip. Her normal neurological status halted immediate surgical resection. A skin lesion biopsy was first performed, revealing limited information with no malignant cells. A short-term follow-up was performed until the intramedullary mass had enlarged on the 5-month follow-up MRI. Based on the frozen biopsy result of benign to low-grade spindle cell mesenchymal tumor, subtotal resection of the mass was done, minimizing damage to the functioning neural tissue. Both the skin lesion and the intramedullary mass were diagnosed as FHI. Postoperative 5.5-year follow-up MRI revealed minimal size change of the residual mass. Despite being diagnosed with a neurogenic bladder, the patient maintained her ability to void spontaneously, managed infrequent UTIs, and continued toilet training, all while demonstrating good mobility and no motor weakness. This case is unique because the lesion resembled the secondary neurulation structures, such as the conus and the filum, along with a related congenital anomaly of the dimple.

The Impact of 131I-Metaiodobenzylguanidine as a Conditioning Regimen of Tandem High-Dose Chemotherapy and Autologous Stem Cell Transplantation for High-Risk Neuroblastoma.

BACKGROUND: The optimal conditioning regimen of tandem high-dose chemotherapy (HDC) and autologous stem cell transplantation (ASCT) for high-risk neuroblastoma (HR-NBL) has not been established. The efficacy of 131I-MIBG therapy is under exploration in newly diagnosed HR-NBL patients. Here, we compared the outcomes of tandem HDC/ASCT between the 131I-MIBG combination and non-MIBG groups. METHODS: We retrospectively analyzed the clinical data of 33 HR-NBL patients who underwent tandem HDC/ASCT between 2007 and 2021 at the Seoul National University Children's Hospital. RESULTS: The median age at diagnosis was 3.6 years. 131I-MIBG was administered to 13 (39.4%) of the patients. Thirty patients (90.9%) received maintenance therapy after tandem HDC/ASCT, twenty-two were treated with isotretinoin ± interleukin-2, and eight received salvage chemotherapy. The five-year overall survival (OS) and event-free survival (EFS) rates of all patients were 80.4% and 69.4%, respectively. Comparing the 131I-MIBG combined group and other groups, the five-year OS rates were 82.1% and 79.7% (p = 0.655), and the five-year EFS rates were 69.2% and 69.6% (p = 0.922), respectively. Among the adverse effects of grade 3 or 4, the incidence of liver enzyme elevation was significantly higher in the non-131I-MIBG group. CONCLUSIONS: Although tandem HDC/ASCT showed promising outcomes, the 131I-MIBG combination did not improve survival rates.

Survival and Malignant Transformation of Pineal Parenchymal Tumors: A 30-Year Retrospective Analysis in a Single-Institution.

BACKGROUND: This study aims to elucidate clinical features, therapeutic strategies, and prognosis of pineal parenchymal tumors (PPT) by analyzing a 30-year dataset of a single institution. METHODS: We reviewed data from 43 patients diagnosed with PPT at Seoul National University Hospital between 1990 and 2020. We performed survival analyses and assessed prognostic factors. RESULTS: The cohort included 10 patients with pineocytoma (PC), 13 with pineal parenchymal tumor of intermediate differentiation (PPTID), and 20 with pineoblastoma (PB). Most patients presented with hydrocephalus at diagnosis. Most patients underwent an endoscopic third ventriculostomy and biopsy, with some undergoing additional resection after diagnosis confirmation. Radiotherapy was administered with a high prevalence of gamma knife radiosurgery for PC and PPTID, and craniospinal irradiation for PB. Chemotherapy was essential in the treatment of grade 3 PPTID and PB. The 5-year progression-free survival rates for PC, grade 2 PPTID, grade 3 PPTID, and PB were 100%, 83.3%, 0%, and 40%, respectively, and the 5-year overall survival rates were 100%, 100%, 40%, and 55%, respectively. High-grade tumor histology was associated with lower survival rates. Significant prognostic factors varied among tumor types, with World Health Organization (WHO) grade and leptomeningeal seeding (LMS) for PPTID, and the extent of resection and LMS for PB. Three patients experienced malignant transformations. CONCLUSION: This study underscores the prognostic significance of WHO grades in PPT. It is necessary to provide specific treatment according to tumor grade. Grade 3 PPTID showed a poor prognosis. Potential LMS and malignant transformations necessitate aggressive multimodal treatment and close-interval screening.

Enrichment of Deleterious Mutated Genes Involved in Ciliary Function and Histone Modification in Brain Cancer Patient-Derived Xenograft Models.

Patient-derived xenograft (PDX) models, which can retain the characteristics of original tumors in an in vivo-mimicking environment, have been developed to identify better treatment options. However, although original tumors and xenograft tissues mostly share oncogenic mutations and global gene expression patterns, their detailed mutation profiles occasionally do not overlap, indicating that selection occurs in the xenograft environment. To understand this mutational alteration in xenografts, we established 13 PDX models derived from 11 brain tumor patients and confirmed their histopathological similarity. Surprisingly, only a limited number of somatic mutations were shared between the original tumor and xenograft tissue. By analyzing deleteriously mutated genes in tumors and xenografts, we found that previously reported brain tumor-related genes were enriched in PDX samples, demonstrating that xenografts are a valuable platform for studying brain tumors. Furthermore, mutated genes involved in cilium movement, microtubule depolymerization, and histone methylation were enriched in PDX samples compared with the original tumors. Even with the limitations of the heterogeneity of clinical lesions with a heterotropic model, our study demonstrates that PDX models can provide more information in genetic analysis using samples with high heterogeneity, such as brain tumors.

Brain Tumor Classification by Methylation Profile.

The goal of the methylation classifier in brain tumor classification is to accurately classify tumors based on their methylation profiles. Accurate brain tumor diagnosis is the first step for healthcare professionals to predict tumor prognosis and establish personalized treatment plans for patients. The methylation classifier can be used to perform classification on tumor samples with diagnostic difficulties due to ambiguous histology or mismatch between histopathology and molecular signatures, i.e., not otherwise specified (NOS) cases or not elsewhere classified (NEC) cases, aiding in pathological decision-making. Here, the authors elucidate upon the application of a methylation classifier as a tool to mitigate the inherent complexities associated with the pathological evaluation of brain tumors, even when pathologists are experts in histopathological diagnosis and have access to enough molecular genetic information. Also, it should be emphasized that methylome cannot classify all types of brain tumors, and it often produces erroneous matches even with high matching scores, so, excessive trust is prohibited. The primary issue is the considerable difficulty in obtaining reference data regarding the methylation profile of each type of brain tumor. This challenge is further amplified when dealing with recently identified novel types or subtypes of brain tumors, as such data are not readily accessible through open databases or authors of publications. An additional obstacle arises from the fact that methylation classifiers are primarily research-based, leading to the unavailability of charging patients. It is important to note that the application of methylation classifiers may require specialized laboratory techniques and expertise in DNA methylation analysis.

Methylation-based Subclassifications of Embryonal Tumor with Multilayered Rosettes in Not Just Pediatric Brains.

The aim of this study is to investigate the genetic profiles and methylation-based classifications of Embryonal tumor with multilayered rosettes (ETMR), with a specific focus on differentiating between C19MC amplified and C19MC-not amplified groups, including cases with DICER1 mutations. To achieve this, next-generation sequencing using a targeted gene panel for brain tumors and methylation class studies using the Epic850K microarray were performed to identify tumor subclasses and their clinicopathological characteristics. The study cohort consisted of four patients, including 3 children (a 4-months/F, a 9-months/M, and a 2 y/F), and one adult (a 30 y/Male). All three tumors in the pediatric patients originated in the posterior fossa and exhibited TTYH1:C19MC fusion and C19MC amplification. The fourth case in the adult patient involved the cerebellopontine angle with biallelic DICER1 mutation. Histopathological examination revealed typical embryonal features characterized by multilayered rosettes and abundant neuropils in all cases, while the DICER1-mutant ETMR also displayed cartilage islands in addition to the classic ETMR pathology. All four tumors showed positive staining for LIN28A. The t-SNE clustering analysis demonstrated that the first three cases clustered with known subtypes of ETMR, specifically C19MC amplified, while the fourth case clustered separately to non-C19MC amplified subclass. During the follow-up period of 6~12 months, leptomeningeal dissemination of the tumor occurred in all patients. Considering the older age of onset in DICER1-mutant ETMR, genetic counseling should be recommended due to the association of DICER1 mutations with germline and second-hit somatic mutations in cancer.

Neuroepithelial tumor with EWSR1::PATZ1 fusion: A literature review.

We present the clinicopathological and molecular genetic characteristics of a neuroepithelial tumor (NET), EWSR1::PATZ1 fusion-positive with a literature review. This fusion has recently been discovered in rare central nervous system tumors and soft tissue sarcomas and was not included in the fifth edition of the WHO classifications. We identified this fusion in 2 NETs. The first case involved a 7-year-old girl and the second case occurred in a 53-year-old man; both presented with headaches and vomiting. The pediatric case initially showed an intermediate grade of the tumor, but upon recurrences, it transformed into a high-grade tumor with 2 relapses in 8.3 years. This case exhibited high mitotic activity (20/10 high-power fields), and a high Ki-67 index (21%). The TERT promoter (TERTp) mutation was present in both initial and recurrent tumors. In contrast, the adult case was a low-grade tumor with no mitotic activity or recurrence over 13.5 months after subtotal resection and gamma knife surgery. Interestingly, the pediatric case demonstrated a longer survival time compared to conventional glioblastoma. The TERTp mutation, similar to being a molecular signature in adult-type glioblastoma, could also be an indicator of high-grade behavior in PATZ1 fusion NET.

Surgical indication of pediatric Rathke's cleft cyst based on a 20-year retrospective cohort.

OBJECTIVE: Rathke's cleft cyst (RCC) is the most commonly encountered pituitary incidentaloma in children. Because RCC is not frequently diagnosed in children, there are few reports on pediatric RCCs. The natural course of the disease and appropriate treatments are still obscure. The present study aimed to elucidate the natural history and surgical indications of RCCs in children. METHODS: The authors retrospectively reviewed the clinical presentations, imaging features, ophthalmological evaluations, endocrine evaluations, and surgical outcomes of pediatric RCCs at a single institution from January 2000 to October 2022. Clinical outcomes between the surgery and observation groups were compared. RESULTS: Among 93 patients, there were 41 patients in the surgery group and 52 patients in the observation group. The mean age at diagnosis was 10.9 years, and the mean follow-up period was 5.6 years. Headache fully or partially improved after surgery (86.2%), but the rate of improvement was not different from that of the observation group (70.0%). Ophthalmological abnormalities were effectively improved by surgical treatment (93.3%). Both the improvement and deterioration rates of endocrine abnormalities were significantly higher in the surgery group (p = 0.026 and p < 0.001, respectively), but the deterioration rate (43.9%) was higher than the improvement rate (14.6%). In the surgery group, the recurrence rate was 17.1% and the reoperation rate was 4.9%. Compared with total cyst wall resection, cyst fenestration with partial wall resection was associated with a higher recurrence rate (26.9%, p = 0.035) but a lower rate of endocrine abnormalities (30.8%, p = 0.049). CONCLUSIONS: Pediatric RCCs of ≥ 10 mm in size were analyzed. Ophthalmological abnormalities are the major surgical indications for pediatric RCCs. Headache and partial endocrine abnormalities may be improved with surgery, but they are not absolute indications for surgery. Cyst fenestration with partial wall resection via an endoscopic endonasal approach is the most recommended surgical method. Follow-up is essential to monitor for the occurrence of visual field defects and the recurrence of cysts.

Deep learning based on dynamic susceptibility contrast MR imaging for prediction of local progression in adult-type diffuse glioma (grade 4).

Adult-type diffuse glioma (grade 4) has infiltrating nature, and therefore local progression is likely to occur within surrounding non-enhancing T2 hyperintense areas even after gross total resection of contrast-enhancing lesions. Cerebral blood volume (CBV) obtained from dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) is a parameter that is well-known to be a surrogate marker of both histologic and angiographic vascularity in tumors. We built two nnU-Net deep learning models for prediction of early local progression in adult-type diffuse glioma (grade 4), one using conventional MRI alone and one using multiparametric MRI, including conventional MRI and DSC-PWI. Local progression areas were annotated in a non-enhancing T2 hyperintense lesion on preoperative T2 FLAIR images, using the follow-up contrast-enhanced (CE) T1-weighted (T1W) images as the reference standard. The sensitivity was doubled with the addition of nCBV (80% vs. 40%, P = 0.02) while the specificity was decreased nonsignificantly (29% vs. 48%, P = 0.39), suggesting that fewer cases of early local progression would be missed with the addition of nCBV. While the diagnostic performance of CBV model is still poor and needs improving, the multiparametric deep learning model, which presumably learned from the subtle difference in vascularity between early local progression and non-progression voxels within perilesional T2 hyperintensity, may facilitate risk-adapted radiotherapy planning in adult-type diffuse glioma (grade 4) patients.