Prognostic Impact of TERT Promoter Mutations in Adult-Type Diffuse Gliomas Based on WHO2021 Criteria.

Mutation in the telomerase reverse transcriptase promoter (TERTp )is commonly observed in various malignancies, such as central nervous system (CNS) tumors, malignant melanoma, bladder cancer, and thyroid carcinoma. These mutations are recognized as significant poor prognostic factors for these tumors. In this investigation, a total of 528 cases of adult-type diffuse gliomas diagnosed at a single institution were reclassified according to the 2021 WHO classifications of CNS tumors, 5th edition (WHO2021). The study analyzed clinicopathological and genetic features, including TERTp mutations in each tumor. The impact of known prognostic factors on patient outcomes was analyzed through Kaplan-Meier survival and Cox regression analysis. TERTp mutations were predominantly identified in 94.1% of oligodendrogliomas (ODG), followed by 66.3% in glioblastoma, IDH-wildtype (GBM-IDHwt), and 9.2% of astrocytomas, IDH-mutant (A-IDHm). When considering A-IDHm and GBM as astrocytic tumors (Group 1) and ODGs (Group 2), TERTp mutations emerged as a significant adverse prognostic factor (p = 0.013) in Group 1. However, within each GBM-IDHwt and A-IDHm, the presence of TERTp mutations did not significantly impact patient prognosis (p = 0.215 and 0.268, respectively). Due to the high frequency of TERTp mutations in Group 2 (ODG) and their consistent prolonged survival, a statistical analysis to evaluate their impact on overall survival was deemed impractical. When considering MGMTp status, the combined TERTp-mutated and MGMTp-unmethylated group exhibited the worst prognosis in OS (p = 0.018) and PFS (p = 0.034) of GBM. This study confirmed that the classification of tumors according to the WHO2021 criteria effectively reflected prognosis. Both uni- and multivariate analyses in GBM, age, MGMTp methylation, and CDKN2A/B homozygous deletion were statistically significant prognostic factors while in univariate analysis in A-IDHm, grade 4, the Ki-67 index and MYCN amplifications were statistically significant prognostic factors. This study suggests that it is important to classify and manage tumors based on their genetic characteristics in adult-type diffuse gliomas.

Comprehensive multiomics analysis reveals distinct differences between pediatric choroid plexus papilloma and carcinoma.

Choroid plexus tumors (CPTs) are intraventricular tumors derived from the choroid plexus epithelium and occur frequently in children. The aim of this study was to investigate the genomic and epigenomic characteristics of CPT and identify the differences between choroid plexus papilloma (CPP) and choroid plexus carcinoma (CPC). We conducted multiomics analyses of 20 CPT patients including CPP and CPC. Multiomics analysis included whole-genome sequencing, whole-transcriptome sequencing, and methylation sequencing. Mutually exclusive TP53 and EPHA7 point mutations, coupled with the amplification of chromosome 1, were exclusively identified in CPC. In contrast, amplification of chromosome 9 was specific to CPP. Differential gene expression analysis uncovered a significant overexpression of genes related to cell cycle regulation and epithelial-mesenchymal transition pathways in CPC compared to CPP. Overexpression of genes associated with tumor metastasis and progression was observed in the CPC subgroup with leptomeningeal dissemination. Furthermore, methylation profiling unveiled hypomethylation in major repeat regions, including long interspersed nuclear elements, short interspersed nuclear elements, long terminal repeats, and retrotransposons in CPC compared to CPP, implying that the loss of epigenetic silencing of transposable elements may play a role in tumorigenesis of CPC. Finally, the differential expression of AK1, regulated by both genomic and epigenomic factors, emerged as a potential contributing factor to the histological difference of CPP against CPC. Our results suggest pronounced genomic and epigenomic disparities between CPP and CPC, providing insights into the pathogenesis of CPT at the molecular level.

Comparison of the transcranial approach and transsphenoidal approach based on the anatomical location of origin in pediatric craniopharyngiomas.

BACKGROUND: Various clinical classifications of craniopharyngiomas (CRPs) have been proposed to suggest optimal surgical planning. We aimed to evaluate the clinical outcomes of pediatric CRPs and the clinical significance of anatomical classification in relation to the diaphragm sellae. METHODS: A retrospective review was conducted on patients under 18 years of age who underwent surgery for CRPs from July 1998 to August 2022. The patients were divided into transcranial approach (TCA), and transsphenoidal approach (TSA) groups, which included microscopic TSA and endoscopic endonasal approach (EEA) groups. EEA has been adopted at our institute since 2011. CRPs were classified by their origin and relationship with the diaphragm sellae. RESULTS: A total of 132 pediatric CRP patients were included in this study, 117 of whom underwent surgery for primary CRP and 15 for recurrent CRP. Among them, 89 (67.4%) underwent TCA, 9 (6.8%) had microscopic TSA, and 34 (25.8%) had EEA. In subdiaphragmatic CRPs with competent diaphragm sellae, TSA tended to yield better outcomes than did TCA in terms of stalk preservation and ophthalmological outcomes. After the introduction of EEA, the proportion of supradiaphragmatic CRPs treated via the TSA increased from 0% to 50% (p < 0.001). Gross total resection (HR=0.194; 95% CI=0.102-0.367, p < 0.001) and adjuvant therapy (HR=0.208; 95% CI=0.048-0.897, p = 0.035) were found to be positive prognostic factors for long-term tumor control. CONCLUSIONS: Over time, with the adoption of EEA at our institute, the impact of anatomical classification on the surgical apprpoach has decreased. Nevertheless, an individualized surgical approach should be employed to improve long-term outcomes and minimize complications for pediatric CRPs.

MRI Scoring Systems for Predicting Isocitrate Dehydrogenase Mutation and Chromosome 1p/19q Codeletion in Adult-type Diffuse Glioma Lacking Contrast Enhancement.

Background According to 2021 World Health Organization criteria, adult-type diffuse gliomas include glioblastoma, isocitrate dehydrogenase (IDH)-wildtype; oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and astrocytoma, IDH-mutant, even when contrast enhancement is lacking. Purpose To develop and validate simple scoring systems for predicting IDH and subsequent 1p/19q codeletion status in gliomas without contrast enhancement using standard clinical MRI sequences. Materials and Methods This retrospective study included adult-type diffuse gliomas lacking contrast at contrast-enhanced MRI from two tertiary referral hospitals between January 2012 and April 2022 with diagnoses confirmed at pathology. IDH status was predicted primarily by using T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign, followed by 1p/19q codeletion prediction. A visual rating of MRI features, apparent diffusion coefficient (ADC) ratio, and relative cerebral blood volume was measured. Scoring systems were developed through univariable and multivariable logistic regressions and underwent calibration and discrimination, including internal and external validation. Results For the internal validation cohort, 237 patients were included (mean age, 44.4 years ± 14.4 [SD]; 136 male patients; 193 patients in IDH prediction and 163 patients in 1p/19q prediction). For the external validation cohort, 35 patients were included (46.1 years ± 15.3; 20 male patients; 28 patients in IDH prediction and 24 patients in 1p/19q prediction). The T2-FLAIR mismatch sign demonstrated 100% specificity and 100% positive predictive value for IDH mutation. IDH status prediction scoring system for tumors without mismatch sign included age, ADC ratio, and morphologic characteristics, whereas 1p/19q codeletion prediction for IDH-mutant gliomas included ADC ratio, cortical involvement, and mismatch sign. For IDH status and 1p/19q codeletion prediction, bootstrap-corrected areas under the receiver operating characteristic curve were 0.86 (95% CI: 0.81, 0.90) and 0.73 (95% CI: 0.65, 0.81), respectively, whereas at external validation they were 0.99 (95% CI: 0.98, 1.0) and 0.88 (95% CI: 0.63, 1.0). Conclusion The T2-FLAIR mismatch sign and scoring systems using standard clinical MRI predicted IDH and 1p/19q codeletion status in gliomas lacking contrast enhancement. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Badve and Hodges in this issue.

Primary epithelioid inflammatory myofibroblastic sarcoma of the brain with EML4::ALK fusion mimicking intra-axial glioma: a case report and brief literature review.

An aggressive subtype of inflammatory myofibroblastic tumor, epithelioid inflammatory myofibroblastic sarcoma occurs primarily inside the abdominal cavity, followed by a pulmonary localization. Most harbor anaplastic lymphoma kinase (ALK) gene rearrangements, with RANBP2 and RRBP1 among the well-documented fusion partners. We report the second case of primary epithelioid inflammatory myofibroblastic sarcoma of the brain, with a well-known EML4::ALK fusion. The case is notable for its intra-axial presentation that clinico-radiologically mimicked glioma.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.