Comprehensive profiling of myxopapillary ependymomas identifies a distinct molecular subtype with relapsing disease

Strong nuclear expression of HOXB13 is a reliable surrogate marker for DNA methylome profiling to distinguish myxopapillary ependymoma from spinal ependymoma

Spinal ependymoma and myxopapillary ependymoma are the two most common spinal ependymal tumor types that feature distinct histological characteristics, genetic alterations and DNA methylation profiles. Their histological distinction may be difficult in individual cases and molecular diagnostic assessment, in particular DNA methylome profiling, may then be required to assign the correct diagnosis. Expression of the homeobox gene HOXB13 at the mRNA and protein levels has been reported as a frequent finding in myxopapillary ependymoma that may serve as a diagnostic marker for these tumors. Here, we evaluated the diagnostic role of HOXB13 immunostaining in 143 spinal neoplasms, comprising 54 histologically classified myxopapillary ependymomas, 46 histologically classified spinal ependymomas, and various other tumor types. Immunohistochemical results for HOXB13 protein were compared to molecular findings obtained by bead array-based DNA methylation and DNA copy number profiling, as well as next generation gene panel sequencing-based mutational analysis. Our findings indicate strong nuclear HOXB13 expression as a reliable diagnostic marker for molecularly confirmed myxopapillary ependymoma. Moreover, we provide evidence that differential HOXB13 protein expression is related to differential HOXB13-associated CpG site methylation in myxopapillary vs. spinal ependymomas, which can be assessed by targeted DNA methylation analysis. Taken together, immunohistochemistry for HOXB13 protein expression and targeted DNA methylation analysis of HOXB13 represent useful surrogate approaches that may substitute for DNA methylome profiling in routine diagnostics and facilitate precise classification of spinal ependymal tumors. In particular, strong nuclear HOXB13 immunoreactivity may serve as a novel diagnostic criterion for the classification of myxopapillary ependymoma.

Central nervous system tumors in adolescents and young adults: A Society for Neuro-Oncology Consensus Review on diagnosis, management, and future directions

Adolescents and young adults (AYAs; ages 15-39 years) are a vulnerable population facing challenges in oncological care, including access to specialized care, transition of care, unique tumor biology, and poor representation in clinical trials. Brain tumors are the second most common tumor type in AYA, with malignant brain tumors being the most common cause of cancer-related death. The 2021 WHO Classification for central nervous system (CNS) Tumors highlights the importance of integrated molecular characterization with histologic diagnosis in several tumors relevant to the AYA population. In this position paper from the Society for Neuro-Oncology (SNO), the diagnosis and management of CNS tumors in AYA is reviewed, focusing on the most common tumor types in this population, namely glioma, medulloblastoma, ependymoma, and CNS germ cell tumor. Current challenges and future directions specific to AYA are also highlighted. Finally, possible solutions to address barriers in the care of AYA patients are discussed, emphasizing the need for multidisciplinary and collaborative approaches that span the pediatric and adult paradigms of care, and incorporating advanced molecular testing, targeted therapy, and AYA-centered care.

Spinal ependymal tumors

Spinal ependymomas are strictly to be subdivided into intramedullary lesions and extramedullary lesions as they are histologically and genetically distinct. Whereas the intramedullary lesions (SPE) are assigned to the WHO grade 2 and very rarely grade 3, the extramedullary lesions or myxopapilary tumors (MPE) are only as recently also assigned to WHO grade 2. The major difference is that in general, an intramedullary lesion of grade 2 remains confined to the local site of origin, even when rarely recurring after complete resection. In contrast, the MPEs have the capacity to spread throughout the cerebrospinal fluid compartment but can also be controlled by cautious complete resection. We here review the clinical features of spinal ependymomas, contrasting the entities, and describe the treatment found best from the literature to manage these lesions including interdisciplinary approaches.

Specifics of spinal neuropathology in the molecular age

Tumors located in the spinal cord and its coverings can be diagnostically challenging and require special consideration regarding treatment options. During the last decade, important advances regarding the molecular characterization of central and peripheral nervous system tumors were achieved, resulting in improved diagnostic precision, and understanding of the tumor spectrum of this compartment. In particular, array-based global DNA methylation profiling has emerged as a valuable tool to delineate biologically and clinically relevant tumor subgroups and has been incorporated in the current WHO classification for central nervous system tumors of 2021. In addition, several genetic drivers have been described, which may also help to define distinct tumor types and subtypes. Importantly, the current molecular understanding not only sharpens diagnostic precision but also provides the opportunity to investigate both targeted therapies as well as risk-adapted changes in treatment intensity. Here, we discuss the current knowledge and the clinical relevance of molecular neuropathology in spinal tumor entities.

Integrated analyses reveal two molecularly and clinically distinct subtypes of H3 K27M-mutant diffuse midline gliomas with prognostic significance

H3 K27M-altered diffuse midline gliomas (DMGs) are highly malignant tumours that arise in the midline structures of the CNS. Most DMGs carry an H3 K27M-mutation in one of the genes encoding for histone H3. Recent studies suggested that epigenetic subgroups of DMGs can be distinguished based on alterations in the MAPK-signalling pathway, tumour localisation, mutant H3-gene, or overall survival (OS). However, as these parameters were studied individually, it is unclear how they collectively influence survival. Hence, we analysed dependencies between different parameters, to define novel epigenetic, clinically meaningful subgroups of DMGs. We collected a multifaceted cohort of 149 H3 K27M-mutant DMGs, also incorporating data of published cases. DMGs were included in the study if they could be clearly allocated to the spinal cord (n = 31; one patient with an additional sellar tumour), medulla (n = 20), pons (n = 64) or thalamus (n = 33), irrespective of further known characteristics. We then performed global genome-wide DNA methylation profiling and, for a subset, DNA sequencing and survival analyses. Unsupervised hierarchical clustering of DNA methylation data indicated two clusters of DMGs, i.e. subtypes DMG-A and DMG-B. These subtypes differed in mutational spectrum, tumour localisation, age at diagnosis and overall survival. DMG-A was enriched for DMGs with MAPK-mutations, medullary localisation and adult age. 13% of DMG-A had a methylated MGMT promoter. Contrarily, DMG-B was enriched for cases with TP53-mutations, PDGFRA-amplifications, pontine localisation and paediatric patients. In univariate analyses, the features enriched in DMG-B were associated with a poorer survival. However, all significant parameters tested were dependent on the cluster attribution, which had the largest effect on survival: DMG-A had a significantly better survival compared to DMG-B (p < 0.001). Hence, the subtype attribution based on two methylation clusters can be used to predict survival as it integrates different molecular and clinical parameters.

Morphology-based molecular classification of spinal cord ependymomas using deep neural networks

Based on DNA-methylation, ependymomas growing in the spinal cord comprise two major molecular types termed spinal (SP-EPN) and myxopapillary ependymomas (MPE(-A/B)), which differ with respect to their clinical features and prognosis. Due to the existing discrepancy between histomorphogical diagnoses and classification using methylation data, we asked whether deep neural networks can predict the DNA methylation class of spinal cord ependymomas from hematoxylin and eosin stained whole-slide images. Using explainable AI, we further aimed to prospectively improve the consistency of histology-based diagnoses with DNA methylation profiling by identifying and quantifying distinct morphological patterns of these molecular ependymoma types. We assembled a case series of 139 molecularly characterized spinal cord ependymomas (nMPE = 84, nSP-EPN = 55). Self-supervised and weakly-supervised neural networks were used for classification. We employed attention analysis and supervised machine-learning methods for the discovery and quantification of morphological features and their correlation to the diagnoses of experienced neuropathologists. Our best performing model predicted the DNA methylation class with 98% test accuracy and used self-supervised learning to outperform pretrained encoder-networks (86% test accuracy). In contrast, the diagnoses of neuropathologists matched the DNA methylation class in only 83% of cases. Domain-adaptation techniques improved model generalization to an external validation cohort by up to 22%. Statistically significant morphological features were identified per molecular type and quantitatively correlated to human diagnoses. The approach was extended to recently defined subtypes of myxopapillary ependymomas (MPE-(A/B), 80% test accuracy). In summary, we demonstrated the accurate prediction of the DNA methylation class of spinal cord ependymomas (SP-EPN, MPE(-A/B)) using hematoxylin and eosin stained whole-slide images. Our approach may prospectively serve as a supplementary resource for integrated diagnostics and may even help to establish a standardized, high-quality level of histology-based diagnostics across institutions-in particular in low-income countries, where expensive DNA-methylation analyses may not be readily available.

Outcomes and Pattern of Care for Spinal Myxopapillary Ependymoma in the Modern Era-A Population-Based Observational Study

(1) Background: Myxopapillary ependymoma (MPE) is a rare tumor of the spine, typically slow-growing and low-grade. Optimal management strategies remain unclear due to limited evidence given the low incidence of the disease. (2) Methods: We analyzed data from 1197 patients with spinal MPE from the Surveillance, Epidemiology, and End Results (SEER) database (2000-2020). Patient demographics, treatment modalities, and survival outcomes were examined using statistical analyses. (3) Results: Most patients were White (89.9%) with a median age at diagnosis of 42 years. Surgical resection was performed in 95% of cases. The estimated 10-year overall survival was 91.4%. Younger age (hazard ratio (HR) = 1.09, p < 0.001) and receipt of surgery (HR = 0.43, p = 0.007) were associated with improved survival. Surprisingly, male sex was associated with worse survival (HR = 1.86, p = 0.008) and a younger age at diagnosis compared to females. (4) Conclusions: This study, the largest of its kind, underscores the importance of surgical resection in managing spinal MPE. The unexpected association between male sex and worse survival warrants further investigation into potential sex-specific pathophysiological factors influencing prognosis. Despite limitations, our findings contribute valuable insights for guiding clinical management strategies for spinal MPE.

Implications of DNA Methylation Classification in Diagnosing Ependymoma

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

[Explainable artificial intelligence in pathology]

With the advancements in precision medicine, the demands on pathological diagnostics have increased, requiring standardized, quantitative, and integrated assessments of histomorphological and molecular pathological data. Great hopes are placed in artificial intelligence (AI) methods, which have demonstrated the ability to analyze complex clinical, histological, and molecular data for disease classification, biomarker quantification, and prognosis estimation. This paper provides an overview of the latest developments in pathology AI, discusses the limitations, particularly concerning the black box character of AI, and describes solutions to make decision processes more transparent using methods of so-called explainable AI (XAI).

Transcriptomic and epigenetic dissection of spinal ependymoma (SP-EPN) identifies clinically relevant subtypes enriched for tumors with and without NF2 mutation

Ependymomas encompass multiple clinically relevant tumor types based on localization and molecular profiles. Tumors of the methylation class "spinal ependymoma" (SP-EPN) represent the most common intramedullary neoplasms in children and adults. However, their developmental origin is ill-defined, molecular data are scarce, and the potential heterogeneity within SP-EPN remains unexplored. The only known recurrent genetic events in SP-EPN are loss of chromosome 22q and NF2 mutations, but neither types and frequency of these alterations nor their clinical relevance have been described in a large, epigenetically defined series. Transcriptomic (n = 72), epigenetic (n = 225), genetic (n = 134), and clinical data (n = 112) were integrated for a detailed molecular overview on SP-EPN. Additionally, we mapped SP-EPN transcriptomes to developmental atlases of the developing and adult spinal cord to uncover potential developmental origins of these tumors. The integration of transcriptomic ependymoma data with single-cell atlases of the spinal cord revealed that SP-EPN display the highest similarities to mature adult ependymal cells. Unsupervised hierarchical clustering of transcriptomic data together with integrated analysis of methylation profiles identified two molecular SP-EPN subtypes. Subtype A tumors primarily carried previously known germline or sporadic NF2 mutations together with 22q loss (bi-allelic NF2 loss), resulting in decreased NF2 expression. Furthermore, they more often presented as multilocular disease and demonstrated a significantly reduced progression-free survival as compared to SP-EP subtype B. In contrast, subtype B predominantly contained samples without NF2 mutation detected in sequencing together with 22q loss (monoallelic NF2 loss). These tumors showed regular NF2 expression but more extensive global copy number alterations. Based on integrated molecular profiling of a large multi-center cohort, we identified two distinct SP-EPN subtypes with important implications for genetic counseling, patient surveillance, and drug development priorities.

Toward Explainable Artificial Intelligence for Precision Pathology

The rapid development of precision medicine in recent years has started to challenge diagnostic pathology with respect to its ability to analyze histological images and increasingly large molecular profiling data in a quantitative, integrative, and standardized way. Artificial intelligence (AI) and, more precisely, deep learning technologies have recently demonstrated the potential to facilitate complex data analysis tasks, including clinical, histological, and molecular data for disease classification; tissue biomarker quantification; and clinical outcome prediction. This review provides a general introduction to AI and describes recent developments with a focus on applications in diagnostic pathology and beyond. We explain limitations including the black-box character of conventional AI and describe solutions to make machine learning decisions more transparent with so-called explainable AI. The purpose of the review is to foster a mutual understanding of both the biomedical and the AI side. To that end, in addition to providing an overview of the relevant foundations in pathology and machine learning, we present worked-through examples for a better practical understanding of what AI can achieve and how it should be done.

Molecular characteristics and improved survival prediction in a cohort of 2023 ependymomas

The diagnosis of ependymoma has moved from a purely histopathological review with limited prognostic value to an integrated diagnosis, relying heavily on molecular information. However, as the integrated approach is still novel and some molecular ependymoma subtypes are quite rare, few studies have correlated integrated pathology and clinical outcome, often focusing on small series of single molecular types. We collected data from 2023 ependymomas as classified by DNA methylation profiling, consisting of 1736 previously published and 287 unpublished methylation profiles. Methylation data and clinical information were correlated, and an integrated model was developed to predict progression-free survival. Patients with EPN-PFA, EPN-ZFTA, and EPN-MYCN tumors showed the worst outcome with 10-year overall survival rates of 56%, 62%, and 32%, respectively. EPN-PFA harbored chromosome 1q gains and/or 6q losses as markers for worse survival. In supratentorial EPN-ZFTA, a combined loss of CDKN2A and B indicated worse survival, whereas a single loss did not. Twelve out of 200 EPN-ZFTA (6%) were located in the posterior fossa, and these tumors relapsed or progressed even earlier than supratentorial tumors with a combined loss of CDKN2A/B. Patients with MPE and PF-SE, generally regarded as non-aggressive tumors, only had a 10-year progression-free survival of 59% and 65%, respectively. For the prediction of the 5-year progression-free survival, Kaplan-Meier estimators based on the molecular subtype, a Support Vector Machine based on methylation, and an integrated model based on clinical factors, CNV data, and predicted methylation scores achieved balanced accuracies of 66%, 68%, and 73%, respectively. Excluding samples with low prediction scores resulted in balanced accuracies of over 80%. In sum, our large-scale analysis of ependymomas provides robust information about molecular features and their clinical meaning. Our data are particularly relevant for rare and hardly explored tumor subtypes and seemingly benign variants that display higher recurrence rates than previously believed.

When a dermatopathologist encounters the ultra-rare: A case series of superficial soft tissue/cutaneous myxopapillary ependymomas

Myxopapillary ependymoma (MPE) is an uncommon variant of ependymoma, almost exclusively seen in conus medullaris or filum terminale. MPE can be diagnostically challenging, especially when arising extra-axially. Here we report 5 cases of superficial soft tissue/cutaneous MPE, identified across three tertiary institutions. All patients were female and three of them (3/5, 60%) were children (median age 11 years, range 6-58 years). The tumors presented as slow-growing masses of the sacrococcygeal subcutaneous soft tissues, occasionally identified after minor trauma and clinically favored to be pilonidal sinuses. Imaging showed no neuraxis connection. Macroscopically, tumors were well-circumscribed, lobulated, and solid and microscopically they exhibited typical histopathology of MPE, at least focally. Two of the tumors (2/5, 40%) showed predominantly solid or trabecular architecture with greater cellular pleomorphism, scattered giant cells, and increased mitotic activity. All tumors (5/5, 100%) showed strong diffuse immunohistochemical expression of GFAP. One tumor clustered at the category "ependymoma, myxopapillary" by methylome analysis. Two patients (2/5, 40%) had local recurrence at 8 and 30 months after the initial surgery. No patients developed metastases during the follow-up period (median 60 months, range 6-116 months). Since a subset of extra-axial MPEs behaves more aggressively, timely and accurate diagnosis is of paramount importance.

Impact of molecular classification on prognosis in children and adolescents with spinal ependymoma: Results from the HIT-MED database

Background

Ependymomas of the spinal cord are rare among children and adolescents, and the individual risk of disease progression is difficult to predict. This study aims to evaluate the prognostic impact of molecular typing on pediatric spinal cord ependymomas.

Methods

Eighty-three patients with spinal ependymomas ≤22 years registered in the HIT-MED database (German brain tumor registry for children, adolescents, and adults with medulloblastoma, ependymoma, pineoblastoma, and CNS-primitive neuroectodermal tumors) between 1992 and 2022 were included. Forty-seven tumors were analyzed by DNA methylation array profiling. In 6 cases, HOXB13 and MYCN proteins were detected as surrogate markers for specific methylation classes. Ten patients had NF2-related schwannomatosis.

Results

With a median follow-up time of 4.9 years, 5- and 10-year overall survival (OS) were 100% and 86%, while 5- and 10-year progression-free survival (PFS) were 65% and 54%. Myxopapillary ependymoma (SP-MPE, n = 32, 63%) was the most common molecular type followed by spinal ependymoma (SP-EPN, n = 17, 33%) and MYCN-amplified ependymoma (n = 2, 4%). One case could not be molecularly classified, and one was reclassified as anaplastic pilocytic astrocytoma. 5-year PFS did not significantly differ between SP-MPE and SP-EPN (65% vs. 78%, P = .64). MYCN-amplification was associated with early relapses (<2.3 years) in both cases and death in one patient. Patients with SP-MPE subtype B (n = 9) showed a non-significant trend for better 5 years-PFS compared to subtype A (n = 18; 86% vs. 56%, P = .15). The extent of resection and WHO tumor grades significantly influenced PFS in a uni- and multivariate analysis.

Conclusions

Molecular typing of pediatric spinal ependymomas aids in identifying very high-risk MYCN-amplified ependymomas. Further insights into the molecular heterogeneity of spinal ependymomas are needed for future clinical decision-making.

Ependymoma from Benign to Highly Aggressive Diseases: A Review

Ependymomas comprise biologically distinct tumor types with respect to age distribution, (epi)genetics, localization, and prognosis. Multimodal risk-stratification, including histopathological and molecular features, is essential in these biologically defined tumor types. Gross total resection (GTR), achieved with intraoperative monitoring and neuronavigation, and if necessary, second-look surgery, is the most effective treatment. Adjuvant radiation therapy is mandatory in high-risk tumors and in case of residual tumor. There is yet growing evidence that some ependymal tumors may be cured by surgery alone. To date, the role of chemotherapy is unclear and subject of current studies.Even though standard therapy can achieve reasonable survival rates for the majority of ependymoma patients, long-term follow-up still reveals a high probability of relapse in certain biological entities.With increasing knowledge of biologically distinct tumor types, risk-adapted adjuvant therapy gains importance. Beyond initial tumor control, and avoidance of therapy-induced morbidity for low-risk patients, intensified treatment for high-risk patients comprises another challenge. With identification of specific risk features regarding molecular alterations, targeted therapy may represent an option for individualized treatment modalities in the future.

Clinical impact of molecular profiling in rare brain tumors

PURPOSE OF REVIEW

The purpose of this review is to describe the commonly used molecular diagnostics and illustrate the prognostic importance to the more accurate diagnosis that also may uncover therapeutic targets.

RECENT FINDINGS

The most recent WHO Classification of Central Nervous System Tumours (2021) lists over 100 distinct tumor types. While traditional histology continues to be an important component, molecular testing is increasingly being incorporated as requisite diagnostic criteria. Specific molecular findings such as co-deletion of the short arm of chromosome 1 (1p) and long arm of chromosome 19 (19q) now define IDH-mutant gliomas as oligodendroglioma. In recent years, DNA methylation profiling has emerged as a dynamic tool with high diagnostic accuracy. The integration of specific genetic (mutations, fusions) and epigenetic (CpG methylation) alterations has led to diagnostic refinement and the discovery of rare brain tumor types with distinct clinical outcomes. Molecular profiling is anticipated to play an increasing role in routine surgical neuropathology, although costs, access, and logistical concerns remain challenging.

SUMMARY

This review summarizes the current state of molecular testing in neuro-oncology highlighting commonly used and developing technologies, while also providing examples of new tumor types/subtypes that have emerged as a result of improved diagnostic precision.

Spinal ependymoma in adults: from molecular advances to new treatment perspectives

Ependymomas are rare glial tumors with clinical and biological heterogeneity, categorized into supratentorial ependymoma, posterior fossa ependymoma, and spinal cord ependymoma, according to anatomical localization. Spinal ependymoma comprises four different types: spinal ependymoma, spinal ependymoma MYCN-amplified, myxopapillary ependymoma, and subependymoma. The clinical onset largely depends on the spinal location of the tumor. Both non-specific and specific sensory and/or motor symptoms can be present. Owing to diverse features and the low incidence of spinal ependymomas, most of the current clinical management is derived from small retrospective studies, particularly in adults. Treatment involves primarily surgical resection, aiming at maximal safe resection. The use of radiotherapy remains controversial and the optimal dose has not been established; it is usually considered after subtotal resection for WHO grade 2 ependymoma and for WHO grade 3 ependymoma regardless of the extent of resection. There are limited systemic treatments available, with limited durable results and modest improvement in progression-free survival. Thus, chemotherapy is usually reserved for recurrent cases where resection and/or radiation is not feasible. Recently, a combination of temozolomide and lapatinib has shown modest results with a median progression-free survival (PFS) of 7.8 months in recurrent spinal ependymomas. Other studies have explored the use of temozolomide, platinum compounds, etoposide, and bevacizumab, but standard treatment options have not yet been defined. New treatment options with targeted treatments and immunotherapy are being investigated. Neurological and supportive care are crucial, even in the early stages. Post-surgical rehabilitation can improve the consequences of surgery and maintain a good quality of life, especially in young patients with long life expectancy. Here, we focus on the diagnosis and treatment recommendations for adults with spinal ependymoma, and discuss recent molecular advances and new treatment perspectives.

Clinical management and prognosis of spinal myxopapillary ependymoma: a single-institution cohort of 72 patients

PURPOSE

Myxopapillary ependymoma (MPE) was classified as grade 2 tumor in the 2021 World Health Organization central nervous system classification because of its high recurrence probability. This study aimed to investigate predictive factors and management of tumor recurrence.

METHODS

Seventy-two patients with spinal MPE underwent initial surgical treatment at our hospital between 2011 and 2021. Kaplan-Meier curves and Cox regression were used to analyze the correlation between clinical variables and progression-free survival (PFS).

RESULTS

The median age at diagnosis was 33.5 years (range 8-60 years). Twenty-one patients (29.2%) had preoperative spinal drop metastases. Gross total resection (GTR) was performed in 37 patients (51.4%). The median follow-up was 7.2 years, and the follow-up rate was 88.9% (64 of 72 cases). Twelve of the 64 patients (18.9%) relapsed, and preoperative drop metastasis occurred in 7 patients (58.3%). The estimated 5-year and 10-year PFS rates were 82% and 77%, respectively. Univariate analysis showed that GTR was associated with improved PFS (hazard ratio [HR] 0.149, p = 0.014), while preoperative drop metastasis (HR 3.648, p = 0.027) and tumor involvement sacrococcygeal region (HR 7.563, p = 0.003) were associated with tumor recurrence. Adjuvant radiotherapy (RT) was significantly associated with improved PFS in patients with preoperative drop metastasis (p = 0.039).

CONCLUSION

Complete surgical resection under the premise of protecting neurological function is an important factor in reducing spinal MPE recurrence. Adjuvant RT is recommended when the tumor invades the capsule with preoperative drop metastasis or adhesion to the nerve and cannot reach GTR.

Cauda Equina Neuroendocrine Tumors: Distinct Epithelial Neuroendocrine Neoplasms of Spinal Origin

The tumor formerly known as "cauda equina paraganglioma" was recently renamed as cauda equina neuroendocrine tumor (CENET) based on distinct biological and genetic properties. Nevertheless, it remains insufficiently understood. For this study, we retrieved CENETs (some previously reported), from the pathology files of 3 institutions; we examined their immunohistochemical profile, including common neuroendocrine tumor-associated hormones and transcription factors. We identified 24 CENETs from 7 female and 17 male adult patients, with a median age of 47 years. Six included neurofilament-positive ganglion cells. All tumors tested were positive for INSM1, synaptophysin, chromogranin A, SSTR2, and CD56 as well as at least 1 keratin (AE1/AE3, CAM5.2); CK7 and CK20 were negative. Glial fibrillary acidic protein was negative, except for peripheral nontumoral elements. S100 protein was variable but mainly expressed in scattered sustentacular cells. All but 1 tumor tested were positive for HOXB13; several stained for SATB2, and all tumors were consistently negative for GATA3. All tumors tested were negative for transcription factors found in various other epithelial neuroendocrine neoplasms including TTF1, CDX2, PIT1, TPIT, SF1, and PAX8; staining for T-brachyury was negative. Four of 5 CENETs tested had at least focal tyrosine hydroxylase reactivity. Serotonin expression was detected in all 21 tumors tested; it was diffusely positive in 5 and had variable positivity in the remainder. A few tumors had scattered cells expressing gastrin, calcitonin, pancreatic polypeptide, and peptide YY, while glucagon, adrenocorticotropic hormone, and monoclonal carcinoembryonic antigen were negative. PSAP expression was found focally in 4 of 5 tumors examined. SDHB was consistently intact; ATRX was intact in 14 tumors and showed only focal loss in 3. The median Ki-67 labeling index was 4.5% (range: 1% to 15%). We conclude that CENET represents a distinct neuroendocrine neoplasm; the subset with ganglion cells qualifies for designation as composite gangliocytoma/neuroma-neuroendocrine tumor (CoGNET) as defined in the 2022 WHO classification of neuroendocrine neoplasms. In addition to INSM1, chromogranin, synaptophysin, and keratins, the most characteristic finding is nuclear HOXB13 expression; a subset also express SATB2. Serotonin is the most common hormone expressed. The cytogenesis and pathogenesis of these lesions remains unclear.

Bromodomain and Extra-Terminal Protein Inhibitors: Biologic Insights and Therapeutic Potential in Pediatric Brain Tumors

Pediatric brain tumors have surpassed leukemia as the leading cause of cancer-related death in children. Several landmark studies from the last two decades have shown that many pediatric brain tumors are driven by epigenetic dysregulation within specific developmental contexts. One of the major determinants of epigenetic control is the histone code, which is orchestrated by a number of enzymes categorized as writers, erasers, and readers. Bromodomain and extra-terminal (BET) proteins are reader proteins that bind to acetylated lysines in histone tails and play a crucial role in regulating gene transcription. BET inhibitors have shown efficacy in a wide range of cancers, and a number have progressed to clinical phase testing. Here, we review the evidence for BET inhibitors in pediatric brain tumor experimental models, as well as their translational potential.