Personalized identification and characterization of genome-wide gene expression differences between patient-matched intracranial and extracranial melanoma metastasis pairs.

Melanoma is the most serious type of skin cancer that frequently spreads to other organs of the human body. Especially melanoma metastases to the brain (intracranial metastases) are hard to treat and a major cause of death of melanoma patients. Little is known about molecular alterations and altered mechanisms that distinguish intra- from extracranial melanoma metastases. So far, almost all existing studies compared intracranial metastases from one set of patients to extracranial metastases of an another set of melanoma patients. This neglects the important facts that each melanoma is highly individual and that intra- and extracranial melanoma metastases from the same patient are more similar to each other than to melanoma metastases from other patients in the same organ. To overcome this, we compared the gene expression profiles of 16 intracranial metastases to their corresponding 21 patient-matched extracranial metastases in a personalized way using a three-state Hidden Markov Model (HMM) to identify altered genes for each individual metastasis pair. This enabled three major findings by considering the predicted gene expression alterations across all patients: (i) most frequently altered pathways include cytokine-receptor interaction, calcium signaling, ECM-receptor interaction, cAMP signaling, Jak-STAT and PI3K/Akt signaling, (ii) immune-relevant signaling pathway genes were downregulated in intracranial metastases, and (iii) intracranial metastases were associated with a brain-like phenotype gene expression program. Further, the integration of all differentially expressed genes across the patient-matched melanoma metastasis pairs led to a set of 103 genes that were consistently down- or up-regulated in at least 11 of the 16 of the patients. This set of genes contained many genes involved in the regulation of immune responses, cell growth, cellular signaling and transport processes. An analysis of these genes in the TCGA melanoma cohort showed that the expression behavior of 11 genes was significantly associated with survival. Moreover, a comparison of the 103 genes to three closely related melanoma metastasis studies revealed a core set of eight genes that were consistently down- or upregulated in intra- compared to extracranial metastases in at least two of the three related studies (down: CILP, DPT, FGF7, LAMP3, MEOX2, TMEM119; up: GLDN, PMP2) including FGF7 that was also significantly associated with survival. Our findings contribute to a better characterization of genes and pathways that distinguish intra- from extracranial melanoma metastasis and provide important hints for future experimental studies to identify potential targets for new therapeutic approaches.

Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups.

Melanoma, the deadliest form of skin cancer, can metastasize to different organs. Molecular differences between brain and extracranial melanoma metastases are poorly understood. Here, promoter methylation and gene expression of 11 heterogeneous patient-matched pairs of brain and extracranial metastases were analyzed using melanoma-specific gene regulatory networks learned from public transcriptome and methylome data followed by network-based impact propagation of patient-specific alterations. This innovative data analysis strategy allowed to predict potential impacts of patient-specific driver candidate genes on other genes and pathways. The patient-matched metastasis pairs clustered into three robust subgroups with specific downstream targets with known roles in cancer, including melanoma (SG1: RBM38, BCL11B, SG2: GATA3, FES, SG3: SLAMF6, PYCARD). Patient subgroups and ranking of target gene candidates were confirmed in a validation cohort. Summarizing, computational network-based impact analyses of heterogeneous metastasis pairs predicted individual regulatory differences in melanoma brain metastases, cumulating into three consistent subgroups with specific downstream target genes.

Exploring the In Vitro and In Vivo Therapeutic Potential of BRAF and MEK Inhibitor Combination in NRAS-Mutated Melanoma.

INTRODUCTION: Patients with NRAS-mutant metastatic melanoma often have an aggressive disease requiring a fast-acting, effective therapy. The MEK inhibitor binimetinib shows an overall response rate of 15% in patients with NRAS-mutant melanoma, providing a backbone for combination strategies. Our previous studies demonstrated that in NRAS-mutant melanoma, the antitumor activity of the MEK inhibitor binimetinib was significantly potentiated by the BRAFV600E/K inhibitor encorafenib through the induction of ER stress, leading to melanoma cell death by apoptotic mechanisms. Encorafenib combined with binimetinib was well tolerated in a phase III trial showing potent antitumor activity in BRAF-mutant melanoma, making a rapid evaluation in NRAS-mutant melanoma imminently feasible. These data provide a mechanistic rationale for the evaluation of binimetinib combined with encorafenib in preclinical and clinical studies on NRAS-mutant metastatic melanoma. METHODS: The combination of BRAFi plus MEKi was tested in a monolayer culture of patient-derived cell lines and in corresponding patient-derived tissue slice cultures of NRAS-mutant melanoma. To investigate the treatment in vivo, NSG (NOD. Cg-PrkdcscidIl2rgtm1Wjl/SzJ) mice were subcutaneously injected with three different BRAF wild-type melanoma models harboring oncogenic NRAS mutations and treated orally with encorafenib (6 mg/kg body weight, daily) with or without binimetinib (8 mg/kg body weight, twice daily). In parallel, an individual healing attempt was carried out by treating one patient with an NRAS-mutated tumor. RESULTS: Encorafenib was able to enhance the inhibitory effect on cell growth of binimetinib only in the cell line SKMel147 in vitro. It failed to enhance the apoptotic effect found in two other NRAS-mutated cell lines. Encorafenib led to a hyperactivation of ERK which could be reduced with the combinational treatment. In two of the three patient-derived tissue slice culture models of NRAS-mutant melanomas, a slight tendency of a combinatorial effect was seen which was not significant. Encorafenib showed a slight induction of the ER stress genes ATF4, CHOP, and NUPR1. The combinational treatment was able to enhance this effect, but not significantly. In the mouse model, the combination therapy of encorafenib with binimetinib resulted in reduced tumor growth compared to the control and encorafenib groups; however, the best effect in terms of tumor growth inhibition was measured in the binimetinib therapy group. The therapy showed no effect in an individual healing attempt for a patient suffering from metastatic, therapy-refractory NRAS-mutated melanoma. CONCLUSION: In in vitro and ex vivo settings, the combination therapy was observed to elicit a response; however, it did not amplify the efficacy observed with binimetinib alone, whereas in a patient, the combinational treatment remained ineffective. The preclinical in vivo data showed no increased combinatorial effect. However, the in vivo effect of binimetinib as monotherapy was unexpectedly high in the tested regimen. Nevertheless, binimetinib proved to be advantageous in the treatment of melanoma in vivo and led to high rates of apoptosis in vitro; hence, it still seems to be a good base for combination with other substances in the treatment of patients with NRAS-mutant melanoma.

Leptomeningeal Metastases in Melanoma Patients: An Update on and Future Perspectives for Diagnosis and Treatment.

Leptomeningeal disease (LMD) is a devastating complication of cancer with a particularly poor prognosis. Among solid tumours, malignant melanoma (MM) has one of the highest rates of metastasis to the leptomeninges, with approximately 10-15% of patients with advanced disease developing LMD. Tumour cells that metastasise to the brain have unique properties that allow them to cross the blood-brain barrier, evade the immune system, and survive in the brain microenvironment. Metastatic colonisation is achieved through dynamic communication between metastatic cells and the tumour microenvironment, resulting in a tumour-permissive milieu. Despite advances in treatment options, the incidence of LMD appears to be increasing and current treatment modalities have a limited impact on survival. This review provides an overview of the biology of LMD, diagnosis and current treatment approaches for MM patients with LMD, and an overview of ongoing clinical trials. Despite the still limited efficacy of current therapies, there is hope that emerging treatments will improve the outcomes for patients with LMD.

Patient-specific identification of genome-wide DNA-methylation differences between intracranial and extracranial melanoma metastases.

Melanomas frequently metastasize to distant organs and especially intracranial metastases still represent a major clinical challenge. Epigenetic reprogramming of intracranial metastases is thought to be involved in therapy failure, but so far only little is known about patient-specific DNA-methylation differences between intra- and extracranial melanoma metastases. Hierarchical clustering of the methylomes of 24 patient-matched intra- and extracranial melanoma metastases pairs revealed that intra- and extracranial metastases of individual patients were more similar to each other than to metastases in the same tissue from other patients. Therefore, a personalized analysis of each metastases pair was done by a Hidden Markov Model to classify methylation levels of individual CpGs as decreased, unchanged or increased in the intra- compared to the extracranial metastasis. The predicted DNA-methylation alterations were highly patient-specific differing in the number and methylation states of altered CpGs. Nevertheless, four important general observations were made: (i) intracranial metastases of most patients mainly showed a reduction of DNA-methylation, (ii) cytokine signaling was most frequently affected by differential methylation in individual metastases pairs, but also MAPK, PI3K/Akt and ECM signaling were often altered, (iii) frequently affected genes were mainly involved in signaling, growth, adhesion or apoptosis, and (iv) an enrichment of functional terms related to channel and transporter activities supports previous findings for a brain-like phenotype. In addition, the derived set of 17 signaling pathway genes that distinguished intra- from extracranial metastases in more than 50% of patients included well-known oncogenes (e.g. PRKCA, DUSP6, BMP4) and several other genes known from neuronal disorders (e.g. EIF4B, SGK1, CACNG8). Moreover, associations of gene body methylation alterations with corresponding gene expression changes revealed that especially the three signaling pathway genes JAK3, MECOM, and TNXB differ strongly in their expression between patient-matched intra- and extracranial metastases. Our analysis contributes to an in-depth characterization of DNA-methylation differences between patient-matched intra- and extracranial melanoma metastases and may provide a basis for future experimental studies to identify targets for new therapeutic approaches.

EGFL7 loss correlates with increased VEGF-D expression, upregulating hippocampal adult neurogenesis and improving spatial learning and memory.

Neural stem cells reside in the subgranular zone, a specialized neurogenic niche of the hippocampus. Throughout adulthood, these cells give rise to neurons in the dentate gyrus, playing an important role in learning and memory. Given that these core cognitive processes are disrupted in numerous disease states, understanding the underlying mechanisms of neural stem cell proliferation in the subgranular zone is of direct practical interest. Here, we report that mature neurons, neural stem cells and neural precursor cells each secrete the neurovascular protein epidermal growth factor-like protein 7 (EGFL7) to shape this hippocampal niche. We further demonstrate that EGFL7 knock-out in a Nestin-CreERT2-based mouse model produces a pronounced upregulation of neurogenesis within the subgranular zone. RNA sequencing identified that the increased expression of the cytokine VEGF-D correlates significantly with the ablation of EGFL7. We substantiate this finding with intraventricular infusion of VEGF-D upregulating neurogenesis in vivo and further show that VEGF-D knock-out produces a downregulation of neurogenesis. Finally, behavioral studies in EGFL7 knock-out mice demonstrate greater maintenance of spatial memory and improved memory consolidation in the hippocampus by modulation of pattern separation. Taken together, our findings demonstrate that both EGFL7 and VEGF-D affect neurogenesis in the adult hippocampus, with the ablation of EGFL7 upregulating neurogenesis, increasing spatial learning and memory, and correlating with increased VEGF-D expression.

Identification of Epigenetically Regulated Genes Distinguishing Intracranial from Extracranial Melanoma Metastases.

Despite remarkable advances in treating patients with metastatic melanoma, the management of melanoma brain metastases remains challenging. Recent evidence suggests that epigenetic reprogramming is an important mechanism for the adaptation of melanoma cells to the brain environment. In this study, the methylomes and transcriptomes of a cohort of matched melanoma metastases were evaluated by integrated omics data analysis. The identified 38 candidate genes displayed distinct promoter methylation and corresponding gene expression changes in intracranial compared with extracranial metastases. The 11 most promising genes were validated on protein level in both tumor and surrounding normal tissue using immunohistochemistry. In accordance with the underlying promoter methylation and gene expression changes, a significantly different protein expression was confirmed for STK10, PDXK, WDR24, CSSP1, NMB, RASL11B, phosphorylated PRKCZ, PRKCZ, and phosphorylated GRB10 in the intracranial metastases. The observed changes imply a distinct intracranial phenotype with increased protein kinase B phosphorylation and a higher frequency of proliferating cells. Knockdown of PRKCZ or GRB10 altered the expression of phosphorylated protein kinase B and decreased the viability of a brain-specific melanoma cell line. In summary, epigenetically regulated cancer-relevant alterations were identified that provide insights into the molecular mechanisms that discriminate brain metastases from other organ metastases, which could be exploited by targeting the affected signaling pathways.

A new approach for clinical translation of infrared spectroscopy: exploitation of the signature of glioblastoma for general brain tumor recognition.

PURPOSE: Infrared (IR) spectroscopy has the potential for tumor delineation in neurosurgery. Previous research showed that IR spectra of brain tumors are generally characterized by reduced lipid-related and increased protein-related bands. Therefore, we propose the exploitation of these common spectral changes for brain tumor recognition. METHODS: Attenuated total reflection IR spectroscopy was performed on fresh specimens of 790 patients within minutes after resection. Using principal component analysis and linear discriminant analysis, a classification model was developed on a subset of glioblastoma (n = 135) and non-neoplastic brain (n = 27) specimens, and then applied to classify the IR spectra of several types of brain tumors. RESULTS: The model correctly classified 82% (517/628) of specimens as "tumor" or "non-tumor", respectively. While the sensitivity was limited for infiltrative glioma, this approach recognized GBM (86%), other types of primary brain tumors (92%) and brain metastases (92%) with high accuracy and all non-tumor samples were correctly identified. CONCLUSION: The concept of differentiation of brain tumors from non-tumor brain based on a common spectroscopic tumor signature will accelerate clinical translation of infrared spectroscopy and related technologies. The surgeon could use a single instrument to detect a variety of brain tumor types intraoperatively in future clinical settings. Our data suggests that this would be associated with some risk of missing infiltrative regions or tumors, but not with the risk of removing non-tumor brain.

Orthotopic Glioblastoma Models for Evaluation of the Clinical Target Volume Concept.

In times of high-precision radiotherapy, the accurate and precise definition of the primary tumor localization and its microscopic spread is of enormous importance. In glioblastoma, the microscopic tumor extension is uncertain and, therefore, population-based margins for Clinical Target Volume (CTV) definition are clinically used, which could either be too small-leading to increased risk of loco-regional recurrences-or too large, thus, enhancing the probability of normal tissue toxicity. Therefore, the aim of this project is to investigate an individualized definition of the CTV in preclinical glioblastoma models based on specific biological tumor characteristics. The microscopic tumor extensions of two different orthotopic brain tumor models (U87MG_mCherry; G7_mCherry) were evaluated before and during fractionated radiotherapy and correlated with corresponding histological data. Representative tumor slices were analyzed using Matrix-Assisted Laser Desorption/Ionization (MALDI) and stained for putative stem-like cell markers as well as invasion markers. The edges of the tumor are clearly shown by the MALDI segmentation via unsupervised clustering of mass spectra and are consistent with the histologically defined border in H&E staining in both models. MALDI component analysis identified specific peaks as potential markers for normal brain tissue (e.g., 1339 m/z), whereas other peaks demarcated the tumors very well (e.g., 1562 m/z for U87MG_mCherry) irrespective of treatment. MMP14 staining revealed only a few positive cells, mainly in the tumor border, which could reflect the invasive front in both models. The results of this study indicate that MALDI information correlates with microscopic tumor spread in glioblastoma models. Therefore, an individualized CTV definition based on biological tumor characteristics seems possible, whereby the visualization of tumor volume and protein heterogeneity can be potentially used to define radiotherapy-sensitive and resistant areas.

A novel molecular signature identifies mixed subtypes in renal cell carcinoma with poor prognosis and independent response to immunotherapy.

BACKGROUND: Renal cell carcinoma (RCC) is a heterogeneous disease comprising histologically defined subtypes. For therapy selection, precise subtype identification and individualized prognosis are mandatory, but currently limited. Our aim was to refine subtyping and outcome prediction across main subtypes, assuming that a tumor is composed of molecular features present in distinct pathological subtypes. METHODS: Individual RCC samples were modeled as linear combination of the main subtypes (clear cell (ccRCC), papillary (pRCC), chromophobe (chRCC)) using computational gene expression deconvolution. The new molecular subtyping was compared with histological classification of RCC using the Cancer Genome Atlas (TCGA) cohort (n = 864; ccRCC: 512; pRCC: 287; chRCC: 65) as well as 92 independent histopathologically well-characterized RCC. Predicted continuous subtypes were correlated to cancer-specific survival (CSS) in the TCGA cohort and validated in 242 independent RCC. Association with treatment-related progression-free survival (PFS) was studied in the JAVELIN Renal 101 (n = 726) and IMmotion151 trials (n = 823). CSS and PFS were analyzed using the Kaplan-Meier and Cox regression analysis. RESULTS: One hundred seventy-four signature genes enabled reference-free molecular classification of individual RCC. We unambiguously assign tumors to either ccRCC, pRCC, or chRCC and uncover molecularly heterogeneous tumors (e.g., with ccRCC and pRCC features), which are at risk of worse outcome. Assigned proportions of molecular subtype-features significantly correlated with CSS (ccRCC (P = 4.1E - 10), pRCC (P = 6.5E - 10), chRCC (P = 8.6E - 06)) in TCGA. Translation into a numerical RCC-R(isk) score enabled prognosis in TCGA (P = 9.5E - 11). Survival modeling based on the RCC-R score compared to pathological categories was significantly improved (P = 3.6E - 11). The RCC-R score was validated in univariate (P = 3.2E - 05; HR = 3.02, 95% CI: 1.8-5.08) and multivariate analyses including clinicopathological factors (P = 0.018; HR = 2.14, 95% CI: 1.14-4.04). Heterogeneous PD-L1-positive RCC determined by molecular subtyping showed increased PFS with checkpoint inhibition versus sunitinib in the JAVELIN Renal 101 (P = 3.3E - 04; HR = 0.52, 95% CI: 0.36 - 0.75) and IMmotion151 trials (P = 0.047; HR = 0.69, 95% CI: 0.48 - 1). The prediction of PFS significantly benefits from classification into heterogeneous and unambiguous subtypes in both cohorts (P = 0.013 and P = 0.032). CONCLUSION: Switching from categorical to continuous subtype classification across most frequent RCC subtypes enables outcome prediction and fosters personalized treatment strategies.

Modeling and simulation of diffusion and reaction processes during the staining of tissue sections on slides.

Histological slides are an important tool in the diagnosis of tumors as well as of other diseases that affect cell shapes and distributions. Until now, the research concerning an optimal staining time has been mainly done empirically. In experimental investigations, it is often not possible to stain an already-stained slide with another stain to receive further information. To overcome these challenges, in the present paper a continuum-based model was developed for conducting a virtual (re-)staining of a scanned histological slide. This model is capable of simulating the staining of cell nuclei with the dye hematoxylin (C.I. 75,290). The transport and binding of the dye are modeled (i) along with the resulting RGB intensities (ii). For (i), a coupled diffusion-reaction equation is used and for (ii) Beer-Lambert's law. For the spatial discretization an approach based on the finite element method (FEM) is used and for the time discretization a finite difference method (FDM). For the validation of the proposed model, frozen sections from human liver biopsies stained with hemalum were used. The staining times were varied so that the development of the staining intensity could be observed over time. The results show that the model is capable of predicting the staining process. The model can therefore be used to perform a virtual (re-)staining of a histological sample. This allows a change of the staining parameters without the need of acquiring an additional sample. The virtual standardization of the staining is the first step towards universal cross-site comparability of histological slides.

Two Pituitary Neuroendocrine Tumors (PitNETs) with Very High Proliferation and TP53 Mutation - High-Grade PitNET or PitNEC?

We report two pituitary neuroendocrine tumors (PitNETs) with very high Ki67 labeling indices, many mitoses and TP53 mutation (nearly all tumor cell nuclei were positive for p53). One of the tumors had bone and liver metastases. One was a corticotroph cell tumor; the other was a lactotroph tumor. The classification of these tumors is the subject of this discussion. Traditionally, pituitary carcinomas are only diagnosed by demonstration of metastases according to the 2017 WHO classification. In contrast, neuroendocrine neoplasms of the gastrointestinal tract and pancreas are classified as either well differentiated NETs that are graded as G1, G2, and G3 based on proliferation as determined by Ki67 indices of ≤ 3, 3-20 and > 20%, and/or < 2, 2-20, and > 20 mitoses per 10 high-power field respectively, or as neuroendocrine carcinomas (NECs) that are poorly differentiated neoplasms with mitoses > 20/HPF and/or a Ki67 index > 20%. With the reclassificiation of PitNETs, in our opinion, the adequate term for the well-differentiated corticotroph tumor that we report is a PitNET G3, whereas the undifferentiated prolactin tumor should be classified as PitNEC. This report expands the spectrum of pituitary neuroendocrine neoplasms.

Label-free multiphoton imaging allows brain tumor recognition based on texture analysis-a study of 382 tumor patients.

BACKGROUND: Label-free multiphoton microscopy has been suggested for intraoperative recognition and delineation of brain tumors. For any future clinical application, appropriate approaches for image acquisition and analysis have to be developed. Moreover, an evaluation of the reliability of the approach, taking into account inter- and intrapatient variability, is needed. METHODS: Coherent anti-Stokes Raman scattering (CARS), two-photon excited fluorescence (TPEF), and second-harmonic generation were acquired on cryosections of brain tumors of 382 patients and 28 human nontumor brain samples. Texture parameters of those images were calculated and used as input for linear discriminant analysis. RESULTS: The combined analysis of texture parameters of the CARS and TPEF signal proved to be most suited for the discrimination of nontumor brain versus brain tumors (low- and high-grade astrocytoma, oligodendroglioma, glioblastoma, recurrent glioblastoma, brain metastases of lung, colon, renal, and breast cancer and of malignant melanoma) leading to a correct rate of 96% (sensitivity: 96%, specificity: 100%). To approximate the clinical setting, the results were validated on 42 fresh, unfixed tumor biopsies. 82% of the tumors and, most important, all of the nontumor samples were correctly recognized. An image resolution of 1 µm was sufficient to distinguish brain tumors and nontumor brain. Moreover, the vast majority of single fields of view of each patient's sample were correctly classified with high probabilities, which is important for clinical translation. CONCLUSION: Label-free multiphoton imaging might allow fast and accurate intraoperative delineation of primary and secondary brain tumors in combination with endoscopic systems.

Label-free multiphoton microscopy as a tool to investigate alterations of cerebral aneurysms.

Cerebral aneurysms are abnormal focal dilatations of arterial vessel walls with pathological vessel structure alterations. Sudden rupture can lead to a subarachnoid hemorrhage, which is associated with a high mortality. Therefore, the origin of cerebral aneurysms as well as the progression to the point of rupture needs to be further investigated. Label-free multimodal multiphoton microscopy (MPM) was performed on resected human aneurysm domes and integrated three modalities: coherent anti-Stokes Raman scattering, endogenous two-photon fluorescence and second harmonic generation. We showed that MPM is a completely label-free and real-time powerful tool to detect pathognomonic histopathological changes in aneurysms, e.g. thickening and thinning of vessel walls, intimal hyperplasia, intra-wall haemorrhage, calcification as well as atherosclerotic changes. In particular, the loss or fragmentation of elastin as well as fibromatous wall remodelling appeared very distinct. Remarkably, cholesterol and lipid deposits were clearly visible in the multiphoton images. MPM provides morphological and biochemical information that are crucial for understanding the mechanisms of aneurysm formation and progression.

Nonmetastatic Medulloblastoma of Early Childhood: Results From the Prospective Clinical Trial HIT-2000 and An Extended Validation Cohort.

PURPOSE: The HIT-2000-BIS4 trial aimed to avoid highly detrimental craniospinal irradiation (CSI) in children < 4 years of age with nonmetastatic medulloblastoma by systemic chemotherapy, intraventricular methotrexate, and risk-adapted local radiotherapy. PATIENTS AND METHODS: From 2001-2011, 87 patients received systemic chemotherapy and intraventricular methotrexate. Until 2006, CSI was reserved for nonresponse or progression. After 2006, local radiotherapy was introduced for nonresponders or patients with classic medulloblastoma (CMB) or large-cell/anaplastic medulloblastoma (LCA). DNA methylation profiles of infantile sonic hedgehog-activated medulloblastoma (SHH-INF) were subdivided into iSHH-I and iSHH-II subtypes in the HIT-2000-BIS4 cohort and a validation cohort (n = 71) from the HIT group and Russia. RESULTS: Five years after diagnosis, patients with desmoplastic medulloblastoma (DMB) or medulloblastoma with extensive nodularity (MBEN; n = 42) had 93% progression-free survival (5y-PFS), 100% overall survival (5y-OS), and 93% CSI-free (5y-CSI-free) survival. Patients with CMB/LCA (n = 45) had 37% 5y-PFS, 62% 5y-OS, and 39% 5y-CSI-free survival. Local radiotherapy did not improve survival in patients with CMB/LCA. All DMB/MBEN assessed by DNA methylation profiling belonged to the SHH-INF subgroup. Group 3 patients (5y-PFS, 36%; n = 14) relapsed more frequently than the SHH-INF group (5y-PFS, 93%; n = 28) or group 4 patients (5y-PFS, 83%; n = 6; P < .001). SHH-INF split into iSHH-I and iSHH-II subtypes in HIT-2000-BIS4 and the validation cohort, without prognostic impact (5y-PFS: iSHH-I, 73%, v iSHH-II, 83%; P = .25; n = 99). Intelligence quotient (IQ) was significantly lower in patients after CSI (mean IQ, 90 [no radiotherapy], v 74 [CSI]; P = .012). CONCLUSION: Systemic chemotherapy and intraventricular methotrexate led to favorable survival in both iSHH subtypes of SHH-activated DMB/MBEN with acceptable neurotoxicity. Survival in patients with non-wingless (WNT)/non-SHH disease with CMB/LCA was not improved by local radiotherapy. Patients with group 4 disease had more favorable survival rates than those with group 3 medulloblastoma.