MRI phenotyping of underlying cerebral small vessel disease in mixed hemorrhage patients

Objective: To investigate underlying cerebral small vessel disease (CSVD) in patients with mixed cerebral hemorrhages patterns and phenotype them according to the contribution of the two most common sporadic CSVD subtypes: cerebral amyloid angiopathy (CAA) vs. hypertensive arteriopathy (HA). Methods: Brain MRIs of patients with intracerebral hemorrhages (ICHs) and/or cerebral microbleeds (CMBs) were assessed for the full spectrum of CSVD markers using validated scales: ICHs, CMBs, cortical superficial siderosis (cSS), white matter hyperintensities, MRI-visible perivascular spaces (PVS). PVS predominance pattern was grouped as centrum-semiovale (CSO)-PVS predominance, basal-ganglia (BG)-PVS predominance, CSO-PVS and BG-PVS equality. Patients with mixed cerebral hemorrhages were classified into mixed CAA-pattern or mixed HA-pattern according to the existence of cSS and/or a CSO-PVS predominance pattern and comparisons were performed. Results: We included 110 patients with CAA (strictly lobar ICHs/CMBs), 33 with HA (strictly deep ICHs/CMBs) and 97 with mixed lobar/deep ICHs/CMBs. Mixed patients were more similar to HA with respect to their MRI-CSVD markers, vascular risk profile and cerebrospinal fluid (CSF) measures. In the mixed patients, 33 (34%) had cSS, a CSO-PVS predominance pattern, or both, and were defined as mixed CAA-pattern cases. The mixed CAA-pattern patients were more alike CAA patients regarding their MRI-CSVD markers, CSF and genetic profile. Conclusion: Our findings suggest that the heterogeneous group of patients with mixed cerebral hemorrhages distribution can be further phenotyped according to the predominant underlying CSVD. cSS presence and a CSO-PVS predominance pattern could serve as strongly suggestive markers of a contribution from CAA among patients with mixed hemorrhages

Correction to Severe depression is associated with increased microglial quinolinic acid in subregions of the anterior cingulate gyrus: Evidence for an immune-modulated glutamatergic neurotransmission? [Journal of Neuroinflammation (2013) 10, 34] 10.1186/1742-2094-10-34

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DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology

ATRT–SHH comprises three molecular subgroups with characteristic clinical and histopathological features and prognostic significance

Atypical teratoid/rhabdoid tumor (ATRT) is an aggressive central nervous system tumor characterized by loss of SMARCB1/INI1 protein expression and comprises three distinct molecular groups, ATRT–TYR, ATRT–MYC and ATRT–SHH. ATRT–SHH represents the largest molecular group and is heterogeneous with regard to age, tumor location and epigenetic profile. We, therefore, aimed to investigate if heterogeneity within ATRT–SHH might also have biological and clinical importance. Consensus clustering of DNA methylation profiles and confirmatory t-SNE analysis of 65 ATRT–SHH yielded three robust molecular subgroups, i.e., SHH-1A, SHH-1B and SHH-2. These subgroups differed by median age of onset (SHH-1A: 18 months, SHH-1B: 107 months, SHH-2: 13 months) and tumor location (SHH-1A: 88% supratentorial; SHH-1B: 85% supratentorial; SHH-2: 93% infratentorial, often extending to the pineal region). Subgroups showed comparable SMARCB1 mutational profiles, but pathogenic/likely pathogenic SMARCB1 germline variants were over-represented in SHH-2 (63%) as compared to SHH-1A (20%) and SHH-1B (0%). Protein expression of proneural marker ASCL1 (enriched in SHH-1B) and glial markers OLIG2 and GFAP (absent in SHH-2) as well as global mRNA expression patterns differed, but all subgroups were characterized by overexpression of SHH as well as Notch pathway members. In a Drosophila model, knockdown of Snr1 (the fly homologue of SMARCB1) in hedgehog activated cells not only altered hedgehog signaling, but also caused aberrant Notch signaling and formation of tumor-like structures. Finally, on survival analysis, molecular subgroup and age of onset (but not ASCL1 staining status) were independently associated with overall survival, older patients (> 3 years) harboring SHH-1B experiencing relatively favorable outcome. In conclusion, ATRT–SHH comprises three subgroups characterized by SHH and Notch pathway activation, but divergent molecular and clinical features. Our data suggest that molecular subgrouping of ATRT–SHH has prognostic relevance and might aid to stratify patients within future clinical trials. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00401-022-02424-5

Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated

PURPOSE: Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for individual patients is of pivotal importance. However, only biomarkers for highly aggressive tumors are established (CDKN2A/B and TERT), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma. METHODS: DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 multicenter cases. RESULTS: Both CNV- and methylation family-based subgrouping independently resulted in increased prediction accuracy of risk of recurrence compared with the WHO classification (c-indexes WHO 2016, CNV, and methylation family 0.699, 0.706, and 0.721, respectively). Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference P = .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively). CONCLUSION: Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction

Recurrent fusions in PLAGL1 define a distinct subset of pediatric-type supratentorial neuroepithelial tumors

Ependymomas encompass a heterogeneous group of central nervous system (CNS) neoplasms that occur along the entire neuroaxis. In recent years, extensive (epi-)genomic profiling efforts have identified several molecular groups of ependymoma that are characterized by distinct molecular alterations and/or patterns. Based on unsupervised visualization of a large cohort of genome-wide DNA methylation data, we identified a highly distinct group of pediatric-type tumors (n = 40) forming a cluster separate from all established CNS tumor types, of which a high proportion were histopathologically diagnosed as ependymoma. RNA sequencing revealed recurrent fusions involving the pleomorphic adenoma gene-like 1 (PLAGL1) gene in 19 of 20 of the samples analyzed, with the most common fusion being EWSR1:PLAGL1 (n = 13). Five tumors showed a PLAGL1:FOXO1 fusion and one a PLAGL1:EP300 fusion. High transcript levels of PLAGL1 were noted in these tumors, with concurrent overexpression of the imprinted genes H19 and IGF2, which are regulated by PLAGL1. Histopathological review of cases with sufficient material (n = 16) demonstrated a broad morphological spectrum of tumors with predominant ependymoma-like features. Immunohistochemically, tumors were GFAP positive and OLIG2- and SOX10 negative. In 3/16 of the cases, a dot-like positivity for EMA was detected. All tumors in our series were located in the supratentorial compartment. Median age of the patients at the time of diagnosis was 6.2 years. Median progression-free survival was 35 months (for 11 patients with data available). In summary, our findings suggest the existence of a novel group of supratentorial neuroepithelial tumors that are characterized by recurrent PLAGL1 fusions and enriched for pediatric patients

Molecular and translational advances in meningiomas.

Meningiomas are the most common primary intracranial neoplasm. The current World Health Organization (WHO) classification categorizes meningiomas based on histopathological features, but emerging molecular data demonstrate the importance of genomic and epigenomic factors in the clinical behavior of these tumors. Treatment options for symptomatic meningiomas are limited to surgical resection where possible and adjuvant radiation therapy for tumors with concerning histopathological features or recurrent disease. At present, alternative adjuvant treatment options are not available in part due to limited historical biological analysis and clinical trial investigation on meningiomas. With advances in molecular and genomic techniques in the last decade, we have witnessed a surge of interest in understanding the genomic and epigenomic landscape of meningiomas. The field is now at the stage to adopt this molecular knowledge to refine meningioma classification and introduce molecular algorithms that can guide prediction and therapeutics for this tumor type. Animal models that recapitulate meningiomas faithfully are in critical need to test new therapeutics to facilitate rapid-cycle translation to clinical trials. Here we review the most up-to-date knowledge of molecular alterations that provide insight into meningioma behavior and are ready for application to clinical trial investigation, and highlight the landscape of available preclinical models in meningiomas

FGFR4 Arg388 allele correlates with tumour thickness and FGFR4 protein expression with survival of melanoma patients

A single nucleotide polymorphism in the gene for FGFR4 (−Arg388) has been associated with progression in various types of human cancer. Although fibroblast growth factors (FGFs) belong to the most important growth factors in melanoma, expression of FGF receptor subtype 4 has not been investigated yet. In this study, the protein expression of this receptor was analysed in 137 melanoma tissues of different progression stages by immunohistochemistry. FGFR4 protein was expressed in 45% of the specimens and correlated with pTNM tumour stages (UICC, P=0.023 and AJCC, P=0.046), presence of microulceration (P=0.009), tumour vascularity (P=0.001), metastases (P=0.025), number of primary tumours (P=0.022), overall survival (P=0.047) and disease-free survival (P=0.024). Furthermore, FGFR4 Arg388 polymorphism was analysed in 185 melanoma patients by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). The Arg388 allele was detected in 45% of the melanoma patients and was significantly associated with tumour thickness (by Clark's level of invasion (P=0.004) and by Breslow in mm (P=0.02)) and the tumour subtype nodular melanoma (P=0.002). However, there was no correlation of the FGFR4 Arg388 allele with overall and disease-free survival. In conclusion, the Arg388 genotype and the protein expression of FGFR4 may be potential markers for progression of melanoma

Reduced PTEN expression in the pancreas overexpressing transforming growth factor-beta 1

PTEN is a candidate tumour suppressor gene and frequently mutated in multiple cancers, however, not in pancreatic cancer. Recently, it has been demonstrated that PTEN expression is regulated by TGF-β1. Using TGF-β1 transgenic mice (n=7) and wildtype littermates (n=6), as well as pancreatic tissues obtained from organ donors (n=10) and patients with pancreatic cancer (n=10), we assessed the expression of PTEN by means of immunohistochemistry and semiquantitative PCR analysis. In addition, PANC-1 cells were treated with TGF-β1 in vitro and the levels of PTEN mRNA were determined in these cells. In human pancreatic cancers PTEN mRNA levels were significantly decreased (P<0.05). In addition, in the pancreas of TGF-β1 transgenic mice the expression of PTEN was significantly reduced (P<0.01), as compared to wildtype littermates and incubation of PANC-1 cells with TGF-β1 decreased PTEN mRNA levels after 24 h. Inasmuch as TGF-β1 decreases PTEN expression in human pancreatic cancer cells and human pancreatic cancers overexpress TGF-β1, the reduced expression of PTEN in pancreatic cancer may be mediated by TGF-β1 overexpression. Thus, although PTEN is not mutated in pancreatic cancers, the reduction of its expression may give pancreatic cancer cells an additional growth advantage