Summary Accurate pathological diagnosis is crucial for optimal management of cancer patients. For the ~100 known central nervous system (CNS) tumour entities, 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. We herein present the development of a comprehensive approach for DNA methylation-based CNS tumour classification across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that availability of this method may have substantial impact on diagnostic precision compared with 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 (www.molecularneuropathology.org) requiring no 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.

SUMMARY Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Herein we demonstrate that a significant proportion of institutionally diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well-defined CNS tumor entities, facilitating diagnosis and appropriate therapy for patients with these tumors. From the remaining fraction of CNS-PNETs we identify four new CNS tumor entities, each associated with a recurrent genetic alteration and distinct histopathological and clinical features. These new molecular entities, designated “CNS neuroblastoma with FOXR2 activation (CNS NB-FOXR2)”, “CNS Ewing sarcoma family tumor with CIC alteration (CNS EFT-CIC)”, “CNS high-grade neuroepithelial tumor with MN1 alteration (CNS HGNET-MN1)”, and “CNS high-grade neuroepithelial tumor with BCOR alteration (CNS HGNET-BCOR)”, will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by poorly differentiated CNS tumors.

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ATRX and IDH1-R132H immunohistochemistry with subsequent copy number analysis and IDH sequencing as a basis for an "integrated" diagnostic approach for adult astrocytoma, oligodendroglioma and glioblastoma Following the concepts of the "ISN-Haarlem", we rediagnosed the series to obtain "integrated" diagnoses with 155 tumors being astrocytomas, 100 oligodendrogliomas and 150 glioblastomas. In a subset of 100 diffuse gliomas from the NOA-04 trial with long-term follow-up data available, the "integrated" diagnosis had a significantly greater prognostic power for overall and progression-free survival compared to WHO 2007. Based on the "integrated" diagnoses, loss of ATRX expression was close to being mutually exclusive to 1p/19q codeletion, with only 2 of 167 ATRX-negative tumors exhibiting 1p/19q codeletion. All but 4 of 141 patients with loss of ATRX expression and diffuse glioma carried either IDH1 or IDH2 mutations. Interestingly, the majority of glioblastoma patients with loss of ATRX expression but no IDH mutations exhibited an H3F3A mutation. Further, all patients with 1p/19 codeletion carried a mutation in IDH1 or IDH2. We present an algorithm based on stepwise analysis with initial immunohistochemistry for ATRX and IDH1-R132H followed by 1p/19q analysis followed by IDH sequencing which reduces the number of molecular analyses and which has a far better association with patient outcome than WHO 2007. or IDH2 mutations. Interestingly, the majority of glioblastoma patients with loss of ATRX expression but no IDH mutations exhibited an H3F3A mutation. Further, all patients with 1p/19 co-deletion carried a mutation in IDH1 or IDH2. We present an algorithm based on stepwise analysis with initial immunohistochemistry for ATRX and IDH1R132H followed by 1p/19q analysis followed by IDH sequencing which reduces the number of molecular analyses and which has a far better association with patient outcome than WHO 2007.

Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications.

Hot spot mutations in the promoter region of telomerase reverse transcriptase (TERT) have recently been described in several human tumor entities. These mutations result in an upregulation of the telomerase complex activity and thus constitute a relevant mechanism for immortalization of tumor cells. Knowledge of the TERT promoter status in tumors is likely to be of interest for molecular classification and as a potential target for therapy. We, therefore, performed a systematic analysis of TERT promoter mutations in 1,515 tumors of the human nervous system and its coverings including 373 pediatric and 1,142 adult patients. We detected a total of 327 mutations. TERT promoter mutations were exceedingly rare in tumors typically encountered in pediatric patients. In entities typically encountered in adult patients TERT promoter mutations were strongly associated with older age (p < 0.0001). Highest mutation frequencies were detected in gliosarcomas (81 %), oligodendrogliomas (78 %), oligoastrocytomas (58 %), primary glioblastomas (54 %), and solitary fibrous tumors (50 %). Related to other molecular alterations, TERT promoter mutations were strongly associated with 1p/19q loss (p < 0.0001), but inversely associated with loss of ATRX expression (p < 0.0001) and IDH1/IDH2 mutations (p < 0.0001). TERT promoter mutations are typically found in adult patients and occur in a highly tumor typeassociated distribution. classification and as a potential target for therapy. We, therefore, performed a systematic analysis of TERT promoter mutations in 1515 tumors of the human nervous system and its coverings including 373 pediatric and 1142 adult patients. We detected a total of 327 mutations. TERT promoter mutations were exceedingly rare in tumors typically encountered in pediatric patients. In entities typically encountered in adult patients TERT promoter mutations were strongly associated with older age (p < 0.0001). Highest mutation frequencies were detected in gliosarcomas (81 %), oligodendrogliomas (78 %), oligoastrocytomas (58 %), primary glioblastomas (54 %) and solitary fibrous tumors (50 %).Related to other molecular alterations, TERT promoter mutations were strongly associated with 1p/19q loss (p < 0.0001), but inversely associated with loss of ATRX expression (p < 0.0001) and IDH1/IDH2

The World Health Organization (WHO) classification and grading system attempts to predict the clinical course of meningiomas based on morphological parameters. However, because of high interobserver variation of some criteria, more reliable prognostic markers are required. Here, we assessed the TERT promoter for mutations in the hotspot regions C228T and C250T in meningioma samples from 252 patients. Mutations were detected in 16 samples (6.4% across the cohort, 1.7%, 5.7%, and 20.0% of WHO grade I, II, and III cases, respectively). Data were analyzed by t test, Fisher's exact test, log-rank test, and Cox proportional hazard model. All statistical tests were two-sided. Within a mean follow-up time in surviving patients of 68.1 months, TERT promoter mutations were statistically significantly associated with shorter time to progression (P < .001). Median time to progression among mutant cases was 10.1 months compared with 179.0 months among wild-type cases. Our results indicate that the inclusion of molecular data (ie, analysis of TERT promoter status) into a histologically and genetically integrated classification and grading system for meningiomas increases prognostic power. Consequently, we propose to incorporate the assessment of TERT promoter status in upcoming grading schemes for meningioma.

Non-central nervous system hemangiopericytoma (HPC) and solitary fibrous tumor (SFT) are considered by pathologists as two variants of a single tumor entity now subsumed under the entity SFT. Recent detection of frequent NAB2-STAT6 fusions in both, HPC and SFT, provided additional support for this view. On the other hand, current neuropathological practice still distinguishes between HPC and SFT. The present study set out to identify genes involved in the formation of meningeal HPC. We performed exome sequencing and detected the NAB2-STAT6 fusion in DNA of 8/10 meningeal HPC thereby providing evidence of close relationship of these tumors with peripheral SFT. Due to the considerable effort required for exome sequencing, we sought to explore surrogate markers for the NAB2-STAT6 fusion protein. We adopted the Duolink proximity ligation assay and demonstrated the presence of NAB2-STAT6 fusion protein in 17/17 HPC and the absence in 15/15 meningiomas. More practical, presence of the NAB2-STAT6 fusion protein resulted in a strong nuclear signal in STAT6 immunohistochemistry. The nuclear reallocation of STAT6 was detected in 35/37 meningeal HPC and 25/25 meningeal SFT but not in 87 meningiomas representing the most important differential diagnosis. Tissues not harboring the NAB2-STAT6 fusion protein presented with nuclear expression of NAB2 and cytoplasmic expression of STAT6 proteins. In conclusion, we provide strong evidence for meningeal HPC and SFT to constitute variants of a single entity which is defined by NAB2-STAT6 fusion. In addition, we demonstrate that this fusion can be rapidly detected by STAT6 immunohistochemistry which shows a consistent nuclear reallocation. This immunohistochemical assay may prove valuable for the differentiation of HPC and SFT from other mesenchymal neoplasms.