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Validation of Whole Genome Methylation Profiling Classifier for Central Nervous System Tumors

ABSTRACT: Validation of Whole Genome Methylation Profiling Classifier for Central Nervous System Tumors

PROVIDER: PRJNA817192 | ENA |

REPOSITORIES: ENA

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Validation of Whole Genome Methylation Profiling Classifier for Central Nervous System Tumors

Project description:The 2021 WHO Classification of Tumors of the Central Nervous System includes several tumor types and subtypes for which the diagnosis is at least partially reliant on utilization of whole genome methylation profiling. The current approach to array DNA methylation profiling utilizes a reference library of tumor DNA methylation data, and a machine learning-based tumor classifier. This approach was pioneered and popularized by the German Cancer Research Network (DKFZ) and University Hospital Heidelberg. This research group has kindly made their classifier for central nervous system tumors freely available as a research tool via a web-based portal. However, this classifier is not maintained in a clinical testing environment. Therefore, we validated our own DNA methylation-based classifier of central nervous system tumors. We validated our classifier using the same training and validation datasets as the DKFZ group. In addition, we performed a validation of samples tested in our own laboratory and compared the performance of both classifiers. Using the validation data set, our classifier’s performance showed high concordance (92%) and comparable accuracy (specificity 94.0% v. 84.9% for DKFZ, sensitivity 88.6% v. 94.7% for DKFZ). Receiver operator curve showed areas under the curve of 0.964 v. 0.966 for NM and DKFZ classifiers, respectively. Our classifier performed comparably well with samples tested in our own laboratory and is currently offered for clinical testing.

2022-03-19 | GSE198855 | GEO

DNA methylation-based classification of human central nervous system tumors [validation set]

Project description:DNA methylation-based classification of human central nervous system tumors [validation set]

| PRJNA430724 | ENA

DNA methylation-based classification of human central nervous system tumors [validation set]

Project description:Background: Modern neuropathology is challenged by an increasing number of clinically-relevant CNS tumor subgroups that require assessment of a multitude of molecular markers for classification, as well a highly trained medical staff. Failure to meet this challenge leads to tumor misclassification, which can have severe consequences for affected patients. Methods: We compiled a cohort of genome-wide DNA methylation profiles of 2,682 tumors from 82 histologically and/or molecularly distinct CNS tumor classes across all ages and histologies that served as reference for a Random Forest-based diagnostic classifier. This classifier was used to prospectively investigate a further 1,104 CNS tumor samples in order to determine its clinical utility. Results: The classifier was able to reliably assign tumor samples to a given diagnostic category with a misclassification rate of less than 2%. The system functioned robustly across laboratories and using different DNA methylation profiling techniques. Prospective application to clinical samples resulted in a reclassification of 12% of tumors compared with standard practice alone. A further 12% could not be classified by methylation profiling – this subset was highly enriched for unusual syndrome-associated tumors and likely novel entities. Conclusion: This study represents a proof-of-concept for the application of machine learning approaches in molecular diagnostics using a single, easy-to-use assay. The reference cohort and Random Forest-based classifier are available online as a valuable community tool for improving precision in brain tumor diagnostics. We expect that approaches similar to the one presented herein will rapidly restructure diagnostic practice in neurooncology and across tumor pathology.

2018-01-18 | GSE109379 | GEO

Efavirenz Central Nervous System Side Effects

Project description:Efavirenz Central Nervous System Side Effects

| PRJNA354669 | ENA

Iodine I 131 Monoclonal Antibody 3F8 in Treating Patients With Central Nervous System Cancer or Leptomeningeal Cancer

Project description:RATIONALE: Radiolabeled monoclonal antibodies, such as iodine I 131 monoclonal antibody 3F8, can find tumor cells and carry tumor-killing substances to them without harming normal cells. This may be an effective treatment for central nervous system cancer or leptomeningeal metastases. PURPOSE: This phase II trial is studying the side effects and how well iodine I 131 monoclonal antibody 3F8 works in treating patients with central nervous system cancer or leptomeningeal cancer.

| 2037925 | ecrin-mdr-crc

DNA methylation-based classification of human central nervous system tumors

Project description:DNA methylation-based classification of human central nervous system tumors

| PRJNA430715 | ENA

Genomic aberrations in primary central nervous system lymphoma (PCNSL)

Project description:Genomic aberrations in primary central nervous system lymphoma (PCNSL). Two-condition experiment, PCNSLs vs. healthy men. Biological replicates: 12 tumors replicates, 13 peripheral blood replicates.

2010-11-13 | E-GEOD-25298 | biostudies-arrayexpress

Genomic profiling combined with gene expression profiling in primary central nervous system lymphoma

Project description:This SuperSeries is composed of the following subset Series: GSE25297: Genome-wide gene expression comparison (primary central nervous system lymphoma (PCNSL) vs normal lymph node) GSE25298: Genomic aberrations in primary central nervous system lymphoma (PCNSL) Refer to individual Series

2010-11-13 | E-GEOD-25299 | biostudies-arrayexpress

Genomic aberrations in primary central nervous system lymphoma (PCNSL)

Project description:Genomic aberrations in primary central nervous system lymphoma (PCNSL).

2010-11-13 | GSE25298 | GEO

Astrocyte-Oligodendrocyte interaction regulates central nervous system regeneration

Project description:Failed regeneration of myelin around neuronal axons following central nervous system damage contributes to nerve dysfunction and clinical decline in various neurological conditions, for which there is an unmet therapeutic demand. Here, we show that interaction between glial cells – astrocytes and mature myelin-forming oligodendrocytes – is a critical determinant of remyelination. Using in vivo/ ex vivo/ in vitro rodent models and human brain lesion analyses, we discover that astrocytes support the survival of regenerating oligodendrocytes, via downregulation of the Nrf2 pathway associated with increased astrocytic cholesterol biosynthesis pathway activation. Remyelination fails following sustained astrocytic Nrf2 activation in focally-lesioned mice yet is restored by either cholesterol biosynthesis/efflux stimulation, or Nrf2 inhibition using the existing therapeutic Luteolin. We identify that astrocyte-oligodendrocyte interaction regulates remyelination, and reveal a drug strategy for central nervous system regeneration centred on targeting this interaction.

2023-05-17 | PXD041850 | Pride

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