Jyotsna Singh, Saumya Sahu, Trishala Mohan, Swati Mahajan, Mehar C Sharma, Chitra Sarkar, Vaishali Suri
{"title":"Current status of DNA methylation profiling in neuro-oncology as a diagnostic support tool: A review.","authors":"Jyotsna Singh, Saumya Sahu, Trishala Mohan, Swati Mahajan, Mehar C Sharma, Chitra Sarkar, Vaishali Suri","doi":"10.1093/nop/npad040","DOIUrl":null,"url":null,"abstract":"<p><p>Over the last 2 decades, high throughput genome-wide molecular profiling has revealed characteristic genetic and epigenetic alterations associated with different types of central nervous system (CNS) tumors. DNA methylation profiling has emerged as an important molecular platform for CNS tumor classification with improved diagnostic accuracy and patient risk stratification in comparison to the standard of care histopathological analysis and any single molecular tests. The emergence of DNA methylation arrays have also played a crucial role in refining existing types and the discovery of new tumor types or subtypes. The adoption of methylation data into neuro-oncology has been greatly aided by the development of a freely accessible machine learning-based classifier. In this review, we discuss methylation workflow, address the utility of DNA methylation profiling in CNS tumors in a routine diagnostic setting, and provide an overview of the methylation-based tumor types and new types or subtypes identified with this platform.</p>","PeriodicalId":199,"journal":{"name":"Journal of Polymer Science Part A: Polymer Chemistry","volume":"25 108","pages":"518-526"},"PeriodicalIF":2.7020,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10666812/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Polymer Science Part A: Polymer Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/nop/npad040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/12/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Materials Science","Score":null,"Total":0}
引用次数: 0
Abstract
Over the last 2 decades, high throughput genome-wide molecular profiling has revealed characteristic genetic and epigenetic alterations associated with different types of central nervous system (CNS) tumors. DNA methylation profiling has emerged as an important molecular platform for CNS tumor classification with improved diagnostic accuracy and patient risk stratification in comparison to the standard of care histopathological analysis and any single molecular tests. The emergence of DNA methylation arrays have also played a crucial role in refining existing types and the discovery of new tumor types or subtypes. The adoption of methylation data into neuro-oncology has been greatly aided by the development of a freely accessible machine learning-based classifier. In this review, we discuss methylation workflow, address the utility of DNA methylation profiling in CNS tumors in a routine diagnostic setting, and provide an overview of the methylation-based tumor types and new types or subtypes identified with this platform.
期刊介绍:
Part A: Polymer Chemistry is devoted to studies in fundamental organic polymer chemistry and physical organic chemistry. This includes all related topics (such as organic, bioorganic, bioinorganic and biological chemistry of monomers, polymers, oligomers and model compounds, inorganic and organometallic chemistry for catalysts, mechanistic studies, supramolecular chemistry aspects relevant to polymer...