{"title":"Updates on germline predisposition in pediatric hematologic malignancies: What is the role of flow cytometry?","authors":"Nadine Demko, Julia T. Geyer","doi":"10.1002/cyto.b.22192","DOIUrl":null,"url":null,"abstract":"<p>Hematologic neoplasms with germline predisposition have been increasingly recognized as a distinct category of tumors over the last few years. As such, this category was added to the World Health Organization (WHO) 4th edition as well as maintained in the WHO 5th edition and International Consensus Classification (ICC) 2022 classification systems. In practice, these tumors require a high index of suspicion and confirmation by molecular testing. Flow cytometry is a cost-effective diagnostic tool that is routinely performed on peripheral blood and bone marrow samples. In this review, we sought to summarize the current body of research correlating flow cytometric immunophenotype to assess its utility in diagnosis of and clinical decision making in germline hematologic neoplasms. We also illustrate these findings using cases mostly from our own institution. We review some of the more commonly mutated genes, including <i>CEBPA, DDX41, RUNX1, ANKRD26, GATA2</i>, Fanconi anemia, Noonan syndrome, and Down syndrome. We highlight that flow cytometry may have a role in the diagnosis (<i>GATA2</i>, Down syndrome) and screening (<i>CEBPA</i>) of some germline predisposition syndromes, although appears to show nonspecific findings in others (<i>DDX41, RUNX1</i>). In many of the others, such as <i>ANKRD26</i>, Fanconi anemia, and Noonan syndrome, further studies are needed to better understand whether specific flow cytometric patterns are observed. Ultimately, we conclude that further studies such as large case series and organized data pipelines are needed in most germline settings to better understand the flow cytometric immunophenotype of these neoplasms.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cyto.b.22192","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Hematologic neoplasms with germline predisposition have been increasingly recognized as a distinct category of tumors over the last few years. As such, this category was added to the World Health Organization (WHO) 4th edition as well as maintained in the WHO 5th edition and International Consensus Classification (ICC) 2022 classification systems. In practice, these tumors require a high index of suspicion and confirmation by molecular testing. Flow cytometry is a cost-effective diagnostic tool that is routinely performed on peripheral blood and bone marrow samples. In this review, we sought to summarize the current body of research correlating flow cytometric immunophenotype to assess its utility in diagnosis of and clinical decision making in germline hematologic neoplasms. We also illustrate these findings using cases mostly from our own institution. We review some of the more commonly mutated genes, including CEBPA, DDX41, RUNX1, ANKRD26, GATA2, Fanconi anemia, Noonan syndrome, and Down syndrome. We highlight that flow cytometry may have a role in the diagnosis (GATA2, Down syndrome) and screening (CEBPA) of some germline predisposition syndromes, although appears to show nonspecific findings in others (DDX41, RUNX1). In many of the others, such as ANKRD26, Fanconi anemia, and Noonan syndrome, further studies are needed to better understand whether specific flow cytometric patterns are observed. Ultimately, we conclude that further studies such as large case series and organized data pipelines are needed in most germline settings to better understand the flow cytometric immunophenotype of these neoplasms.