Philadelphia Negative MPNs, MDS/MPNs and MDS in the Context of Recent WHO Changes and Inclusion of Molecular Signatures into Prognostic Tools: A Single Centre Experience
{"title":"Philadelphia Negative MPNs, MDS/MPNs and MDS in the Context of Recent WHO Changes and Inclusion of Molecular Signatures into Prognostic Tools: A Single Centre Experience","authors":"N. Singh, Sujeet Kumar, Avinash Gupta","doi":"10.31557/apjcb.2023.8.1.5-11","DOIUrl":null,"url":null,"abstract":"Introduction: The fifth edition of WHO classification of myeloid neoplasms has introduced major changes in the defining criteria and grouping of MDS, MDS/MPNs and MPNs. Recently published literature has also cited the importance of new risk-scoring systems by integrating genomic profiling with hematologic and cytogenetic characteristics, in order to improve the prognostic discrimination of patients and represents a valuable tool for clinical decision-making. Aim: To find out the prevalence and molecular spectrum of Philadelphia-negative MPNs, MDS/MPNs and MDS in our subset of patients and henceforth to evaluate the impact on diagnosis, risk stratification and treatment decision-making of patients. Methods: This retrospective observational study included all newly diagnosed patients of non-Philadelphia positive MPNs, MDS, and MPN/MDS, in whom complete baseline diagnostic work-up was available including complete blood counts, bone marrow morphology and biopsy, cytogenetic and molecular studies. Results: The most frequent entities in our cohort of patients were primary myelofibrosis (32.8%), MDS (32.8%) and CMML (16.4%). In PIMF, 50% patients were JAK2- mutated while 30% were triple negative (JAK-, CALR-, MPL-). The commoner epigenetic modifiers among MPNs were ASXL1, TET2 and IDH2. The predominant CMML molecular signatures in our patients were NRAS, U2AF2, SETBP1, ASXL and SH2B3. There was no significant effect of WHO changes and recently introduced molecular scoring models on the diagnosis and risk stratification of all these MPN and MDS/MPN patients However, in MDS and PIMF patients, recent WHO subtyping plus IPSS-M & GIPSS scoring respectively enabled refining of risk groups. Conclusion: Molecular profiling helps in better risk stratification of patients across all groups as well as in making therapeutic decisions. However, in resource constrained settings, it is not always possible to stratify patients on the basis of molecular signatures and hence, scoring models such as DIPSS and IPSS-R holds their ground strongly even today for offering appropriate therapy to patients without compromising on quality care. \n ","PeriodicalId":8848,"journal":{"name":"Asian Pacific Journal of Cancer Biology","volume":"30 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Pacific Journal of Cancer Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31557/apjcb.2023.8.1.5-11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: The fifth edition of WHO classification of myeloid neoplasms has introduced major changes in the defining criteria and grouping of MDS, MDS/MPNs and MPNs. Recently published literature has also cited the importance of new risk-scoring systems by integrating genomic profiling with hematologic and cytogenetic characteristics, in order to improve the prognostic discrimination of patients and represents a valuable tool for clinical decision-making. Aim: To find out the prevalence and molecular spectrum of Philadelphia-negative MPNs, MDS/MPNs and MDS in our subset of patients and henceforth to evaluate the impact on diagnosis, risk stratification and treatment decision-making of patients. Methods: This retrospective observational study included all newly diagnosed patients of non-Philadelphia positive MPNs, MDS, and MPN/MDS, in whom complete baseline diagnostic work-up was available including complete blood counts, bone marrow morphology and biopsy, cytogenetic and molecular studies. Results: The most frequent entities in our cohort of patients were primary myelofibrosis (32.8%), MDS (32.8%) and CMML (16.4%). In PIMF, 50% patients were JAK2- mutated while 30% were triple negative (JAK-, CALR-, MPL-). The commoner epigenetic modifiers among MPNs were ASXL1, TET2 and IDH2. The predominant CMML molecular signatures in our patients were NRAS, U2AF2, SETBP1, ASXL and SH2B3. There was no significant effect of WHO changes and recently introduced molecular scoring models on the diagnosis and risk stratification of all these MPN and MDS/MPN patients However, in MDS and PIMF patients, recent WHO subtyping plus IPSS-M & GIPSS scoring respectively enabled refining of risk groups. Conclusion: Molecular profiling helps in better risk stratification of patients across all groups as well as in making therapeutic decisions. However, in resource constrained settings, it is not always possible to stratify patients on the basis of molecular signatures and hence, scoring models such as DIPSS and IPSS-R holds their ground strongly even today for offering appropriate therapy to patients without compromising on quality care.