Myeloid/lymphoid neoplasms with eosinophilia and tyrosine kinase fusion genes: A workshop report with focus on novel entities and a literature review including paediatric cases

Rare Hematologic Malignancies and Pre-Leukemic Entities in Children and Adolescents Young Adults

There are a variety of rare hematologic malignancies and germline predispositions syndromes that occur in children and adolescent young adults (AYAs). These entities are important to recognize, as an accurate diagnosis is essential for risk assessment, prognostication, and treatment. This descriptive review summarizes rare hematologic malignancies, myelodysplastic neoplasms, and germline predispositions syndromes that occur in children and AYAs. We discuss the unique biology, characteristic genomic aberrations, rare presentations, diagnostic challenges, novel treatments, and outcomes associated with these rare entities.

Hematological Neoplasms with Eosinophilia

Eosinophils in peripheral blood account for 0.3-5% of leukocytes, which is equivalent to 0.05-0.5 × 109/L. A count above 0.5 × 109/L is considered to indicate eosinophilia, while a count equal to or above 1.5 × 109/L is defined as hypereosinophilia. In bone marrow aspirate, eosinophilia is considered when eosinophils make up more than 6% of the total nuclear cells. In daily clinical practice, the most common causes of reactive eosinophilia are non-hematologic, whether they are non-neoplastic (allergic diseases, drugs, infections, or immunological diseases) or neoplastic (solid tumors). Eosinophilia that is associated with a hematological malignancy may be reactive or secondary to the production of eosinophilopoietic cytokines, and this is mainly seen in lymphoid neoplasms (Hodgkin lymphoma, mature T-cell neoplasms, lymphocytic variant of hypereosinophilic syndrome, and B-acute lymphoblastic leukemia/lymphoma). Eosinophilia that is associated with a hematological malignancy may also be neoplastic or primary, derived from the malignant clone, usually in myeloid neoplasms or with its origin in stem cells (myeloid/lymphoid neoplasms with eosinophilia and tyrosine kinase gene fusions, acute myeloid leukemia with core binding factor translocations, mastocytosis, myeloproliferative neoplasms, myelodysplastic/myeloproliferative neoplasms, and myelodysplastic neoplasms). There are no concrete data in standardized cytological and cytometric procedures that could predict whether eosinophilia is reactive or clonal. The verification is usually indirect, based on the categorization of the accompanying hematologic malignancy. This review focuses on the broad differential diagnosis of hematological malignancies with eosinophilia.

The role of flow cytometry in the classification of myeloid disorders

The World Health Organization classification (WHO-HAEM5) and the International Consensus Classification (ICC 2022) of myeloid neoplasms are based on the integration of clinical, morphologic, immunophenotypic, and genomic data. Flow cytometric immunophenotyping (FCIP) allows the identification, enumeration, and characterization of hematopoietic cells, and is therefore a powerful tool in the diagnosis, classification, and monitoring of hematological neoplasms. The vast majority of flow cytometry (FCM) studies in chronic myeloid neoplasms focus on its role in myelodysplastic neoplasms (MDS). FCM can also be helpful for the assessment of myeloproliferative neoplasms (MPN) and MDS/MPN, including the early detection of evolving myeloid or lymphoid blast crisis and the characterization of monocytic subsets. The classification of acute myeloid leukemia (AML) is primarily based on cytogenetic and molecular findings; however, FCIP is needed for subclassification of AML, not otherwise specified (NOS; ICC)/AML defined by differentiation (WHO-HAEM5). The main role of FCM in AML remains in making a rapid diagnosis and as a tool for measurable residual disease monitoring. Machine learning and artificial intelligence approaches can be used to analyze and classify FCM data. This article, based on an invited lecture at the 106th Annual Meeting of the German Society of Pathology in 2023, reviews the role of FCM in the classification of myeloid neoplasms, including recent publications on the application of artificial intelligence.