A practical approach to the modern diagnosis and classification of T- and NK-cell lymphomas
- PMID: 38728419
- PMCID: PMC11830980
- DOI: 10.1182/blood.2023021786
A practical approach to the modern diagnosis and classification of T- and NK-cell lymphomas
Abstract
T- and natural killer (NK)-cell lymphomas are neoplasms derived from immature T cells (lymphoblastic lymphomas), or more commonly, from mature T and NK cells (peripheral T-cell lymphomas, PTCLs). PTCLs are rare but show marked biological and clinical diversity. They are usually aggressive and may present in lymph nodes, blood, bone marrow, or other organs. More than 30 T/NK-cell-derived neoplastic entities are recognized in the International Consensus Classification and the classification of the World Health Organization (fifth edition), both published in 2022, which integrate the most recent knowledge in hematology, immunology, pathology, and genetics. In both proposals, disease definition aims to integrate clinical features, etiology, implied cell of origin, morphology, phenotype, and genetic features into biologically and clinically relevant clinicopathologic entities. Cell derivation from innate immune cells or specific functional subsets of CD4+ T cells such as follicular helper T cells is a major determinant delineating entities. Accurate diagnosis of T/NK-cell lymphoma is essential for clinical management and mostly relies on tissue biopsies. Because the histological presentation may be heterogeneous and overlaps with that of many benign lymphoid proliferations and B-cell lymphomas, the diagnosis is often challenging. Disease location, morphology, and immunophenotyping remain the main features guiding the diagnosis, often complemented by genetic analysis including clonality and high-throughput sequencing mutational studies. This review provides a comprehensive overview of the classification and diagnosis of T-cell lymphoma in the context of current concepts and scientific knowledge.
© 2024 American Society of Hematology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Conflict of interest statement
Conflict-of-interest disclosure: L.d.L. had a consulting or advisory role for Abbvie, Lunaphore Technologies, Bayer, Blueprint Medicines, Novartis, and Roche (all institutional), and received travel grants from Roche. P.G. received research funding from Alderan, Innate Pharma, Takeda, and Sanofi; had a consulting or advisory role for Takeda and Gilead; and received travel grants from Roche. A.D. received research support from Roche and Astra-Zeneca.
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