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From Cell Lines to Avatars: Charting the Future of Preclinical Modeling in T-Cell Malignancies.

Cells 2026 Vol.15(4)

Piccaluga PP, Cimmino L, Tsekhovska V, Cimatti P, Innocenti C, Seidenari S, Calafato G, Di Paola FJ, Tallini G

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T-cell malignancies represent a complex spectrum of clinically and biologically heterogeneous diseases.

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BibTeX ↓ RIS ↓
APA Piccaluga PP, Cimmino L, et al. (2026). From Cell Lines to Avatars: Charting the Future of Preclinical Modeling in T-Cell Malignancies.. Cells, 15(4). https://doi.org/10.3390/cells15040368
MLA Piccaluga PP, et al.. "From Cell Lines to Avatars: Charting the Future of Preclinical Modeling in T-Cell Malignancies.." Cells, vol. 15, no. 4, 2026.
PMID 41744811

Abstract

T-cell malignancies represent a complex spectrum of clinically and biologically heterogeneous diseases. Effective translational research and drug development are critically dependent on preclinical models that faithfully recapitulate this diversity. This review analyzes the current preclinical landscape, identifying a profound disparity between the clinical spectrum of T-cell neoplasms and the available in vitro tools. We demonstrate that the existing armamentarium of cell lines is heavily skewed, with an abundance of models for T-cell lymphoblastic leukemia/lymphoma (T-ALL), cutaneous T-cell lymphoma (CTCL), and anaplastic large cell lymphoma (ALCL). This skew is a direct result of a biological selection bias, as these entities are often driven by potent, TME-independent oncogenes (e.g., mutations, fusions) conducive to immortalization. Conversely, the majority of peripheral T-cell lymphoma (PTCL) subtypes, which are frequently TME-dependent and clinically aggressive, remain "preclinical orphans" with few or no authenticated models. This "preclinical void" constitutes a major bottleneck, impeding mechanistic studies and therapeutic progress. We discuss the limitations of 2D cultures and highlight the necessity of adopting advanced platforms, such as patient-derived xenografts (PDX) and 3D organoid systems. These "avatar" models preserve vital tumor heterogeneity and microenvironmental context, offering superior predictive value. The systematic development and integration of these next-generation models are essential to bridge the translational gap and advance precision medicine for all patients with T-cell malignancies.