Toggle Main Menu Toggle Search

Open Access padlockePrints

Underlying biology, challenges and emergent concepts in the treatment of relapsed and refractory pediatric T-cell acute lymphoblastic leukemia

Lookup NU author(s): Dr Frederik van DelftORCiD

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

© The Author(s), under exclusive licence to Springer Nature Limited 2025.Relapsed and refractory disease in children with T-cell acute lymphoblastic leukemia (R/R T-ALL) remains a major clinical challenge. Outcomes for children who relapse or exhibit resistance to initial treatments are dismal, with survival rates frequently below 25% despite aggressive therapy. To minimize toxicities and improve outcomes, individualized precision medicine approaches targeting the underlying biology of R/R T-ALL are especially important, considering that T-ALL is characterized by genetic, epigenetic and posttranscriptional heterogeneity, and organ and niche specificities (e.g. the central nervous system), all of which underlie disease progression and therapy resistance. Here, we summarize the current understanding of the complexity of pediatric T-ALL biology and how such knowledge may be clinically leveraged, emphasizing the need for innovative therapeutic routes to improve outcomes for children with R/R T-ALL. Emerging approaches that hold promise or show palpable results include proteasome inhibitors, BCL-2 antagonists, and JAK (for JAK- and IL-7R-driven cases), ABL and SRC family tyrosine kinase (for LCK-activated cases), MEK or PI3K-mTOR inhibitors. MYC-targeting agents, DNA demethylating agents, histone deacetylase inhibitors, splicing modulators, or drugs exploring T-ALL metabolic vulnerabilities, are other examples for potential pharmacological intervention. Immunotherapies, particularly CAR T-cell products targeting CD7 and other markers, but also biologics (e.g. targeting CD38), are under development and increasing interest. These agents should be rationally integrated into precision medicine combination therapies informed by genetic, epigenetic, and posttranscriptional insights that will be essential to refine risk stratification and minimize the risk of resistance. Novel strategies leveraging artificial intelligence and machine learning could accelerate discovery and optimize treatment frameworks.


Publication metadata

Author(s): Amaral P, Christie R, Gresham DOF, Lucas EJM, Xu LK, Behrmann L, Bond J, Degerman S, van Delft FW, Goossens S, Hagleitner M, Halsey C, Jones N, Lammens T, van Leeuwen FN, Mansour MR, Ntziachristos P, O'Connor D, Barata JT

Publication type: Review

Publication status: Published

Journal: Leukemia

Year: 2025

Pages: epub ahead of print

Online publication date: 14/08/2025

Acceptance date: 21/07/2025

ISSN (print): 0887-6924

ISSN (electronic): 1476-5551

Publisher: Springer Nature

URL: https://doi.org/10.1038/s41375-025-02723-2

DOI: 10.1038/s41375-025-02723-2


Share