AUTHOR=Ke Yanhao , Zhou Fen 

TITLE=Biomarkers for predicting CAR-T cell therapy outcomes in B-cell acute lymphoblastic leukemia: a systematic review

JOURNAL=Frontiers in Immunology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1656108

DOI=10.3389/fimmu.2025.1656108

ISSN=1664-3224

ABSTRACT=IntroductionChimeric antigen receptor (CAR) T-cell therapy has revolutionized the treatment of relapsed/refractory B-cell acute lymphoblastic leukemia (B-ALL), yet challenges such as cytokine release syndrome (CRS), neurotoxicity (ICANS), and variable long-term efficacy persist. This systematic review evaluates the role of biomarkers in predicting CAR-T therapy outcomes, toxicity risks, and guiding personalized treatment strategies.MethodsFollowing PRISMA guidelines, we systematically searched PubMed, Web of Science, and Embase for studies published between 2018–2024. A total of 33 studies involving 2,095 patients were included in the analysis.ResultsKey findings identified tumor burden and minimal residual disease (MRD) as dual-predictive biomarkers. High tumor burden (≥40% blasts) correlated with reduced complete remission rates (87% vs. 100%) and increased CRS/ICANS risks, while MRD negativity (NGS threshold <10⁻⁶) predicted superior 2-year event-free survival (68% vs. 23%). CAR-T functional parameters, including PD-1/LAG-3 expression (>5.2% in CD4+ cells) and peak expansion kinetics, linked efficacy to toxicity trade-offs. Genetic biomarkers (IKZF1 mutations, complex karyotypes) and biochemical indicators (m-EASIX >6.2, ferritin ≥10,000 ng/mL) further stratified risks. Unidirectional efficacy biomarkers included T-cell subsets (e.g., CD8+ naive T cells) and B-cell aplasia, while IL-6 dynamics specifically predicted CRS severity.DiscussionDespite promising insights, heterogeneity in toxicity grading systems, inconsistent biomarker thresholds, and retrospective study designs limit clinical standardization. Future directions emphasize cytoreductive bridging therapies, biomarker-guided combinatorial approaches (e.g., MDM2 inhibitors for TP53 mutations), and multicenter validation of integrated predictive models to optimize personalized CAR-T therapy strategies.