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Immunol."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>Chimeric 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Following PRISMA guidelines, we systematically searched PubMed, Web of Science, and Embase for studies published between 2018\u20132024. A total of 33 studies involving 2,095 patients were included in the analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Key findings identified tumor burden and minimal residual disease (MRD) as dual-predictive biomarkers. High tumor burden (\u226540% blasts) correlated with reduced complete remission rates (87% vs. 100%) and increased CRS\/ICANS risks, while MRD negativity (NGS threshold &amp;lt;10\u207b\u2076) predicted superior 2-year event-free survival (68% vs. 23%). CAR-T functional parameters, including PD-1\/LAG-3 expression (&amp;gt;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 &amp;gt;6.2, ferritin \u226510,000 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>Despite 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.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fimmu.2025.1656108","type":"journal-article","created":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T05:32:02Z","timestamp":1760592722000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Biomarkers for predicting CAR-T cell therapy outcomes in B-cell acute lymphoblastic leukemia: a systematic review"],"prefix":"10.3389","volume":"16","author":[{"given":"Yanhao","family":"Ke","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fen","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,10,16]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.19.01086","article-title":"Outcome in children with standard-risk B-cell acute lymphoblastic leukemia: results of children\u2019s oncology group trial AALL0331","volume":"38","author":"Maloney","year":"2019","journal-title":"J Clin Oncol"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra1400972","article-title":"Acute lymphoblastic leukemia in children. 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