B-cell Acute Lymphoblastic Leukemia (B-ALL), the most common pediatric cancer, presents critical challenges in clinical management, particularly in identifying patients at high risk of mortality. Although the bone marrow microenvironment plays a crucial role in disease progression, a comprehensive understanding of the immunological landscape and its predictive potential remains an unmet need.

Our study aimed to validate a panel of immune signatures as a novel and robust tool for risk stratification in pediatric B- ALL.

We performed a longitudinal analysis by profiling 48 soluble immune mediators in the Peripheral Blood (PB) and Bone Marrow (BM) of 36 pediatric B-ALL patients, of whom 25 completed remission chemotherapy (B-ALL RG) and 11 died during induction therapy (B-ALL DG), and 25 healthy controls. Samples were collected at Diagnosis (D0) and at three time points during remission chemotherapy (D15, D35, and D84). We utilized multiplex assays and a decision-tree approach to identify specific mediator panels that predict patient mortality.

At D0, we identified a strongly exacerbated systemic immune profile that robustly predicted subsequent mortality. This key finding establishes the prognostic value of immune signatures, with highly accurate predictive panels composed of specific mediators. The panel from PB, including CCL5, IL-6, CXCL9, and IL-2Rα, predicted mortality with exceptional accuracy (AUC=0.996). Similarly, a panel from BM (CXCL12, CCL4) also demonstrated high predictive power (AUC = 0.900). These immune signatures were more than isolated events; they represented a consistent prognostic signal throughout the patient's treatment.

In summary, our data provide strong evidence that specific immune signatures at D0 can serve as a powerful new prognostic tool. We found that the immune profile is not fully re-established following chemotherapy, highlighting persistent dysregulations. The identification of these robust, high-accuracy biomarker panels offers a practical guide for hematologists, enabling more precise risk stratification and paving the way for personalized therapeutic interventions tailored to children with B-ALL.