: Adult acute lymphoblastic leukemia (ALL) is a highly heterogeneous hematologic malignancy where treatment response and relapse risk do not exclusively rely on the identification of genetic lesions but also on dynamic biological states sustained by specific transcriptional and epigenetic programs. Although the integrated application of multi-omics approaches has significantly expanded our knowledge of oncogenic dependencies, cellular plasticity, and mechanisms of therapeutic resistance, its systematic translation into the clinical practice of adult ALL is yet to become a reality. The aim of this review is to provide a critical and focused synthesis on how the integration of genomics, transcriptomics, and epigenetics enables the interpretation of disease biological behaviors and may guide personalized therapeutic strategies while simultaneously addressing the major limitations that hinder clinical implementation. Genomics allows for the identification of driver events and pharmacologically actionable vulnerabilities, whereas transcriptomics, including single-cell analyses, reveals functional states associated with clonal persistence, glucocorticoid resistance, and therapeutic adaptation, even in the absence of new mutations. In parallel, epigenetic signatures emerge as key elements in stabilizing oncogenic programs and resistant phenotypes, contributing to the biological plasticity of leukemic cells and representing potentially reversible therapeutic targets. Taken together, multi-omics signatures provide an integrated functional readout of adult ALL and support a dynamic precision-medicine model. However, adaptive therapeutic decisions aimed at relapse prevention require the full integration of these approaches through standardized strategies, longitudinal studies, and a sustainable implementation of molecular profiling and minimal residual disease monitoring.

Multi-Omics Applications in Adult Acute Lymphoblastic Leukemia: From Biological Mechanisms to Precision Therapies

Marco Rossi
2026-01-01

Abstract

: Adult acute lymphoblastic leukemia (ALL) is a highly heterogeneous hematologic malignancy where treatment response and relapse risk do not exclusively rely on the identification of genetic lesions but also on dynamic biological states sustained by specific transcriptional and epigenetic programs. Although the integrated application of multi-omics approaches has significantly expanded our knowledge of oncogenic dependencies, cellular plasticity, and mechanisms of therapeutic resistance, its systematic translation into the clinical practice of adult ALL is yet to become a reality. The aim of this review is to provide a critical and focused synthesis on how the integration of genomics, transcriptomics, and epigenetics enables the interpretation of disease biological behaviors and may guide personalized therapeutic strategies while simultaneously addressing the major limitations that hinder clinical implementation. Genomics allows for the identification of driver events and pharmacologically actionable vulnerabilities, whereas transcriptomics, including single-cell analyses, reveals functional states associated with clonal persistence, glucocorticoid resistance, and therapeutic adaptation, even in the absence of new mutations. In parallel, epigenetic signatures emerge as key elements in stabilizing oncogenic programs and resistant phenotypes, contributing to the biological plasticity of leukemic cells and representing potentially reversible therapeutic targets. Taken together, multi-omics signatures provide an integrated functional readout of adult ALL and support a dynamic precision-medicine model. However, adaptive therapeutic decisions aimed at relapse prevention require the full integration of these approaches through standardized strategies, longitudinal studies, and a sustainable implementation of molecular profiling and minimal residual disease monitoring.
2026
adult acute lymphoblastic leukemia
epigenetic regulation
genomic and transcriptomic profiling
multi-omics integration
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12317/117001
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