2023CancersOpen access

Optimizing Molecular Minimal Residual Disease Analysis in Adult Acute Lymphoblastic Leukemia

Irene Della Starza, Lucia Anna De Novi, Loredana Elia, Vittorio Bellomarino, Marco Beldinanzi, Roberta Soscia, Deborah Cardinali, Sabina Chiaretti, Anna Guarini, Robin Foà

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Abstract

Minimal/measurable residual disease (MRD) evaluation has resulted in a fundamental instrument to guide patient management in acute lymphoblastic leukemia (ALL). From a methodological standpoint, MRD is defined as any approach aimed at detecting and possibly quantifying residual neoplastic cells beyond the sensitivity level of cytomorphology. The molecular methods to study MRD in ALL are polymerase chain reaction (PCR) amplification-based approaches and are the most standardized techniques. However, there are some limitations, and emerging technologies, such as digital droplet PCR (ddPCR) and next-generation sequencing (NGS), seem to have advantages that could improve MRD analysis in ALL patients. Furthermore, other blood components, namely cell-free DNA (cfDNA), appear promising and are also being investigated for their potential role in monitoring tumor burden and response to treatment in hematologic malignancies. Based on the review of the literature and on our own data, we hereby discuss how emerging molecular technologies are helping to refine the molecular monitoring of MRD in ALL and may help to overcome some of the limitations of standard approaches, providing a benefit for the care of patients.

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Minimal/measurable residual disease (MRD) evaluation has resulted in a fundamental instrument to guide patient management in acute lymphoblastic leukemia (ALL). From a methodological standpoint, MRD is defined as any approach aimed at detecting and possibly quantifying residual neoplastic cells beyond the sensitivity level of cytomorphology. The molecular methods to study MRD in ALL are polymerase chain reaction (PCR) amplification-based approaches and are the most standardized techniques. However, there are some limitations, and emerging technologies, such as digital droplet PCR (ddPCR) and next-generation sequencing (NGS), seem to have advantages that could improve MRD analysis in ALL patients. Furthermore, other blood components, namely cell-free DNA (cfDNA), appear promising and are also being investigated for their potential role in monitoring tumor burden and response to treatment in hematologic malignancies. Based on the review of the literature and on our own data, we hereby discuss how emerging molecular technologies are helping to refine the molecular monitoring of MRD in ALL and may help to overcome some of the limitations of standard approaches, providing a benefit for the care of patients.

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Available abstract

Minimal/measurable residual disease (MRD) evaluation has resulted in a fundamental instrument to guide patient management in acute lymphoblastic leukemia (ALL). From a methodological standpoint, MRD is defined as any approach aimed at detecting and possibly quantifying residual neoplastic cells beyond the sensitivity level of cytomorphology. The molecular methods to study MRD in ALL are polymerase chain reaction (PCR) amplification-based approaches and are the most standardized techniques. However, there are some limitations, and emerging technologies, such as digital droplet PCR (ddPCR) and next-generation sequencing (NGS), seem to have advantages that could improve MRD analysis in ALL patients. Furthermore, other blood components, namely cell-free DNA (cfDNA), appear promising and are also being investigated for their potential role in monitoring tumor burden and response to treatment in hematologic malignancies. Based on the review of the literature and on our own data, we hereby discuss how emerging molecular technologies are helping to refine the molecular monitoring of MRD in ALL and may help to overcome some of the limitations of standard approaches, providing a benefit for the care of patients.

Key concepts: Minimal residual disease, Digital polymerase chain reaction, Medicine, Polymerase chain reaction, Lymphoblastic Leukemia, Computational biology, Molecular diagnostics, Oncology

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