Genetic studies of haematological cancers have pointed out the heterogeneity of leukaemia in its different subpopulations, with distinct mutations and characteristics, impacting the treatment response. Next-generation sequencing (NGS) and genome-wide analyses, as well as single-cell technologies, have offered unprecedented insights into the clonal heterogeneity within the same tumour. A key component of this heterogeneity that remains unexplored is the intracellular metabolome, a dynamic network that determines cell functions, signalling, epigenome regulation, immunity and inflammation. Understanding the metabolic diversities among cancer cells and their surrounding environments is therefore essential in unravelling the complexities of leukaemia and improving therapeutic strategies. Here, we describe the currently available methodologies and approaches to addressing the dynamic heterogeneity of leukaemia progression. In the second section, we focus on metabolic leukaemic vulnerabilities in acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL). Lastly, we provide a comprehensive overview of the most interesting clinical trials designed to target these metabolic dependencies, highlighting their potential to advance therapeutic strategies in leukaemia treatment. The integration of multi-omics data for cancer identification with the metabolic states of tumour cells will enable a comprehensive “micro-to-macro” approach for the refinement of clinical practices and delivery of personalised therapies.

Capelletti, M., Montini, O., Ruini, E., Tettamanti, S., Savino, A., Sarno, J. (2025). Unlocking the Heterogeneity in Acute Leukaemia: Dissection of Clonal Architecture and Metabolic Properties for Clinical Interventions. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 26(1) [10.3390/ijms26010045].

Unlocking the Heterogeneity in Acute Leukaemia: Dissection of Clonal Architecture and Metabolic Properties for Clinical Interventions

Capelletti, Martina Maria
Co-primo
;
Montini, Orsola
Co-primo
;
Tettamanti, Sarah
;
Savino, Angela Maria
Co-ultimo
;
Sarno, Jolanda
Co-ultimo
2025

Abstract

Genetic studies of haematological cancers have pointed out the heterogeneity of leukaemia in its different subpopulations, with distinct mutations and characteristics, impacting the treatment response. Next-generation sequencing (NGS) and genome-wide analyses, as well as single-cell technologies, have offered unprecedented insights into the clonal heterogeneity within the same tumour. A key component of this heterogeneity that remains unexplored is the intracellular metabolome, a dynamic network that determines cell functions, signalling, epigenome regulation, immunity and inflammation. Understanding the metabolic diversities among cancer cells and their surrounding environments is therefore essential in unravelling the complexities of leukaemia and improving therapeutic strategies. Here, we describe the currently available methodologies and approaches to addressing the dynamic heterogeneity of leukaemia progression. In the second section, we focus on metabolic leukaemic vulnerabilities in acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL). Lastly, we provide a comprehensive overview of the most interesting clinical trials designed to target these metabolic dependencies, highlighting their potential to advance therapeutic strategies in leukaemia treatment. The integration of multi-omics data for cancer identification with the metabolic states of tumour cells will enable a comprehensive “micro-to-macro” approach for the refinement of clinical practices and delivery of personalised therapies.
Articolo in rivista - Review Essay
acute leukaemia; intratumour heterogeneity; metabolism; single-cell technologies;
English
24-dic-2024
2025
26
1
45
open
Capelletti, M., Montini, O., Ruini, E., Tettamanti, S., Savino, A., Sarno, J. (2025). Unlocking the Heterogeneity in Acute Leukaemia: Dissection of Clonal Architecture and Metabolic Properties for Clinical Interventions. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 26(1) [10.3390/ijms26010045].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/535421
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