Multiple myeloma (MM) is one of the most common hematological malignancies and remains incurable. However, the survival of multiple myeloma patients has significantly increased due to the implementation of novel therapies along with autologous stem cell transplantation, changing the natural history of the disease. Consequently, there is an unmet need for more sensitive response assessment techniques capable of quantifying minimal tumor burden to identify patients at higher risk of early relapse. Multiparameter flow cytometry (MFC) is an essential tool for diagnosing and monitoring patients with various hematological conditions and has recently gained prominence in identifying, characterizing, and monitoring malignant plasma cells. The implementation of Next-Generation Flow (NGF) by EuroFlow aims to overcome the pitfalls of conventional MFC, including lack of standardization and lower sensitivity, by offering standardized and optimized protocols for evaluating response depth. Both MFC and NGF have wide-ranging applications in MM for diagnosis and measurable residual disease (MRD) monitoring. Plasma cell identification and clonality evaluation through MFC and NGF assist in diagnostic workup and are routinely used to assess therapeutic response through MRD analysis. Additionally, flow cytometry is applied for circulating tumor plasma cell (CTPC) enumeration, which has demonstrated significant prognostic value. Immune composition studies through MFC may provide better understanding of disease biology. Furthermore, MFC provides additional information about other bone marrow cell populations, assessing cellularity, immunophenotypic characteristics of plasma cells, and possible hemodilution. This review explores the applications of MFC and NGF in MM, highlighting their roles in diagnosis, response assessment, and prognosis. Beyond their established use in MRD monitoring, flow cytometry-derived immunophenotypic profiles show strong potential as cost-effective prognostic tools. We advocate for future studies to validate and integrate these markers into risk stratification models, complementing cytogenetic analyses and guiding individualized treatment strategies.

Acute myeloid leukemia (AML) continues to pose significant therapeutic challenges, with high relapse rates driven largely by leukemic stem cells (LSCs), a rare, therapy-resistant population with self-renewal capacity, niche adaptation, and the ability to re-initiate disease. In this state-of-the-art review, we synthesize recent advances in LSC biology, addressing (i) how LSCs differ functionally and phenotypically from normal hematopoietic stem cells (HSCs), (ii) practical approaches for LSC quantification using multiparameter flow cytometry and LSC-enriched marker panels, (iii) the dysregulated signaling, metabolic and epigenetic programs that enable LSC persistence under chemotherapy and contribute to measurable residual disease, and (iv) current therapeutic strategies targeting LSC eradication, including antibody-based therapies, apoptosis and metabolic inhibitors, and emerging epigenetic agents. We also examine the key translational barriers, particularly antigen overlap with normal progenitors, microenvironmental protection, and the need for assay harmonization, while proposing a practical framework for integrating LSC assessment into risk stratification and therapeutic development.

Multiple myeloma (MM) is one of the most common hematological malignancies and remains incurable. However, survival of multiple myeloma patients has significantly increased due to the implementation of novel therapies along with autologous stem cell transplantation, changing the natural history of the disease. Consequently, there is an unmet need for more sensitive response assessment techniques capable of quantifying minimal tumor burden to identify patients at higher risk of early relapse. Multiparameter flow cytometry (MFC) is an essential tool for diagnosing and monitoring patients with various hematological conditions and has recently gained prominence in identifying, characterizing, and monitoring malignant plasma cells. The implementation of Next Generation Flow (NGF) by EuroFlow aims to overcome the pitfalls of conventional MFC, including lack of standardization and lower sensitivity, by offering standardized and optimized protocols for evaluating response depth. Both MFC and NGF have wide-ranging applications in MM for diagnosis and minimal residual disease (MRD) monitoring. Plasma cell identification and clonality evaluation through MFC and NGF assist in diagnostic workup and are routinely used to assess therapeutic response through MRD analysis. Additionally, flow cytometry is applied for circulating tumor plasma cell (CTPC) enumeration, which has demonstrated significant prognostic value. Immune composition studies through MFC may provide better understanding of disease biology. Furthermore, MFC provides additional information about other bone marrow cell populations, assessing cellularity, immunophenotypic characteristics of plasma cells, and possible hemodilution. This review explores the applications of MFC and NGF in MM, highlighting their roles in diagnosis, response assessment, and prognosis, and underscores the importance of incorporating these techniques into routine clinical practice for enhanced patient monitoring.

Acute myeloid leukemia (AML) continues to pose significant therapeutic challenges, with high relapse rates driven largely by leukemic stem cells (LSCs), a rare, therapy-resistant population with self-renewal capacity, niche adaptation, and the ability to re-initiate disease. In this state-of-the-art review, we synthesize recent advances in LSC biology, addressing (i) how LSCs differ functionally and phenotypically from normal hemato-poietic stem cells, (ii) practical approaches for LSC quantification using multiparameter flow cytometry and LSC-enriched marker panels, (iii) the metabolic and epigenetic programs that enable LSC persistence under chemotherapy and contribute to measurable residual disease, and (iv) current therapeutic strategies targeting LSC eradication, in-cluding antibody-based therapies, apoptosis and metabolic inhibitors, and emerging epigenetic agents. We also examine the key translational barriers, particularly antigen overlap with normal progenitors, microenvironmental protection, and the need for assay harmonization, and propose a practical framework for integrating LSC assessment into risk stratification and therapeutic development.

Chronic lymphocytic leukemia (CLL) is a biologically heterogeneous B-cell malignancy in which B-cell receptor signaling, microenvironmental interactions, genomic lesions, and epigenetic deregulation cooperate to shape disease behavior. The imprinted DLK1-DIO3 locus at chromosome 14q32 contains the largest human miRNA cluster and has been implicated in cancer-related regulatory networks; however, its systems-level contribution to CLL remains incompletely defined. In the present study, we investigated the potential involvement of DLK1-DIO3 miRNAs in CLL biology by integrating public transcriptomic datasets with miRNA-centered pathway analysis. GSE70830 was used as a discovery dataset and GSE66117 as a supportive validation cohort to identify genes consistently downregulated in CLL compared with normal B cells. The overlap between the two datasets yielded a 345-gene consensus downregulated CLL signature, which was subsequently used as gene filter input for DIANA-miRPath v3.0 analysis of the expressed DLK1-DIO3 miRNA cluster. This analysis identified eight enriched KEGG pathways, mainly converging on B-cell receptor signaling, NF-kappa B signaling, cell adhesion molecules, leukocyte transendothelial migration, and glycan-related processes. DIANA-miRPath v4.0 was further used as a pathway-centered refinement approach, supporting the involvement of individual DLK1-DIO3 miRNAs in signaling, adhesion, migration, and microenvironment-associated programs. Post hoc annotation also showed that members of an IGHV-associated DLK1-DIO3 miRNA panel were represented within several of these pathway categories. Overall, our findings support a systems-level association between the DLK1-DIO3 miRNA locus and CLL-relevant transcriptional programs, providing a hypothesis-generating framework that warrants further experimental validation.

Background/Objectives: Chronic lymphocytic leukemia (CLL) is a heterogeneous B-cell malignancy in which B-cell receptor signaling, microenvironmental interactions, genomic lesions, and epigenetic deregulation cooperate to shape disease behavior. The imprinted DLK1-DIO3 locus at chromosome 14q32 contains the largest human miRNA cluster and has been implicated in cancer-related regulatory networks; however, its contribution to CLL remains incompletely defined. Methods: In the present study, we investigated the potential involvement of DLK1-DIO3 miRNAs in CLL biology by integrating public transcriptomic datasets with miRNA-centered pathway analysis. GSE70830 was used as a discovery dataset and GSE66117 as a supportive validation cohort to identify genes consistently downregulated in CLL compared with normal B cells. Results: The analyses identified 1236 and 2145 downregulated genes, respectively, and their intersection yielded a 345-gene consensus set. The overlap was significantly greater than expected by chance (odds ratio 2.33; p = 1.55 × 10⁻³¹). This set was used as gene-filter input for DIANA-miRPath v3.0 analysis of the DLK1-DIO3 miRNA cluster, identifying eight KEGG pathways mainly involving B-cell receptor/NF-κB signaling, cell adhesion, leukocyte transendothelial migration, and glycan-related processes. DIANA-miRPath v4.0 provided pathway-centered refinement. GSE216258 miRNA analysis did not show generalized locus-wide upregulation, while a GSE12366 sensitivity analysis showed that 32 of the 345 genes overlapped the strongest naïve-memory B-cell differentiation signatures. The absence of uniform locus-wide upregulation suggests that these data do not establish a direct link between DLK1-DIO3 activation and generalized repression of the 345-gene set. Future studies are needed to identify gene- and pathway-specific effects. Conclusions: Overall, our findings support an association between DLK1-DIO3 miRNA target/pathway annotations and CLL-relevant transcriptional programs, providing a hypothesis-generating framework that warrants further experimental validation.