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Multiple myeloma (MM) is a hematologic malignancy characterized by the proliferation of clonal plasma cells in the bone marrow (BM). It is known that early genetic mutations in post-germinal center B/plasma cells are the cause of myelomagenesis. The acquisition of additional chromosomal abnormalities and distinct mutations further promote the outgrowth of malignant plasma cell populations that are resistant to conventional treatments, finally resulting in relapsed and therapy-refractory terminal stages of MM. In addition, myeloma cells are supported by autocrine signaling pathways and the tumor microenvironment (TME), which consists of diverse cell types such as stromal cells, immune cells, and components of the extracellular matrix. The TME provides essential signals and stimuli that induce proliferation and/or prevent apoptosis. In particular, the molecular pathways by which MM cells interact with the TME are crucial for the development of MM. To generate successful therapies and prevent MM recurrence, a thorough understanding of the molecular mechanisms that drive MM progression and therapy resistance is essential. In this review, we summarize key mechanisms that promote myelomagenesis and drive the clonal expansion in the course of MM progression such as autocrine signaling cascades, as well as direct and indirect interactions between the TME and malignant plasma cells. In addition, we highlight drug-resistance mechanisms and emerging therapies that are currently tested in clinical trials to overcome therapy-refractory MM stages.
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http://dx.doi.org/10.3389/fimmu.2023.1243997 | DOI Listing |
Virchows Arch
September 2025
Department of Oral Surgery and Pathology, School of Dentistry, Universidade Federal de Minas Gerais, Minas Gerais, Av. Antônio Carlos, Pampulha, Belo Horizonte, 31270-901, Brazil.
Plasmablastic lymphoma (PBL) is a rare and aggressive non-Hodgkin lymphoma with a poor prognosis and short survival rates. It is classified as a large B-cell lymphoma subtype, but carries a plasmacytic immunophenotype. Therefore, PBL has pathogenetic overlaps with diffuse large B-cell lymphoma not otherwise specified (DLBCL NOS) and plasma cell neoplasms (PCNs).
View Article and Find Full Text PDFLeukemia
September 2025
Department of Internal Medicine II, University Hospital of Würzburg, Würzburg, Germany.
Intern Med
September 2025
Division of Hematology/Oncology, Department of Medicine, Kameda Medical Center, Japan.
We herein report two cases of immunotactoid glomerulopathy (ITG) associated with multiple myeloma treated with daratumumab-based regimens. The first patient was an 81-year-old woman with severe renal insufficiency and IgAκ multiple myeloma (MM) that progressed to end-stage renal disease despite administering daratumumab-based therapy. The second patient, a 69-year-old man with smoldering MM, showed a favorable response to daratumumab-based treatment, with a resolution of nephrotic proteinuria.
View Article and Find Full Text PDFTransplant Cell Ther
September 2025
Fred Hutchinson Cancer Center, Seattle, WA, USA; University of Washington, Seattle, WA, USA.
Background: BCMA-directed chimeric antigen receptor (CAR)-T cell therapy represents a major therapeutic breakthrough for relapsed/refractory multiple myeloma (RRMM), offering deep and durable responses in heavily pretreated patients. However, a subset of patients experience early relapse or fail to respond, highlighting the need for strategies to enhance efficacy. Gamma-secretase inhibitors (GSIs) have been shown to increase surface BCMA expression on malignant plasma cells and may potentiate the activity of BCMA CAR-T cells, particularly in patients with low baseline BCMA antigen density.
View Article and Find Full Text PDFComput Methods Programs Biomed
August 2025
The Institute of Cancer Research, London, UK. Electronic address:
Background And Objective: Apparent Diffusion Coefficient (ADC) values and Total Diffusion Volume (TDV) from Whole-body diffusion-weighted MRI (WB-DWI) are recognised cancer imaging biomarkers. However, manual disease delineation for ADC and TDV measurements is unfeasible in clinical practice, demanding automation. As a first step, we propose an algorithm to generate fast and reproducible probability maps of the skeleton, adjacent internal organs (liver, spleen, urinary bladder, and kidneys), and spinal canal.
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