Editorial: Multiple Myeloma: Molecular Mechanism and Targeted Therapy.

Multiple myeloma (MM) is a plasma cell disorder representing the second most common blood cancer [...

Multiple Myeloma Derived Extracellular Vesicle Uptake by Monocyte Cells Stimulates IL-6 and MMP-9 Secretion and Promotes Cancer Cell Migration and Proliferation.

Multiple Myeloma (MM) is an incurable haematological malignancy caused by uncontrolled growth of plasma cells. MM pathogenesis is attributed to crosstalk between plasma cells and the bone marrow microenvironment, where extracellular vesicles (EVs) play a role. In this study, EVs secreted from a panel of MM cell lines were isolated from conditioned media by ultracentrifugation and fluorescently stained EVs were co-cultured with THP-1 monocyte cells.

Bleeding and Thrombosis in Multiple Myeloma: Platelets as Key Players during Cell Interactions and Potential Use as Drug Delivery Systems.

Multiple myeloma (MM) is a hematological malignancy originated in the bone marrow and characterized by unhindered plasma cell proliferation that results in several clinical manifestations. Although the main role of blood platelets lies in hemostasis and thrombosis, platelets also play a pivotal role in a number of other pathological conditions. Platelets are the less-explored components from the tumor microenvironment in MM.

Using Proteomics Data to Identify Personalized Treatments in Multiple Myeloma: A Machine Learning Approach.

This paper describes a machine learning (ML) decision support system to provide a list of chemotherapeutics that individual multiple myeloma (MM) patients are sensitive/resistant to, based on their proteomic profile. The methodology used in this study involved understanding the parameter space and selecting the dominant features (proteomics data), identifying patterns of proteomic profiles and their association to the recommended treatments, and defining the decision support system of personalized treatment as a classification problem. During the data analysis, we compared several ML algorithms, such as linear regression, Random Forest, and support vector machines, to classify patients as sensitive/resistant to therapeutics.

Proteomic and Metabolomic Analysis of Bone Marrow and Plasma from Patients with Extramedullary Multiple Myeloma Identifies Distinct Protein and Metabolite Signatures.

Multiple myeloma (MM) is an incurable haematological malignancy of plasma cells in the bone marrow. In rare cases, an aggressive form of MM called extramedullary multiple myeloma (EMM) develops, where myeloma cells enter the bloodstream and colonise distal organs or soft tissues. This variant is associated with refractoriness to conventional therapies and a short overall survival.