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Breast Cancer Exosomal microRNAs Facilitate Pre-Metastatic Niche Formation in the Bone: A Mathematical Model.
Siewe, Nourridine; Friedman, Avner.
Afiliação
  • Siewe N; School of Mathematical Sciences, College of Science, Rochester Institute of Technology, Rochester, NY, USA. nourridine@aims.ac.za.
  • Friedman A; Department of Mathematics, The Ohio State University, Columbus, OH, USA.
Bull Math Biol ; 85(2): 12, 2023 01 06.
Article em En | MEDLINE | ID: mdl-36607440
Pre-metastatic niche is a location where cancer cells, separating from a primary tumor, find "fertile soil" for growth and proliferation, ensuring successful metastasis. Exosomal miRNAs of breast cancer are known to enter the bone and degrade it, which facilitates cancer cells invasion into the bone interior and ensures its successful colonization. In this paper, we use a mathematical model to first describe, in health, the continuous remodeling of the bone by bone-forming osteoblasts, bone-resorbing osteoclasts and the RANKL-OPG-RANK signaling system, which keeps the balance between bone formation and bone resorption. We next demonstrate how breast cancer exosomal miRNAs disrupt this balance, either by increasing or by decreasing the ratio of osteoclasts/osteoblasts, which results in abnormal high bone resorption or abnormal high bone forming, respectively, and in bone weakening in both cases. Finally we consider the case of abnormally high resorption and evaluate the effect of drugs, which may increase bone density to normal level, thus protecting the bone from invasion by cancer cells.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Reabsorção Óssea / Neoplasias da Mama / MicroRNAs Tipo de estudo: Prognostic_studies Limite: Female / Humans Idioma: En Revista: Bull Math Biol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Reabsorção Óssea / Neoplasias da Mama / MicroRNAs Tipo de estudo: Prognostic_studies Limite: Female / Humans Idioma: En Revista: Bull Math Biol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos