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Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model.

ABSTRACT: The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model's parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

SUBMITTER: Mohammad Mirzaei N

PROVIDER: S-EPMC8959189 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model.

Mohammad Mirzaei Navid N Changizi Navid N Asadpoure Alireza A Su Sumeyye S Sofia Dilruba D Tatarova Zuzana Z Zervantonakis Ioannis K IK Chang Young Hwan YH Shahriyari Leili L

PLoS computational biology 20220316 3

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a ...[more]

PMID: 35294447

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Project description:BackgroundMicroRNAs (miRNAs) are small non-coding RNA molecules of about 22 nucleotides which function to silence the expression of their target genes. Numerous studies have shown that miRNAs are not only key regulators in important cellular processes but are also drivers in the development of many diseases, especially cancer. Estrogen receptor positive luminal B is the second most common but the least studied subtype of breast cancer. Only a few studies have examined the expression profiles of miRNAs in luminal B breast cancer, and their regulatory roles in cancer progression have yet to be investigated.MethodsIn this study, using polyoma middle T antigen (PyMT) mice, a widely used luminal B breast cancer model, we profiled microRNA (miRNA) expression at four time points that represent different key developmental stages of cancer progression. We considered the expression of both miRNAs and messenger RNAs (mRNAs) at these time points to improve the identification of regulatory targets of miRNAs. By combining gene functional and pathway annotation with miRNA-mRNA interactions, we created a PyMT-specific tripartite miRNA-mRNA-pathway network and identified novel functional regulatory programs (FRPs).ResultsWe identified 151 differentially expressed miRNAs with a strict dual nature of either upregulation or downregulation during the whole course of disease progression. Among 82 newly discovered breast-cancer-related miRNAs, 35 can potentially regulate 271 protein-coding genes based on their sequence complementarity and expression profiles. We also identified miRNA-mRNA regulatory modules driving specific cancer-related biological processes.ConclusionsIn this study we profiled the expression of miRNAs during breast cancer progression in the PyMT mouse model. By integrating miRNA and mRNA expression profiles, we identified differentially expressed miRNAs and their target genes involved in several hallmarks of cancer. We applied a novel clustering method to an annotated miRNA-mRNA regulatory network and identified network modules involved in specific cancer-related biological processes.

Project description:In humans, platelet count within the normal range is required for physiological hemostasis, but, adversely, platelets also support pathological thrombosis. Moreover, by releasing growth factors, they may enhance neoplastic proliferation. We hypothesize that platelet count correlates with platelet-dependent pathologies, even within the range of hemostatic competence. Because platelet production is promoted by thrombopoietin signaling through the myeloproliferative leukemia virus oncogene (cMPL), a receptor expressed on megakaryocytes, we evaluated the feasibility of selective targeting of hepatic thrombopoietin production to test this hypothesis. We synthesized murine- and primate-specific antisense oligonucleotides (THPO-ASO) that silence hepatic thrombopoietin gene (THPO) expression without blocking extrahepatic THPO. Repeated doses of THPO-ASO were administered to mice and a baboon, causing a sustained 50% decline in plasma thrombopoietin levels and platelet count within 4 weeks in both species. To investigate whether reducing platelet count within the translationally relevant hemostatic range could alter a neoplastic process, we administered THPO-ASO to 6-week-old transgenic MMTV-PyMT mice that develop early ductal atypia that progresses into cMPL-negative fatal metastatic breast cancer within 2 to 3 months. THPO-ASO treatment increased the average time to euthanasia (primary humane endpoint) at 2 cm3 combined palpable tumor volume. Our results show that THPO-ASO reduced blood platelet count, plasma platelet factor 4, vascular endothelial growth factor, thrombopoietin levels, bone marrow megakaryocyte density, tumor growth rate, proliferation index, vascularization, platelet and macrophage content, and pulmonary metastases vs untreated controls. These findings confirm that sustained and moderate pharmacological platelet count reduction is feasible with THPO-ASO administration and can delay progression of certain platelet-dependent pathological processes within a safe hemostatic platelet count range.

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Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model.

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Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model.

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