Project description:Despite major advances in understanding the molecular and genetic basis of cancer, metastasis remains the cause of >90% of cancer-related mortality1. Understanding metastasis initiation and progression is critical to develop new therapeutic strategies to treat and prevent metastatic disease. Prevailing theories hypothesize that metastases are seeded by rare tumor cells with unique properties, which may function like stem cells in their ability to initiate and propagate metastatic tumors.2 3-5 However, the identity of metastasis-initiating cells in human breast cancer remains elusive, and whether metastases are hierarchically organized is unknown.2 Here we show at the single-cell level that early stage metastatic cells possess a distinct stem-like gene expression signature. To identify and isolate metastatic cells from patient-derived xenograft (PDX) models of human breast cancer, we developed a highly sensitive FACS-based assay, which allowed us to enumerate metastatic cells in mouse peripheral tissues. We compared gene signatures in metastatic cells from tissues with low vs. high metastatic burden. Metastatic cells from low-burden tissues were distinct due to their increased expression of stem cell, EMT, pro-survival, and dormancy-associated genes. In contrast, metastatic cells from high-burden tissues were similar to primary tumor cells, which were more heterogeneous and expressed higher levels of luminal differentiation genes. Transplantation of stem-like metastatic cells from low-burden tissues showed that they have significant tumor-initiating capacity, and differentiate to produce luminal-like cancer cells. Progression to high metastatic burden was associated with increased proliferation and cMYC expression, which could be attenuated by treatment with cyclin dependent kinase (CDK) inhibitors. These findings support a hierarchical model for metastasis, where metastases are initiated by stem-like cells that proliferate and differentiate to produce advanced metastatic disease.

Project description:The paper describes a model of tumor invasion to bone marrow. Created by COPASI 4.26 (Build 213) This model is described in the article: Modeling invasion of metastasizing cancer cells to bone marrow utilizing ecological principles Kun-Wan Chen, Kenneth J Pienta Theoretical Biology and Medical Modelling 2011, 8:36 Abstract: Background: The invasion of a new species into an established ecosystem can be directly compared to the steps involved in cancer metastasis. Cancer must grow in a primary site, extravasate and survive in the circulation to then intravasate into target organ (invasive species survival in transport). Cancer cells often lay dormant at their metastatic site for a long period of time (lag period for invasive species) before proliferating (invasive spread). Proliferation in the new site has an impact on the target organ microenvironment (ecological impact) and eventually the human host (biosphere impact). Results: Tilman has described mathematical equations for the competition between invasive species in a structured habitat. These equations were adapted to study the invasion of cancer cells into the bone marrow microenvironment as a structured habitat. A large proportion of solid tumor metastases are bone metastases, known to usurp hematopoietic stem cells (HSC) homing pathways to establish footholds in the bone marrow. This required accounting for the fact that this is the natural home of hematopoietic stem cells and that they already occupy this structured space. The adapted Tilman model of invasion dynamics is especially valuable for modeling the lag period or dormancy of cancer cells. Conclusions: The Tilman equations for modeling the invasion of two species into a defined space have been modified to study the invasion of cancer cells into the bone marrow microenvironment. These modified equations allow a more flexible way to model the space competition between the two cell species. The ability to model initial density, metastatic seeding into the bone marrow and growth once the cells are present, and movement of cells out of the bone marrow niche and apoptosis of cells are all aspects of the adapted equations. These equations are currently being applied to clinical data sets for verification and further refinement of the models. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Single-cell analysis reveals a stem cell program in human metastatic breast cancer cells (PDX mice - cancer cells)

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