Project description:A transcriptome study in mouse hematopoietic stem cells was performed using a sensitive SAGE method, in an attempt to detect medium and low abundant transcripts expressed in these cells. Among a total of 31,380 unique transcript, 17,326 (55%) known genes were detected, 14,054 (45%) low-copy transcripts that have no matches to currently known genes. 3,899 (23%) were alternatively spliced transcripts of the known genes and 3,754 (22%) represent anti-sense transcripts from known genes. Mouse hematopoietic stem cells were purified from bone marrow cells using negative and positive selection with a Magnetic-Activated Cell Sorter (MACS). total RNA and mRNA were purified from the purified cells using Trizol reagent and magnetic oligo dT beads. Double strand cDNAs were synthesized using a cDNA synthesis kit and anchored oligo dT primers. After NlaIII digestion, 3’ cDNAs were isolated and amplified through 16-cycle PCR. SAGE tags were released from the 3’ cDNA after linker ligation. Ditags were formed, concatemerized and cloned into a pZERO vector. Sequencing reactions were performed with the ET sequencing terminator kit. Sequences were collected using a Megabase 1000 sequencer. SAGE tag sequences were extracted using SAGE 2000 software.
Project description:Hematopoietic stem cells give rise to all blood lineages, can fully re-populate the bone marrow, and easily outlive the host organism. To better understand how stem cells remain fit during aging, we analyzed the proteome of hematopoietic stem and progenitor cells.
Project description:Aged hematopoietic stem cells (HSCs) display myeloid-biased differentiation and reduced regenerative potential. In this study, we uncover that P-selectin (Selp) marks a subset of aged HSCs with reduced repopulation capacity. This population of HSCs expresses a prominent aging transcriptome. Overexpression of Selp in young HSCs impaired long-term reconstitution potential and repressed erythropoiesis. We show that IL-1β is elevated in aged bone marrow and administration of IL-1β induces expression of Selp and other aging-associated genes in HSCs. Finally, we demonstrate that transplantation of aged HSCs into young recipients restores a young-like transcriptome, specifically by repressing pro-inflammatory pathways, highlighting the important role of the bone marrow microenvironment in HSC aging.
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.
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.
Project description:ATAC-seq profiling of Nfat5 KO and wild type macrophages derived from bone marrow (primary cells), treated or not with Lipopolysaccharide (LPS).
Project description:Abstract:
The cancer stem cell hypothesis has gained currency in recent times but concerns remain about its scientific foundations because of significant gaps that exist between research findings and comprehensive knowledge about cancer stem cells (CSCs). In this light, a mathematical model that considers hematopoietic dynamics in the diseased state of the bone marrow and peripheral blood is proposed and used to address findings about CSCs. The ensuing model, resulting from a modification and refinement of a recent model, develops out of the position that mathematical models of CSC development, that are few at this time, are needed to provide insightful underpinnings for biomedical findings about CSCs as the CSC idea gains traction. Accordingly, the mathematical challenges brought on by the model that mirror general challenges in dealing with nonlinear phenomena are discussed and placed in context. The proposed model describes the logical occurrence of discrete time delays, that by themselves present mathematical challenges, in the evolving cell populations under consideration. Under the challenging circumstances, the steady state properties of the model system of delay differential equations are obtained, analyzed, and the resulting mathematical predictions arising therefrom are interpreted and placed within the framework of findings regarding CSCs. Simulations of the model are carried out by considering various parameter scenarios that reflect different experimental situations involving disease evolution in human hosts.
Model analyses and simulations suggest that the emergence of the cancer stem cell population alongside other malignant cells engenders higher dimensions of complexity in the evolution of malignancy in the bone marrow and peripheral blood at the expense of healthy hematopoietic development. The model predicts the evolution of an aberrant environment in which the malignant population particularly in the bone marrow shows tendencies of reaching an uncontrollable equilibrium state. Essentially, the model shows that a structural relationship exists between CSCs and non-stem malignant cells that confers on CSCs the role of temporally enhancing and stimulating the expansion of non-stem malignant cells while also benefitting from increases in their own population and these CSCs may be the main protagonists that drive the ultimate evolution of the uncontrollable equilibrium state of such malignant cells and these may have implications for treatment.
Project description:A transcriptome study in mouse hematopoietic stem cells was performed using a sensitive SAGE method, in an attempt to detect medium and low abundant transcripts expressed in these cells. Among a total of 31,380 unique transcript, 17,326 (55%) known genes were detected, 14,054 (45%) low-copy transcripts that have no matches to currently known genes. 3,899 (23%) were alternatively spliced transcripts of the known genes and 3,754 (22%) represent anti-sense transcripts from known genes.