Fragile DNA Repair Mechanism Reduces Ageing in Multicellular Model

DNA damages, as well as mutations, increase with age. It is believed that these result from increased genotoxic stress and decreased capacity for DNA repair. The two causes are not independent, DNA damage can, for example, through mutations, compromise the capacity for DNA repair, which in turn increases the amount of unrepaired DNA damage. Despite this vicious circle, we ask, can cells maintain a high DNA repair capacity for some time or is repair capacity bound to continuously decline with age? We here present a simple mathematical model for ageing in multicellular systems where cells subjected to DNA damage can undergo full repair, go apoptotic, or accumulate mutations thus reducing DNA repair capacity. Our model predicts that at the tissue level repair rate does not continuously decline with age, but instead has a characteristic extended period of high and non-declining DNA repair capacity, followed by a rapid decline. Furthermore, the time of high functionality increases, and consequently slows down the ageing process, if the DNA repair mechanism itself is vulnerable to DNA damages. Although counterintuitive at first glance, a fragile repair mechanism allows for a faster removal of compromised cells, thus freeing the space for healthy peers. This finding might be a first step toward understanding why a mutation in single DNA repair protein (e.g. Wrn or Blm) is not buffered by other repair proteins and therefore, leads to severe ageing disorders

CD44 targeting reduces tumour growth and prevents post-chemotherapy relapse of human breast cancers xenografts

CD44 is a marker of tumour-initiating cells and is upregulated in invasive breast carcinoma; however, its role in the cancer progression is unknown. Here, we show that antibody-mediated CD44-targeting in human breast cancer xenografts (HBCx) significantly reduces tumour growth and that this effect is associated to induction of growth-inhibiting factors. Moreover, treatment with this antibody prevents tumour relapse after chemotherapy-induced remission in a basal-like HBCx

Modeling the clonal heterogeneity of stem cells

Recent experimental studies suggest that tissue stem cell pools are composed of functionally diverse clones. Metapopulation models in ecology concentrate on collections of populations and their role in stabilizing coexistence and maintaining selected genetic or epigenetic variation. Such models are characterized by expansion and extinction of spatially distributed populations. We develop a mathematical framework derived from the multispecies metapopulation model of Tilman et al (1994) to study the dynamics of heterogeneous stem cell metapopulations. In addition to normal stem cells, the model can be applied to cancer cell populations and their response to treatment. In our model disturbances may lead to expansion or contraction of cells with distinct properties, reflecting proliferation, apoptosis, and clonal competition. We first present closed-form expressions for the basic model which defines clonal dynamics in the presence of exogenous global disturbances. We then extend the model to include disturbances which are periodic and which may affect clones differently. Within the model framework, we propose a method to devise an optimal strategy of treatments to regulate expansion, contraction, or mutual maintenance of cells with specific properties

Mechanisms of blood homeostasis: lineage tracking and a neutral model of cell populations in rhesus macaques

BACKGROUND: How a potentially diverse population of hematopoietic stem cells (HSCs) differentiates and proliferates to supply more than 10(11) mature blood cells every day in humans remains a key biological question. We investigated this process by quantitatively analyzing the clonal structure of peripheral blood that is generated by a population of transplanted lentivirus-marked HSCs in myeloablated rhesus macaques. Each transplanted HSC generates a clonal lineage of cells in the peripheral blood that is then detected and quantified through deep sequencing of the viral vector integration sites (VIS) common within each lineage. This approach allowed us to observe, over a period of 4-12 years, hundreds of distinct clonal lineages. RESULTS: While the distinct clone sizes varied by three orders of magnitude, we found that collectively, they form a steady-state clone size-distribution with a distinctive shape. Steady-state solutions of our model show that the predicted clone size-distribution is sensitive to only two combinations of parameters. By fitting the measured clone size-distributions to our mechanistic model, we estimate both the effective HSC differentiation rate and the number of active HSCs. CONCLUSIONS: Our concise mathematical model shows how slow HSC differentiation followed by fast progenitor growth can be responsible for the observed broad clone size-distribution. Although all cells are assumed to be statistically identical, analogous to a neutral theory for the different clone lineages, our mathematical approach captures the intrinsic variability in the times to HSC differentiation after transplantation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12915-015-0191-8) contains supplementary material, which is available to authorized users

Combining transcriptional profiling and genetic linkage analysis to uncover gene networks operating in hematopoietic stem cells and their progeny

Stem cells are unique in that they possess both the capacity to self-renew and thereby maintain their original pool as well as the capacity to differentiate into mature cells. In the past number of years, transcriptional profiling of enriched stem cell populations has been extensively performed in an attempt to identify a universal stem cell gene expression signature. While stem-cell-specific transcripts were identified in each case, this approach has thus far been insufficient to identify a universal group of core “stemness” genes ultimately responsible for self-renewal and multipotency. Similarly, in the hematopoietic system, comparisons of transcriptional profiles between different hematopoietic cell stages have had limited success in revealing core genes ultimately responsible for the initiation of differentiation and lineage specification. Here, we propose that the combined use of transcriptional profiling and genetic linkage analysis, an approach called “genetical genomics”, can be a valuable tool to assist in the identification of genes and gene networks that specify “stemness” and cell fate decisions. We review past studies of hematopoietic cells that utilized transcriptional profiling and/or genetic linkage analysis, and discuss several potential future applications of genetical genomics

Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis

Cellular decision-making is mediated by a complex interplay of external stimuli with the intracellular environment, in particular transcription factor regulatory networks. Here we have determined the expression of a network of 18 key haematopoietic transcription factors in 597 single primary blood stem and progenitor cells isolated from mouse bone marrow. We demonstrate that different stem/progenitor populations are characterized by distinctive transcription factor expression states, and through comprehensive bioinformatic analysis reveal positively and negatively correlated transcription factor pairings, including previously unrecognized relationships between Gata2, Gfi1 and Gfi1b. Validation using transcriptional and transgenic assays confirmed direct regulatory interactions consistent with a regulatory triad in immature blood stem cells, where Gata2 may function to modulate cross-inhibition between Gfi1 and Gfi1b. Single-cell expression profiling therefore identifies network states and allows reconstruction of network hierarchies involved in controlling stem cell fate choices, and provides a blueprint for studying both normal development and human disease

Further phenotypic characterization of the primitive lineage− CD34+CD38−CD90+CD45RA− hematopoietic stem cell/progenitor cell sub-population isolated from cord blood, mobilized peripheral blood and patients with chronic myelogenous leukemia

The most primitive hematopoietic stem cell (HSC)/progenitor cell (PC) population reported to date is characterized as being Lin−CD34+CD38−CD90+CD45R. We have a long-standing interest in comparing the characteristics of hematopoietic progenitor cell populations enriched from normal subjects and patients with chronic myelogenous leukemia (CML). In order to investigate further purification of HSCs and for potential targetable differences between the very primitive normal and CML stem/PCs, we have phenotypically compared the normal and CML Lin−CD34+CD38−CD90+CD45RA− HSC/PC populations. The additional antigens analyzed were HLA-DR, the receptor tyrosine kinases c-kit and Tie2, the interleukin-3 cytokine receptor, CD33 and the activation antigen CD69, the latter of which was recently reported to be selectively elevated in cell lines expressing the Bcr-Abl tyrosine kinase. Notably, we found a strikingly low percentage of cells from the HSC/PC sub-population isolated from CML patients that were found to express the c-kit receptor (<1%) compared with the percentages of HSC/PCs expressing the c-kitR isolated from umbilical cord blood (50%) and mobilized peripheral blood (10%). Surprisingly, Tie2 receptor expression within the HSC/PC subset was extremely low from both normal and CML samples. Using in vivo transplantation studies, we provide evidence that HLA-DR, c-kitR, Tie2 and IL-3R may not be suitable markers for further partitioning of HSCs from the Lin−CD34+CD38−CD90+CD45RA− sub-population

A self-renewal assay for cancer stem cells

Cancers of epithelial origin are responsible for the majority of cancer-related deaths in the USA. Unfortunately, although chemotherapy and/or radiation therapy can sometimes shrink tumors, metastatic cancers of epithelial origin are essentially incurable. It is clear that new approaches are needed to treat these diseases. Although cancer cell lines provide invaluable information, their biological properties often differ in crucial ways from de novo cancer cells. Our laboratory has developed a novel mouse model that reliably permits individual cancer cells isolated directly from patients’ tumors to be assayed. This will allow the characterization of crucial signaling pathways involved in processes such as self-renewal that are critical for tumor formation by the cancer cells within de novo tumors. These tools should lead to new insights into the cellular and molecular mechanisms that drive human breast cancer growth and invasion.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46932/1/280_2005_Article_97.pd