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Tag Archives: Campbell Family Institute for Cancer Research

Friday Science Review: February 18, 2011

Mapping the Development of the Pancreatic Lineage

McEwen Centre for Regenerative Medicine ♦ Published in Development, Mar. 2011 (Epub ahead of print)

Human pluripotent stem cells (PSCs) are being investigated as a means to produce insulin-positive cells for the treatment of diabetes. The most efficient mode of producing functional cell types in vitro is to navigate the signaling pathways and temporal cues that lead to their formation during embryonic development. In the case of insulin-producing cells the key is to recreate the pivotal steps in pancreatic development including the induction of definite endoderm, specification of endoderm to the pancreatic fate, and finally the generation of mature endocrine/exocrine cells. Despite the scientific community having a grasp on pancreatic development, current differentiation protocols suffer from low efficiency and an inability to produce homogenous results across a variety of PSC lines using identical treatments. We have yet to identify the optimal signaling pathways that must be leveraged to produce insulin+ cells. Robust differentiation protocols are also hampered by variations in the characteristics of PSC lines which lead to variability in the quality of differentiation cultures. Dr. Gordon Keller and his lab team ambitiously probed this issue by mapping the pancreatic development of several different PSC lines in order to identify the optimal signaling pathways and temporal requirements essential for producing cells of the pancreatic fate.

Keller’s team found that temporally modulating activin/nodal signaling early in the differentiation protocol was crucial for the development of definite endoderm and ultimately for pancreatic differentiation. Wnt signaling and inhibition of BMP signaling at various stages was also prerequisite for the production of insulin+ cells, noting that the degree of BMP inhibition required for efficient differentiation varied extensively amongst PSC lines. By implementing this stage-specific optimization approach for different cell lines, Keller and his colleagues were able to increase insulin expression in cell cultures by a whopping 250 times; some populations contained as much as 25% C-peptide+ cells (prior to C-peptide being cleaved from the pro-insulin molecule, it acts as a linker between the A and B chains of insulin).

This is the second, recent, body of research from Gordon Keller’s lab that emphasizes the importance of identifying the crucial temporal steps that must be satisfied for highly efficient differentiation to terminal cell fates. This paper also reminds us that individual PSC lines will likely require unique treatments in culture to produce maximal results for transplantation therapy.

IL-7 Therapy: A Stimulus Package for the Immune System

Campbell Family Institute for Cancer Research ♦ Published in Cell, Feb. 18, 2011 (Epub ahead of print)

After the immune system succumbs to uncontrollable viral turnover, it eventually fails, leaving the host prone to any number of opportunistic infections. This is the case with HIV infection. One of the primary focuses of HIV research today is the modulation of immune response to encourage the clearance of chronic viral infections. It appears that a certain cytokine, interleukin-7 (IL-7), may be able to prop up the immune system allowing it to move around mechanisms that circumvent immune response during times of chronic infection. In this study led by Dr. Tak Mak, researchers hypothesized that cytokines supporting homeostatic proliferation would be promising candidates for promoting immune response. Indeed, IL-7 did just that.

After administering IL-7 to mice that were chronically infected with lymphocytic chorimeningitis virus (LCMV) variant clone 13, researchers observed an increase in size of the naive T-cell pool, and an enhanced function and cytokine output in LCMV-specific T-cells. IL-7 therapy resulted in clearance of LCMV from chronically infected mice. The cytokine also appears to serve a second function — bolstering levels of the cytoprotective cytokine IL-22. An increase in IL-22 levels has the added benefit of protecting the liver from viral infection, an organ that is particularly prone to damage under the circumstances. Researchers believe IL-7 exerts its effects by downregulating suppressor of cytokine signaling 3 (Socs3) expression in T-cells through the suppression of the FoxO transcription factors.

Friday Science Review: January 28, 2011

Cancer’s Byzantine Architecture – The Plot Thickens

Campbell Family Institute for Cancer Research ♦ Ontario Cancer Institute ♦ University of Toronto

Published in Nature, 20 Jan., 2011

In the mid 90s one of Canada’s foremost stem cell researchers, John Dick, made the rather shocking discovery that not all cancer cells are equivalent. Based on his eloquent work we were able to formulate our current thinking on cancer biology, which has it that only a small sub-population of cells within tumours support malignant expansion, while the majority of cancer cells — although dividing — can only divide so many times before they hit cell cycle arrest and begin to senesce. Therefore, to completely eradicate a population of cancer cells, this minority of “cancer stem cells” must be targeted and destroyed. Our historical view on transformation was that single cells accumulate mutations over time, and in a step-wise fashion their genetic contents slowly mutates to the point that the cell itself loses control over its proliferation. Under this model each clone, or descendant of the original transformant, is linearly related. However, recent genomic work in the area indicates that this view is all too simple. It is now apparent that the architecture, the “framework” upon which cancer supports itself, is in fact a complex and branching network of sub-clones that each have the capacity to support tumour growth. Working with human BCR-ABL lymphoblastic leukemia cell lines, John Dick and his colleagues found that many diagnostic patient samples had several genetically distinct leukemia-initiating clones. DNA copy number alteration (CNA) profiling allowed them to reconstruct an evolutionary map of these clones. Transplantation of clones into xenograft models revealed that the predominant diagnostic clone, sometimes, but not always, was associated with the most aggressive growth properties. In some cases, interestingly, minor subclones proved to be the most potent leukemia-initiating cells. Next generation cancer therapeutics are being targeted to cancer stem cells, but now it appears — for these to be effective — they must target not only the dominant cancer stem cell clone, but all of the minor subclones that may be equally, if not more, vicious.

Freeing Systems Biology Data from the Shackles of the 2D Realm

University of Toronto ♦ Published in PLoS ONE, Jan. 10, 2011

One of the great challenges of systems biology will be to integrate multiple data sets, of widely differing scales, into an interactive and visual interface for human interpretation. Visualization is an important element in elucidating the connections between diverse data sets. Only in recent times have platforms existed that have the capacity to weave together large quantities of data into meaningful 3D representations. Historically, visualizations of biological data have been limited to 2D outputs that fail to do justice to the underlying connections between different biological processes. The need for 3D visualization tools is essential. We as humans have lived and evolved in a 3D environment and as a result have adapted a profound capacity to reason and conceptualize along three axes. In addition, biological processes occur within 3D environments, so carrying out analysis of biological data sets in three dimensions is logical. As a solution to this challenge, a group of researchers at the University of Toronto led by Dr. Nicholas Provart have created an open-source template that integrates and visualizes systems biology data as  interactive 3D representations on the world wide web. The group applied their template to the model plant organism Aribidopsis thaliana and have dubbed it ePlant. The platform incorporates proteome-scale protein structure prediction and annotation along with existing -omics scale data, and allows users to evaluate protein structure and function, protein-protein interactions, protein subcellular locations (great visual display here), gene expression patterns, and genetic variation. The result is a program that integrates systems biology data found on the nanoscale with genetic variation found on the kilometer-scale. The open-source nature and flexibility of the ePlant framework circumvents one of the major limitations of current computational systems biology tools — accessibility. ePlant does not require users to download specific data visualization and analysis software to their specific operating system, reducing the learning curve required to grasp the program. Software development on the world wide web also allows for community-driven expansion of systems biology software like that of ePlant, allowing for continued growth and refinement.


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