The Importance of Proposed Changes in the “Common Rule” for ­Clinical and Translational Researchers

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88061/1/j.1752-8062.2011.00352.x.pd

Modeling invasion of metastasizing cancer cells to bone marrow utilizing ecological principles

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.http://deepblue.lib.umich.edu/bitstream/2027.42/112967/1/12976_2011_Article_309.pd

Forging the Association for Clinical and Translational Science (ACTS)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91162/1/j.1752-8062.2012.00404.x.pd

Successfully Accelerating Translational Research at an Academic Medical Center: The University of MichiganCoulter Translational Research Partnership Program

Abstract Translational research encompasses the effective movement of new knowledge and discoveries into new approaches for prevention, diagnosis, and treatment of disease. There are many roadblocks to successful bench to bedside research, but few have received as much recent attention as the "valley of death. " The valley of death refers to the lack of funding and support for research that moves basic science discoveries into diagnostics, devices, and treatments in humans, and is ascribed to be the result of companies unwilling to fund research development that may not result in a drug or device that will be utilized in the clinic and conversely, the fact that researchers have no access to the funding needed to carry out preclinical and early clinical development to demonstrate potential effi cacy in humans. The valley of death also exists because bridging the translational gap is dependent on successfully managing an additional four risks: scientifi c, intellectual property, market, and regulatory. The University of Michigan (UM) has partnered with the Wallace H. Coulter Foundation (CF) to create a model providing an infrastructure to overcome these risks. This model is easily adoptable to other academic medical centers (AMCs). Clin Trans Sci 2010; Volume 3: 316-31

Chemical transfection of dye‐conjugated microRNA precursors for microRNA functional analysis of M2 macrophages

MicroRNAs (miRNAs) are short noncoding ribonucleic acids known to affect gene expression at the translational level and there is mounting evidence that miRNAs play a role in the function of tumor‐associated macrophages (TAMs). To aid the functional analyses of miRNAs in an in‐vitro model of TAMs known as M2 macrophages, a transfection method to introduce artificial miRNA constructs or miRNA molecules into primary human monocytes is needed. Unlike differentiated macrophages or dendritic cells, undifferentiated primary human monocytes have been known to show resistance to lentiviral transduction. To circumvent this challenge, other techniques such as electroporation and chemical transfection have been used in other applications to deliver small gene constructs into human monocytes. To date, no studies have compared these two methods objectively to evaluate their suitability in the miRNA functional analysis of M2 macrophages. Of the methods tested, the electroporation of miRNA‐construct containing plasmids and the chemical transfection of miRNA precursor molecules are the most efficient approaches. The use of a silencer siRNA labeling kit (Ambion) to conjugate Cy 3 fluorescence dyes to the precursor molecules allowed the isolation of successfully transfected cells with fluorescence‐activated cell sorting. The chemical transfection of these dye‐conjugated miRNA precursors yield an efficiency of 37.5 ± 0.6% and a cell viability of 74 ± 1%. RNA purified from the isolated cells demonstrated good quality, and was fit for subsequent mRNA expression qPCR analysis. While electroporation of plasmids containing miRNA constructs yield transfection efficiencies comparable to chemical transfection of miRNA precursors, these electroporated primary monocytes seemed to have lost their potential for differentiation. Among the most common methods of transfection, the chemical transfection of dye‐conjugated miRNA precursors was determined to be the best‐suited approach for the functional analysis of M2 macrophages. J. Cell. Biochem. 113: 1714–1723, 2012. © 2012 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90531/1/24041_ftp.pd

Evidence for lectin signaling to the nuclear matrix: Cellular interpretation of the glycocode

No abstractPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34902/1/1135_ftp.pd

Erythropoietin supports the survival of prostate cancer, but not growth and bone metastasis

Erythropoietin (Epo) is used in clinical settings to enhance hematopoietic function and to improve the quality of life for patients undergoing chemotherapy by reducing fatigue and the need for transfusions. However, several meta‐analyses have revealed that Epo treatments are associated with an increased risk of mortality in cancer patients. In this study, we examined the role of Epo in prostate cancer (PCa) progression, using in vitro cell culture systems and in vivo bone metastatic assays. We found that Epo did not stimulate the proliferation of PCa cell lines, but did protect PCa cells from apoptosis. In animal models of PCa metastasis, no evidence was found to support the hypothesis that Epo enhances metastasis. Together, these findings suggest that Epo may be useful for treating severe anemia in PCa patients without increasing metastatic risk. J. Cell. Biochem. 114: 2471–2478, 2013. © 2013 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100159/1/jcb24592.pd

Modeling Somatic Evolution in Tumorigenesis

Tumorigenesis in humans is thought to be a multistep process where certain mutations confer a selective advantage, allowing lineages derived from the mutated cell to outcompete other cells. Although molecular cell biology has substantially advanced cancer research, our understanding of the evolutionary dynamics that govern tumorigenesis is limited. This paper analyzes the computational implications of cancer progression presented by Hanahan and Weinberg in The Hallmarks of Cancer. We model the complexities of tumor progression as a small set of underlying rules that govern the transformation of normal cells to tumor cells. The rules are implemented in a stochastic multistep model. The model predicts that (i) early-onset cancers proceed through a different sequence of mutation acquisition than late-onset cancers; (ii) tumor heterogeneity varies with acquisition of genetic instability, mutation pathway, and selective pressures during tumorigenesis; (iii) there exists an optimal initial telomere length which lowers cancer incidence and raises time of cancer onset; and (iv) the ability to initiate angiogenesis is an important stage-setting mutation, which is often exploited by other cells. The model offers insight into how the sequence of acquired mutations affects the timing and cellular makeup of the resulting tumor and how the cellular-level population dynamics drive neoplastic evolution