Project 6. Identification of the mechanisms that control lineage-specification of mesenchymal stem cells (Micro-array analysis method development)


This project is a subproject of the collaboration between Schering-Plough, STW and the RU Nijmegen on "Gene expression analysis of self renewal, lineage commitment and differentiation of human mesenchymal stem cells induced by polypeptide growth factors" and is conducted in close collaboration with with prof. van Zoelen, Cell Biology, RUN.


Key project members: Eugene van Someren, Susanne Bauerschmidt (Schering-Plough ) , Peter Kuijpers (master student, TU Delft) , Martijn Jansen (bachelor student, HAN)


Sponsor: STW and Schering-Plough


Project Goals

The ability of stem cells to form and regenerate tissues of multicellular organisms has roused great scientific interest, because of their potential applications in prevention and treatment of age-related degenerative diseases. Mesenchymal stem cells (MSCs) use bone marrow as their niche, from where they can invade tissues and contribute to the formation of all mesodermal cell types. When isolated from bone marrow and cultured in vitro, human MSCs can still differentiate into osteoblasts, chondroblasts and adipocytes, depending on the type of external stimulus applied. Understanding the molecular mechanisms that underlie human MSC self-renewal and lineage-directed differentiation can provide the tools to develop therapeutics for the treatment and prevention of e.g. osteoporosis, obesity, osteoarthritis or rheumatoid arthritis.


The key goals are:

  • To identify mesenchymal stem cell markers.
  • To determine which processes play a role during commitment and differentiation.
  • To determine key regulators of differentiation.



A genome-wide profiling of genes is performed to identify genes that are specifically expressed at the stem cell stage, as well as during homogeneous differentiation into either the osteogenic, adipogenic or chondrogenic lineages. Bioinformatics methods are developed to select the genes relevant to each goal, to identify relevant processes and pathways, to determine corresponding key regulators and to infer relations between these genes, processes and regulators in the context of development. To this end, a novel biclustering method for time-series data is being developed that relates modules of functionally similar and co-expressed genes to different stages of development. In addition, a novel promotor analysis tool is developed to identify the transcription factors that may regulate groups of genes. Furthermore, our approach to reverse engineer gene regulatory networks is being augmented to incorporate prior knowledge about genetic interactions. A red line in this bioinformatics project is to solve biological questions using (existing) bioinformatics tools by combining microarray data with relevant biological knowledge. This to create added value and new biological understanding.



A completely novel set of cell-membrane genes has been identified that is able to classify stem cells from differentiated cells. A set of genes has been identified with an accelerated profile in one of the osteogenic treatments. Our in house developed promotor analysis tool was used to identify the transcription factors that may regulate this group of genes. Currently our hypothesis that one transcription factor plays a previously unknown role in accelerating osteogenesis is validated.



2007 J.R. de Haan, R. Wehrens, S. Bauerschmidt, E. Piek, R.C. van Schaik, L.M.C. Buydens. Interpretation of ANOVA models for microarray data using PCA. Bioinformatics 23, 184-190.

2006 E.P. van Someren, B.L. Vaes, W.T. Steegenga, A.M. Sijbers, K.J. Dechering, M.J. Reinders. Least absolute regression network analysis of the murine osteoblast differentiation network. Bioinformatics 22 (4), 477-484.

2006 B.L. Vaes, P. Ducy, A.M. Sijbers, J.M. Hendriks, E.P. van Someren, N.G. de Jong, E.R. van den Heuvel, W. Olijve, E.J. van Zoelen, K.J. Dechering. Microarray analysis on Runx2-deficient mouse embryos reveals novel Runx2 functions and target genes during intramembranous and endochondral bone formation. Bone 39 (4), 724-738.

2005 B.L. Vaes, K.J. Dechering, E.P. van Someren, J.M. Hendriks, C.J. van de Ven, A. Feijen, C.L. Mummery, M.J. Reinders, W. Olijve, E.J. van Zoelen, W.T. Steegenga. Microarray analysis reveals expression regulation of Wnt antagonists in differentiating osteoblasts. Bone 36 (5), 803-811.