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Group Anders Ståhlberg

Research Summary

Cells have a remarkable ability to respond to internal and external stimuli in a specific manner. Yet, cells are in many aspects unique in their characteristics also within a seemingly homogenous population. Cells of the same type show highly variable responses to identical stimuli in tissues and organs. The limited understanding of tumor heterogeneity and its importance in disease is caused by the lack of analytical techniques to study individual cells in detail. Furthermore, responses from anticancer drugs are evaluated at cell population level, but would benefit from detailed studies at the single cell level to show their effects on different subpopulations of tumor cells. Recent development of single-cell and single-molecule techniques opens up new avenues to investigate tumor heterogeneity and the dynamic transition between cell states. Our research is focused on human sarcomas caused by specific fusion oncogenes (Myxoid/Round cell liposarcoma and Ewing sarcoma) and breast cancer. We are particular interested in understanding cell fate mechanisms between cancer stem cells, expansion phase cells and senescent cells. In collaboration, we are also studying other tumor entities and stem cells at the single-cell level. In the short-term perspective we expect that our research will reveal fundamental information about tumor origin, tumor cell diversity and deeper understanding of molecular mechanisms in sarcoma and breast cancer development. Ultimately, this will contribute to the development of novel treatment paradigms and a more precise diagnosis and prognosis of cancer patients. Specific projects include:

• To define tumor cell hierarchy and to determine key cell fate decisions
• Functional single-cell analysis
• To define biological processes behind tumor drug resistance
• Development of multi-analyte analysis in the same single-cell
• Development of tumor bioreactors for next generation drug test systems, including 3D printing.
• Development and evaluation of non-invasive methods in cancer diagnostics, including ultrasensitive mutation detection using circulating cell-free tumor DNA. 

Research Tools and Resources

We use several single-cell and single-molecule techniques to study tumor biology, including qPCR, PLA and NGS. In addition to clinical samples, we also use stem cells, tumor cell lines, reporter cell lines, primary cells and mouse xenografts as model systems. We work closely with the Translational Genomics Platform (http://wcmtm.gu.se/research-groups/genomics-platform).

Current group members

Anders Ståhlberg, PhD, Associate Professor
Daniel Andersson, Postdoc
Soheila Dolatabadi, Postdoc
Amin Forootan, PhD student
Emma Jonasson, PhD student
Stefan Filges, PhD student
Gustav Johansson, PhD student
Jennifer Pettersson, associated PhD student
Joakim Karlsson, associated PhD student
Emma Persson, associated PhD student
Christoffer Vannas, associated PhD student
Cristiana Rimniceanu, associated PhD student
Malin Nilsson, associated PhD student
Anna Gustafsson, associated PhD student
Karoline Berger, associated PhD student

We have openings for MSc thesis Projects.

Recent selected publications

  1. Karlsson J, Kroneis T, Jonasson E, Larsson E, Ståhlberg A. Transcriptomic characterization of the human cell cycle in individual unsynchronized cells. Journal of Molecular Biology, 2017, online.
  2. Ståhlberg A, El-Heliebi A, Sedlmayr P, Kroneis T. Unravelling the biological secrets of microchimerism by single-cell analysis. Briefings in Functional Genomics, 2017, online.
  3. Kubista M, Dreyer J, Ståhlberg A, The secrets of the cell. Molecular Aspects of Medicine, 2017. online.
  4. Ståhlberg A, Kubista M. Technical aspects and recommendations for single-cell qPCR. Molecular Aspects of Medicine, 2017, online.
  5. Kroneis T, Jonasson E, Andersson D, Dolatabadi S, Ståhlberg A. Global preamplification simplifies targeted mRNA quantification. Scientific Reports, 2017, 7:45219.
  6. Ståhlberg A, Krzyzanowski PM, Egyud M, Filges S, Stein L, Godfrey TE. Simple multiplexed PCR-based barcoding of DNA for ultrasensitive mutation detection by next-generation sequencing. Nature Protocols, 2017, 12:664-82.
  7. Dolatabadi S, Candia J, Akrap N, Vannas C, Tesan Tomic T, Losert W, Landberg G, Åman P, Ståhlberg A. Cell cycle and cell size dependent gene expression reveals distinct subpopulations at single-cell level. Frontiers Genetics, 2017, 8:1.

 

PubMed

Page Manager: Ulrika Lantz Carlsson|Last update: 11/13/2017
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