Weischenfeldt Group

We are interested in the mutational mechanisms and clonal evolution of cancer, in particular mechanisms of complex structural variants and the impact on 3D chromatin organization. We are collaborating closely with clinicians, to identify the earliest mutational processes in a tumor.














Cancer is a disease of the genome, fueled by the accumulation of genomic alterations that improve the fitness of the cell. We use computational cancer genomics approaches to study clonal evolution and cancer stem cell models, with the overarching goal to understand the mutational processes that allow tumor cells to escape and evolve in time and space to cause treatment-resistance. We have a particular interest in the larger complex structural variants, their presence and impact on cancer and clonal evolution, and how they impact the chromatin architecture.


































Clonal evolution analysis to identify recurrent mechanisms of treatment resistance and identify novel therapeutic targets

  • Predict clinical trajectories from cancer patients by developing methods to i) reconstruct and model the clonal evolution, ii) analyze clonal dynamics and interplay with tumor microenvironment, with the overarching goal to study mechanisms of cancer stem cells.

Schematic of a clinical trajectory of a cancer patient (top), the clonal evolition (middle part) and mutational mechanisms (bottom). For detailed description please contact communication@bric.ku.dkHow complex structural variants emerge and affect the 3D chromatin architecture in cancer

  • Integrate epigenetic with somatic alterations and patient-related data using data-driven quantitative genetics-based computational approaches.
  • Apply chromatin architecture methodologies such as Hi-C to identify how genomic alterations can impact gene regulation through altered chromatin looping

SV-mediated Enhancer Hijacking. For further details and describtion of the figure please contact communication@bric.ku.dk



We use a combination of computational and molecular biology technologies to reach our research aims. We have optimized and integrated a range of different sequencing approaches on clinical material including paired-end sequencing, RNA-seq, ATAC-seq, Hi-C, Capture-Hi-C, mate-pair seq, DNA panel seq, single-cell sequencing, long-read sequencing. We carry out our compute on HPC systems, primarily computerome.dk. We use git for code version control and Docker to deploy our code on other systems.




















Selected publications

Structural variations in cancer and the 3D genome. # Dubois, F., Sidiropoulos, N., Weischenfeldt, J., and Beroukhim, R. 2022. Structural variations in cancer and the 3D genome. Nat Rev Cancer. DOI:10.1038/s41568-022-00488-9 (joint corresp author).

Somatic structural variant formation is guided by and influences genome architecture. # Sidiropoulos, N., Mardin, B. R., Rodríguez-González, F. G., Bochkov, I. D., Garg, S., Stütz, A. M., Korbel, J. O., Aiden, E. L., and Weischenfeldt, J. 2022. Genome Res 32: 643–655. DOI:10.1101/gr.275790.121 (first author, joint corresp author).

    Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. # Rheinbay, E., Nielsen, M. M., Abascal, F., Wala, J. A., Shapira, O. et al. Nature, 578(7793), 102-111. doi:10.1038/s41586-020-1965-x  (joint corresp author). 

    Patterns of somatic structural variation in human cancer genomes. # Li, Y., Roberts, N. D., Wala, J. A., Shapira, O., et al. Nature, 578(7793), 112-121. doi:10.1038/s41586-019-1913-9 (joint corresp author).

    Molecular Evolution of Early-Onset PCa Identifies Molecular Risk Markers and Clinical Trajectories. # Gerhauser, C., Favero, F., Risch, T., Simon, R., Feuerbach, L., Assenov, Y., et al. Cancer Cell, 34(6), 996-1011.e8. doi:10.1016/j.ccell.2018.10.016  (joint first, and corresp author). 

    Pan-cancer analysis of somatic copy-number alterations implicates IRS4 and IGF2 in enhancer hijacking. * Weischenfeldt, J., Dubash, T., Drainas, A. P. et al. Nat Genet, 49(1), 65-74. doi:10.1038/ng.3722 (joint first author).

    Integrative genomic analyses reveal an androgen-driven somatic alteration landscape in early-onset PCa. * Weischenfeldt, J., Simon, R., Feuerbach, L., Schlangen, K., Weichenhan, D., Minner, S., et al. Cancer Cell, 23(2), 159-170. doi:10.1016/j.ccr.2013.01.002  (joint first author).

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    In the media

    Studying DNA rearrangement to understand cancer

    05 February 2020 - EurekAlert.org

    Scientists identify new genetic drivers of cancer

    05 February 2020 - EurekAlert.org

    Global study maps cancer mutations in large catalogue

    05 February 2020 - University of Copenhagen

    Stort kræft-forskningsprojekt kortlægger uudforsket del af vores DNA

    05 February 2020 - Videnskab.dk

    Danskere afslører mekanisme bag aggressive kræftformer

    22 November 2016 - Videnskab.dk. 
    Article (in Danish) on how 'big data' can be used to understand how cancer genes are activated.

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    Collaborative Research Programs