New publication in PLoS Computational Biology

Dr. Seifert has published a new article on „Network-based analysis of prostate cancer cell lines reveals novel marker gene candidates associated with radioresistance and patient relapse“ in PLoS Computational Biology in close collaboration with the Dubrovska lab from the National Center for Radiation Research in Oncology.

We developed a network-based approach based on lasso regression in combination with network propagation for the analysis of prostate cancer cell lines with acquired radioresistance to identify clinically relevant marker genes associated with radioresistance in prostate cancer patients. We found that 14 driver candidates that were able to distinguish irradiated prostate cancer patients into early and late relapse groups. In-depth wet lab validations of a selected driver candidate showed that  silencing of this gene increased the radiosensitivity in cell culture models.

Link to publication: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007460