Pathway and network analyses in context of Wnt signaling in breast cancer
von Michaela Bayerlová
Datum der mündl. Prüfung:2016-01-14
Betreuer:Prof. Dr. Tim Beißbarth
Gutachter:Prof. Dr. Tim Beißbarth
Gutachter:Prof. Dr. Burkhard Morgenstern
EnglischA complex network of interplaying signaling pathways governs cell behavior and phenotype. Wnt signaling pathways are part of this network and play an important role in embryonic development as well as in carcinogenesis. In particular, non-canonical Wnt signaling is considered critical for breast cancer cell proliferation and migration. However, specific outcomes of distinct Wnt signaling pathways are still poorly understood. To better characterize these processes, gene expression responses of aberrant Wnt signaling can be quantified by expression profiling, and further analyzed using various bioinformatic approaches. In particular, pathway enrichment and network integration are effective strategies to obtain a comprehensive interpretation of the results of differential expression analysis. Enrichment analysis is a widely used tool to detect pathways significantly altered between two experimental conditions. Before applying this approach in the Wnt signaling context, enrichment methods were evaluated in an extensive comparative study to assess the contribution of pathway structure integration into the enrichment analysis. Standard gene-set methods were compared against pathway topology-based methods in multiple simulation scenarios and on benchmark data. These results as well as a critical consideration of methodological principles suggest that simple gene-set enrichment methods are favorable. In order to elucidate the role of Wnt signaling in aggressive breast cancer, changes in the expression profiles of breast cancer cells after over-expression of the non-canonical Wnt receptor Ror2 were analyzed. Over-expression resulted in increased cell invasion and over 2000 differential target genes of this perturbation were identified. These targets were further placed into the context of known signaling pathways and molecular networks. To this end, the public Wnt pathway knowledge was assembled into signaling network models representing distinct Wnt pathways. Subsequently, the Wnt networks were analyzed with regard to their structural properties, and also utilized for the analysis of targets. Results of the enrichment analysis suggest that the Ror2 over-expression activates non-canonical Wnt signaling, whereas canonical Wnt signaling appears not to be affected. Furthermore, integration of targets with the non-canonical Wnt network revealed a differentially regulated module of the non-canonical Wnt signaling and its topologically essential elements were identified. Moreover, target hubs were determined by integration with protein-protein interaction network. To validate whether the identified Wnt module genes and hub genes are indeed associated with the observed phenotype of increased cell invasion, the results were translated into a clinical context of metastatic breast cancer patients. These two gene lists were utilized as signatures to test prognosis of metastasis-free survival. Both signatures as well as multiple individual genes were shown to be significantly associated with breast cancer outcome; including several genes that have been previously reported to be potential therapeutic targets or biomarkers. In conclusion, gene set enrichment analysis as well as bioinformatic approaches derived from network theory were demonstrated to be powerful tools for analyzing the complex gene expression patterns of breast cancer cells. These strategies were shown to provide valuable insights into signaling processes underlying breast cancer phenotypes, particularly highlighting the importance of the non-canonical Wnt pathway in aggressive breast cancer.
Keywords: Bioinformatics; Wnt signaling pathways; Gene expression; Pathway enrichment methods; Network integration; Breast cancer subtypes