Topological pathway enrichment analysis of gene expression in high grade serous ovarian cancer reveals tumor-stoma cross-talk

Identifying the biological pathways that are significantly regulated in a given condition is a fundamental step to understanding biological phenomena. Existing pathway approaches were designed for the analysis of a single dataset and are not optimized for simultaneous analysis of multiple data sources. Increasing availability of multiple omics datasets obtained on the same sample allows for a more complete understanding of pathway behavior in human diseases. We propose a pathway analysis approach in which we integrate multiple molecular datasets using multivariate analysis and apply dynamical importance to extract topology-based pathway scores.