The supplementary file discusses the limitations of existing tools, performance of CrosstalkNet, along with more biological case studies.
Funding
National Institutes of Health
Cancer Research Society
Canadian Institutes of Health Research
Princess Margaret Cancer
Natural Sciences and Engineering Research Council of Canada
Ministry of Economic Development, Innovation
Ministry of Research & Innovation of Ontario,
Stand Up To Cancer Canada—Canadian Cancer Society Breast Cancer Dream Team Research
Government of Ontario
American Association for Cancer Research International—Canada
ARTICLE ABSTRACT
Variations in physiological conditions can rewire molecular interactions between biological compartments, which can yield novel insights into gain or loss of interactions specific to perturbations of interest. Networks are a promising tool to elucidate intercellular interactions, yet exploration of these large-scale networks remains a challenge due to their high dimensionality. To retrieve and mine interactions, we developed CrosstalkNet, a user friendly, web-based network visualization tool that provides a statistical framework to infer condition-specific interactions coupled with a community detection algorithm for bipartite graphs to identify significantly dense subnetworks. As a case study, we used CrosstalkNet to mine a set of 54 and 22 gene-expression profiles from breast tumor and normal samples, respectively, with epithelial and stromal compartments extracted via laser microdissection. We show how CrosstalkNet can be used to explore large-scale co-expression networks and to obtain insights into the biological processes that govern cross-talk between different tumor compartments.Significance: This web application enables researchers to mine complex networks and to decipher novel biological processes in tumor epithelial-stroma cross-talk as well as in other studies of intercompartmental interactions. Cancer Res; 78(8); 2140–3. ©2018 AACR.
