Communication breakdown and evolution of the cancer cell

Understanding the mechanisms through which cancer cells communicate with their microenvironment could boost novel precision therapies in oncology. Here, we studied cell-cell communication networks in large scale transcriptomic datasets, finding that cancer cell-cell interactions (CCIs) are more coexpressed than any other protein-protein interaction (PPI) type and, likewise, they are the most co-evolved PPI class in sequenced genomes. Similar regulation and evolutionary trends are observed when comparing extracellular vs intracellular interactions mediated by G protein Coupled Receptors (GPCRs), whose ligand interactions are also characterized by a higher mutational burden in later tumor stages. CCIs undergo the most extensive rewiring of their tumor co-expression networks relative to healthy tissues, more so than any other PPI type, with a set of CCI hubs highly conserved across multiple tumor tissues, and a higher diversity on healthy ones. Cancer rewiring is also associated with the formation of recurrent circuits of coexpressed CCI pairs, represented by enriched network motifs such as triad or tetrad cliques. These act as integrative hotspots to facilitate the crosstalk of distinct processes and the interaction of the cancer cell with its tumor microenvironment (TME). Remarkably, many CCI circuits are significantly associated with patient survival and are predictive of patient response to immunotherapy. CCI circuits mapping to Allograft Rejection and Inflammatory Response inform immunotherapy response prediction, while those related to Epithelial Mesenchymal Transition are associated with poorer prognosis. CCI cliques highlight the potential for combination targeting opportunities. We found that most drug combinations targeting CCI clique receptors are reported to be synergistic in cancer cell lines screening. In particular, the clique FLT1-KDR-PGF & PDGFB-PDGFRA-PDGFRB, which is synergistically targeted by the Axitinib-Sorafenib combination in breast carcinoma cell lines, is also found to be significantly associated to lower survival in breast cancer patients. Overall, we show that CCIs expression signatures could be effectively exploited to stratify patients and, at the same time, they offer new combination therapy opportunities in personalized oncology settings.