Comprehensive characterization of protein-protein interactions perturbed by disease mutations

Technological and computational advances in genomics and interactomics have made it possible to identify how disease mutations perturb protein-protein interaction (PPI) networks within human cells. Here, we show that disease-associated germline variants are significantly enriched in sequences encoding PPI interfaces compared to variants identified in healthy participants from the projects 1000 Genomes and ExAC. Somatic missense mutations are also significantly enriched in PPI interfaces compared to noninterfaces in 10,861 tumor exomes. We computationally identified 470 putative oncoPPIs in a pan-cancer analysis and demonstrate that oncoPPIs are highly correlated with patient survival and drug resistance/sensitivity. We experimentally validate the network effects of 13 oncoPPIs using a systematic binary interaction assay, and also demonstrate the functional consequences of two of these on tumor cell growth. In summary, this human interactome network framework provides a powerful tool for prioritization of alleles with PPI-perturbing mutations to inform pathobiological mechanism- and genotype-based therapeutic discovery.

Automated summary

Recent advancements in genomics and interactomics have allowed researchers to identify how disease mutations disrupt protein-protein interaction networks within human cells. Disease-associated germline variants and somatic missense mutations are significantly enriched in protein-protein interaction interfaces, and oncoPPIs identified in cancer analysis are correlated with patient survival and drug resistance/sensitivity. Experimental validation of oncoPPIs and their effects on tumor cell growth demonstrate the potential of using this interactome network framework for prioritizing therapeutic targets.