Comprehensive characterization of protein–protein interactions perturbed by disease mutations
Top Cited Papers
- 8 February 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Nature Genetics
- Vol. 53 (3), 342-353
- https://doi.org/10.1038/s41588-020-00774-y
Abstract
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.Keywords
Funding Information
- American Heart Association (D700382, CV-19, AHA CRADA TC02274.0)
- Foundation for the National Institutes of Health (U01 HG007690, P50 GM107618, U54 HL119145, K99 HL138272, R00 HL138272, 3R01AG066707-01S1, R01AG066707, P50 HG004233, U41 HG001715, P50 HG004233, U41 HG001715)
- VeloSano Pilot Program (Cleveland Clinic Taussig Cancer Institute
- the Sondra J. and Stephen R. Hardis Endowed Chair in Cancer Genomic Medicine at the Cleveland Clinic, and an ACS Clinical Research Professor.
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