Mapping genetic interactions in cancer: a road to rational combination therapies.

The discovery of synthetic lethal interactions between poly (ADP-ribose) polymerase (PARP) inhibitors and BRCA genes, which are involved in homologous recombination, led to the approval of PARP inhibition as a monotherapy for patients with BRCA1/2-mutated breast or ovarian cancer. Studies following the initial observation of synthetic lethality demonstrated that the reach of PARP inhibitors is well beyond just BRCA1/2 mutants. Insights into the mechanisms of action of anticancer drugs are fundamental for the development of targeted monotherapies or rational combination treatments that will synergize to promote cancer cell death and overcome mechanisms of resistance. The development of targeted therapeutic agents is premised on mapping the physical and functional dependencies of mutated genes in cancer. An important part of this effort is the systematic screening of genetic interactions in a variety of cancer types. Until recently, genetic-interaction screens have relied either on the pairwise perturbations of two genes or on the perturbation of genes of interest combined with inhibition by commonly used anticancer drugs. Here, we summarize recent advances in mapping genetic interactions using targeted, genome-wide, and high-throughput genetic screens, and we discuss the therapeutic insights obtained through such screens. We further focus on factors that should be considered in order to develop a robust analysis pipeline. Finally, we discuss the integration of functional interaction data with orthogonal methods and suggest that such approaches will increase the reach of genetic-interaction screens for the development of rational combination therapies

The next frontier of systems biology: higher-order and interspecies interactions

Systems biology is set to go beyond single species to the study of interspecies interactions

Towards accurate imputation of quantitative genetic interactions

Recent technological breakthroughs have enabled high-throughput quantitative measurements of hundreds of thousands of genetic interactions among hundreds of genes in Saccharomyces cerevisiae. However, these assays often fail to measure the genetic interactions among up to 40% of the studied gene pairs. Here we present a novel method, which combines genetic interaction data together with diverse genomic data, to quantitatively impute these missing interactions. We also present data on almost 190,000 novel interactions.Tel Aviv University. Edmond J, Safra Bioinformatics CenterIsrael Science Foundation (grant no. 802/08)Raymond and Beverley Sackler Foundatio

Differential network biology

Protein and genetic interaction maps have typically been generated under a single condition, providing a static view of the interactome. Recent studies employing differential analysis, however, have revealed that widespread re-wiring of the interactome underlies key biological responses

UNC93B1 recruits syntenin-1 to dampen TLR7 signalling and prevent autoimmunity.

At least two members of the Toll-like receptor (TLR) family, TLR7 and TLR9, can recognize self-RNA and self-DNA, respectively. Despite the structural and functional similarities between these receptors, their contributions to autoimmune diseases such as systemic lupus erythematosus can differ. For example, TLR7 and TLR9 have opposing effects in mouse models of systemic lupus erythematosus-disease is exacerbated in TLR9-deficient mice but attenuated in TLR7-deficient mice1. However, the mechanisms of negative regulation that differentiate between TLR7 and TLR9 are unknown. Here we report a function for the TLR trafficking chaperone UNC93B1 that specifically limits signalling of TLR7, but not TLR9, and prevents TLR7-dependent autoimmunity in mice. Mutations in UNC93B1 that lead to enhanced TLR7 signalling also disrupt binding of UNC93B1 to syntenin-1, which has been implicated in the biogenesis of exosomes2. Both UNC93B1 and TLR7 can be detected in exosomes, suggesting that recruitment of syntenin-1 by UNC93B1 facilitates the sorting of TLR7 into intralumenal vesicles of multivesicular bodies, which terminates signalling. Binding of syntenin-1 requires phosphorylation of UNC93B1 and provides a mechanism for dynamic regulation of TLR7 activation and signalling. Thus, UNC93B1 not only enables the proper trafficking of nucleic acid-sensing TLRs, but also sets the activation threshold of potentially self-reactive TLR7

Backup without redundancy: genetic interactions reveal the cost of duplicate gene loss.

Many genes can be deleted with little phenotypic consequences. By what mechanism and to what extent the presence of duplicate genes in the genome contributes to this robustness against deletions has been the subject of considerable interest. Here, we exploit the availability of high-density genetic interaction maps to provide direct support for the role of backup compensation, where functionally overlapping duplicates cover for the loss of their paralog. However, we find that the overall contribution of duplicates to robustness against null mutations is low ( approximately 25%). The ability to directly identify buffering paralogs allowed us to further study their properties, and how they differ from non-buffering duplicates. Using environmental sensitivity profiles as well as quantitative genetic interaction spectra as high-resolution phenotypes, we establish that even duplicate pairs with compensation capacity exhibit rich and typically non-overlapping deletion phenotypes, and are thus unable to comprehensively cover against loss of their paralog. Our findings reconcile the fact that duplicates can compensate for each other's loss under a limited number of conditions with the evolutionary instability of genes whose loss is not associated with a phenotypic penalty

Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

<p>Abstract</p> <p>Background</p> <p>Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks.</p> <p>Results</p> <p>We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter.</p> <p>Conclusion</p> <p>We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.</p