Genetic synthetic lethality screen at the single gene level in cultured human cells

Multi-view graph convolutional network for cancer cell-specific synthetic lethality prediction

Synthetic lethal (SL) genetic interactions have been regarded as a promising focus for investigating potential targeted therapeutics to tackle cancer. However, the costly investment of time and labor associated with wet-lab experimental screenings to discover potential SL relationships motivates the development of computational methods. Although graph neural network (GNN) models have performed well in the prediction of SL gene pairs, existing GNN-based models are not designed for predicting cancer cell-specific SL interactions that are more relevant to experimental validation in vitro. Besides, neither have existing methods fully utilized diverse graph representations of biological features to improve prediction performance. In this work, we propose MVGCN-iSL, a novel multi-view graph convolutional network (GCN) model to predict cancer cell-specific SL gene pairs, by incorporating five biological graph features and multi-omics data. Max pooling operation is applied to integrate five graph-specific representations obtained from GCN models. Afterwards, a deep neural network (DNN) model serves as the prediction module to predict the SL interactions in individual cancer cells (iSL). Extensive experiments have validated the model's successful integration of the multiple graph features and state-of-the-art performance in the prediction of potential SL gene pairs as well as generalization ability to novel genes.

A synthetic-lethality RNAi screen reveals an ERK-mTOR co-targeting pro-apoptotic switch in PIK3CA+ oral cancers

mTOR inhibition has emerged as a promising strategy for head and neck squamous cell carcinomas (HNSCC) treatment. However, most targeted therapies ultimately develop resistance due to the activation of adaptive survival signaling mechanisms limiting the activity of targeted agents. Thus, co-targeting key adaptive mechanisms may enable more effective cancer cell killing. Here, we performed a synthetic lethality screen using shRNA libraries to identify druggable candidates for combinatorial signal inhibition. We found that the ERK pathway was the most highly represented. Combination of rapamycin with trametinib, a MEK1/2 inhibitor, demonstrated strong synergism in HNSCC-derived cells in vitro and in vivo, including HNSCC cells expressing the HRAS and PIK3CA oncogenes. Interestingly, cleaved caspase-3 was potently induced by the combination therapy in PIK3CA+ cells in vitro and tumor xenografts. Moreover, ectopic expression of PIK3CA mutations into PIK3CA- HNSCC cells sensitized them to the pro-apoptotic activity of the combination therapy. These findings indicate that co-targeting the mTOR/ERK pathways may provide a suitable precision strategy for HNSCC treatment. Moreover, PIK3CA+ HNSCC are particularly prone to undergo apoptosis after mTOR and ERK inhibition, thereby providing a potential biomarker of predictive value for the selection of patients that may benefit from this combination therapy.

Identification of novel synergistic targets for rational drug combinations with PI3 kinase inhibitors using siRNA synthetic lethality screening against GBM

Several small molecules that inhibit the PI3 kinase (PI3K)-Akt signaling pathway are in clinical development. Although many of these molecules have been effective in preclinical models, it remains unclear whether this strategy alone will be sufficient to interrupt the molecular events initiated and maintained by signaling along the pathways because of the activation of other pathways that compensate for the inhibition of the targeted kinase. In this study, we performed a synthetic lethality screen to identify genes or pathways whose inactivation, in combination with the PI3K inhibitors PX-866 and NVPBEZ-235, might result in a lethal phenotype in glioblastoma multiforme (GBM) cells. We screened GBM cells (U87, U251, and T98G) with a large-scale, short hairpin RNA library (GeneNet), which contains 43 800 small interfering RNA sequences targeting 8500 well-characterized human genes. To decrease off-target effects, we selected overlapping genes among the 3 cell lines that synergized with PX-866 to induce cell death. To facilitate the identification of potential targets, we used a GSE4290 dataset and The Cancer Genome Atlas GBM dataset, identifying 15 target genes overexpressed in GBM tissues. We further analyzed the selected genes using Ingenuity Pathway Analysis software and showed that the 15 genes were closely related to cancer-promoting pathways, and a highly interconnected network of aberrations along the MYC, P38MAPK, and ERK signaling pathways were identified. Our findings suggest that inhibition of these pathways might increase tumor sensitivity to PX-866 and therefore represent a potential clinical therapeutic strategy.

Harnessing synthetic lethal interactions in anticancer drug discovery

Unique features of tumours that can be exploited by targeted therapies are a key focus of current cancer research. One such approach is known as synthetic lethality screening, which involves searching for genetic interactions of two mutations whereby the presence of either mutation alone has no effect on cell viability but the combination of the two mutations results in cell death. The presence of one of these mutations in cancer cells but not in normal cells can therefore create opportunities to selectively kill cancer cells by mimicking the effect of the second genetic mutation with targeted therapy. Here, we summarize strategies that can be used to identify synthetic lethal interactions for anticancer drug discovery, describe examples of such interactions that are currently being investigated in preclinical and clinical studies of targeted anticancer therapies, and discuss the challenges of realizing the full potential of such therapies.

Methodological approaches in application of synthetic lethality screening towards anticancer therapy

A promising direction in the development of selective less toxic cancer drugs is the usage of synthetic lethality concept. The availability of large-scale synthetic low-molecular-weight chemical libraries has allowed HTS for compounds synergistic lethal with defined human cancer aberrations in activated oncogenes or tumour suppressor genes. The search for synthetic lethal chemicals in human/mouse tumour cells is greatly aided by a prior knowledge of relevant signalling and DNA repair pathways, allowing for educated guesses on the preferred potential therapeutic targets. The recent generation of human/rodents genome-wide siRNAs, and shRNA-expressing libraries, should further advance this more focused approach to cancer drug discovery.

The concept of synthetic lethality in the context of anticancer therapy

Two genes are synthetic lethal if mutation of either alone is compatible with viability but mutation of both leads to death. So, targeting a gene that is synthetic lethal to a cancer-relevant mutation should kill only cancer cells and spare normal cells. Synthetic lethality therefore provides a conceptual framework for the development of cancer-specific cytotoxic agents. This paradigm has not been exploited in the past because there were no robust methods for systematically identifying synthetic lethal genes. This is changing as a result of the increased availability of chemical and genetic tools for perturbing gene function in somatic cells.

shRNA-mediated RNA interference as a tool for genetic synthetic lethality screening in mouse embryo fibroblasts

Previously, we demonstrated the establishment of synthetic lethality screening in cultured somatic human cells, or mouse embryo fibroblasts (MEFs), for chemicals or mutant genes synergistically lethal with a mutated gene of interest. Here, we show in MEFs that the usage of RNA interference-based genetic suppressor elements encoding short hairpin RNAs (shRNAs) enables for genetic synthetic lethality screening at a frequency much higher than that achieved before with short truncated sense and antisense RNAs. These findings open up the possibility of using in mammalian cells genome-wide shRNA libraries for genetic synthetic lethality screening at the multi-gene level.

Development through the eyes of functional genomics

In many of the model organisms used to study development, it is becoming relatively routine to carry out global analyses of gene function. These analyses take many forms, from microarray analyses to the construction of physical interaction maps to the systematic analyses of loss-of-function phenotypes. Such large-scale datasets can be integrated to generate complex gene networks, and we explore how these gene networks can contribute to an understanding of developmental pathways. In particular, we examine how combining large-scale expression experiments and gene networks may move us towards a molecular description of the events of development, embodied in a succession of stage-specific subnetworks sampled from an organism's overall gene network.

Complex phenotypic assays in high-throughput screening

High-throughput screening (HTS), systematically testing thousands of small molecules to find candidates for lead optimization, primarily involves exposure of purified proteins to arrayed collections of small molecules. More complex phenotypic assays, such as cell-based or whole-organism assays, traditionally have flanked HTS, preceding it to validate new therapeutic targets, and following it to characterize new lead compounds in cellular contexts. Recently, however, cell- and organism-based phenotypic assays have increasingly been adopted as a primary screening platform for annotating small molecules.

A high-throughput, homogeneous microplate assay for agents that kill mammalian tissue culture cells

Screens for cytostasis/cytoxicity have considerable value for the discovery of therapeutic agents and the investigation of the biology of apoptosis. For instance, genetic screens for proteins, protein fragments, peptides, RNAs, or chemicals that kill tissue culture cells may aid in identifying new cancer therapeutic targets. A microplate assay for cell death is needed to achieve throughputs sufficient to sift through thousands of agents from expression or chemical libraries. The authors describe a homogeneous assay for cell death in tissue culture cells compatible with 96- or 384-well plates. In combination with a previously described system for retroviral packaging and transduction, nearly 6000 expression library clones could be screened per week in a 96-well plate format. The screening system may also prove useful for chemical screens.

Characterization of the depletion of 2-C-methyl-D-erythritol-2,4-cyclodiphosphate synthase in Escherichia coli and Bacillus subtilis

The ispF gene product in Escherichia coli has been shown to catalyze the formation of 2-C-methyl-D-erythritol 2,4-cyclodiphosphate (MEC) in the deoxyxylulose (DOXP) pathway for isoprenoid biosynthesis. In this work, the E. coli gene ispF and its Bacillus subtilis orthologue, yacN, were deleted and conditionally complemented by expression of these genes from distant loci in the respective organisms. In E. coli, complementation was achieved through integration of ispF at the araBAD locus with control from the arabinose-inducible araBAD promoter, while in B. subtilis, yacN was placed at amyE under control of the xylose-inducible xylA promoter. In both cases, growth was severely retarded in the absence of inducer, consistent with these genes being essential for survival. E. coli cells depleted of MEC synthase revealed a filamentous phenotype. This was in contrast to the depletion of MEC synthase in B. subtilis, which resulted in a loss of rod shape, irregular septation, multicompartmentalized cells, and thickened cell walls. To probe the nature of the predominant deficiency of MEC synthase-depleted cells, we investigated the sensitivity of these conditionally complemented mutants, grown with various concentrations of inducer, to a wide variety antibiotics. Synthetic lethal behavior in MEC synthase-depleted cells was prevalent for cell wall-active antibiotics.