Modeling synthetic lethality

Background  

Synthetic lethality defines a genetic interaction where the combination of mutations in two or more genes leads to cell death. The implications of synthetic lethal screens have been discussed in the context of drug development as synthetic lethal pairs could be used to selectively kill cancer cells, but leave normal cells relatively unharmed. A challenge is to assess genome-wide experimental data and integrate the results to better understand the underlying biological processes. We propose statistical and computational tools that can be used to find relationships between synthetic lethality and cellular organizational units.     

Synthetic Lethal Targeting of Superoxide Dismutase 1 Selectively Kills RAD54B-Deficient Colorectal Cancer Cells

Synthetic lethality is a rational approach to identify candidate drug targets for selective killing of cancer cells harboring somatic mutations that cause chromosome instability (CIN). To identify a set of the most highly connected synthetic lethal partner genes in yeast for subsequent testing in mammalian cells, we used the entire set of 692 yeast CIN genes to query the genome-wide synthetic lethal datasets. Hierarchical clustering revealed a highly connected set of synthetic lethal partners of yeast genes whose human orthologs are somatically mutated in colorectal cancer. Testing of a small matrix of synthetic lethal gene pairs in mammalian cells suggested that members of a pathway that remove reactive oxygen species that cause DNA damage would be excellent candidates for further testing. We show that the synthetic lethal interaction between budding yeast rad54 and sod1 is conserved within a human colorectal cancer context. Specifically, we demonstrate RAD54B-deficient cells are selectively killed relative to controls via siRNA-based silencing and chemical inhibition and further demonstrate that this interaction is conserved in an unrelated cell type. We further show that the DNA double strand breaks, resulting from increased reactive oxygen species following SOD1 inhibition, persist within the RAD54B-deficient cells and result in apoptosis. Collectively, these data identify SOD1 as a novel candidate cancer drug target and suggest that SOD1 inhibition may have broad-spectrum applicability in a variety of tumor types exhibiting RAD54B deficiencies.     

Genetic interaction motif finding by expectation maximization – a novel statistical model for inferring gene modules from synthetic lethality

Background  

Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership in a single protein complex) may be inferred between genes that share synthetic lethal interaction partners than genes that are directly synthetic lethal. Probabilistic algorithms that identify gene modules based on motif discovery are highly appropriate for the analysis of synthetic lethal genetic interaction data and have great potential in integrative analysis of heterogeneous datasets.     

Studying synthetic lethal interactions in the zebrafish system: insight into disease genes and mechanisms

The post-genomic era is marked by a pressing need to functionally characterize genes through understanding gene-gene interactions, as well as interactions between biological pathways. Exploiting a phenomenon known as synthetic lethality, in which simultaneous loss of two interacting genes leads to loss of viability, aids in the investigation of these interactions. Although synthetic lethal screening is a powerful technique that has been used with great success in many model organisms, including Saccharomyces cerevisiae, Drosophila melanogaster and Caenorhabditis elegans, this approach has not yet been applied in the zebrafish, Danio rerio. Recently, the zebrafish has emerged as a valuable system to model many human disease conditions; thus, the ability to conduct synthetic lethal screening using zebrafish should help to uncover many unknown disease-gene interactions. In this article, we discuss the concept of synthetic lethality and provide examples of its use in other model systems. We further discuss experimental approaches by which the concept of synthetic lethality can be applied to the zebrafish to understand the functions of specific genes.     

Identification of synthetic lethality based on a functional network by using machine learning algorithms

Synthetic lethality is the synthesis of mutations leading to cell death. Tumor-specific synthetic lethality has been targeted in research to improve cancer therapy. With the advances of techniques in molecular biology, such as RNAi and CRISPR/Cas9 gene editing, efforts have been made to systematically identify synthetic lethal interactions, especially for frequently mutated genes in cancers. However, elucidating the mechanism of synthetic lethality remains a challenge because of the complexity of its influencing conditions. In this study, we proposed a new computational method to identify critical functional features that can accurately predict synthetic lethal interactions. This method incorporates several machine learning algorithms and encodes protein-coding genes by an enrichment system derived from gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways to represent their functional features. We built a random forest-based prediction engine by using 2120 selected features and obtained a Matthews correlation coefficient of 0.532. We examined the top 15 features and found that most of them have potential roles in synthetic lethality according to previous studies. These results demonstrate the ability of our proposed method to predict synthetic lethal interactions and provide a basis for further characterization of these particular genetic combinations.     

Isolation of synthetic lethal mutations in the rsm1-null mutant of fission yeast

To identify mutations in genes that are genetically linked to rsm1, we performed a synthetic lethal genetic screen in the fission yeast, Schizosaccharomyces pombe. Four mutations that showed synthetic lethality in combination with the rsm1null allele were isolated from approximately 320,000 colonies and defined in three complementation groups. One mutant (SLrsm1) exhibited a significant accumulation of poly(A)⁺ RNA in the nucleus under synthetic lethal conditions, while the rest had no mRNA export defects. In addition, some genes (spmex67, rae1, or mlo3) required for mRNA export complemented the growth defects of the identified mutants. These results suggest that the isolated mutants contain mutations in genes that are involved in mRNA export and/or pre-mRNA retention.     

Genetics and Lineage-Specific Evolution of a Lethal Hybrid Incompatibility Between Drosophila mauritiana and Its Sibling Species

The Dobzhansky–Muller model posits that intrinsic postzygotic reproductive isolation—the sterility or lethality of species hybrids—results from the evolution of incompatible epistatic interactions between species: favorable or neutral alleles that become fixed in the genetic background of one species can cause sterility or lethality in the genetic background of another species. The kind of hybrid incompatibility that evolves between two species, however, depends on the particular evolutionary history of the causative substitutions. An allele that is functionally derived in one species can be incompatible with an allele that is functionally derived in the other species (a derived-derived hybrid incompatibility). But an allele that is functionally derived in one species can also be incompatible with an allele that has retained the ancestral state in the other species (a derived-ancestral hybrid incompatibility). The relative abundance of such derived-derived vs. derived-ancestral hybrid incompatibilities is unknown. Here, we characterize the genetics and evolutionary history of a lethal hybrid incompatibility between Drosophila mauritiana and its two sibling species, D. sechellia and D. simulans. We show that a hybrid lethality factor(s) in the pericentric heterochromatin of the D. mauritiana X chromosome, hybrid lethal on the X (hlx), is incompatible with a factor(s) in the same small autosomal region from both D. sechellia and D. simulans, Suppressor of hlx [Su(hlx)]. By combining genetic and phylogenetic information, we infer that hlx-Su(hlx) hybrid lethality is likely caused by a derived-ancestral incompatibility, a hypothesis that can be tested directly when the genes are identified.     

The Role of Protein Interactions in Mediating Essentiality and Synthetic Lethality

Genes are characterized as essential if their knockout is associated with a lethal phenotype, and these “essential genes” play a central role in biological function. In addition, some genes are only essential when deleted in pairs, a phenomenon known as synthetic lethality. Here we consider genes displaying synthetic lethality as “essential pairs” of genes, and analyze the properties of yeast essential genes and synthetic lethal pairs together. As gene duplication initially produces an identical pair or sets of genes, it is often invoked as an explanation for synthetic lethality. However, we find that duplication explains only a minority of cases of synthetic lethality. Similarly, disruption of metabolic pathways leads to relatively few examples of synthetic lethality. By contrast, the vast majority of synthetic lethal gene pairs code for proteins with related functions that share interaction partners. We also find that essential genes and synthetic lethal pairs cluster in the protein-protein interaction network. These results suggest that synthetic lethality is strongly dependent on the formation of protein-protein interactions. Compensation by duplicates does not usually occur mainly because the genes involved are recent duplicates, but is more commonly due to functional similarity that permits preservation of essential protein complexes. This unified view, combining genes that are individually essential with those that form essential pairs, suggests that essentiality is a feature of physical interactions between proteins protein-protein interactions, rather than being inherent in gene and protein products themselves.     

Identification of embryonic lethal genes in humans by autozygosity mapping and exome sequencing in consanguineous families

BackgroundIdentifying genetic variants that lead to discernible phenotypes is the core of Mendelian genetics. An approach that considers embryonic lethality as a bona fide Mendelian phenotype has the potential to reveal novel genetic causes, which will further our understanding of early human development at a molecular level. Consanguineous families in which embryonic lethality segregates as a recessive Mendelian phenotype offer a unique opportunity for high throughput novel gene discovery as has been established for other recessive postnatal phenotypes.ResultsWe have studied 24 eligible families using autozygosity mapping and whole-exome sequencing. In addition to revealing mutations in genes previously linked to embryonic lethality in severe cases, our approach revealed seven novel candidate genes (THSD1, PIGC, UBN1, MYOM1, DNAH14, GALNT14, and FZD6). A founder mutation in one of these genes, THSD1, which has been linked to vascular permeability, accounted for embryonic lethality in three of the study families. Unlike the other six candidate genes, we were able to identify a second mutation in THSD1 in a family with a less severe phenotype consisting of hydrops fetalis and persistent postnatal edema, which provides further support for the proposed link between this gene and embryonic lethality.ConclusionsOur study represents an important step towards the systematic analysis of “embryonic lethal genes” in humans.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0681-6) contains supplementary material, which is available to authorized users.     

Hybrid lethality caused by two complementary dominant genes in cabbage (<Emphasis Type="Italic">Brassica oleracea</Emphasis> L.)

Hybrid lethality, a type of postzygotic reproductive barrier, is important for species. Discovering novel hybrid lethality cases and analyzing corresponding causal genes may provide new insights into the establishment and maintenance of reproductive isolation. In this study, we observed the hybrid lethality phenomena in a cross between two cabbage inbred lines, 09-211 and 09-222. Genetic analysis revealed that the hybrid lethality was controlled by two complementary dominant genes, BolC.HL1.a and BolC.HL2.a, from 09-211 and 09-222, respectively. Further analysis indicated that the two genes conform to the Bateson-Dobzhansky-Muller model. Fine mapping of hybrid lethal genes revealed that BolC.HL1.a was located on the C01 chromosome by Indels HL132 and HL134, with a genetic distance of 0.2 and 0.1 cM, respectively. The interval distance between the two markers was 101 kb. BolC.HL2.a was fine-mapped on the C04 chromosome by HL235 and HL234 at a distance of 0.3 and 0.3 cM, respectively. The physical distance was 70 kb. These findings lay the foundation for cloning the hybrid lethality genes in the future and contribute to our understanding of the molecular and evolutionary mechanisms of hybrid lethality in Brassica oleracea.     

Synthetic lethal interactions for the development of cancer therapeutics: biological and methodological advancements

Synthetic lethal interaction is defined as a combination of two mutations that is lethal when present in the same cell; each individual mutation is non-lethal. Synthetic lethal interactions attract attention in cancer research fields since the discovery of synthetic lethal genes with either oncogenes or tumor suppressor genes (TSGs) provides novel cancer therapeutic targets. Due to the selective lethal effect on cancer cells harboring specific genetic alterations, it is expected that targeting synthetic lethal genes would provide wider therapeutic windows compared with cytotoxic chemotherapeutics. Here, we review the current status of the application of synthetic lethal screening in cancer research fields from biological and methodological viewpoints. Very recent studies seeking to identify synthetic lethal genes with K-RAS and p53, which are known to be the most frequently occurring oncogenes and TSGs, respectively, are introduced. Among the accumulating amount of research on synthetic lethal interactions, the synthetic lethality between BRCA1/2 and PARP1 inhibition has been clinically proven. Thus, both preclinical and clinical data showing a preferential anti-tumor effect on BRCA1/2 deficient tumors by a PARP1 inhibitor are the best examples of the synthetic lethal approach of cancer therapeutics. Finally, methodological progress regarding synthetic lethal screening, including barcode shRNA screening and in vivo synthetic lethal screening, is described. Given the fact that an increasing number of synthetic lethal genes for major cancerous genes have been validated in preclinical studies, this intriguing approach awaits clinical verification of preferential benefits for cancer patients with specific genetic alterations as a clear predictive factor for tumor response.     

Cross-Species Functional Genomic Analysis Identifies Resistance Genes of the Histone Deacetylase Inhibitor Valproic Acid

The mechanisms of successful epigenetic reprogramming in cancer are not well characterized as they involve coordinated removal of repressive marks and deposition of activating marks by a large number of histone and DNA modification enzymes. Here, we have used a cross-species functional genomic approach to identify conserved genetic interactions to improve therapeutic effect of the histone deacetylase inhibitor (HDACi) valproic acid, which increases survival in more than 20% of patients with advanced acute myeloid leukemia (AML). Using a bidirectional synthetic lethality screen revealing genes that increased or decreased VPA sensitivity in C. elegans, we identified novel conserved sensitizers and synthetic lethal interactors of VPA. One sensitizer identified as a conserved determinant of therapeutic success of HDACi was UTX (KDM6A), which demonstrates a functional relationship between protein acetylation and lysine-specific methylation. The synthetic lethal screen identified resistance programs that compensated for the HDACi-induced global hyper-acetylation, and confirmed MAPKAPK2, HSP90AA1, HSP90AB1 and ACTB as conserved hubs in a resistance program for HDACi that are drugable in human AML cell lines. Hence, these resistance hubs represent promising novel targets for refinement of combinatorial epigenetic anti-cancer therapy.     

Identification of Druggable Cancer Driver Genes Amplified across TCGA Datasets

The Cancer Genome Atlas (TCGA) projects have advanced our understanding of the driver mutations, genetic backgrounds, and key pathways activated across cancer types. Analysis of TCGA datasets have mostly focused on somatic mutations and translocations, with less emphasis placed on gene amplifications. Here we describe a bioinformatics screening strategy to identify putative cancer driver genes amplified across TCGA datasets. We carried out GISTIC2 analysis of TCGA datasets spanning 14 cancer subtypes and identified 461 genes that were amplified in two or more datasets. The list was narrowed to 73 cancer-associated genes with potential “druggable” properties. The majority of the genes were localized to 14 amplicons spread across the genome. To identify potential cancer driver genes, we analyzed gene copy number and mRNA expression data from individual patient samples and identified 40 putative cancer driver genes linked to diverse oncogenic processes. Oncogenic activity was further validated by siRNA/shRNA knockdown and by referencing the Project Achilles datasets. The amplified genes represented a number of gene families, including epigenetic regulators, cell cycle-associated genes, DNA damage response/repair genes, metabolic regulators, and genes linked to the Wnt, Notch, Hedgehog, JAK/STAT, NF-KB and MAPK signaling pathways. Among the 40 putative driver genes were known driver genes, such as EGFR, ERBB2 and PIK3CA. Wild-type KRAS was amplified in several cancer types, and KRAS-amplified cancer cell lines were most sensitive to KRAS shRNA, suggesting that KRAS amplification was an independent oncogenic event. A number of MAP kinase adapters were co-amplified with their receptor tyrosine kinases, such as the FGFR adapter FRS2 and the EGFR family adapter GRB7. The ubiquitin-like ligase DCUN1D1 and the histone methyltransferase NSD3 were also identified as novel putative cancer driver genes. We discuss the patient tailoring implications for existing cancer drug targets and we further discuss potential novel opportunities for drug discovery efforts.     

Mapping genetically compensatory pathways from synthetic lethal interactions in yeast

Background

Synthetic lethal genetic interaction analysis has been successfully applied to predicting the functions of genes and their pathway identities. In the context of synthetic lethal interaction data alone, the global similarity of synthetic lethal interaction patterns between two genes is used to predict gene function. With physical interaction data, such as protein-protein interactions, the enrichment of physical interactions within subsets of genes and the enrichment of synthetic lethal interactions between those subsets of genes are used as an indication of compensatory pathways.

Result

In this paper, we propose a method of mapping genetically compensatory pathways from synthetic lethal interactions. Our method is designed to discover pairs of gene-sets in which synthetic lethal interactions are depleted among the genes in an individual set and where such gene-set pairs are connected by many synthetic lethal interactions. By its nature, our method could select compensatory pathway pairs that buffer the deleterious effect of the failure of either one, without the need of physical interaction data. By focusing on compensatory pathway pairs where genes in each individual pathway have a highly homogenous cellular function, we show that many cellular functions have genetically compensatory properties.

Conclusion

We conclude that synthetic lethal interaction data are a powerful source to map genetically compensatory pathways, especially in systems lacking physical interaction information, and that the cellular function network contains abundant compensatory properties.     

Hyperactivated Wnt Signaling Induces Synthetic Lethal Interaction with Rb Inactivation by Elevating TORC1 Activities

Inactivation of the Rb tumor suppressor can lead to increased cell proliferation or cell death depending on specific cellular context. Therefore, identification of the interacting pathways that modulate the effect of Rb loss will provide novel insights into the roles of Rb in cancer development and promote new therapeutic strategies. Here, we identify a novel synthetic lethal interaction between Rb inactivation and deregulated Wg/Wnt signaling through unbiased genetic screens. We show that a weak allele of axin, which deregulates Wg signaling and increases cell proliferation without obvious effects on cell fate specification, significantly alters metabolic gene expression, causes hypersensitivity to metabolic stress induced by fasting, and induces synergistic apoptosis with mutation of fly Rb ortholog, rbf. Furthermore, hyperactivation of Wg signaling by other components of the Wg pathway also induces synergistic apoptosis with rbf. We show that hyperactivated Wg signaling significantly increases TORC1 activity and induces excessive energy stress with rbf mutation. Inhibition of TORC1 activity significantly suppressed synergistic cell death induced by hyperactivated Wg signaling and rbf inactivation, which is correlated with decreased energy stress and decreased induction of apoptotic regulator expression. Finally the synthetic lethality between Rb and deregulated Wnt signaling is conserved in mammalian cells and that inactivation of Rb and APC induces synergistic cell death through a similar mechanism. These results suggest that elevated TORC1 activity and metabolic stress underpin the evolutionarily conserved synthetic lethal interaction between hyperactivated Wnt signaling and inactivated Rb tumor suppressor.     

Inhibiting JNK Dephosphorylation and Induction of Apoptosis by Novel Anticancer Agent NSC-741909 in Cancer Cells

NSC-741909 is a recently identified novel anticancer agent that suppresses the growth of several NCI-60 cancer cell lines with a unique anticancer spectrum. However, its molecular mechanisms remain unknown. To determine the molecular mechanisms of NSC-741909-induced antitumor activity, we analyzed the changes of 77 protein biomarkers in a sensitive lung cancer cell line after treatment with this compound by using reverse-phase protein microarray. The results showed that phosphorylation of mitogen-activated protein (MAP) kinases (P38 MAPK, ERK, and JNK) were persistently elevated by the treatment with NSC-741909. However, only the JNK-specific inhibitor SP600125 effectively blocked the apoptosis induced by NSC-741909. Moreover, NSC-741909-mediated apoptosis was also blocked by a dominant-negative JNK construct, suggesting that sustained activation of JNK is critical for the apoptosis induction. Further studies revealed that treatment with NSC-741909 suppressed dephosphorylation of JNK and the expression of MAPK phosphatase-1. Thus, NSC-741909-mediated inhibition of JNK dephosphorylation results in sustained JNK activation, which leads to apoptosis in cancer cells.Because of genetic and epigenetic changes in cancer cells, it is possible to identify tumor-selective cytotoxic agents by synthetic lethality screening for compounds that kill isogenic cancer cells but not their normal counterparts (1). The term synthetic lethality was originally used to describe a lethal phenotype caused by mutations of two genes (2), i.e. mutations of the two genes are lethal if they occur together but viable if they occur separately. A synthetically lethal phenotype often indicates that the two genes or two related pathways affect a common essential biologic function. Unfortunately, our current knowledge of molecular networks in normal or cancer cells is not adequate for us to predict what genes are synthetically lethal partners to an oncogene or a mutated tumor suppressor gene. Nevertheless, synthetic lethality screening allows us to identify cytotoxic agents specific for certain cancer cells because a compound targeting to such a partner can be identified by their lethality when administered to cancer cells with elevated activities of a particular oncogene.Using synthetic lethality screening, we recently identified an indole compound (designated oncrasin-1) that kills immortalized and tumorigenic human ovarian epithelial cells expressing mutant K-Ras but not cells expressing wild-type Ras genes (3). Furthermore, this compound effectively induced apoptosis at low micromolar or nanomolar concentrations in a variety of lung cancer cells with K-Ras mutations but did not kill cells with wild-type Ras genes. Molecular characterization revealed that oncrasin-1 can induce abnormal aggregation of protein kinase C-ι in the nucleus of oncrasin-sensitive cells but not in oncrasin-resistant cells and that oncrasin-1-induced apoptosis was blocked by siRNA³ of K-Ras or protein kinase C-ι (3), demonstrating that oncrasin-1 is synthetically lethal for K-Ras and protein kinase C-ι, one of the downstream effectors of Ras signaling pathways (4). Our search for oncrasin-1 analogues identified several active compounds with similar chemical structures. Testing of one of the oncrasin-1 analogues, oncrasin-60 (NSC-741909), on NCI-60 cancer cell lines showed that it is highly active against several cell lines derived from lung, colon, breast, ovary, and kidney cancers and that it lies outside the category of adequately studied classes of antitumor agents, suggesting that those compounds could be novel anticancer agents. However, the mechanisms of apoptosis induction by oncrasin compounds remain to be characterized. Here, we used reverse-phase protein array to determine molecular changes induced by NSC-741909 in a sensitive cell line. Our results indicated that sustained c-Jun N-terminal protein kinase (JNK) activation caused by suppression of JNK dephosphorylation contributes to NSC-741909-induced apoptosis.     

Mitogenome evidence for the existence of cryptic species in Coelomactra antiquata

Cryptic species which improve our understanding of species diversity and evolutionary histories within marine animals have been increasingly revealed in the marine realm. Coelomactra antiquate is an important commercial bivalve species, but has been suffering from severe population decline due to over-exploitation and deterioration of environmental conditions. To test the hypothesis that cryptic species might exist in C. antiquate presented in previous study, four complete mitogenomes of C. antiquate from northern and southern China were determined here. Comprehensive comparative analysis of the mitochondrial genomes of C. antiquate between northern and southern population reveals significant differences in genome composition, protein coding genes, tRNA genes, non-coding regions, genetic divergence and phylogenetic analysis. The results provide strong mitogenome evidence for the existence of cryptic species in C. antiquate. Besides, our results also support that comprehensive comparative analysis of mtDNA represents an accessible and powerful tool to identify cryptic species.     

An RNA Interference Lethality Screen of the Human Druggable Genome to Identify Molecular Vulnerabilities in Epithelial Ovarian Cancer

Targeted therapies have been used to combat many tumor types; however, few have effectively improved the overall survival in women with epithelial ovarian cancer, begging for a better understanding of this deadly disease and identification of essential drivers of tumorigenesis that can be targeted effectively. Therefore, we used a loss-of-function screening approach to help identify molecular vulnerabilities that may represent key points of therapeutic intervention. We employed an unbiased high-throughput lethality screen using a 24,088 siRNA library targeting over 6,000 druggable genes and studied their effects on growth and/or survival of epithelial ovarian cancer (EOC) cell lines. The top 300 “hits” affecting the viability of A1847 cells were rescreened across additional EOC cell lines and non-tumorigenic, human immortalized ovarian epithelial cell lines. Fifty-three gene candidates were found to exhibit effects in all tumorigenic cell lines tested. Extensive validation of these hits refined the list to four high quality candidates (HSPA5, NDC80, NUF2, and PTN). Mechanistic studies show that silencing of three genes leads to increased apoptosis, while HSPA5 silencing appears to alter cell growth through G1 cell cycle arrest. Furthermore, two independent gene expression studies show that NDC80, NUF2 and PTN were significantly aberrantly overexpressed in serous adenocarcinomas. Overall, our functional genomics results integrated with the genomics data provide an important unbiased avenue towards the identification of prospective therapeutic targets for drug discovery, which is an urgent and unmet clinical need for ovarian cancer.