Synthetic lethality and synergetic effect: the effective strategies for therapy of IDH-mutated cancers

AbstractMutant isocitrate dehydrogenase 1/2 (mIDH1/2) gain a novel function for the conversion of α-ketoglutarate (α-KG) to oncometabolite R-2-hydroxyglutarate (R-2-HG). Two molecular entities namely enasidenib (AG-221) and ivosidenib (AG-120) targeting mIDH2 and mIDH1 respectively, have already been approved by FDA for the treatment of relapsed/refractory acute myeloid leukemia (R/R AML). However, the low responses, drug-related adverse effects, and most significantly, the clinically-acquired resistance of AG-221 and AG-120 has shown great influence on their clinical application. Therefore, searching for novel therapeutic strategies to enhance tumor sensitivity, reduce drug-related side effects, and overcome drug resistance have opened a new research field for defeating IDH-mutated cancers. As the effective methods, synthetic lethal interactions and synergetic therapies are extensively investigated in recent years for the cure of different cancers. In this review, the molecules displaying synergetic effects with mIDH1/2 inhibitors, as well as the targets showing relevant synthetic lethal interactions with mIDH1/2 are described emphatically. On these foundations, we discuss the opportunities and challenges for translating these strategies into clinic to combat the defects of existing IDH inhibitors.

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A network-based approach to integrate nutrient environment in the prediction of synthetic lethality in cancer metabolism

10.1101/2021.09.01.458495 ◽

2021 ◽

Author(s):

Iñigo Apaolaza ◽

Edurne San José-Enériz ◽

Luis Valcarcel ◽

Xabier Agirre ◽

Felipe Prosper ◽

...

Keyword(s):

Cancer Metabolism ◽

Synthetic Lethality ◽

Experimental Proof ◽

Synthetic Lethal ◽

New Family ◽

Novel Approach ◽

Synthetic Lethal Interactions ◽

Nutrient Environment ◽

Tumor Environment ◽

Definition Of

Synthetic Lethality (SL) is a promising concept in cancer research. A number of computational methods have been developed to predict SL in cancer metabolism, among which our network-based computational approach, based on genetic Minimal Cut Sets (gMCSs), can be found. A major challenge of these approaches to SL is to systematically consider tumor environment, which is particularly relevant in cancer metabolism. Here, we propose a novel definition of SL for cancer metabolism that integrates genetic interactions and nutrient availability in the environment. We extend our gMCSs approach to determine this new family of metabolic synthetic lethal interactions. A computational and experimental proof-of-concept is presented for predicting the lethality of dihydrofolate reductase inhibition in different environments. Finally, our novel approach is applied to identify extracellular nutrient dependences of tumor cells, elucidating cholesterol and myo-inositol depletion as potential vulnerabilities in different malignancies.

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SL-BioDP: Multi-Cancer Interactive Tool for Prediction of Synthetic Lethality and Response to Cancer Treatment

Cancers ◽

10.3390/cancers11111682 ◽

2019 ◽

Vol 11 (11) ◽

pp. 1682 ◽

Cited By ~ 4

Author(s):

Xiang Deng ◽

Shaoli Das ◽

Kristin Valdez ◽

Kevin Camphausen ◽

Uma Shankavaram

Keyword(s):

Clinical Relevance ◽

Synthetic Lethality ◽

Drug Efficacy ◽

Synthetic Lethal ◽

Cancer Data ◽

Cancer Pathways ◽

Kaplan Meier ◽

Survival Pathways ◽

Synthetic Lethal Interactions ◽

Cancer Genome Atlas

Synthetic lethality exploits the phenomenon that a mutation in a cancer gene is often associated with new vulnerability which can be uniquely targeted therapeutically, leading to a significant increase in favorable outcome. DNA damage and survival pathways are among the most commonly mutated networks in human cancers. Recent data suggest that synthetic lethal interactions between a tumor defect and a DNA repair pathway can be used to preferentially kill tumor cells. We recently published a method, DiscoverSL, using multi-omic cancer data, that can predict synthetic lethal interactions of potential clinical relevance. Here, we apply the generality of our models in a comprehensive web tool called Synthetic Lethality Bio Discovery Portal (SL-BioDP) and extend the cancer types to 18 cancer genome atlas cohorts. SL-BioDP enables a data-driven computational approach to predict synthetic lethal interactions from hallmark cancer pathways by mining cancer’s genomic and chemical interactions. Our tool provides queries and visualizations for exploring potentially targetable synthetic lethal interactions, shows Kaplan–Meier plots of clinical relevance, and provides in silico validation using short hairpin RNA (shRNA) and drug efficacy data. Our method would thus shed light on mechanisms of synthetic lethal interactions and lead to the discovery of novel anticancer drugs.

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Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization

BMC Bioinformatics ◽

10.1186/s12859-019-3197-3 ◽

2019 ◽

Vol 20 (S19) ◽

Author(s):

Jiang Huang ◽

Min Wu ◽

Fan Lu ◽

Le Ou-Yang ◽

Zexuan Zhu

Keyword(s):

Matrix Factorization ◽

Drug Targets ◽

Synthetic Lethality ◽

Cancer Therapeutics ◽

The Self ◽

Interaction Data ◽

Synthetic Lethal Interaction ◽

Synthetic Lethal ◽

Interaction Prediction ◽

Synthetic Lethal Interactions

Abstract Background Synthetic lethality has attracted a lot of attentions in cancer therapeutics due to its utility in identifying new anticancer drug targets. Identifying synthetic lethal (SL) interactions is the key step towards the exploration of synthetic lethality in cancer treatment. However, biological experiments are faced with many challenges when identifying synthetic lethal interactions. Thus, it is necessary to develop computational methods which could serve as useful complements to biological experiments. Results In this paper, we propose a novel graph regularized self-representative matrix factorization (GRSMF) algorithm for synthetic lethal interaction prediction. GRSMF first learns the self-representations from the known SL interactions and further integrates the functional similarities among genes derived from Gene Ontology (GO). It can then effectively predict potential SL interactions by leveraging the information provided by known SL interactions and functional annotations of genes. Extensive experiments on the synthetic lethal interaction data downloaded from SynLethDB database demonstrate the superiority of our GRSMF in predicting potential synthetic lethal interactions, compared with other competing methods. Moreover, case studies of novel interactions are conducted in this paper for further evaluating the effectiveness of GRSMF in synthetic lethal interaction prediction. Conclusions In this paper, we demonstrate that by adaptively exploiting the self-representation of original SL interaction data, and utilizing functional similarities among genes to enhance the learning of self-representation matrix, our GRSMF could predict potential SL interactions more accurately than other state-of-the-art SL interaction prediction methods.

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Cross-species synthetic lethal interaction screening as a strategy for the identification of novel therapeutic targets in cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.11105 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. 11105-11105

Author(s):

John P. Shen ◽

Rohith Srivas ◽

Ana Bojorquez-Gomez ◽

Katherine Licon ◽

Jian Feng Li ◽

...

Keyword(s):

Tumor Suppressor ◽

Tumor Suppressor Genes ◽

Synthetic Lethality ◽

Control Cell ◽

Therapeutic Targets ◽

Model Organisms ◽

Suppressor Genes ◽

Synthetic Lethal ◽

Synthetic Lethal Interactions ◽

Novel Therapeutic

11105 Background: Mutation, deletion, or epigenetic silencing of tumor suppressor genes is a near universal feature of malignant cells. However, therapeutic strategies for restoring the function of mutated or deleted genes have proven difficult. Synthetic lethality, an event in which the simultaneous perturbation of two genes results in cellular death, has been proposed as a method to selectively target cancer cells. Identifying and pharmacologically inhibiting proteins encoded by genes that are synthetic lethal with known tumor suppressor mutations should result in selective toxicity to tumor cells. Methods: To identify candidate target proteins we measured all pair-wise genetic interactions between all known orthologs of human tumor suppressor genes (162 genes) and all orthologs of druggable human proteins (~400 genes) in the model organism S. Cerevisiae. Analysis of the data uncovered 2,087 distinct synthetic lethal interactions between a tumor suppressor and druggable gene. A computational algorithm was then developed to identify those interactions which were likely to be conserved in humans based on conservation of the synthetic lethal relationship in the distant fission yeast S. pombe. Results: Our bioinformatic analysis suggested a high probability of conservation of the synthetic lethal interactions between the yeast RAD51 (ortholog of BRCA1) and RAD57 (ortholog of XRCC3) with HDA1 (a histone deacetylase; HDAC). We confirmed this by treating LN428 cells with stable lentiviral knockdown of BRCA1 or XRCC3 with the HDAC inhibitors vorinostat (SAHA) and entinostat (MS-275). Both the BRCA1 and XRCC3 knockdown cell lines were significantly more sensitive to HDAC inhibition relative to wild-type (non-silencing lentiviral control) cell line (Table). Conclusions: These results demonstrate that high-throughput approaches for screening synthetic lethal interactions in model organisms such as S. cerevisiae and S. pombecan serve as a valuable resource in helping to identify novel therapeutic targets in human cancer. [Table: see text]

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Targeting mutant p53 for cancer therapy: direct and indirect strategies

Journal of Hematology & Oncology ◽

10.1186/s13045-021-01169-0 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Jiahao Hu ◽

Jiasheng Cao ◽

Win Topatana ◽

Sarun Juengpanich ◽

Shijie Li ◽

...

Keyword(s):

Noncoding Rna ◽

Synthetic Lethality ◽

Noncoding Rnas ◽

Research Progress ◽

Mutant P53 ◽

Wild Type ◽

Synthetic Lethal ◽

Therapeutic Benefits ◽

Synthetic Lethal Interactions ◽

Wild Type P53

AbstractTP53 is a critical tumor-suppressor gene that is mutated in more than half of all human cancers. Mutations in TP53 not only impair its antitumor activity, but also confer mutant p53 protein oncogenic properties. The p53-targeted therapy approach began with the identification of compounds capable of restoring/reactivating wild-type p53 functions or eliminating mutant p53. Treatments that directly target mutant p53 are extremely structure and drug-species-dependent. Due to the mutation of wild-type p53, multiple survival pathways that are normally maintained by wild-type p53 are disrupted, necessitating the activation of compensatory genes or pathways to promote cancer cell survival. Additionally, because the oncogenic functions of mutant p53 contribute to cancer proliferation and metastasis, targeting the signaling pathways altered by p53 mutation appears to be an attractive strategy. Synthetic lethality implies that while disruption of either gene alone is permissible among two genes with synthetic lethal interactions, complete disruption of both genes results in cell death. Thus, rather than directly targeting p53, exploiting mutant p53 synthetic lethal genes may provide additional therapeutic benefits. Additionally, research progress on the functions of noncoding RNAs has made it clear that disrupting noncoding RNA networks has a favorable antitumor effect, supporting the hypothesis that targeting noncoding RNAs may have potential synthetic lethal effects in cancers with p53 mutations. The purpose of this review is to discuss treatments for cancers with mutant p53 that focus on directly targeting mutant p53, restoring wild-type functions, and exploiting synthetic lethal interactions with mutant p53. Additionally, the possibility of noncoding RNAs acting as synthetic lethal targets for mutant p53 will be discussed.

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Synthetic-lethal interactions between ATR inhibition and functional genetic and proteomic biomarkers to predict responses in endometriosis-associated cancers.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e18000 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e18000-e18000

Author(s):

Oren Gilad ◽

Dansu Li ◽

Erin George ◽

Rakesh Chettier ◽

Fiona Simpkins ◽

...

Keyword(s):

Synthetic Lethality ◽

In Vivo Studies ◽

Multiple Cancer ◽

Driver Genes ◽

Synthetic Lethal ◽

Cancer Driver ◽

Synthetic Lethal Interactions ◽

Synthetically Lethal

e18000 Background: Endometriosis is a common gynecologic disorder proven to be a precursor to several cancer types. We developed a potent and selective inhibitor (ATRN-119) of a critical DNA damage response (DDR) protein kinase: the ataxia telangiectasia and Rad3-related protein (ATR). Treatment with ATRN-119 is synthetically lethal with multiple cancer-associated changes in DDR pathways, representing a new and effective strategy to treat cancer. The objective of this study is to evaluate the overlap of DDR genes that respond to ATRN-119 and those mutated in endometriosis. Methods: We sequenced the exomes of 2,932 unrelated women with surgically-confirmed endometriosis (GERMLINE) and 274 tissue blocks containing endometriosis lesions (LESION). DNA was extracted using standard methods. Missense and truncation variants were analyzed. These data were compared to analysis of a whole proteome screen for factors that respond to exposure to ATRN-119 and may influence responsiveness to treatment. Factors observed in both methods were considered high-priority biomarker candidates and were experimentally tested for synthetic lethality with ATRN-119 treatment. Results: Analysis of endometriosis patients found 89% of the LESION samples had 2 or more DDR mutations vs 83% of the GERMLINE samples. There is an excess of DDR mutations per sample in LESION (5.5 mutations) vs GERMLINE (3.89 mutations) [p = 4.66x10-6, Mann Whitney test]. In parallel, we identified 92 genes as protein responders to ATRN-119 treatment. Mutations in 21 of these 92 genes show nominal association with surgical endometriosis (p < 0.05). However, of these responsive genes, 18 are known TIER 1 cancer-driver genes and well-characterized mutations were found in three dominant genes in the LESION tissue (ATM, DDB1, and ARID1A). Overall 20% of the patients who’s LESION we examined subsequently developed an endometriosis-associated cancer. Both in vitro and in vivo studies confirmed synthetic-lethal interactions between ATRN-119 treatment and alteration of these genes. Conclusions: The overlap between DDR genes responding to ATRN-119 and those mutated in endometriosis-associated cancer suggest that genetic markers underlying response and resistance will be critical to extend the use of these drugs while increasing efficacy and minimizing toxicities. Furthermore, our data support the inclusion of endometriosis-associated cancer patients in planned ATRN-119 clinical trials.

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Exploiting vulnerabilities of SWI/SNF chromatin remodelling complexes for cancer therapy

Oncogene ◽

10.1038/s41388-021-01781-x ◽

2021 ◽

Author(s):

Marek Wanior ◽

Andreas Krämer ◽

Stefan Knapp ◽

Andreas C. Joerger

Keyword(s):

Therapeutic Strategy ◽

Synthetic Lethality ◽

Chromatin Remodelling ◽

Regulatory Proteins ◽

Chemical Probes ◽

Synthetic Lethal ◽

Anticancer Effects ◽

Synthetic Lethal Interactions ◽

Genomic Studies ◽

Encoding Genes

AbstractMulti-subunit ATPase-dependent chromatin remodelling complexes SWI/SNF (switch/sucrose non-fermentable) are fundamental epigenetic regulators of gene transcription. Functional genomic studies revealed a remarkable mutation prevalence of SWI/SNF-encoding genes in 20–25% of all human cancers, frequently driving oncogenic programmes. Some SWI/SNF-mutant cancers are hypersensitive to perturbations in other SWI/SNF subunits, regulatory proteins and distinct biological pathways, often resulting in sustained anticancer effects and synthetic lethal interactions. Exploiting these vulnerabilities is a promising therapeutic strategy. Here, we review the importance of SWI/SNF chromatin remodellers in gene regulation as well as mechanisms leading to assembly defects and their role in cancer development. We will focus in particular on emerging strategies for the targeted therapy of SWI/SNF-deficient cancers using chemical probes, including proteolysis targeting chimeras, to induce synthetic lethality.

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Chromosomal arrangement of synthetic lethal gene pairs: repulsion or attraction?

10.1101/2020.05.05.078626 ◽

2020 ◽

Author(s):

Sayed-Rzgar Hosseini ◽

Bishoy Wadie ◽

Evangelia Petsalaki

Keyword(s):

Synthetic Lethality ◽

Yeast Genome ◽

Lethal Gene ◽

Bacterial Genomes ◽

Synthetic Lethal ◽

Evolutionary Forces ◽

Gene Pairs ◽

Chromosomal Arrangement ◽

Synthetic Lethal Interactions ◽

2D And 3D

AbstractSynthetic lethal interactions are of paramount importance both in biology and in medicine, and hence increasing efforts have been devoted to their systematic identification. Our previous computational analysis revealed that in prokaryotic species, synthetic lethal genes tend to be further away in chromosomes than random (i.e. repulsion), which was shown to provide bacterial genomes with greater robustness to large-scale DNA deletions. To test the generalizability of this observation in eukaryotic genomes, we leveraged the wealth of experimentally determined synthetic lethal genetic interactions of yeast that are curated in the BioGRID (Biological General Repository for Interaction Datasets) database. We observed an opposite trend that is the genomic proximity of synthetic lethal gene pairs both on the 2D and 3D chromosomal space of the yeast genome (i.e. 2D and 3D attraction). To gain mechanistic insights into the origin of the attraction of synthetic lethal gene pairs in S. cerevisiae, we characterized four classes of genes, in which synthetic lethal interactions are enriched and partly explain the observed patterns of genomic attraction: i) gene pairs operating on the same pathways, 2) co-expressed genes, 3) gene pairs whose protein products physically interact and 4) the paralogs. However, our analysis revealed that the contribution of these four types of genes is not sufficient to fully explain the observed 2D and 3D attraction of synthetic lethal gene pairs and hence its evolutionary origin still remains as an open question.Significance statementUnravelling the organizing principles underlying gene arrangements is one of the fundamental questions of research in evolutionary biology. One understudied aspect of this organization is the relative chromosomal arrangement of synthetic lethal gene pairs. In this study, by analyzing a wealth of synthetic lethality data in yeast, we provide evidence that synthetic lethal gene pairs tend to be attracted to each other both on 2D and 3D chromosomal space of the yeast genome. This observation is in sharp contrast with the repulsion of synthetic lethal (metabolic) gene pairs that we observed previously in bacterial genomes. Characterizing the evolutionary forces underlying this genomic pattern in yeast can open the door towards an evolutionary theory of genome organization in eukaryotes.

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FANCM, BRCA1, and BLM cooperatively resolve the replication stress at the ALT telomeres

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1708065114 ◽

2017 ◽

Vol 114 (29) ◽

pp. E5940-E5949 ◽

Cited By ~ 44

Author(s):

Xiaolei Pan ◽

William C. Drosopoulos ◽

Louisa Sethi ◽

Advaitha Madireddy ◽

Carl L. Schildkraut ◽

...

Keyword(s):

Single Molecule ◽

Mammalian Cells ◽

Synthetic Lethality ◽

Replication Stress ◽

Fragile Sites ◽

Telomere Maintenance ◽

Synthetic Lethal ◽

Synthetic Lethal Interactions ◽

Dna End Resection ◽

Single Molecule Analysis

In the mammalian genome, certain genomic loci/regions pose greater challenges to the DNA replication machinery (i.e., the replisome) than others. Such known genomic loci/regions include centromeres, common fragile sites, subtelomeres, and telomeres. However, the detailed mechanism of how mammalian cells cope with the replication stress at these loci/regions is largely unknown. Here we show that depletion of FANCM, or of one of its obligatory binding partners, FAAP24, MHF1, and MHF2, induces replication stress primarily at the telomeres of cells that use the alternative lengthening of telomeres (ALT) pathway as their telomere maintenance mechanism. Using the telomere-specific single-molecule analysis of replicated DNA technique, we found that depletion of FANCM dramatically reduces the replication efficiency at ALT telomeres. We further show that FANCM, BRCA1, and BLM are actively recruited to the ALT telomeres that are experiencing replication stress and that the recruitment of BRCA1 and BLM to these damaged telomeres is interdependent and is regulated by both ATR and Chk1. Mechanistically, we demonstrated that, in FANCM-depleted ALT cells, BRCA1 and BLM help to resolve the telomeric replication stress by stimulating DNA end resection and homologous recombination (HR). Consistent with their roles in resolving the replication stress induced by FANCM deficiency, simultaneous depletion of BLM and FANCM, or of BRCA1 and FANCM, leads to increased micronuclei formation and synthetic lethality in ALT cells. We propose that these synthetic lethal interactions can be explored for targeting the ALT cancers.

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Viral protein engagement of GBF1 induces host cell vulnerability through synthetic lethality

10.1101/2020.10.12.336487 ◽

2020 ◽

Author(s):

Arti T Navare ◽

Fred D Mast ◽

Jean Paul Olivier ◽

Thierry Bertomeu ◽

Maxwell Neal ◽

...

Keyword(s):

Protein Interactions ◽

Viral Protein ◽

Synthetic Lethality ◽

Host Cells ◽

Loss Of Function ◽

Host Proteins ◽

Synthetic Lethal ◽

Cancer Driver ◽

Synthetic Lethal Interactions ◽

Infected Cells

AbstractViruses co-opt host proteins to carry out their lifecycle. Repurposed host proteins may thus become functionally compromised; a situation analogous to a loss-of-function mutation. We term such host proteins viral-induced hypomorphs. Cells bearing cancer driver loss-of-function mutations have successfully been targeted with drugs perturbing proteins encoded by the synthetic lethal partners of cancer-specific mutations. Synthetic lethal interactions of viral-induced hypomorphs have the potential to be similarly targeted for the development of host-based antiviral therapeutics. Here, we use GBF1, which supports the infection of many RNA viruses, as a proof-of-concept. GBF1 becomes a hypomorph upon interaction with the poliovirus protein 3A. Screening for synthetic lethal partners of GBF1 revealed ARF1 as the top hit, disruption of which, selectively killed cells that synthesize poliovirus 3A. Thus, viral protein interactions can induce hypomorphs that render host cells vulnerable to perturbations that leave uninfected cells intact. Exploiting viral-induced vulnerabilities could lead to broad-spectrum antivirals for many viruses, including SARS-CoV-2.SummaryUsing a viral-induced hypomorph of GBF1, Navare et al., demonstrate that the principle of synthetic lethality is a mechanism to selectively kill virus-infected cells.

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