Network targeting combination therapy of synthetic lethal vulnerabilities in 9p21-deficient glioblastoma: A case report
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PROVIDER: S-EPMC10771271 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature
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Project description:Network targeting of disease-specific nodes represents a useful principle for designing combination cancer therapy. In this case of a patient with relapsed leptomeningeal glioblastoma, comprehensive molecular diagnosis led to the identification of a disease network characterized by multiple disease-specific synthetic lethal vulnerabilities involving DNA repair, REDOX homeostasis, and impaired autophagy which suggested a novel network-targeting combination therapy (NTCT). A treatment regimen consisting of lomustine, olaparib, digoxin, metformin, and high dose intravenous ascorbate was employed using the principle of intra-patient dose escalation to deliver the treatment with adequate safety measures to achieve a definitive clinical result.
| S-EPMC10644375 | biostudies-literature
Project description:The CDH1 gene, encoding the cell adhesion protein E-cadherin, is one of the most frequently mutated genes in gastric cancer and inactivating germline CDH1 mutations are responsible for hereditary diffuse gastric cancer syndrome (HDGC). Using cell viability assays, we identified that breast (MCF10A) and gastric (NCI-N87) cells lacking CDH1 expression are more sensitive to allosteric AKT inhibitors than their CDH1-expressing isogenic counterparts. Apoptosis priming and total apoptosis assays in the isogenic MCF10A cells confirmed the enhanced sensitivity of E-cadherin-null cells to the AKT inhibitors. In addition, two of these inhibitors, ARQ-092 and MK2206, preferentially targeted mouse-derived gastric Cdh1-/- organoids for growth arrest. AKT protein expression and activation (as measured by phosphorylation of serine 473) were differentially regulated in E-cadherin-null MCF10A and NCI-N87 cells, with downregulation in the normal breast cells, but upregulation in the gastric cancer cells. Bioinformatic analysis of the TCGA STAD dataset revealed that AKT3, but not AKT1 or AKT2, is upregulated in the majority of E-cadherin-deficient gastric cancers. In conclusion, allosteric AKT inhibitors represent a promising class of drugs for chemoprevention and chemotherapy of cancers with E-cadherin loss.
| S-EPMC6769709 | biostudies-literature
Project description:Synthetic lethality is a genetic interaction that results in cell death when two genetic deficiencies co-occur but not when either deficiency occurs alone, which can be co-opted for cancer therapeutics. Pairs of paralog genes are among the most straightforward potential synthetic-lethal interactions by virtue of their redundant functions. Here, we demonstrate a paralog-based synthetic lethality by targeting vaccinia-related kinase 1 (VRK1) in glioblastoma (GBM) deficient of VRK2, which is silenced by promoter methylation in approximately two thirds of GBM. Genetic knockdown of VRK1 in VRK2-null or VRK2-methylated cells resulted in decreased activity of the downstream substrate barrier to autointegration factor (BAF), a regulator of post-mitotic nuclear envelope formation. Reduced BAF activity following VRK1 knockdown caused nuclear lobulation, blebbing, and micronucleation, which subsequently resulted in G2-M arrest and DNA damage. The VRK1-VRK2 synthetic-lethal interaction was dependent on VRK1 kinase activity and was rescued by ectopic expression of VRK2. In VRK2-methylated GBM cell line-derived xenograft and patient-derived xenograft models, knockdown of VRK1 led to robust tumor growth inhibition. These results indicate that inhibiting VRK1 kinase activity could be a viable therapeutic strategy in VRK2-methylated GBM.SignificanceA paralog synthetic-lethal interaction between VRK1 and VRK2 sensitizes VRK2-methylated glioblastoma to perturbation of VRK1 kinase activity, supporting VRK1 as a drug discovery target in this disease.
| S-EPMC9627132 | biostudies-literature
Project description:BackgroundPharmacological synergisms are an attractive anticancer strategy. However, with more than 5000 approved-drugs and compounds in clinical development, identifying synergistic treatments represents a major challenge.MethodsHigh-throughput screening was combined with target deconvolution and functional genomics to reveal targetable vulnerabilities in glioblastoma. The role of the top gene hit was investigated by RNA interference, transcriptomics and immunohistochemistry in glioblastoma patient samples. Drug combination screen using a custom-made library of 88 compounds in association with six inhibitors of the identified glioblastoma vulnerabilities was performed to unveil pharmacological synergisms. Glioblastoma 3D spheroid, organotypic ex vivo and syngeneic orthotopic mouse models were used to validate synergistic treatments.FindingsNine targetable vulnerabilities were identified in glioblastoma and the top gene hit RRM1 was validated as an independent prognostic factor. The associations of CHK1/MEK and AURKA/BET inhibitors were identified as the most potent amongst 528 tested pairwise drug combinations and their efficacy was validated in 3D spheroid models. The high synergism of AURKA/BET dual inhibition was confirmed in ex vivo and in vivo glioblastoma models, without detectable toxicity.InterpretationOur work provides strong pre-clinical evidence of the efficacy of AURKA/BET inhibitor combination in glioblastoma and opens new therapeutic avenues for this unmet medical need. Besides, we established the proof-of-concept of a stepwise approach aiming at exploiting drug poly-pharmacology to unveil druggable cancer vulnerabilities and to fast-track the identification of synergistic combinations against refractory cancers.FundingThis study was funded by institutional grants and charities.
| S-EPMC10433015 | biostudies-literature
Project description:BackgroundThe E-cadherin gene (CDH1) is frequently mutated in diffuse gastric cancer and lobular breast cancer, and germline mutations predispose to the cancer syndrome Hereditary Diffuse Gastric Cancer. We are taking a synthetic lethal approach to identify druggable vulnerabilities in CDH1-mutant cancers.MethodsDensity distributions of cell viability data from a genome-wide RNAi screen of isogenic MCF10A and MCF10A-CDH1-/- cells were used to identify protein classes affected by CDH1 mutation. The synthetic lethal relationship between selected protein classes and E-cadherin was characterised by drug sensitivity assays in both the isogenic breast MCF10A cells and CDH1-isogenic gastric NCI-N87. Endocytosis efficiency was quantified using cholera toxin B uptake. Pathway metagene expression of 415 TCGA gastric tumours was statistically correlated with CDH1 expression.ResultsMCF10A-CDH1-/- cells showed significantly altered sensitivity to RNAi inhibition of groups of genes including the PI3K/AKT pathway, GPCRs, ion channels, proteosomal subunit proteins and ubiquitinylation enzymes. Both MCF10A-CDH1-/- and NCI-N87-CDH1-/- cells were more sensitive than wild-type cells to compounds that disrupted plasma membrane composition and trafficking, but showed contrasting sensitivities to inhibitors of actin polymerisation and the chloride channel inhibitor NS3728. The MCF10A-CDH1-/- cell lines showed reduced capacity to endocytose cholera toxin B. Pathway metagene analysis identified 20 Reactome pathways that were potentially synthetic lethal in tumours. Genes involved in GPCR signalling, vesicle transport and the metabolism of PI3K and membrane lipids were strongly represented amongst the candidate synthetic lethal genes.ConclusionsE-cadherin loss leads to disturbances in receptor signalling and plasma membrane trafficking and organisation, creating druggable vulnerabilities.
| S-EPMC6394693 | biostudies-literature
Project description:KRAS is the most commonly mutated oncogene in human cancer. Most KRAS-mutant cancers depend on sustained expression and signaling of KRAS, thus making it a high-priority therapeutic target. Unfortunately, development of direct small molecule inhibitors of KRAS function has been challenging. An alternative therapeutic strategy for KRAS-mutant malignancies involves targeting codependent vulnerabilities or synthetic lethal partners that are preferentially essential in the setting of oncogenic KRAS. KRAS activates numerous effector pathways that mediate proliferation and survival signals. Moreover, cancer cells must cope with substantial oncogenic stress conferred by mutant KRAS. These oncogenic signaling pathways and compensatory coping mechanisms of KRAS-mutant cancer cells form the basis for synthetic lethal interactions. Here, we review the compendium of previously identified codependencies in KRAS-mutant cancers, including the results of numerous functional genetic screens aimed at identifying KRAS synthetic lethal targets. Importantly, many of these vulnerabilities may represent tractable therapeutic opportunities.
| S-EPMC5990478 | biostudies-literature
Project description:Identification of targeted therapies for TNBC is an urgent medical need. Using a drug combination screen reliant on synthetic lethal interactions, we identified clinically relevant combination therapies for different TNBC subtypes. Two drug combinations targeting the BET family were further explored. The first, targeting BET and CXCR2, is specific for mesenchymal TNBC and induces apoptosis, whereas the second, targeting BET and the proteasome, is effective for major TNBC subtypes and triggers ferroptosis. Ferroptosis was induced at low drug doses and was associated with increased cellular iron and decreased glutathione levels, concomitant with reduced levels of GPX4 and key glutathione biosynthesis genes. Further functional studies, analysis of clinical datasets and breast cancer specimens revealed a unique vulnerability of TNBC to ferroptosis inducers, enrichment of ferroptosis gene signature, and differential expression of key proteins that increase labile iron and decrease glutathione levels. This study identified potent combination therapies for TNBC and unveiled ferroptosis as a promising therapeutic strategy.
| S-EPMC7442484 | biostudies-literature
Project description: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.
| S-EPMC3813862 | biostudies-literature
Project description:Cancer is a major cause of death throughout the world, and there is a large need for better and more personalized approaches to combat the disease. Over the past decade, synthetic lethal approaches have been developed that are designed to exploit the aberrant molecular origins (i.e. defective genes) that underlie tumorigenesis. BLM and CHEK2 are two evolutionarily conserved genes that are somatically altered in a number of tumor types. Both proteins normally function in preserving genome stability through facilitating the accurate repair of DNA double strand breaks. Thus, uncovering synthetic lethal interactors of BLM and CHEK2 will identify novel candidate drug targets and lead chemical compounds. Here we identify an evolutionarily conserved synthetic lethal interaction between SOD1 and both BLM and CHEK2 in two distinct cell models. Using quantitative imaging microscopy, real-time cellular analyses, colony formation and tumor spheroid models we show that SOD1 silencing and inhibition (ATTM and LCS-1 treatments), or the induction of reactive oxygen species (2ME2 treatment) induces selective killing within BLM- and CHEK2-deficient cells relative to controls. We further show that increases in reactive oxygen species follow SOD1 silencing and inhibition that are associated with the persistence of DNA double strand breaks, and increases in apoptosis. Collectively, these data identify SOD1 as a novel candidate drug target in BLM and CHEK2 cancer contexts, and further suggest that 2ME2, ATTM and LCS-1 are lead therapeutic compounds warranting further pre-clinical study.
| S-EPMC4695034 | biostudies-literature
Project description:BackgroundA pair of genes is defined as synthetically lethal if defects on both cause the death of the cell but a defect in only one of the two is compatible with cell viability. Ideally, if A and B are two synthetic lethal genes, inhibiting B should kill cancer cells with a defect on A, and should have no effects on normal cells. Thus, synthetic lethality can be exploited for highly selective cancer therapies, which need to exploit differences between normal and cancer cells.ResultsIn this paper, we present a new method for predicting synthetic lethal (SL) gene pairs. As neighbouring genes in the genome have highly correlated profiles of copy number variations (CNAs), our method clusters proximal genes with a similar CNA profile, then predicts mutually exclusive group pairs, and finally identifies the SL gene pairs within each group pairs. For mutual-exclusion testing we use a graph-based method which takes into account the mutation frequencies of different subjects and genes. We use two different methods for selecting the pair of SL genes; the first is based on the gene essentiality measured in various conditions by means of the "Gene Activity Ranking Profile" GARP score; the second leverages the annotations of gene to biological pathways.ConclusionsThis method is unique among current SL prediction approaches, it reduces false-positive SL predictions compared to previous methods, and it allows establishing explicit collateral lethality relationship of gene pairs within mutually exclusive group pairs.
| S-EPMC8126165 | biostudies-literature