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Results for “Synthetic Lethal Mutations”

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At least 19 recordsLinked to original sources

PubMed1992

Synthetic lethal mutations suggest interactions between U5 small nuclear RNA and four proteins required for the second step of splicing.

To investigate the function of the U5 small nuclear ribonucleoprotein (snRNP) in pre-mRNA splicing, we have screened for factors that genetically interact with Saccharomyces cerevisiae U5 snRNA. We isolated trans-acting mutations that exacerbate the phenotypes of conditional alleles of the U5 snRNA and named these genes SLU, for synergistically lethal with U5 snRNA. SLU1 and SLU2 are essential for the first catalytic step of splicing, while SLU7 and SLU4 (an allele of PRP17 [U. Vijayraghavan, M. Company, and J. Abelson, Genes Dev. 3:1206-1216, 1989]) are required only for the second step of splicing. Furthermore, slu4-1 and slu7-1 are lethal in combination with mutations in PRP16 and PRP18, which also function in the second step, but not with mutations in factors required for the first catalytic step, such as PRP8 and PRP4. We infer from these data that SLU4, SLU7, PRP18, PRP16, and the U5 snRNA interact functionally and that a major role of the U5 snRNP is to coordinate a set of factors that are required for the completion of the second catalytic step of splicing.

Base Sequence↗

PubMed2025

Mutations in tumor signaling, metastases, and synthetic lethality establish distinct patterns.

Effective identification of oncogenic mutations is essential for diagnosis, forecasting resistance, and metastasis in remission. It is required for an optimal drug regimen. We develop a framework to discover mutations that co-exist in different oncoproteins, and those that are excluded, likely encoding oncogene-induced senescence. First, mapping the proteins onto pathways assists combinatorial drug selections and helps to detect metastases. Second, it provides the molecular basis for synthetic lethality, to date investigated at the genome level. Our pan-cancer profiles of ~60,000 tumor sequences, detect 3424 co-existing tumor-specific mutations. Mapping them onto pathways indicates that they preferentially promote specific primary tumors. We uncover metastatic mutations and provide metastatic breast-cancer markers. This work not only clarifies the mechanistic basis of intratumor mutational diversity but usefully reveals markers for metastasis in patients' genomes and introduces a novel computational framework for detecting metastasis based on tumor mutational profiles. Mapping the mutations onto pathways provides an invaluable metastasis-targeting resource, guiding drug combinations.

Humans↗

PubMed1990

Sec2 protein contains a coiled-coil domain essential for vesicular transport and a dispensable carboxy terminal domain.

SEC2 function is required at the post-Golgi apparatus stage of the yeast secretory pathway. The SEC2 sequence encodes a protein product of 759 amino acids containing an amino terminal region that is predicted to be in an alpha-helical, coiled-coil conformation. Two temperature-sensitive alleles, sec2-41 and sec2-59, encode proteins truncated by opal stop codons and are suppressible by an opal tRNA suppressor. Deletion analysis indicates that removal of the carboxyl terminal 251 amino acids has no apparent phenotype, while truncation of 368 amino acids causes temperature sensitivity. The amino terminal half of the protein, containing the putative coiled-coil domain, is essential at all temperatures. Sec2 protein is found predominantly in the soluble fraction and displays a native molecular mass of greater than 500 kD. All phenotypes of the temperature-sensitive sec2 alleles are partially suppressed by duplication of the SEC4 gene, but the lethality of a sec2 disruption is not suppressed. The sec2-41 mutation exhibits synthetic lethality with the same subset of the late acting sec mutants as does sec4-8 and sec15-1. The Sec2 protein may function in conjunction with the Sec4 and Sec15 proteins to control vesicular traffic.

Amino Acid Sequence↗

PubMed2026

GiGCN: a network-based framework for uncovering synthetic lethal and viable genetic interactions.

Genetic interactions (GIs) underpin the functional connectivity of genes and pathways, and are important for dissecting genotype-phenotype relationships and identifying therapeutic targets for diseases. However, the scale of the human genome restricts systematic experimental interrogation of GIs. Existing computational tools focus on predicting synthetic lethality (SL) and synthetic viability (SV), the two primary forms of GIs, yet their accuracy and biological interpretability are compromised by inadequate modeling of the molecular mechanisms behind positive and negative interactions, as well as the limitation of negative samples. To overcome these challenges, we developed Genetic Interaction Graph Convolutional Network (GiGCN), a signed network modeling framework for the joint identification of gene pairs with SL and SV. We built a high-confidence signed genetic network by integrating verified GIs, and non-interacting gene pairs, together with gene semantic similarity derived from biological processes. By leveraging disentangled subspace decomposition, this framework separately models distinct functional dimensions within gene networks, enabling robust representation of context-dependent regulatory relationships and accurate discrimination of SL and SV events. Benchmark experiments demonstrate that GiGCN outperforms state-of-the-art approaches (area under receiver operating-characteristic curve: 0.978, and area under precision-recall curve: 0.944). Further analyses reveal biologically meaningful insights, including known and novel SL interactions centered on the oncogene MYC Proto-Oncogene (MYC), as well as SV interactions linked to autophagy and mitophagy pathways. This study provides a robust and interpretable network-based strategy for systematically exploring GIs. The GiGCN framework not only improves the precision of SL and SV prediction, but also offers mechanistic insights into gene functional relationships, thereby supporting the discovery of actionable therapeutic targets for cancer and other human diseases.

Humans↗

PubMed2026

Integrative multi-omics and single-cell analysis identifies EGFR pathway activation and metabolic reprogramming as potential synthetic lethal vulnerabilities in resistance to the FGFR inhibitor AZD4547.

BACKGROUND: Although fibroblast growth factor receptor (FGFR) inhibitors (FGFRi) have demonstrated clinical promise, the inevitable emergence of acquired resistance remains a critical bottleneck, severely compromising their long-term clinical efficacy. The pan-cancer molecular landscape and heterogeneous mechanisms driving this resistance, ranging from genetic alterations to dynamic network rewiring, remain poorly understood. METHODS: We integrated large-scale pharmacogenomic profiling of the FGFR inhibitor AZD4547 from the GDSC2 and PRISM databases with single-cell RNA sequencing to dissect the multi-omics landscape of FGFRi resistance across 312 cell lines from 8 cancer types. This multi-omics framework was further extended by machine learning modeling and systematic synthetic lethality screening to uncover actionable therapeutic targets. In vitro viability assays and western blot analysis were subsequently conducted to experimentally evaluate the predicted FGFR-EGFR synthetic lethality. RESULTS: Our dual-database analysis unveiled a multi-dimensional atlas of FGFRi resistance. We identified cancer-specific genomic drivers, such as ELF4 amplification in glioblastoma, alongside key transcriptomic markers including UCP2 and FSCN1, highlighting a shift towards metabolic reprogramming and epithelial-mesenchymal transition (EMT). Single-cell analysis unveiled that resistance is linked to the heterogeneous enrichment of baseline subpopulations characterized by distinct metaprograms, including cell-cycle dysregulation. Furthermore, a random forest model built on a LASSO-derived transcriptomic signature was constructed, demonstrating promising predictive capability for AZD4547 sensitivity (mean test-set AUC = 0.73, 95% CI [0.63, 0.80]); the signature generalized well to erdafitinib but showed limited transferability to some other FGFR inhibitors (e.g. pemigatinib, BGJ398). Most notably, our synthetic lethal screening revealed a convergent reliance on compensatory RTK signaling (specifically EGFR pathway enrichment) and downstream MAPK/PI3K cascades in resistant phenotypes, providing converging computational evidence for EGFR pathway activation as an adaptive bypass mechanism. This predicted synthetic lethality was experimentally supported in two FGFR-dependent cell line models (RT112 and CCLP1), in which combined FGFR-EGFR inhibition produced marked synergistic antiproliferative effects. CONCLUSIONS: This study establishes a comprehensive multi-omics atlas of resistance to the FGFR inhibitor AZD4547, delineating convergent mechanisms of metabolic reprogramming and EGFR-mediated bypass signaling. Our findings characterize the resistance as a dynamic network rewiring and nominate rational combination strategies to overcome this therapeutic bottleneck. While FGFR-EGFR co-inhibition is experimentally supported, metabolic co-targeting remains a computationally derived, hypothesis-generating strategy.

Benzamides↗

PubMed2025

Genetic mapping and predictive modeling of paralog synthetic lethality.

Paralogs are abundant in the human genome and thought to be a primary source of synthetic lethality, yet the vast paralogome remains largely uncharacterized. A digenic screen of 36,648 paralogous pairs in the human genome revealed that synthetic lethalities were infrequent and varied in penetrance in different tumor backgrounds. We hypothesized that the variable penetrance of synthetic lethalities resulted from complex polygenic interactions with different cellular contexts. A machine learning classifier of a subset of paralog pairs tested across 49 cancer models revealed that endogenous perturbations in related pathways predicted paralog synthetic lethality. Further, predictive modeling of paralog synthetic lethality showed that the strength of synthetic lethal interactions was largely due to the overlap and essentiality of the protein-protein interaction networks shared by the paralog pairs. Collectively, this study tested 36,648 digenic paralog interactions and delineated the key feature classes that underlie the heterogeneity of paralog synthetic lethalities.

Humans↗

PubMed2026

Biallelic loss of RB1 in hepatocellular carcinoma as synthetic lethal target for artificial intelligence-guided therapy.

The retinoblastoma (RB1) gene is a critical tumor suppressor that regulates cell cycle progression and genomic stability. Although RB1 alterations have been reported in hepatocellular carcinoma (HCC), the biological and clinical consequences of biallelic RB1 inactivation (RB1-Bi) remain poorly defined. We performed a comprehensive allele-specific genomic analysis of HCC patients from the TCGA-LIHC (n = 355) and in-house AMC (n = 206) cohorts, collectively comprising the AMC-TCGA discovery cohort. In this combined cohort, RB1-Bi was identified in 14.6% of tumors, was enriched in poorly differentiated HCCs and was independently associated with significantly reduced overall survival (adjusted hazard ratio 3.32, 95% CI 1.93-5.72, p < 0.001). Additionally, a deep learning-based histopathology model using hematoxylin and eosin-stained slides (i.e., FR-MIL model) accurately predicted RB1-Bi status (F1 score 84.39% [95% CI, ±0.02]), making it readily identifiable in routine clinical practice. The prevalence and prognostic impact of RB1-Bi, as well as FR-MIL model performance, were consistent across independent validation cohorts, including advanced-stage tumors and external institutions. High-throughput drug screening in isogenic HCC models revealed that RB1-Bi HCC cells were particularly sensitive to inhibitors targeting mitotic regulators (e.g., AURKA, PLK1, KSP) and DNA damage response pathways (e.g., PARP inhibitors). Synthetic lethal interactions between RB1-Bi and these compounds were demonstrated in vitro and in vivo, and combination treatment with mitotic and PARP inhibitors had synergistic effects with acceptable tolerability. We conclude that RB1-Bi represents a clinically actionable biomarker that identifies a high-risk HCC subtype with specific therapeutic vulnerabilities, offering new opportunities for precision medicine.

Humans↗

PubMed2026

VHL synthetic lethality screens uncover CBF-β as a negative regulator of STING.

Clear cell renal cell carcinoma (ccRCC) represents the most common form of kidney cancer and is typified by biallelic inactivation of the von Hippel-Lindau (VHL) tumour suppressor gene. Here, we undertake genome-wide CRISPR/Cas9 screening to reveal synthetic lethal interactors of VHL, and uncover that loss of Core Binding Factor β (CBF-β) causes cell death in VHL-null ccRCC cell lines and impairs tumour establishment and growth in vivo. This synthetic relationship is independent of the elevated activity of hypoxia inducible factors (HIFs) in VHL-null cells, but does involve the RUNX transcription factors that are known binding partners of CBF-β. Mechanistically, CBF-β loss leads to upregulation of type I interferon signalling, and we uncover a direct inhibitory role for CBF-β at the STING locus controlling Interferon Stimulated Gene expression. Targeting CBF-β in kidney cancer both selectively induces tumour cell lethality and promotes activation of type I interferon signalling.

Humans↗

PubMed2024

Targeting the transcription factor YY1 is synthetic lethal with loss of the histone demethylase KDM5C.

An understanding of the enzymatic and scaffolding functions of epigenetic modifiers is important for the development of epigenetic therapies for cancer. The H3K4me2/3 histone demethylase KDM5C has been shown to regulate transcription. The diverse roles of KDM5C are likely determined by its interacting partners, which are still largely unknown. In this study, we screen for KDM5C-binding proteins and show that YY1 interacts with KDM5C. A synergistic antitumor effect is exerted when both KDM5C and YY1 are depleted, and targeting YY1 appears to be a vulnerability in KDM5C-deficient cancer cells. Mechanistically, KDM5C promotes global YY1 chromatin recruitment, especially at promoters. Moreover, an intact KDM5C JmjC domain but not KDM5C histone demethylase activity is required for KDM5C-mediated YY1 chromatin binding. Transcriptional profiling reveals that dual inhibition of KDM5C and YY1 increases transcriptional repression of cell cycle- and apoptosis-related genes. In summary, our work demonstrates a synthetic lethal interaction between YY1 and KDM5C and suggests combination therapies for cancer treatments.

YY1 Transcription Factor↗

PubMed1992

Characterization of TPM1 disrupted yeast cells indicates an involvement of tropomyosin in directed vesicular transport.

Disruption of the yeast tropomyosin gene TPM1 results in the apparent loss of actin cables from the cytoskeleton (Liu, H., and A. Bretscher. 1989. Cell. 57:233-242). Here we show that TPM1 disrupted cells grow slowly, show heterogeneity in cell size, have delocalized deposition of chitin, and mate poorly because of defects in both shmooing and cell fusion. The transit time of alpha-factor induced a-agglutinin secretion to the cell surface is longer than in isogenic wild-type strains, and some of the protein is mislocalized. Many of the TPM1-deleted cells contain abundant vesicles, similar in morphology to late secretory vesicles, but without an abnormal accumulation of intermediates in the delivery of either carboxypeptidase Y to the vacuole or invertase to the cell surface. Combinations of the TPM1 disruption with sec13 or sec18 mutations, which affect early steps in the secretory pathway, block vesicle accumulation, while combinations with sec1, sec4 or sec6 mutations, which affect a late step in the secretory pathway, have no effect on the vesicle accumulation. The phenotype of the TPM1 disrupted cells is very similar to that of a conditional mutation in the MYO2 gene, which encodes a myosin-like protein (Johnston, G. C., J. A. Prendergast, and R. A. Singer. 1991. J. Cell Biol. 113:539-551). The myo2-66 conditional mutation shows synthetic lethality with the TPM1 disruption, indicating that the MYO2 and TPM1 gene products may be involved in the same, or parallel function. We conclude that tropomyosin, and by inference actin cables, may facilitate directed vesicular transport of components to the correct location on the cell surface.

Chitin↗

PubMed2026

Changes in the transcriptome and synthetic lethal dependencies following KRAS mutant expression reveal profound tissue specificity.

Oncogenic KRAS mutations exhibit a striking tissue-restricted tropism, occurring with high frequency in pancreatic, colorectal, and lung adenocarcinomas while remaining rare in other lineages. The molecular basis for why these specific tissues are uniquely permissive to KRAS transformation, and how this context shapes therapeutic vulnerabilities, remains poorly defined. Here, we utilized CRISPR-mediated genome engineering to generate endogenous, conditional KRAS-mutant isogenic cell line models across three primary permissive lineages (lung, colon, and pancreas) and the nonpermissive breast lineage. Integrated genome-wide CRISPR fitness screens and comparative transcriptome analyses revealed that KRAS-driven synthetic lethal (SL) dependencies are profoundly shaped by their tissue of origin. Strikingly, we observed minimal overlap in SL hits across lineages, with only three genes shared among the permissive lines, suggesting that the KRAS oncogene operates through divergent, context-specific genetic networks. Mechanistically, we show that KRAS activation induces a universal MYC-driven metabolic signature, but the specific machinery required to sustain this state is lineage-restricted. We identified a dependency on the diphthamide synthesis pathway to maintain translational fidelity amid a KRAS-induced hypertranslational state. These findings demonstrate that even when driven by the same oncogene, tumors exhibit distinct regulatory landscapes and unique genetic vulnerabilities. Our results provide a framework for developing lineage-aware therapeutic strategies, moving beyond universal KRAS inhibition toward targeted interventions tailored to a tumor's specific tissue context.

Proto-Oncogene Proteins p21(ras)↗

PubMed1992

A new subclass of nucleoporins that functionally interact with nuclear pore protein NSP1.

NSP1 is a nuclear pore protein (nucleoporin) essential for cell growth. To identify the components that functionally interact with NSP1 in the living cell, we developed a genetic screen for mutants that are lethal in a genetic background of mutated, but not wild type NSP1. Fourteen synthetic lethal mutants were obtained, belonging to at least four different complementation groups. The genes of two complementation groups, NSP116 and NSP49, were cloned. Like the previously described nucleoporins, these genes encode proteins with many repeat sequences. NSP116 and NSP49, however, contain a new repetitive sequence motif 'GLFG', which classifies them as a subclass of nucleoporins. NSP116 and NSP49, tagged with the IgG binding domain of protein A and expressed in yeast, are located at the nuclear envelope. These data provide in vivo evidence that distinct subclasses of nucleoporins physically interact or share overlapping function in nuclear pore complexes.

Amino Acid Sequence↗

PubMed2026

The transposable element-PARP axis underpins synthetic lethality and immunogenic vulnerability in blood cancer.

Transposable elements (TEs) are emerging regulators of hematopoiesis and leukemia, creating vulnerabilities exploitable for therapy. Recent evidence shows that TE reactivation induces innate immune signaling, DNA damage responses, and dependence on poly(ADP-ribose) polymerase (PARP)-mediated protection, enabling synthetic lethality with PARP inhibition even in homologous recombination-proficient leukemias with epigenetic gene mutations. In this article, we highlight the biology underpinning this novel TE-PARP axis, its therapeutic implications, and strategies to expand PARP inhibition beyond HR-deficient cancers through rational combinations with immunotherapy and refined patient stratification.

Humans↗

PubMed2026

Exploiting DNA damage tolerance for precision oncology.

Unresolved DNA lesions trigger replication stress, forcing cancer cells to hijack DNA damage tolerance (DDT) networks, specifically translesion synthesis (TLS) and template switching, to sustain replication. While DDT prevents lethal fork collapse, error-prone TLS drives mutagenesis, tumor evolution, chemoresistance and radioresistance. Proliferating cell nuclear antigen post-translational modifications dynamically govern pathway selection. Cancer cells exploit this plasticity, creating actionable vulnerabilities such as postreplicative single-stranded DNA gaps. Emerging inhibitors targeting TLS polymerases, upstream regulators such as ubiquitin-specific peptidase 1 (USP1), and critical protein-protein interactions offer unprecedented opportunities for precision oncology. By integrating DDT inhibition with biomarkers such as homologous recombination deficiency and tumor mutational burden, we can drive synthetic lethality, sensitize tumors to genotoxic agents, suppress treatment-induced mutagenesis, and potentially enhance responses to immunotherapy.

DDT↗

PubMed2026

Deficiency in POLE Exonuclease Causes Synthetic Lethality in Highly Aneuploid Cancer Cells.

UNLABELLED: Aneuploidy is a hallmark of cancer and is associated with drug resistance and poor clinical outcomes across diverse cancer types. However, no therapies have been clinically established to target highly aneuploid tumors. By analyzing nearly half a million tumor samples subjected to comprehensive genomic profiling, we identified a striking mutual exclusivity between POLE exonuclease domain mutations and high aneuploidy burden. This observation was independently validated using data from The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE). Probabilistic modeling revealed that the elevated quantity and unique spectrum of mutations induced by POLE exonuclease deficiency increase the likelihood of inactivating essential genes on chromosome arms harboring losses, leading to a synthetic lethal phenotype in highly aneuploid cells. Functional experiments demonstrated that POLE exonuclease activity is essential for the viability of highly aneuploid cancer cell lines but dispensable in diploid cells. These findings suggest that selective inhibition of POLE exonuclease activity may represent a promising therapeutic strategy for targeting highly aneuploid tumors. SIGNIFICANCE: An integrated approach using large-scale genomic analyses, probabilistic modeling and functional validation identified POLE exonuclease as a potential synthetic lethal target to overcome cancer aneuploidy.

Humans↗

PubMed2026

Using cancer profiles to identify synthetic lethal therapeutic targets and predictive biomarkers in cancer gene dependency data.

MOTIVATION: Large scale loss-of-function screens utilising CRISPR or siRNA can provide profound insights into the importance of individual genes for the survival of a cancer cell and can drive the identification of therapeutic targets and biomarkers, and the development of targeted drugs. However, the analysis of these data and the substantial bodies of metadata that relate to them, is technically challenging and typically requires substantial expertise in data science and computer coding. RESULTS: To facilitate the analysis of cancer gene dependency data by cancer biologists and clinical scientists, we have developed DepMine-a computational toolkit providing a powerful system for framing complex queries relating cancer gene dependency to the underlying genetic changes that occur in cancer cells. DepMine identifies synthetic lethal relationships between putative target genes and complex 'cancer profiles' built from user-specified combinations of mutations, copy-number variation, and expression levels, and can refine these to optimal biomarker definitions for target dependency. AVAILABILITY: The Python implementation of DepMine and associated data files can be obtained at https://github.com/UOSbioinformaticslab/depmine and is free to academics and Not-For-Profit organisations. The DepMine release referenced in this paper is archived as DOI: 10.5281/zenodo.19570601.

Humans↗

PubMed1992

Genetic interactions among Chlamydomonas reinhardtii mutations that confer resistance to anti-microtubule herbicides.

We previously described two types of genetic interactions among recessive mutations in the APM1 and APM2 loci of Chlamydomonas reinhardtii that may reflect a physical association of the gene products or their involvement in a common structure/process: (1) allele-specific synthetic lethality, and (2) unlinked noncomplementation, or dominant enhancement. To further investigate these interactions, we isolated revertants in which the heat sensitivity caused by the apm2-1 mutation is lost. The heat-insensitive revertants were either fully or partially suppressed for the drug-resistance caused by the apm2-1 allele. In recombination tests the revertants behaved as if the suppressing mutation mapped within the APM2 locus; the partial suppressors of apm2-1 herbicide resistance failed to complement apm2-1, leading to the conclusion that they were likely to be intragenic pseudorevertants. The apm2-1 partial suppressor mutations reversed apm1-apm2-1 synthetic lethality in an allele-specific manner with respect both to apm1- alleles and apm2-1 suppressor mutations. Those apm1- apm2-1rev strains that regained viability also regained heat sensitivity characteristic of the original apm2-1 mutation, even though the apm2-1 suppressor strains were fully heat-insensitive. The Hs+ phenotypes of apm2-1 partial suppressors were also reversed by treatment with the microtubule-stabilizing agent deuterium oxide (D2O). In addition to the above interactions, we observed interallelic complementation and phenotypic enhancement of temperature conditionality among apm1- alleles. Evidence of a role for the products of the two genes in microtubule-based processes was obtained from studying flagellar assembly in apm1- and apm2- mutants.

Alleles↗

PubMed1992

A gene encoding a putative tyrosine phosphatase suppresses lethality of an N-end rule-dependent mutant.

The N-end rule relates the in vivo half-life of a protein to the identity of its N-terminal residue. In the yeast Saccharomyces cerevisiae, mutational inactivation of the N-end rule pathway is neither lethal nor phenotypically conspicuous. We have used a "synthetic lethal" screen to isolate a mutant that requires the N-end rule pathway for viability. An extragenic suppressor of this mutation was cloned and found to encode a 750-residue protein with strong sequence similarities to protein phosphotyrosine phosphatases. This heat-inducible gene was named PTP2. Null ptp2 mutants grow slowly, are hypersensitive to heat, and are viable in either the presence or absence of the N-end rule pathway. We discuss possible connections between dephosphorylation of phosphotyrosine in proteins and the N-end rule pathway of protein degradation.

Amino Acid Sequence↗