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At least 19 recordsLinked to original sources
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

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↗
PubMed2026

Genome-wide CRISPR screens map synthetic lethal interactions across recurrent cancer driver alterations.

Synthetic lethality (SL) provides a treatment paradigm for targeting cancer with alterations in driver genes that are not conventionally druggable, including tumor suppressor genes. We execute a series of genome-wide CRISPR screens using functionally validated isogenic cell lines and conduct a large-scale SL analysis using data from the cancer dependency map (DepMap). We chart SL interactions across 15 driver alterations: FBXW7, CCNE1, CDK12, ARID1A, KMT2D, DNMT3A, TET2, KEAP1, STK11, IDH1, SF3B1, SRSF2, U2AF1, chromosome 18q loss, and chromosome 13q loss. We show validation of several SL interactions, including ARID1A and the hexosamine biosynthetic pathway aminotransferase GFPT1, STK11 with CAMK protein kinase MARK2, FBXW7 and the CDK1 regulatory kinase PKMYT1, and CCNE1 amplification and the anaphase-promoting complex or cyclosome (APC/C). In summary, this study offers a rich resource of genetic interactions across cancer drivers enabling the discovery of biological insights and drug targets for future therapeutic development.

CP: cancer↗
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

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↗
PubMed1992

A synthetic lethal screen identifies SLK1, a novel protein kinase homolog implicated in yeast cell morphogenesis and cell growth.

The Saccharomyces cerevisiae SPA2 protein localizes at sites involved in polarized cell growth in budding cells and mating cells. spa2 mutants have defects in projection formation during mating but are healthy during vegetative growth. A synthetic lethal screen was devised to identify mutants that require the SPA2 gene for vegetative growth. One mutant, called slk-1 (for synthetic lethal kinase), has been characterized extensively. The SLK1 gene has been cloned, and sequence analysis predicts that the SLK1 protein is 1,478 amino acid residues in length. Approximately 300 amino acids at the carboxy terminus exhibit sequence similarity with the catalytic domains of protein kinases. Disruption mutations have been constructed in the SLK1 gene. slk1 null mutants cannot grow at 37 degrees C, but many cells can grow at 30, 24, and 17 degrees C. Dead slk1 mutant cells usually have aberrant cell morphologies, and many cells are very small, approximately one-half the diameter of wild-type cells. Surviving slk1 cells also exhibit morphogenic defects; these cells are impaired in their ability to form projections upon exposure to mating pheromones. During vegetative growth, a higher fraction of slk1 cells are unbudded compared with wild-type cells, and under nutrient limiting conditions, slk1 cells exhibit defects in cell cycle arrest. The different slk1 mutant defects are partially rescued by an extra copy of the SSD1/SRK1 gene. SSD1/SRK1 has been independently isolated as a suppressor of mutations in genes involved in growth control, sit4, pde2, bcy1, and ins1 (A. Sutton, D. Immanuel, and K.T. Arnat, Mol. Cell. Biol. 11:2133-2148, 1991; R.B. Wilson, A.A. Brenner, T.B. White, M.J. Engler, J.P. Gaughran, and K. Tatchell, Mol. Cell. Biol. 11:3369-3373, 1991). These data suggest that SLK1 plays a role in both cell morphogenesis and the control of cell growth. We speculate that SLK1 may be a regulatory link for these two cellular processes.

Amino Acid Sequence↗
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)↗
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↗
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↗
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↗
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↗
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↗
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&#x2009;=&#x2009;355) and in-house AMC (n&#x2009;=&#x2009;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&#x2009;<&#x2009;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, &#xb1;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↗
PubMed1989

Extragenic suppression and synthetic lethality among Chlamydomonas reinhardtii mutants resistant to anti-microtubule drugs.

The antimicrotubule agents oryzalin (ORY), colchicine (COL) and taxol (TAX) were used to select three recessive, conditional lethal (ts-) mutants which defined two new essential loci, ory1 and cor1. The two ory1 mutants conferred resistance to ORY, TAX, and COL; the cor1 mutant conferred resistance only to COL. Each of the mutants displayed wild-type sensitivity to a number of unrelated inhibitors. Assembly and disassembly of flagellar microtubules in the ory1 mutants displayed wild-type sensitivity to ORY and COL, suggesting that the ory1 gene product either does not participate in these processes or the ory1 gene product alone is not sufficient to confer resistance. The ory1 locus mapped to linkage group X; cor1 was mapped to the left arm of linkage group XII. A synthetic lethal interaction was observed between ory1 and cor1 mutations, i.e., inferred ory1 cor1 double mutants were inviable at the permissive temperature. The conditional lethal phenotype of ory1-1 was used to select many spontaneous TS+ revertants, which arose at high frequencies. Genetic and phenotypic characterization of the revertants demonstrated that (1) the revertants fell into four phenotypic classes, including some which conferred supersensitivity to ORY and others which conferred cold-sensitive lethality, (2) reversion was caused in most or all cases by extragenic suppressors, (3) suppressor mutations displayed complex behavior in heterozygous (sup/+) diploids, (4) many different loci may be capable of suppressing ory1 mutants, and (5) suppressors of ory1-1 efficiently suppressed an independently isolated allele, ory1-2. Taken together the ory1, cor1, and suppressor mutations identify a number of interacting loci involved in essential cellular processes which are specifically susceptible to antimicrotubule agents.

Alkaloids↗
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↗
PubMed1991

Use of a screen for synthetic lethal and multicopy suppressee mutants to identify two new genes involved in morphogenesis in Saccharomyces cerevisiae.

Genes CDC24 and CDC42 are required for the establishment of cell polarity and for bud formation in Saccharomyces cerevisiae. Temperature-sensitive (Ts-) mutations in either of these genes cause arrest as large, unbudded cells in which the nuclear cycle continues. MSB1 was identified previously as a multicopy suppressor of Ts- cdc24 and cdc42 mutations. We have now sequenced MSB1 and constructed a deletion of this gene. The predicted amino acid sequence does not closely resemble any other in the available data bases, and the deletion does not produce any readily detectable phenotype. However, we have used a colony-sectoring assay to identify additional genes that appear to interact with MSB1 and play a role in bud emergence. Starting with a strain deleted for the chromosomal copy of MSB1 but containing MSB1 on a high-copy-number plasmid, mutants were identified in which MSB1 had become essential for viability. The new mutations defined two genes, BEM1 and BEM2; both the bem1 and bem2 mutations are temperature sensitive and are only partially suppressed by MSB1. In bem1 cells, a single copy of MSB1 is necessary and sufficient for viability at 23 or 30 degrees C, but even multiple copies of MSB1 do not fully suppress the growth defect at 37 degrees C. In bem2 cells, a single copy of MSB1 is necessary and sufficient for viability at 23 degrees C, multiple copies are necessary for viability at 30 degrees C, and even multiple copies of MSB1 do not suppress the growth defect at 37 degrees C. In a wild-type background (i.e., a single chromosomal copy of MSB1), both bem1 and bem2 mutations cause cells to become large and multinucleate even during growth at 23 degrees C, suggesting that these genes are involved in bud emergence. This suggestion is supported for BEM1 by other evidence obtained in a parallel study (J. Chant, K. Corrado, J. Pringle, and I. Herskowitz, submitted for publication). BEM1 maps centromere distal to TYR1 on chromosome II, and BEM2 maps between SPT15 and STP2 on chromosome V.

Amino Acid Sequence↗
PubMed1975

[Report of "lethal factor" synthetized by Bacillus cereus (author's transl)].

Bacillus cereus growing in nutrition broth produces during logarithmic growth and in stationary phase a lethal factor extremely toxic for rodents. This toxin is only produced in the presence of oxygen and depends on bacterial replication. The highest titers of toxin are obtained using bacteria in a concentration of 10(7) to 10(9) per ml of nutrition broth. During regression phase of Bacillus cereus the titer of toxin declines to zero. Toxicity of the lethal factor becomes not altered in an alcaline or acidic medium. Temperatures exceeding 65 degrees C inactivate the toxin indicating its thermolability. Oral and rectal dispension of large quantities of the lethal factor does not induce toxic symptoms in rodents. However, when applicating toxin containing cultural filtrate of Bacillus cereus as an i.v., i.p., i.n. or s.c. injection it becomes highly toxic for mice, rats, hamsters, guinea pigs and rabbits. All animals injected by the different ways parenterally died.

Administration, Intranasal↗