Academic literature on the topic 'SWItch/Sucrose Non-Fermentable complex'

Switch/sucrose non-fermentable (SWI/SNF)-related matrix-associated actin-dependent regulator of chromatin (SMARC) subfamily B member 1 (SMARCB1) is a core subunit of the switch/sucrose non-fermentable (SWI/SNF) complex, one of the adenosine triphosphate (ATP)-dependent chromatin remodeler complexes. The unique role of SMARCB1 has been reported in various cellular contexts. Here, we focused on the general role of the ubiquitous expression of SMARCB1 in a normal cell state. We selected ARPE19 (human primary retinal pigment epithelium) and IMR90 (from human fetal lung fibroblasts) cell lines as they have completely different contexts. Furthermore, although these cell lines have been immortalized, they are relatively close to normal human cells. The loss of SMARCB1 in ARPE19 and IMR90 cells reduced cell cycle progression via the upregulation of P21. Transcriptome analysis followed by SMARCB1 knockdown in both cell lines revealed that SMARCB1 was not only involved in cell maintenance but also conferred immunomodulation. Of note, SMARCB1 bound to interleukin (IL) 6 promoter in a steady state and dissociated in an active immune response state, suggesting that SMARCB1 was a direct repressor of IL6, which was further confirmed via loss- and gain-of-function studies. Taken together, we demonstrated that SMARCB1 is a critical gatekeeper molecule of the cell cycle and immune response.

Mature vascular smooth muscle cells (VSMC) exhibit a remarkable degree of plasticity, a characteristic that has intrigued cardiovascular researchers for decades. Recently, it has become increasingly evident that the chromatin remodeler SWItch/Sucrose Non-Fermentable (SWI/SNF) complex plays a pivotal role in orchestrating chromatin conformation, which is critical for gene regulation. In this review, we provide a summary of research related to the involvement of the SWI/SNF complexes in VSMC and cardiovascular diseases (CVD), integrating these discoveries into the current landscape of epigenetic and transcriptional regulation in VSMC. These novel discoveries shed light on our understanding of VSMC biology and pave the way for developing innovative therapeutic strategies in CVD treatment.

The packaging of genomic DNA into nucleosomes creates a barrier to transcription that can be relieved through ATP-dependent chromatin remodeling via complexes such as the switch-sucrose non-fermentable (SWI-SNF) chromatin remodeling complex. The SWI-SNF complex remodels chromatin via conformational or positional changes of nucleosomes, thereby altering the access of transcriptional machinery to target genes. The SWI-SNF complex has limited ability to bind to sequence-specific elements, and, therefore, its recruitment to target loci is believed to require interaction with DNA-associated transcription factors. The Cdx family of homeodomain transcript ion factors (Cdx1, Cdx2, and Cdx4) are essential for a number of developmental programs in the mouse. Cdx1 and Cdx2 also regulate intestinal homeostasis throughout life. Although a number of Cdx target genes have been identified, the basis by which Cdx members impact their transcription is poorly understood. We have found that Cdx members interact with the SWI-SNF complex and make direct contact with Brg1, a catalytic member of SWI-SNF. Both Cdx2 and Brg1 co-occupy a number of Cdx target genes, and both factors are necessary for transcriptional regulation of such targets. Finally, Cdx2 and Brg1 occupancy occurs coincident with chromatin remodeling at some of these loci. Taken together, our findings suggest that Cdx transcription factors regulate target gene expression, in part, through recruitment of Brg1-associated SWI-SNF chromatin remodeling activity.

The SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin-remodeling complex is one of the most remarkably altered epigenetic regulators in cancer. Pathogenic mutations in genes encoding SWI/SNF-related proteins have been recently described in many solid tumors, including rare and aggressive malignancies with rhabdoid features with no standard therapies in advanced or metastatic settings. In recent years, clinical trials with targeted drugs aimed at restoring its function have shown discouraging results. However, preclinical data have found an association between these epigenetic alterations and response to immune therapy. Thus, the rationale for immunotherapy strategies in SWI/SNF complex alteration-related tumors is strong. Here, we review the SWI/SNF complex and how its dysfunction drives the oncogenesis of rhabdoid tumors and the proposed strategies to revert this alteration and promising novel therapeutic approaches, including immune checkpoint inhibition and adoptive cell therapy.

Sinonasal carcinomas are aggressive neoplasms that present a high morbidity and mortality rate with an unfavorable prognosis. This group of tumors exhibits morphological and genetic diversity. Genetic and epigenetic alterations in these neoplasms are the current targets for diagnosis and treatment. The most common type of cancer originating in the sinonasal tract is sinonasal squamous cell carcinomas (SNSCCs), which present different histological patterns and variable histological aggressiveness. A significant number of alterations have been reported in sinonasal tumors, including deficiencies in the Switch/Sucrose non-fermentable (SWI/SNF) chromatin remodeling complex. In the sinonasal tract, deficiencies of the subunits SMARCB1/INI1, SMARCA4/BRG1, and SMARCA2 have been noted in carcinomas, adenocarcinomas, and soft tissue tumors with a distinctive high-grade morphology and a fatal prognosis. Objective: The objective of this study is to identify the status of the SWI/SNF complex using immunohistochemistry in sinonasal squamous cell carcinomas and their association with morphology and survival. Methods: A total of 103 sinonasal carcinomas with different grades of squamous differentiation were analyzed; the selection was based on those cases with high-grade morphology. The carcinomas were then evaluated immunohistochemically for SMARCB1 and SMARCA4 proteins. Their expression was compared with the biological behavior and survival of the patients. Results: Among the SNSCCs, 47% corresponded to the non-keratinizing squamous cell carcinoma (NKSCC) type with high-grade characteristics, 40% were keratinizing squamous cell carcinomas (KSCCs), 9% were SMARCB1-deficient carcinomas, and 4% were SMARCA4-deficient carcinomas. Mosaic expression for SMARCB1 (NKSCC—33%; KSCC—21.9%) and SMARCA4 (NKSCC—14.6%; KSCC—12.2%) was identified, showing an impact on tumor size and progression. Conclusions: We identified that that the partial loss (mosaic expression) of SMARCB1 in SNSCCs is associated with high-grade malignant characteristics and a negative effect on patient survival; meanwhile, SMARCA4-mosaic expression in SNSCCs is associated with high-grade malignant characteristics and an increase in tumor size concerning the intact SMARCA4.

Myogenesis is the biological process by which skeletal muscle tissue forms. Regulation of myogenesis involves a variety of conventional, epigenetic, and epigenomic mechanisms that control chromatin remodeling, DNA methylation, histone modification, and activation of transcription factors. Chromatin remodeling enzymes utilize ATP hydrolysis to alter nucleosome structure and/or positioning. The mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) family of chromatin remodeling enzymes is essential for myogenesis. Here we review diverse and novel mechanisms of regulation of mSWI/SNF enzymes by kinases and phosphatases. The integration of classic signaling pathways with chromatin remodeling enzyme function impacts myoblast viability and proliferation as well as differentiation. Regulated processes include the assembly of the mSWI/SNF enzyme complex, choice of subunits to be incorporated into the complex, and sub-nuclear localization of enzyme subunits. Together these processes influence the chromatin remodeling and gene expression events that control myoblast function and the induction of tissue-specific genes during differentiation.

ARID1A, a subunit of the SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin-remodeling complex, localizes to both promoters and enhancers to influence transcription. However, the role of ARID1A in higher-order spatial chromosome partitioning and genome organization is unknown. Here, we show that ARID1A spatially partitions interphase chromosomes and regulates higher-order genome organization. The SWI/SNF complex interacts with condensin II, and they display significant colocalizations at enhancers. ARID1A knockout drives the redistribution of condensin II preferentially at enhancers, which positively correlates with changes in transcription. ARID1A and condensin II contribute to transcriptionally inactive B-compartment formation, while ARID1A weakens the border strength of topologically associated domains. Condensin II redistribution induced by ARID1A knockout positively correlates with chromosome sizes, which negatively correlates with interchromosomal interactions. ARID1A loss increases the trans interactions of small chromosomes, which was validated by three-dimensional interphase chromosome painting. These results demonstrate that ARID1A is important for large-scale genome folding and spatially partitions interphase chromosomes.

The two-meter-long DNA is compressed into chromatin in the nucleus of every cell, which serves as a significant barrier to transcription. Therefore, for processes such as replication and transcription to occur, the highly compacted chromatin must be relaxed, and the processes required for chromatin reorganization for the aim of replication or transcription are controlled by ATP-dependent nucleosome remodelers. One of the most highly studied remodelers of this kind is the BRG1- or BRM-associated factor complex (BAF complex, also known as SWItch/sucrose non-fermentable (SWI/SNF) complex), which is crucial for the regulation of gene expression and differentiation in eukaryotes. Chromatin remodeling complex BAF is characterized by a highly polymorphic structure, containing from four to 17 subunits encoded by 29 genes. The aim of this paper is to provide an overview of the role of BAF complex in chromatin remodeling and also to use literature mining and a set of computational and bioinformatics tools to analyze structural properties, intrinsic disorder predisposition, and functionalities of its subunits, along with the description of the relations of different BAF complex subunits to the pathogenesis of various human diseases.

The switch/sucrose non-fermentable (SWI/SNF) (SWI/SNF) complex uses energy from ATP hydrolysis to mobilise nucleosomes on chromatin. Components of SWI/SNF are mutated in 20% of all human cancers, of which mutations in AT-rich binding domain protein 1A (ARID1A) are the most common. ARID1A is mutated in nearly half of ovarian clear cell carcinoma and around one-third of endometrial and ovarian carcinomas of the endometrioid type. This review will examine in detail the molecular functions of ARID1A, including its role in cell cycle control, enhancer regulation, and the prevention of telomerase activity. ARID1A has key roles in the maintenance of genomic integrity, including DNA double-stranded break repair, DNA decatenation, integrity of the cohesin complex, and reduction in replication stress, and is also involved in mismatch repair. The role of ARID1A loss in the pathogenesis of some of the most common human cancers is discussed, with a particular emphasis on gynaecological cancers. Finally, several promising synthetic lethal strategies, which exploit the specific vulnerabilities of ARID1A-deficient cancer cells, are briefly mentioned.

Mutations in subunits of the SWItch Sucrose Non-Fermentable (SWI/SNF) complex occur in 20% of all human tumors. Among these, the core subunit SMARCB1 is the most frequently mutated, and SMARCB1 loss represents a founder driver event in several malignancies, such as malignant rhabdoid tumors (MRT), epithelioid sarcoma, poorly differentiated chordoma, and renal medullary carcinoma (RMC). Intriguingly, SMARCB1-deficient pediatric MRT and RMC have recently been reported to be immunogenic, despite their very simple genome and low tumor mutational burden. Responses to immune checkpoint inhibitors have further been reported in some SMARCB1-deficient diseases. Here, we will review the preclinical data and clinical data that suggest that immunotherapy, including immune checkpoint inhibitors, may represent a promising therapeutic strategy for SMARCB1-defective tumors. We notably discuss the heterogeneity that exists among the spectrum of malignancies driven by SMARCB1-loss, and highlight challenges that are at stake for developing a personalized immunotherapy for these tumors, notably using molecular profiling of the tumor and of its microenvironment.

De nos jours, la communauté scientifique s'accorde sur la nécessité de diagnostics et de thérapies personnalisés pour les patients atteints de cancer, conçus par des études translationnelles combinant approches expérimentales et statistiques. Les défis actuels incluent la validation de modèles expérimentaux précliniques et leur profilage multi-omiques, ainsi que la conception de méthodes bioinformatiques et mathématiques dédiées pour identifier les combinaisons de médicaments optimales pour chaque patient.Cette thèse a visé à concevoir de telles approches statistiques pour analyser différents types de données à grande échelle et les intégrer afin d'identifier les vulnérabilités ciblables des lignées cancéreuses. Nous nous sommes focalisés sur les altérations du complexe de remodelage de la chromatine SWI/SNF, muté dans ~20 % des cancers, pour lesquels aucune thérapie efficace n'est disponible. Nous avons utilisé un panel de lignées cellulaires isogéniques HAP1 mutées pour les sous-unités du complexe SWI/SNF ou d'autres enzymes épigénétiques, pour lesquelles des données de transcriptomique, protéomique et de criblage de médicaments étaient disponibles.Nous avons travaillé sur quatre axes méthodologiques. Premièrement, nous avons conçu une méthodologie optimisée d'enrichissement pour détecter les voies de régulation différentiellement activées entre mutants et type sauvage. Ensuite, nous avons croisé les résultats des criblages de médicaments et les bases d'interaction gène-médicament, pour inférer des voies de régulation ciblables spécifiquement chez les lignées mutantes. Ensuite, la validation de ces cibles potentielles a été réalisée à l'aide d'une nouvelle méthode détectant la létalité synthétique à partir de données transcriptomiques et CRISPR de lignées cancéreuses indépendantes du projet DepMap. Enfin, en vue de l'optimisation de thérapies multi-agents, nous avons conçu une première représentation digitale des voies de régulation ciblables pour les tumeurs mutées SMARCA4, en construisant un réseau dirigé d'interaction protéine-protéine reliant les cibles inférées des analyses multi-omiques HAP1 et CRISPR DepMap. Nous avons utilisé la base de données OmniPath pour récupérer les interactions protéiques directes et ajouté les protéines liant celles présentes dans le réseau avec l'algorithme Neko.Ces développements méthodologiques ont été appliqués aux ensembles de données disponibles pour le panel HAP1. En utilisant notre méthodologie d'enrichissement optimisée, nous avons identifié le Métabolisme des protéines comme la catégorie de voies de régulation la plus fréquemment dérégulée dans les lignées SWI/SNF-KO. Ensuite, l'analyse de criblage de médicaments a révélé des médicaments cytotoxiques et épigénétiques ciblant sélectivement les mutants SWI/SNF, notamment les inhibiteurs de CBP/EP300 ou de la respiration mitochondriale, également identifiés comme létaux synthétiques par notre analyse CRISPR DepMap. Ces résultats ont été validés dans deux modèles expérimentaux isogéniques indépendants. L'analyse CRISPR DepMap a également été utilisée pour identifier des interactions létales synthétiques dans le glioblastome, qui se sont révélées pertinentes pour des lignées cellulaires dérivées de patients et sont en cours de validation.En résumé, nous avons développé des méthodes computationnelles pour intégrer des données d'expression multi-omiques avec des criblages de médicaments et des tests CRISPR, et identifié de nouvelles vulnérabilités chez les mutants SWI/SNF, qui ont été validées expérimentalement. Cette étude était limitée à l'identification de monothérapies efficaces. Pour l'avenir, nous proposons de concevoir des modèles mathématiques représentant les réseaux de protéines ciblables à l'aide d'équations différentielles et de les utiliser dans des procédures d'optimisation numérique et d'apprentissage automatique pour étudier les cibles médicamenteuses concomitantes et personnaliser les combinaisons de médicaments
Nowadays the cancer community agrees on the need for patient-tailored diagnostics and therapies, which calls for the design of translational studies combining experimental and statistical approaches. Current challenges include the validation of preclinical experimental models and their multi-omics profiling, along with the design of dedicated bioinformatics and mathematical pipelines (i.e. dimension reduction, multi-omics integration, mechanism-based digital twins) for identifying patient-specific optimal drug combinations.To address these challenges, we designed bioinformatics and statistical approaches to analyze various large-scale data types and integrate them to identify targetable vulnerabilities in cancer cell lines. We developed our pipeline in the context of alterations of the SWItch Sucrose Non-Fermentable (SWI/SNF) chromatin remodeling complex. SWI/SNF mutations occur in ~20% of all cancers, but such malignancies still lack efficient therapies. We leveraged a panel of HAP1 isogenic cell lines mutated for SWI/SNF subunits or other epigenetic enzymes for which transcriptomics, proteomics and drug screening data were available.We worked on four methodological axes, the first one being the design of an optimized pathway enrichment pipeline to detect pathways differentially activated in the mutants against the wild-type. We developed a pruning algorithm to reduce gene and pathway redundancy in the Reactome database and improve the interpretability of the results. We evidenced the bad performance of first-generation enrichment methods and proposed to combine the topology-based method ROntoTools with pre-ranked GSEA to increase enrichment performance .Secondly, we analyzed drug screens, processed drug-gene interaction databases to obtain genes and pathways targeted by effective drugs and integrated them with proteomics enrichment results to infer targetable vulnerabilities selectively harming mutant cell lines. The validation of potential targets was achieved using a novel method detecting synthetic lethality from transcriptomics and CRISPR data of independent cancer cell lines in DepMap, run for each studied epigenetic enzyme. Finally, to further inform multi-agent therapy optimization, we designed a first digital representation of targetable pathways for SMARCA4-mutated tumors by building a directed protein-protein interaction network connecting targets inferred from multi-omics HAP1 and DepMap CRISPR analyses. We used the OmniPath database to retrieve direct protein interactions and added the connecting neighboring genes with the Neko algorithm.These methodological developments were applied to the HAP1 panel datasets. Using our optimized enrichment pipeline, we identified Metabolism of proteins as the most frequently dysregulated pathway category in SWI/SNF-KO lines. Next, the drug screening analysis revealed cytotoxic and epigenetic drugs selectively targeting SWI/SNF mutants, including CBP/EP300 or mitochondrial respiration inhibitors, also identified as synthetic lethal by our Depmap CRISPR analysis. Importantly, we validated these findings in two independent isogenic cancer-relevant experimental models. The Depmap CRISPR analysis was also used in a separate project to identify synthetic lethal interactions in glioblastoma, which proved relevant for patient-derived cell lines and are being validated in dedicated drug screens.To sum up, we developed computational methods to integrate multi-omics expression data with drug screening and CRISPR assays and identified new vulnerabilities in SWI/SNF mutants which were experimentally revalidated. This study was limited to the identification of effective single agents. As a future direction, we propose to design mathematical models representing targetable protein networks using differential equations and their use in numerical optimization and machine learning procedures as a key tool to investigate concomitant druggable targets and personalize drug combinations