Global quantification exposes abundant low-level off-target activity by base editors.

Base editors are dedicated engineered deaminases that enable directed conversion of specific bases in the genome or transcriptome in a precise and efficient manner, and hold promise for correcting pathogenic mutations. A major concern limiting application of this powerful approach is the issue of off-target edits. Several recent studies have shown substantial off-target RNA activity induced by base editors and demonstrated that off-target mutations may be suppressed by improved deaminases versions or optimized guide RNAs. Here, we describe a new class of off-target events that are invisible to the established methods for detection of genomic variations and were thus far overlooked. We show that nonspecific, seemingly stochastic, off-target events affect a large number of sites throughout the genome or the transcriptome, and account for the majority of off-target activity. We develop and employ a different, complementary approach that is sensitive to the stochastic off-target activity and use it to quantify the abundant off-target RNA mutations due to current, optimized deaminase editors. We provide a computational tool to quantify global off-target activity, which can be used to optimize future base editors. Engineered base editors enable directed manipulation of the genome or transcriptome at single-base resolution. We believe that implementation of this computational approach would facilitate design of more specific base editors.

Aberrant mitochondrial function in patient-derived neural cells from CDKL5 deficiency disorder and Rett syndrome.

The X-linked neurodevelopmental diseases CDKL5 deficiency disorder (CDD) and Rett syndrome (RTT) are associated with intellectual disability, infantile spasms and seizures. Although mitochondrial dysfunction has been suggested in RTT, less is understood about mitochondrial function in CDD. A comparison of bioenergetics and mitochondrial function between isogenic wild-type and mutant neural progenitor cell (NPC) lines revealed increased oxygen consumption in CDD mutant lines, which is associated with altered mitochondrial function and structure. Transcriptomic analysis revealed differential expression of genes related to mitochondrial and REDOX function in NPCs expressing the mutant CDKL5. Furthermore, a similar increase in oxygen consumption specific to RTT patient-derived isogenic mutant NPCs was observed, though the pattern of mitochondrial functional alterations was distinct from CDKL5 mutant-expressing NPCs. We propose that aberrant neural bioenergetics is a common feature between CDD and RTT disorders. The observed changes in oxidative stress and mitochondrial function may facilitate the development of therapeutic agents for CDD and related disorders.

Decreased A-to-I RNA editing as a source of keratinocytes' dsRNA in psoriasis.

Recognition of dsRNA molecules activates the MDA5-MAVS pathway and plays a critical role in stimulating type-I interferon responses in psoriasis. However, the source of the dsRNA accumulation in psoriatic keratinocytes remains largely unknown. A-to-I RNA editing is a common co- or post-transcriptional modification that diversifies adenosine in dsRNA, and leads to unwinding of dsRNA structures. Thus, impaired RNA editing activity can result in an increased load of endogenous dsRNAs. Here we provide a transcriptome-wide analysis of RNA editing across dozens of psoriasis patients, and we demonstrate a global editing reduction in psoriatic lesions. In addition to the global alteration, we also detect editing changes in functional recoding sites located in the IGFBP7, COPA, and FLNA genes. Accretion of dsRNA activates autoimmune responses, and therefore the results presented here, linking for the first time an autoimmune disease to reduction in global editing level, are relevant to a wide range of autoimmune diseases.

A model-driven methodology for exploring complex disease comorbidities applied to autism spectrum disorder and inflammatory bowel disease.

We propose a model-driven methodology aimed to shed light on complex disorders. Our approach enables exploring shared etiologies of comorbid diseases at the molecular pathway level. The method, Comparative Comorbidities Simulation (CCS), uses stochastic Petri net simulation for examining the phenotypic effects of perturbation of a network known to be involved in comorbidities to predict new roles for mutations in comorbid conditions. To demonstrate the utility of our novel methodology, we investigated the molecular convergence of autism spectrum disorder (ASD) and inflammatory bowel disease (IBD) on the autophagy pathway. In addition to validation by domain experts, we used formal analyses to demonstrate the model's self-consistency. We then used CCS to compare the effects of loss of function (LoF) mutations previously implicated in either ASD or IBD on the autophagy pathway. CCS identified similar dynamic consequences of these mutations in the autophagy pathway. Our method suggests that two LoF mutations previously implicated in IBD may contribute to ASD, and one ASD-implicated LoF mutation may play a role in IBD. Future targeted genomic or functional studies could be designed to directly test these predictions.

DNA and RNA base editors can correct the majority of pathogenic single nucleotide variants.

The majority of human genetic diseases are caused by single nucleotide variants (SNVs) in the genome sequence. Excitingly, new genomic techniques known as base editing have opened efficient pathways to correct erroneous nucleotides. Due to reliance on deaminases, which have the capability to convert A to I(G) and C to U, the direct applicability of base editing might seem constrained in terms of the range of mutations that can be reverted. In this evaluation, we assess the potential of DNA and RNA base editing methods for treating human genetic diseases. Our findings indicate that 62% of pathogenic SNVs found within genes can be amended by base editing; 30% are G>A and T>C SNVs that can be corrected by DNA base editing, and most of them by RNA base editing as well, and 29% are C>T and A>G SNVs that can be corrected by DNA base editing directed to the complementary strand. For each, we also present several factors that affect applicability such as bystander and off-target occurrences. For cases where editing the mismatched nucleotide is not feasible, we introduce an approach that calculates the optimal substitution of the deleterious amino acid with a new amino acid, further expanding the scope of applicability. As personalized therapy is rapidly advancing, our demonstration that most SNVs can be treated by base editing is of high importance. The data provided will serve as a comprehensive resource for those seeking to design therapeutic base editors and study their potential in curing genetic diseases.

Selective CDK7 Inhibition Suppresses Cell Cycle Progression and MYC Signaling While Enhancing Apoptosis in Therapy-resistant Estrogen Receptor-positive Breast Cancer.

PURPOSE: Resistance to endocrine therapy (ET) and CDK4/6 inhibitors (CDK4/6i) is a clinical challenge in estrogen receptor (ER)-positive (ER+) breast cancer. Cyclin-dependent kinase 7 (CDK7) is a candidate target in endocrine-resistant ER+ breast cancer models and selective CDK7 inhibitors (CDK7i) are in clinical development for the treatment of ER+ breast cancer. Nonetheless, the precise mechanisms responsible for the activity of CDK7i in ER+ breast cancer remain elusive. Herein, we sought to unravel these mechanisms. EXPERIMENTAL DESIGN: We conducted multi-omic analyses in ER+ breast cancer models in vitro and in vivo, including models with different genetic backgrounds. We also performed genome-wide CRISPR/Cas9 knockout screens to identify potential therapeutic vulnerabilities in CDK4/6i-resistant models. RESULTS: We found that the on-target antitumor effects of CDK7 inhibition in ER+ breast cancer are in part p53 dependent, and involve cell cycle inhibition and suppression of c-Myc. Moreover, CDK7 inhibition exhibited cytotoxic effects, distinctive from the cytostatic nature of ET and CDK4/6i. CDK7 inhibition resulted in suppression of ER phosphorylation at S118; however, long-term CDK7 inhibition resulted in increased ER signaling, supporting the combination of ET with a CDK7i. Finally, genome-wide CRISPR/Cas9 knockout screens identified CDK7 and MYC signaling as putative vulnerabilities in CDK4/6i resistance, and CDK7 inhibition effectively inhibited CDK4/6i-resistant models. CONCLUSIONS: Taken together, these findings support the clinical investigation of selective CDK7 inhibition combined with ET to overcome treatment resistance in ER+ breast cancer. In addition, our study highlights the potential of increased c-Myc activity and intact p53 as predictors of sensitivity to CDK7i-based treatments.

Static network structure can be used to model the phenotypic effects of perturbations in regulatory networks.

MOTIVATION: Biological processes are dynamic, whereas the networks that depict them are typically static. Quantitative modeling using differential equations or logic-based functions can offer quantitative predictions of the behavior of biological systems, but they require detailed experimental characterization of interaction kinetics, which is typically unavailable. To determine to what extent complex biological processes can be modeled and analyzed using only the static structure of the network (i.e. the direction and sign of the edges), we attempt to predict the phenotypic effect of perturbations in biological networks from the static network structure. RESULTS: We analyzed three networks from different sources: The EGFR/MAPK and PI3K/AKT network from a detailed experimental study, the TNF regulatory network from the STRING database and a large network of all NCI-curated pathways from the Protein Interaction Database. Altogether, we predicted the effect of 39 perturbations (e.g. by one or two drugs) on 433 target proteins/genes. In up to 82% of the cases, an algorithm that used only the static structure of the network correctly predicted whether any given protein/gene is upregulated or downregulated as a result of perturbations of other proteins/genes. CONCLUSION: While quantitative modeling requires detailed experimental data and heavy computations, which limit its scalability for large networks, a wiring-based approach can use available data from pathway and interaction databases and may be scalable. These results lay the foundations for a large-scale approach of predicting phenotypes based on the schematic structure of networks.

TREM2 has a significant, gender-specific, effect on human obesity.

Triggering Receptor Expressed On Myeloid Cells 2 (TREM2) is a membrane protein expressed on immune cells, involved in neurodegenerative diseases and cancer. Recently, it was shown that TREM2 is expressed on lipid associated macrophages in adipose tissue, and that TREM2 knockout mice suffer from metabolic symptoms. Here, a computational study using public databases, brings direct evidence for the involvement of TREM2 in human obesity. First, we show a significant correlation between TREM2 expression levels and BMI in adipose tissues in samples from the GTEx database. This association was evident for males but not for females. Second, we identified in the UK Biobank cohort a coding SNP in TREM2 with a significant effect on BMI. Compared to previously identified SNPs associated with BMI, this SNP (rs2234256 SNP, L211P) has the strongest association, reflected in significantly higher BMI values of people carrying the SNP as heterozygous and even more for homozygous. Strikingly, this association was evident only for females. These observations suggest a novel gender-specific role of TREM2 in human obesity, and call for further studies to elucidate the mechanism by which this gene correlates with an obese phenotype.

A Distinct Chromatin State Drives Therapeutic Resistance in Invasive Lobular Breast Cancer.

Most invasive lobular breast cancers (ILC) are of the luminal A subtype and are strongly hormone receptor-positive. Yet, ILC is relatively resistant to tamoxifen and associated with inferior long-term outcomes compared with invasive ductal cancers (IDC). In this study, we sought to gain mechanistic insights into these clinical findings that are not explained by the genetic landscape of ILC and to identify strategies to improve patient outcomes. A comprehensive analysis of the epigenome of ILC in preclinical models and clinical samples showed that, compared with IDC, ILC harbored a distinct chromatin state linked to gained recruitment of FOXA1, a lineage-defining pioneer transcription factor. This resulted in an ILC-unique FOXA1-estrogen receptor (ER) axis that promoted the transcription of genes associated with tumor progression and poor outcomes. The ILC-unique FOXA1-ER axis led to retained ER chromatin binding after tamoxifen treatment, which facilitated tamoxifen resistance while remaining strongly dependent on ER signaling. Mechanistically, gained FOXA1 binding was associated with the autoinduction of FOXA1 in ILC through an ILC-unique FOXA1 binding site. Targeted silencing of this regulatory site resulted in the disruption of the feed-forward loop and growth inhibition in ILC. In summary, ILC is characterized by a unique chromatin state and FOXA1-ER axis that is associated with tumor progression, offering a novel mechanism of tamoxifen resistance. These results underscore the importance of conducting clinical trials dedicated to patients with ILC in order to optimize treatments in this breast cancer subtype. SIGNIFICANCE: A unique FOXA1-ER axis in invasive lobular breast cancer promotes disease progression and tamoxifen resistance, highlighting a potential therapeutic avenue for clinical investigations dedicated to this disease. See related commentary by Blawski and Toska, p. 3668.

CoBRA: Containerized Bioinformatics Workflow for Reproducible ChIP/ATAC-seq Analysis.

Chromatin immunoprecipitation sequencing (ChIP-seq) and the Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) have become essential technologies to effectively measure protein-DNA interactions and chromatin accessibility. However, there is a need for a scalable and reproducible pipeline that incorporates proper normalization between samples, correction of copy number variations, and integration of new downstream analysis tools. Here we present Containerized Bioinformatics workflow for Reproducible ChIP/ATAC-seq Analysis (CoBRA), a modularized computational workflow which quantifies ChIP-seq and ATAC-seq peak regions and performs unsupervised and supervised analyses. CoBRA provides a comprehensive state-of-the-art ChIP-seq and ATAC-seq analysis pipeline that can be used by scientists with limited computational experience. This enables researchers to gain rapid insight into protein-DNA interactions and chromatin accessibility through sample clustering, differential peak calling, motif enrichment, comparison of sites to a reference database, and pathway analysis. CoBRA is publicly available online at https://bitbucket.org/cfce/cobra.

Targeting the actin nucleation promoting factor WASp provides a therapeutic approach for hematopoietic malignancies.

Cancer cells depend on actin cytoskeleton rearrangement to carry out hallmark malignant functions including activation, proliferation, migration and invasiveness. Wiskott-Aldrich Syndrome protein (WASp) is an actin nucleation-promoting factor and is a key regulator of actin polymerization in hematopoietic cells. The involvement of WASp in malignancies is incompletely understood. Since WASp is exclusively expressed in hematopoietic cells, we performed in silico screening to identify small molecule compounds (SMCs) that bind WASp and promote its degradation. We describe here one such identified molecule; this WASp-targeting SMC inhibits key WASp-dependent actin processes in several types of hematopoietic malignancies in vitro and in vivo without affecting naïve healthy cells. This small molecule demonstrates limited toxicity and immunogenic effects, and thus, might serve as an effective strategy to treat specific hematopoietic malignancies in a safe and precisely targeted manner.

Increased RNA editing in maternal immune activation model of neurodevelopmental disease.

The etiology of major neurodevelopmental disorders such as schizophrenia and autism is unclear, with evidence supporting a combination of genetic factors and environmental insults, including viral infection during pregnancy. Here we utilized a mouse model of maternal immune activation (MIA) with the viral mimic PolyI:C infection during early gestation. We investigated the transcriptional changes in the brains of mouse fetuses following MIA during the prenatal period, and evaluated the behavioral and biochemical changes in the adult brain. The results reveal an increase in RNA editing levels and dysregulation in brain development-related gene pathways in the fetal brains of MIA mice. These MIA-induced brain editing changes are not observed in adulthood, although MIA-induced behavioral deficits are observed. Taken together, our findings suggest that MIA induces transient dysregulation of RNA editing at a critical time in brain development.

Tissue necrosis and its role in cancer progression.

Great efforts have been made in revealing the mechanisms governing cancer resistance and recurrence. The in-situ effects of cell death, caused by hypoxia and metabolic stress, were largely studied in association with inflammation. However, in this work, we focused on the direct effects of necrosis on cancer promotion and on the tumor microenvironment. The conditions leading to cell necrosis, upon nutrient and oxygen deprivation, were recapitulated in-vitro and were used to generate samples for computational proteomic analysis. Under these conditions, we identified clusters of enriched pathways that may be involved in tumor resistance, leading to cancer recurrence. We show that the content of necrotic cells enhances angiogenesis and proliferation of endothelial cells, induces vasculature, as well as increases migration, invasion, and cell-cell interactions. In-vivo studies, where MDA-MB-231 xenografts were exposed to necrotic lysates, resulted in an increase in both proliferation and angiogenesis. Histological analysis of tumor tissues revealed high expression levels of key mediators that were identified by proteomic analysis. Moreover, when cells were injected systemically, coupled with necrotic lysates, a higher number of large lesions was detected in the lung. Finally, using xenografts, we demonstrated that combining an antagonist of a necrotic signal with an anticancer treatment potentiates the prolonged therapeutic effect. This approach suggests a paradigm shift in which targeting late necrotic-secreted factors may increase survival and enhance the efficacy of anticancer therapy.

Allele-Specific Chromatin Recruitment and Therapeutic Vulnerabilities of ESR1 Activating Mutations.

Estrogen receptor α (ER) ligand-binding domain (LBD) mutations are found in a substantial number of endocrine treatment-resistant metastatic ER-positive (ER+) breast cancers. We investigated the chromatin recruitment, transcriptional network, and genetic vulnerabilities in breast cancer models harboring the clinically relevant ER mutations. These mutants exhibit both ligand-independent functions that mimic estradiol-bound wild-type ER as well as allele-specific neomorphic properties that promote a pro-metastatic phenotype. Analysis of the genome-wide ER binding sites identified mutant ER unique recruitment mediating the allele-specific transcriptional program. Genetic screens identified genes that are essential for the ligand-independent growth driven by the mutants. These studies provide insights into the mechanism of endocrine therapy resistance engendered by ER mutations and potential therapeutic targets.

Comprehensive Analysis of Tissue-wide Gene Expression and Phenotype Data Reveals Tissues Affected in Rare Genetic Disorders.

Linking putatively pathogenic variants to the tissues they affect is necessary for determining the correct diagnostic workup and therapeutic regime in undiagnosed patients. Here, we explored how gene expression across healthy tissues can be used to infer this link. We integrated 6,665 tissue-wide transcriptomes with genetic disorder knowledge bases covering 3,397 diseases. Receiver-operating characteristics (ROC) analysis using expression levels in each tissue and across tissues indicated significant but modest associations between elevated expression and phenotype for most tissues (maximum area under ROC curve = 0.69). At extreme elevation, associations were marked. Upregulation of disease genes in affected tissues was pronounced for genes associated with autosomal dominant over recessive disorders. Pathways enriched for genes expressed and associated with phenotypes highlighted tissue functionality, including lipid metabolism in spleen and DNA repair in adipose tissue. These results suggest features useful for evaluating the likelihood of particular tissue manifestations in genetic disorders. The web address of an interactive platform integrating these data is provided.

A novel Fer/FerT targeting compound selectively evokes metabolic stress and necrotic death in malignant cells.

Disruption of the reprogrammed energy management system of malignant cells is a prioritized goal of targeted cancer therapy. Two regulators of this system are the Fer kinase, and its cancer cell specific variant, FerT, both residing in subcellular compartments including the mitochondrial electron transport chain. Here, we show that a newly developed inhibitor of Fer and FerT, E260, selectively evokes metabolic stress in cancer cells by imposing mitochondrial dysfunction and deformation, and onset of energy-consuming autophagy which decreases the cellular ATP level. Notably, Fer was also found to associate with PARP-1 and E260 disrupted this association thereby leading to PARP-1 activation. The cooperative intervention with these metabolic pathways leads to energy crisis and necrotic death in malignant, but not in normal human cells, and to the suppression of tumors growth in vivo. Thus, E260 is a new anti-cancer agent which imposes metabolic stress and cellular death in cancer cells.The tyrosine-kinases Fer/FerT associate with the mitochondrial electron transport chain in cancer cells supporting their metabolic reprogramming. Here the authors discover a compound that disrupts Fer /FerT activity and selectively induces cell death of cancer cell lines displaying anti-tumor activity in vivo.

CAOS-Episodic Cerebellar Ataxia, Areflexia, Optic Atrophy, and Sensorineural Hearing Loss: A Third Allelic Disorder of the ATP1A3 Gene.

We describe the molecular basis of a distinctive syndrome characterized by infantile stress-induced episodic weakness, ataxia, and sensorineural hearing loss, with permanent areflexia and optic nerve pallor. Whole exome sequencing identified a deleterious heterozygous c.2452 G>A, p.(E818K) variant in the ATP1A3 gene and structural analysis predicted its protein-destabilizing effect. This variant has not been reported in context with rapid-onset dystonia parkinsonism and alternating hemiplegia of childhood, the 2 main diseases associated with ATP1A3. The clinical presentation in the family described here differs categorically from these diseases in age of onset, clinical course, cerebellar over extrapyramidal movement disorder predominance, and peripheral nervous system involvement. While this paper was in review, a highly resembling phenotype was reported in additional patients carrying the same c.2452 G>A variant. Our findings substantiate this variant as the cause of a unique inherited autosomal dominant neurologic syndrome that constitutes a third allelic disease of the ATP1A3 gene.

Co-expression and co-localization of hub proteins and their partners are encoded in protein sequence.

Spatiotemporal coordination is a critical factor in biological processes. Some hubs in protein-protein interaction networks tend to be co-expressed and co-localized with their partners more strongly than others, a difference which is arguably related to functional differences between the hubs. Based on numerous analyses of yeast hubs, it has been suggested that differences in co-expression and co-localization are reflected in the structural and molecular characteristics of the hubs. We hypothesized that if indeed differences in co-expression and co-localization are encoded in the molecular characteristics of the protein, it may be possible to predict the tendency for co-expression and co-localization of human hubs based on features learned from systematically characterized yeast hubs. Thus, we trained a prediction algorithm on hubs from yeast that were classified as either strongly or weakly co-expressed and co-localized with their partners, and applied the trained model to 800 human hub proteins. We found that the algorithm significantly distinguishes between human hubs that are co-expressed and co-localized with their partners and hubs that are not. The prediction is based on sequence derived features such as "stickiness", i.e. the existence of multiple putative binding sites that enable multiple simultaneous interactions, "plasticity", i.e. the existence of predicted structural disorder which conjecturally allows for multiple consecutive interactions with the same binding site and predicted subcellular localization. These results suggest that spatiotemporal dynamics is encoded, at least in part, in the amino acid sequence of the protein and that this encoding is similar in yeast and in human.

Neighbor overlap is enriched in the yeast interaction network: analysis and implications.

The yeast protein-protein interaction network has been shown to have distinct topological features such as a scale free degree distribution and a high level of clustering. Here we analyze an additional feature which is called Neighbor Overlap. This feature reflects the number of shared neighbors between a pair of proteins. We show that Neighbor Overlap is enriched in the yeast protein-protein interaction network compared with control networks carefully designed to match the characteristics of the yeast network in terms of degree distribution and clustering coefficient. Our analysis also reveals that pairs of proteins with high Neighbor Overlap have higher sequence similarity, more similar GO annotations and stronger genetic interactions than pairs with low ones. Finally, we demonstrate that pairs of proteins with redundant functions tend to have high Neighbor Overlap. We suggest that a combination of three mechanisms is the basis for this feature: The abundance of protein complexes, selection for backup of function, and the need to allow functional variation.