ChEA3: transcription factor enrichment analysis by orthogonal omics integration

Novel immune cross-talk between inflammatory bowel disease and IgA nephropathy

The mechanisms underlying the complex correlation between immunoglobulin A nephropathy (IgAN) and inflammatory bowel disease (IBD) remain unclear. This study aimed to identify the optimal cross-talk genes, potential pathways, and mutual immune-infiltrating microenvironments between IBD and IgAN to elucidate the linkage between patients with IBD and IgAN. The IgAN and IBD datasets were obtained from the Gene Expression Omnibus (GEO). Three algorithms, CIBERSORTx, ssGSEA, and xCell, were used to evaluate the similarities in the infiltrating microenvironment between the two diseases. Weighted gene co-expression network analysis (WGCNA) was implemented in the IBD dataset to identify the major immune infiltration modules, and the Boruta algorithm, RFE algorithm, and LASSO regression were applied to filter the cross-talk genes. Next, multiple machine learning models were applied to confirm the optimal cross-talk genes. Finally, the relevant findings were validated using histology and immunohistochemistry analysis of IBD mice. Immune infiltration analysis showed no significant differences between IBD and IgAN samples in most immune cells. The three algorithms identified 10 diagnostic genes, MAPK3, NFKB1, FDX1, EPHX2, SYNPO, KDF1, METTL7A, RIDA, HSDL2, and RIPK2; FDX1 and NFKB1 were enhanced in the kidney of IBD mice. Kyoto Encyclopedia of Genes and Genomes analysis showed 15 mutual pathways between the two diseases, with lipid metabolism playing a vital role in the cross-talk. Our findings offer insights into the shared immune mechanisms of IgAN and IBD. These common pathways, diagnostic cross-talk genes, and cell-mediated abnormal immunity may inform further experimental studies.

Benchmarking tools for transcription factor prioritization

Spatiotemporal regulation of gene expression is controlled by transcription factor (TF) binding to regulatory elements, resulting in a plethora of cell types and cell states from the same genetic information. Due to the importance of regulatory elements, various sequencing methods have been developed to localise them in genomes, for example using ChIP-seq profiling of the histone mark H3K27ac that marks active regulatory regions. Moreover, multiple tools have been developed to predict TF binding to these regulatory elements based on DNA sequence. As altered gene expression is a hallmark of disease phenotypes, identifying TFs driving such gene expression programs is critical for the identification of novel drug targets. In this study, we curated 84 chromatin profiling experiments (H3K27ac ChIP-seq) where TFs were perturbed through e.g., genetic knockout or overexpression. We ran nine published tools to prioritize TFs using these real-world datasets and evaluated the performance of the methods in identifying the perturbed TFs. This allowed the nomination of three frontrunner tools, namely RcisTarget, MEIRLOP and monaLisa. Our analyses revealed opportunities and commonalities of tools that will help to guide further improvements and developments in the field.

Integrated in silico analysis of transcriptomic alterations in nanoparticle toxicity across human and mouse models

Nanoparticles, due to their exceptional physicochemical properties are used in our day-to-day environment. They are currently not regulated which might lead to increased levels in the biological systems causing adverse effects. However, the overall mechanism behind nanotoxicity remains elusive. Previously, we analysed the transcriptome datasets of copper oxide nanoparticles using in silico tools and identified IL-17, chemokine signaling pathway, and cytokine-cytokine receptor interaction as the key pathways altered. Based on the findings, we hypothesized a common pathway could be involved in transition metal oxide nanoparticles toxicity irrespective of the variables. Further, there could be unique transcriptome changes between metal oxide nanoparticles and other nanoparticles. To accomplish this, the overall transcriptome datasets of nanoparticles consisting of microarray and RNA-Seq were obtained. >90 studies for 17 different nanoparticles, performed in humans, rats, and mice were assessed. After initial screening, 24 mouse studies (with 196 datasets) and 34 human studies (with 200 datasets) were used for further analyses. The common genes that are dysregulated upon NPs exposure were identified for human and mouse datasets separately. Further, an overrepresentation functional enrichment analysis was performed. The common genes, their gene ontology, gene-gene, and protein-protein interactions were assessed. The overall results suggest that IL-17 and its related pathways might be commonly altered in nanoparticle exposure with lung as one of the major organs affected.

Bioavailable testosterone and androgen receptor activation, but not total testosterone, are associated with muscle mass and strength in females

Testosterone, the major androgen, influences the reproductive and non-reproductive systems in males and females via binding to the androgen receptor (AR). Both circulating endogenous testosterone and muscle AR protein content are positively associated with muscle mass and strength in males, but there is no such evidence in females. Here, we tested whether circulating testosterone levels were associated with muscle mass, function, or the muscle anabolic response to resistance training in pre-menopausal females. Twenty-seven pre-menopausal, untrained females (aged 23.5 ± 4.8 years) underwent a 12-week resistance training programme. Muscle strength, size, power, and plasma and urine androgen hormone levels were measured. Skeletal muscle biopsies were collected before and after the training programme to quantify the effect of resistance training on AR content and nuclear localisation. Primary muscle cell lines were cultured from a subset (n = 6) of the participants' biopsies and treated with testosterone to investigate its effect on myotube diameter, markers of muscle protein synthesis and AR cellular localisation. Physiological levels of total testosterone were not associated with muscle mass or strength at baseline or with the changes in muscle mass and strength that occurred in response to resistance training in our cohort of pre-menopausal females. In contrast, bioavailable testosterone and the proportion of nuclear-localised AR were positively associated with skeletal muscle mass and strength in pre-menopausal females. In vitro, supra-physiological doses of testosterone increased myocyte diameter, but this did not occur via the Akt/mTOR pathway as previously suggested. Instead, we show a marked increase in AR nuclear localisation with testosterone administration in vitro. KEY POINTS: Total circulating testosterone was not related to muscle mass or strength before or after resistance training in pre-menopausal females. Bioavailable testosterone was positively related to exercise-induced muscle hypertrophy in pre-menopausal females. In vivo nuclear localisation of the androgen receptor was positively related to muscle mass in pre-menopausal females at baseline, but not to resistance training-induced hypertrophy. Testosterone treatment induced androgen receptor nuclear translocation but did not induce mTOR signalling in primary skeletal myocytes cultured from pre-menopausal female muscle.

CRISPR-GEM: A Novel Machine Learning Model for CRISPR Genetic Target Discovery and Evaluation

CRISPR gene editing strategies are shaping cell therapies through precise and tunable control over gene expression. However, limitations in safely delivering high quantities of CRISPR machinery demand careful target gene selection to achieve reliable therapeutic effects. Informed target gene selection requires a thorough understanding of the involvement of target genes in gene regulatory networks (GRNs) and thus their impact on cell phenotype. Effective decoding of these complex networks has been achieved using machine learning models, but current techniques are limited to single cell types and focus mainly on transcription factors, limiting their applicability to CRISPR strategies. To address this, we present CRISPR-GEM, a multilayer perceptron (MLP) based synthetic GRN constructed to accurately predict the downstream effects of CRISPR gene editing. First, input and output nodes are identified as differentially expressed genes between defined experimental and target cell/tissue types, respectively. Then, MLP training learns regulatory relationships in a black-box approach allowing accurate prediction of output gene expression using only input gene expression. Finally, CRISPR-mimetic perturbations are made to each input gene individually, and the resulting model predictions are compared to those for the target group to score and assess each input gene as a CRISPR candidate. The top scoring genes provided by CRISPR-GEM therefore best modulate experimental group GRNs to motivate transcriptomic shifts toward a target group phenotype. This machine learning model is the first of its kind for predicting optimal CRISPR target genes and serves as a powerful tool for enhanced CRISPR strategies across a range of cell therapies.

Phenotype remodelling of HNSCC cells in the muscle invasion environment

BACKGROUND

Tumour invading muscle in head and neck squamous cell carcinoma (HNSCC) is often associated with destructive growth and poor prognosis. However, the phenotypic functions and pathological mechanisms of muscle-invasive cancer cells in tumour progress remains unknown. In this study, we aimed to investigate the phenotypic functions of muscle-invasive cancer cells of HNSCC and their potential crosstalk with tumour microenvironment.

METHODS

We obtained scRNA-seq data (SC) from GSE103322 (N = 18) and GSE181919 (N = 37), spatial RNA-seq data (ST) from GSE208253 and GSE181300 (N = 4), transcriptomics of human HNSCC samples from GSE42743 (N = 12) and GSE41613 (N = 97). Utilizing the TCGA-HNSC dataset, we conducted univariate and multivariate Cox analyses to investigate the prognostic impact of muscle-invasion in HNSCC, with validation in an additional cohort. Through Stutility and AUCell approaches, we identified and characterized muscle-invasive cancer cell clusters, including their functional phenotypes and gene-specific profiles. Integration of SC and ST data was achieved using Seurat analysis, multimodal intersection analysis, and spatial deconvolution. The results were further validated via in vitro and in vivo experiments.

RESULTS

Our analyses of the TCGA-HNSC cohort revealed the presence of muscle-invasion was associated with a poor prognosis. By combining ST and SC, we identified muscle-invasive cancer cells exhibiting epithelial-to-mesenchymal transition (EMT) and myoepithelial-like transcriptional programs, which were correlated with a poor prognosis. Furthermore, we identified G0S2 as a novel marker of muscle-invasive malignant cells that potentially promotes EMT and the acquisition of myoepithelium-like phenotypes. These findings were validated through in vitro assays and chorioallantoic membranes experiments. Additionally, we demonstrated that G0S2-overexpressing cancer cells might attract human ECs via VEGF signalling. Subsequent in vitro and in vivo experiments revealed G0S2 plays key roles in promoting the proliferation and invasion of cancer cells.

CONCLUSIONS

In this study, we profiled the transcriptional programs of muscle-invasive HNSCC cell populations and characterized their EMT and myoepithelial-like phenotypes. Furthermore, our findings highlight the presence of muscle-invasion as a predictive marker for HNSCC patients. G0S2 as one of the markers of muscle-invasive cancer cells is involved in HNSCC intravasation, probably via VEGF signalling.

The use of a multi-metric readout screen to identify EHMT2/G9a-inhibition as a modulator of cancer-associated fibroblast activation state

Cancer-associated fibroblasts (CAFs) play a pivotal role in cancer progression, including mediating tumour cell invasion via their pro-invasive secretory profile and ability to remodel the extracellular matrix (ECM). Given that reduced CAF abundance in tumours correlates with improved outcomes in various cancers, we set out to identify epigenetic targets involved in CAF activation in regions of tumour-stromal mixing with the goal of reducing tumour aggressiveness. Using the GLAnCE (Gels for Live Analysis of Compartmentalized Environments) platform, we performed an image-based, phenotypic screen that enabled us to identify modulators of CAF abundance and the capacity of CAFs to induce tumour cell invasion. We identified EHMT2 (also known as G9a), an enzyme that targets the methylation of histone 3 lysine 9 (H3K9), as a potent modulator of CAF abundance and CAF-mediated tumour cell invasion. Transcriptomic and functional analysis of EHMT2-inhibited CAFs revealed EHMT2 participated in driving CAFs towards a pro-invasive phenotype and mediated CAF hyperproliferation, a feature typically associated with activated fibroblasts in tumours. Our study suggests that EHMT2 regulates CAF state within the tumour microenvironment by impacting CAF activation, as well as by magnifying the pro-invasive effects of these activated CAFs on tumour cell invasion through promoting CAF hyperproliferation.

Sustained alterations in proximal tubule gene expression in primary culture associate with HNF4A loss

Primary cultures of proximal tubule cells are widely used to model the behavior of kidney epithelial cells in vitro. However, de-differentiation of primary cells upon culture has been observed and appreciated for decades, yet the mechanisms driving this phenomenon remain poorly understood. This confounds the interpretation of experiments using primary kidney epithelial cells and prevents their use to engineer functional kidney tissue ex vivo. In this report, we measure the dynamics of cell-state transformations in early primary culture of mouse proximal tubules to identify key pathways and processes that correlate with and may drive de-differentiation. Our data show that the loss of proximal-tubule-specific genes is rapid, uniform, and sustained even after confluent, polarized epithelial monolayers develop. This de-differentiation occurs uniformly across many common culture condition variations. Changes in early culture were strongly associated with the loss of HNF4A. Exogenous re-expression of HNF4A can promote expression of a subset of proximal tubule genes in a de-differentiated proximal tubule cell line. Using genetically labeled proximal tubule cells, we show that selective pressures very early in culture influence which cells grow to confluence. Together, these data indicate that the loss of in vivo function in proximal tubule cultures occurs very early and suggest that the sustained loss of HNF4A is a key regulatory event mediating this change.

Propofol Protects the Blood-Brain Barrier After Traumatic Brain Injury by Stabilizing the Extracellular Matrix via Prrx1: From Neuroglioma to Neurotrauma

The purpose of this study is to explore the shared molecular pathogenesis of traumatic brain injury (TBI) and high-grade glioma and investigate the mechanism of propofol (PF) as a potential protective agent. By analyzing the Chinese glioma genome atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases, we compared the transcriptomic data of high-grade glioma and TBI patients to identify common pathological mechanisms. Through bioinformatics analysis, in vitro experiments and in vivo TBI model, we investigated the regulatory effect of PF on extracellular matrix (ECM)-related genes through Prrx1 under oxidative stress. The impact of PF on BBB integrity under oxidative stress was investigated using a dual-layer BBB model, and we explored the protective effect of PF on tight junction proteins and ECM-related genes in mice after TBI. The study found that high-grade glioma and TBI share ECM instability as an important molecular pathological mechanism. PF stabilizes the ECM and protects the BBB by directly binding to Prrx1 or indirectly regulating Prrx1 through miRNAs. In addition, PF reduces intracellular calcium ions and ROS levels under oxidative stress, thereby preserving BBB integrity. In a TBI mouse model, PF protected BBB integrity through up-regulated tight junction proteins and stabilized the expression of ECM-related genes. Our study reveals the shared molecular pathogenesis between TBI and glioblastoma and demonstrate the potential of PF as a protective agent of BBB. This provides new targets and approaches for the development of novel neurotrauma therapeutic drugs.

Augmenting CAR T-cell Functions with LIGHT

Chimeric antigen receptor (CAR) T-cell therapy has resulted in remarkable clinical success in the treatment of B-cell malignancies. However, its clinical efficacy in solid tumors is limited, primarily by target antigen heterogeneity. To overcome antigen heterogeneity, we developed CAR T cells that overexpress LIGHT, a ligand of both lymphotoxin-β receptor on cancer cells and herpes virus entry mediator on immune cells. LIGHT-expressing CAR T cells displayed both antigen-directed cytotoxicity mediated by the CAR and antigen-independent killing mediated through the interaction of LIGHT with lymphotoxin-β receptor on cancer cells. Moreover, CAR T cells expressing LIGHT had immunostimulatory properties that improved the cells' proliferation and cytolytic profile. These data indicate that LIGHT-expressing CAR T cells may provide a way to eliminate antigen-negative tumor cells to prevent antigen-negative disease relapse.

Hepatic WDR23 proteostasis mediates insulin homeostasis by regulating insulin-degrading enzyme capacity

Maintaining insulin homeostasis is critical for cellular and organismal metabolism. In the liver, insulin is degraded by the activity of the insulin-degrading enzyme (IDE). Here, we establish a hepatic regulatory axis for IDE through WDR23-proteostasis. Wdr23KO mice have increased IDE expression, reduced circulating insulin, and defective insulin responses. Genetically engineered human cell models lacking WDR23 also increase IDE expression and display dysregulated phosphorylation of insulin signaling cascade proteins, IRS-1, AKT2, MAPK, FoxO, and mTOR, similar to cells treated with insulin, which can be mitigated by chemical inhibition of IDE. Mechanistically, the cytoprotective transcription factor NRF2, a direct target of WDR23-Cul4 proteostasis, mediates the enhanced transcriptional expression of IDE when WDR23 is ablated. Moreover, an analysis of human genetic variation in WDR23 across a large naturally aging human cohort in the US Health and Retirement Study reveals a significant association of WDR23 with altered hemoglobin A1C (HbA1c) levels in older adults, supporting the use of WDR23 as a new molecular determinant of metabolic health in humans.

Exome sequencing of 20,979 individuals with epilepsy reveals shared and distinct ultra-rare genetic risk across disorder subtypes

Identifying genetic risk factors for highly heterogeneous disorders such as epilepsy remains challenging. Here we present, to our knowledge, the largest whole-exome sequencing study of epilepsy to date, with more than 54,000 human exomes, comprising 20,979 deeply phenotyped patients from multiple genetic ancestry groups with diverse epilepsy subtypes and 33,444 controls, to investigate rare variants that confer disease risk. These analyses implicate seven individual genes, three gene sets and four copy number variants at exome-wide significance. Genes encoding ion channels show strong association with multiple epilepsy subtypes, including epileptic encephalopathies and generalized and focal epilepsies, whereas most other gene discoveries are subtype specific, highlighting distinct genetic contributions to different epilepsies. Combining results from rare single-nucleotide/short insertion and deletion variants, copy number variants and common variants, we offer an expanded view of the genetic architecture of epilepsy, with growing evidence of convergence among different genetic risk loci on the same genes. Top candidate genes are enriched for roles in synaptic transmission and neuronal excitability, particularly postnatally and in the neocortex. We also identify shared rare variant risk between epilepsy and other neurodevelopmental disorders. Our data can be accessed via an interactive browser, hopefully facilitating diagnostic efforts and accelerating the development of follow-up studies.

Blood RNA-sequencing across the continuum of ANA-positive autoimmunity reveals insights into initiating immunopathology

OBJECTIVE

Mechanisms underpinning clinical evolution to systemic lupus erythematosus (SLE) from preceding antinuclear antibodies (ANA) positivity are poorly understood. This study aimed to understand blood immune cell transcriptional signatures associated with subclinical ANA positivity, and progression or non-progression to SLE.

METHODS

Bulk RNA-sequencing of peripheral blood mononuclear cells isolated at baseline from 35 ANA positive (ANA+) subjects with non-diagnostic symptoms was analysed using differential gene expression, weighted gene co-expression network analysis, deconvolution of cell subsets and functional enrichment analyses. ANA+ subjects, including those progressing to classifiable SLE at 12 months (n=15) and those with stable subclinical ANA positivity (n=20), were compared with 15 healthy subjects and 18 patients with SLE.

RESULTS

ANA+ subjects demonstrated extensive transcriptomic dysregulation compared with healthy controls with reduced CD4+naïve T-cells and resting NK cells, but higher activated dendritic cells. B-cell lymphopenia was evident in SLE but not ANA+ subjects. Two-thirds of dysregulated genes were common to ANA+ progressors and non-progressors. ANA+ progressors showed elevated modular interferon signature in which constituent genes were inducible by both type I interferon (IFN-I) and type II interferon (IFN-II) in vitro. Baseline downregulation of mitochondrial oxidative phosphorylation complex I components significantly associated with progression to SLE but did not directly correlate with IFN modular activity. Non-progressors demonstrated more diverse cytokine profiles.

CONCLUSIONS

ANA positivity, irrespective of clinical trajectory, is profoundly dysregulated and transcriptomically closer to SLE than to healthy immune function. Metabolic derangements and IFN-I activation occur early in the ANA+ preclinical phase and associated with diverging transcriptomic profiles which distinguish subsequent clinical evolution.

Systemic deficits in lipid homeostasis promote aging-associated impairments in B cell progenitor development

Organismal aging has been associated with diverse metabolic and functional changes across tissues. Within the immune system, key features of physiological hematopoietic cell aging include increased fat deposition in the bone marrow, impaired hematopoietic stem and progenitor cell (HSPC) function, and a propensity towards myeloid differentiation. This shift in lineage bias can lead to pre-malignant bone marrow conditions such as clonal hematopoiesis of indeterminate potential (CHIP) or clonal cytopenias of undetermined significance (CCUS), frequently setting the stage for subsequent development of age-related cancers in myeloid or lymphoid lineages. At the systemic as well as sub-cellular level, human aging has also been associated with diverse lipid alterations, such as decreased phospholipid membrane fluidity that arises as a result of increased saturated fatty acid (FA) accumulation and a decay in n-3 polyunsaturated fatty acid (PUFA) species by the age of 80 years, however the extent to which impaired FA metabolism contributes to hematopoietic aging is less clear. Here, we performed comprehensive multi-omics analyses and uncovered a role for a key PUFA biosynthesis gene, ELOVL2 , in mouse and human immune cell aging. Whole transcriptome RNA-sequencing studies of bone marrow from aged Elovl2 mutant (enzyme-deficient) mice compared with age-matched controls revealed global down-regulation in lymphoid cell markers and expression of genes involved specifically in B cell development. Flow cytometric analyses of immune cell markers confirmed an aging-associated loss of B cell markers that was exacerbated in the bone marrow of Elovl2 mutant mice and unveiled CD79B, a vital molecular regulator of lymphoid progenitor development from the pro-B to pre-B cell stage, as a putative surface biomarker of accelerated immune aging. Complementary lipidomic studies extended these findings to reveal select alterations in lipid species in aged and Elovl2 mutant mouse bone marrow samples, suggesting significant changes in the biophysical properties of cellular membranes. Furthermore, single cell RNA-seq analysis of human HSPCs across the spectrum of human development and aging uncovered a rare subpopulation (<7%) of CD34 + HSPCs that expresses ELOVL2 in healthy adult bone marrow. This HSPC subset, along with CD79B -expressing lymphoid-committed cells, were almost completely absent in CD34 + cells isolated from elderly (>60 years old) bone marrow samples. Together, these findings uncover new roles for lipid metabolism enzymes in the molecular regulation of cellular aging and immune cell function in mouse and human hematopoiesis. In addition, because systemic loss of ELOVL2 enzymatic activity resulted in down-regulation of B cell genes that are also associated with lymphoproliferative neoplasms, this study sheds light on an intriguing metabolic pathway that could be leveraged in future studies as a novel therapeutic modality to target blood cancers or other age-related conditions involving the B cell lineage.

Pan-cancer analysis of ADAR1 with its prognostic relevance in low-grade glioma

ADAR1, known as the primary enzyme for adenosine-to-inosine RNA editing, has recently been implicated in cancer development through both RNA editing-dependent and -independent pathways. These discoveries suggest that ADAR1's functions may extend beyond our current understanding. A pan-cancer analysis offers a unique opportunity to identify both common and distinct mechanisms across various cancers, thereby advancing personalized medicine. Low-grade glioma (LGG), characterized by a diverse group of tumor cells, presents a challenge in risk stratification, leading to significant variations in treatment approaches. Recently discovered molecular alterations in LGG have helped to refine the stratification of of these tumors and offered novel targets for predicting likely outcomes. This study aims to provide a detailed analysis of ADAR mRNA across multiple cancers, emphasizing its prognostic significance in LGG. We observed inconsistent mRNA and consistent protein expression patterns of ADAR1/ADAR in pan-cancer analyses that across tumor types. ADAR mRNA expression did not always correlate with ADAR1 protein expression. Nevertheless, the transcript levels correlated significantly with genetic alterations, tumor mutation burden, microsatellite instability, overall survival, recurrence-free survival, immune marker presence, immune infiltration, and the survival of patients undergoing immunotherapy in select cancers. Furthermore, ADAR and its top 50 associated genes were primarily involved in mRNA-related events, as identified through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Utilizing the Cox proportional hazards model, we developed a 3-gene signature (ADAR, HNRNPK, and SMG7), which effectively stratified patients into high- and low-risk groups, with high-risk patients exhibiting poorer overall survival, higher tumor grades, and a greater number of non-codeletions. Overall, this signature was inversely related to immune infiltration across cancers. Transcription factor SPI1 and miR-206, potential upstream regulators of the signature genes, were closely linked to patient survival in LGG. The promoter regions of these genes were hypermethylated, further associating them with patient outcomes. Additionally, these genes displayed consistent drug susceptibility patterns. In conclusion, our findings reveal multiple aspects of ADAR1's role in cancer and underscore its prognostic value in LGG, offering insights into potential therapeutic targets and strategies.

An integrative analysis of cell-specific transcriptomics and nuclear proteomics of sleep-deprived mouse cerebral cortex

Sleep regulation follows a homeostatic pattern. The mammalian cerebral cortex is the repository of homeostatic sleep drive and neurons and astrocytes of the cortex are principal responders of sleep need. The molecular mechanisms by which these two cell types respond to sleep loss are not yet clearly understood. By combining cell-type specific transcriptomics and nuclear proteomics we investigated how sleep loss affects the cellular composition and molecular profiles of these two cell types in a focused approach. The results indicate that sleep deprivation regulates gene expression and nuclear protein abundance in a cell-type-specific manner. Our integrated multi-omics analysis suggests that this distinction arises because neurons and astrocytes employ different gene regulatory strategies under accumulated sleep pressure. These findings provide a comprehensive view of the effects of sleep deprivation on gene regulation in neurons and astrocytes.

Knockouts of CYP51A1, DHCR24, or SC5D from cholesterol synthesis reveal pathways modulated by sterol intermediates

Sterols from cholesterol synthesis are crucial for cholesterol production, but also have individual roles difficult to assess in vivo due to essentiality of cholesterol. We developed HepG2 cell models with knockouts (KOs) for three enzymes of cholesterol synthesis, each accumulating specific sterols. Surprisingly, KOs of CYP51, DHCR24, and SC5D shared only 9% of differentially expressed genes. The most striking was the phenotype of CYP51 KO with highly elevated lanosterol and 24,25-dihydrolanosterol, significant increase in G2+M phase and enhanced cancer and cell cycle pathways. Comparisons with mouse liver Cyp51 KO data suggest 24,25-dihydrolanosterol activates similar cell proliferation pathways, possibly via elevated LEF1 and WNT/NFKB signaling. In contrast, SC5D and DHCR24 KO cells with elevated lathosterol or desmosterol proliferated slowly, with downregulated E2F, mitosis, and enriched HNF1A. These findings demonstrate that increase of lanosterol and 24,25-dihydrolanosterol, but not other sterols, promotes cell proliferation in hepatocytes.

ICOS limits memory-like properties and function of exhausted PD-1 + CD8 T cells

During persistent antigen stimulation, PD-1 + CD8 T cells are maintained by progenitor exhausted PD-1 + TCF-1 + CD8 T cells (Tpex). Tpex respond to PD-1 blockade, and regulation of Tpex differentiation into more functional Tex is of major interest for cancer immunotherapies. Tpex express high levels of Inducible Costimulator (ICOS), but the role of ICOS for PD-1 + CD8 T cell responses has not been addressed. In chronic infection, ICOS-deficiency increased both number and quality of virus-specific CD8 T cells, with accumulation of effector-like Tex due to enhanced survival. Mechanistically, loss of ICOS signaling potentiated FoxO1 activity and memory-like features of Tpex. In mice with established chronic infection, ICOS-Ligand blockade resulted in expansion of effector-like Tex and reduction in viral load. In a mouse model of hepatocellular carcinoma, ICOS inhibition improved cytokine production by tumor-specific PD-1 + CD8 T cells and delayed tumor growth. Overall, we show that ICOS limits CD8 T cell responses during chronic antigen exposure.

Advances in omics data for eosinophilic esophagitis: moving towards multi-omics analyses

Eosinophilic esophagitis (EoE) is a chronic, allergic inflammatory disease of the esophagus characterized by eosinophil accumulation and has a growing global prevalence. EoE significantly impairs quality of life and poses a substantial burden on healthcare resources. Currently, only two FDA-approved medications exist for EoE, highlighting the need for broader research into its management and prevention. Recent advancements in omics technologies, such as genomics, epigenetics, transcriptomics, proteomics, and others, offer new insights into the genetic and immunologic mechanisms underlying EoE. Genomic studies have identified genetic loci and mutations associated with EoE, revealing predispositions that vary by ancestry and indicating EoE's complex genetic basis. Epigenetic studies have uncovered changes in DNA methylation and chromatin structure that affect gene expression, influencing EoE pathology. Transcriptomic analyses have revealed a distinct gene expression profile in EoE, dominated by genes involved in activated type 2 immunity and epithelial barrier function. Proteomic approaches have furthered the understanding of EoE mechanisms, identifying potential new biomarkers and therapeutic targets. However, challenges in integrating diverse omics data persist, largely due to their complexity and the need for advanced computational methods. Machine learning is emerging as a valuable tool for analyzing extensive and intricate datasets, potentially revealing new aspects of EoE pathogenesis. The integration of multi-omics data through sophisticated computational approaches promises significant advancements in our understanding of EoE, improving diagnostics, and enhancing treatment effectiveness. This review synthesizes current omics research and explores future directions for comprehensively understanding the disease mechanisms in EoE.

Single-cell and bulk transcriptional profiling of mouse ovaries reveals novel genes and pathways associated with DNA damage response in oocytes

Immature oocytes enclosed in primordial follicles stored in female ovaries are under constant threat of DNA damage induced by endogenous and exogenous factors. Checkpoint kinase 2 (CHEK2) is a key mediator of the DNA damage response (DDR) in all cells. Genetic studies have shown that CHEK2 and its downstream targets, p53, and TAp63, regulate primordial follicle elimination in response to DNA damage. However, the mechanism leading to their demise is still poorly characterized. Single-cell and bulk RNA sequencing were used to determine the DDR in wild-type and Chek2-deficient ovaries. A low but oocyte-lethal dose of ionizing radiation induces ovarian DDR that is solely dependent on CHEK2. DNA damage activates multiple response pathways related to apoptosis, p53, interferon signaling, inflammation, cell adhesion, and intercellular communication. These pathways are differentially employed by different ovarian cell types, with oocytes disproportionately affected by radiation. Novel genes and pathways are induced by radiation specifically in oocytes, shedding light on their sensitivity to DNA damage, and implicating a coordinated response between oocytes and pregranulosa cells within the follicle. These findings provide a foundation for future studies on the specific mechanisms regulating oocyte survival in the context of aging, therapeutic and environmental genotoxic exposures.

Aryl hydrocarbon receptor restricts axon regeneration of DRG neurons in response to injury

Injured neurons sense environmental cues to balance neural protection and axon regeneration, but the mechanisms are unclear. Here, we unveil aryl hydrocarbon receptor (AhR), a ligand-activated bHLH-PAS transcription factor, as a molecular sensor and key regulator of acute stress response at the expense of axon regeneration. We demonstrate responsiveness of DRG sensory neurons to AhR signaling, which functions to inhibit axon regeneration. Conditional Ahr deletion in neurons accelerates axon regeneration after sciatic nerve injury. Ahr deletion partially mimics the conditioning lesion in priming DRG to initiate axonogenesis gene programs; upon peripheral axotomy, Ahr ablation suppresses inflammation and stress signaling while augmenting pro-growth pathways. Moreover, comparative transcriptomics revealed signaling interactions between AhR and HIF-1α, two structurally related bHLH-PAS α units that share the dimerization partner Arnt/HIF-1β. Functional assays showed that the growth advantage of AhR-deficient DRG neurons requires HIF-1α; but in the absence of Arnt, DRG neurons can still mount a regenerative response. We further unveil a link between bHLH-PAS transcription factors and DNA hydroxymethylation in response to peripheral axotomy, while RNA-seq of DRG neurons and neuronal single cell RNA-seq analysis revealed a link of AhR regulon to RNA regulation and integrated stress response (ISR). Altogether, AhR activation favors stress coping and inflammation at the expense of axon regeneration; targeting AhR has the potential to enhance nerve repair.

Identification of autophagy-related genes as potential biomarkers correlated with immune infiltration in bipolar disorder: a bioinformatics analysis

BACKGROUND

Bipolar disorder (BPD) is a kind of manic and depressive phase alternate episodes of serious mental illness, and it is correlated with well-documented cortical brain abnormalities. Emerging evidence supports that autophagy dysfunction in neuronal system contributes to pathophysiological changes in neurological disease. However, the role of autophagy in bipolar disorder has rarely been elucidated. This study aimed to identify the autophagy-related gene as a potential biomarker Correlated to immune infiltration in BPD.

METHODS

The microarray dataset GSE23848 and autophagy-related genes (ARGs) were downloaded. Differentially expressed genes (DEGs) between normal and BPD samples were screened using the R software. Machine learning algorithms were performed to screen the significant candidate biomarker from autophagy-related differentially expressed genes (ARDEGs). The correlation between the screened ARDEGs and infiltrating immune cells was explored through correlation analysis.

RESULTS

In this study, the autophagy pathway was abundantly enriched and activated in BPD, as indicated by Pathway enrichment analysis. We identified 16 ARDEGs in BPD compared to the normal group. A signature of 4 ARDEGs (ERN1, ATG3, CTSB, and EIF2AK3) was screened. ROC analysis showed that the above genes have good diagnostic performance. In addition, immune correlation analysis considered that the above four genes significantly correlated with immune cells in BPD.

CONCLUSIONS

Autophagy - immune cell axis mediates pathophysiological changes in BPD. Four important ARDEGs are prospective to be potential biomarkers associated with immune infiltration in BPD and helpful for the prediction or diagnosis of BPD.

Unveiling and Validating the Role of Fatty Acid Metabolism in Ulcerative Colitis

Background

Ulcerative colitis (UC) is a debilitating intestinal disorder that imposes a significant burden on those affected. Fatty acid metabolism plays a pivotal role in regulating immune cell function and maintaining internal homeostasis. This study investigates the biological and clinical significance of fatty acid metabolism within the context of UC.

Methods

Gene expression profiles from patients with UC and healthy controls were retrieved, enabling the identification of differentially expressed genes (DEGs) specific to UC. These DEGs were then intersected with genes related to fatty acid metabolism, resulting in the identification of differentially expressed fatty acid metabolism-related genes (FAM-DEGs). Machine learning was employed to pinpoint key feature genes from the FAM-DEGs, which were subsequently used to construct a predictive UC model and to uncover molecular subtypes associated with fatty acid metabolism in UC. An animal model of UC was established using 3% dextran sulfate sodium (DSS) administration. Western blot analysis confirmed the expression levels of genes in intestinal tissues.

Results

The machine learning analysis identified three pivotal genes-ACAT1, ACOX2, and HADHB-culminating in a highly predictive nomogram. Consensus cluster analysis further categorized 637 UC samples into two distinct subgroups. The molecular subtypes related to fatty acid metabolism in UC exhibited significant differences in gene expression, biological activities, and enrichment pathways. Immune infiltration analysis highlighted elevated expression of two genes (excluding HADHB) in subtype 1, which corresponded with a marked increase in immune cell infiltration within this subtype. Western blot analysis demonstrated that ACAT1, ACOX2, and HADHB expression levels in the DSS group were significantly reduced, paralleling those observed in the normal group.

Conclusion

This study highlights the critical role of specific fatty acid metabolism-related genes in UC, emphasizing their potential as targets for therapeutic intervention and shedding light on the underlying mechanisms of UC progression.

Multiscale mapping of transcriptomic signatures for cardiotoxic drugs

Drug-induced gene expression profiles can identify potential mechanisms of toxicity. We focus on obtaining signatures for cardiotoxicity of FDA-approved tyrosine kinase inhibitors (TKIs) in human induced-pluripotent-stem-cell-derived cardiomyocytes, using bulk transcriptomic profiles. We use singular value decomposition to identify drug-selective patterns across cell lines obtained from multiple healthy human subjects. Cellular pathways affected by cardiotoxic TKIs include energy metabolism, contractile, and extracellular matrix dynamics. Projecting these pathways to published single cell expression profiles indicates that TKI responses can be evoked in both cardiomyocytes and fibroblasts. Integration of transcriptomic outlier analysis with whole genomic sequencing of our six cell lines enables us to correctly reidentify a genomic variant causally linked to anthracycline-induced cardiotoxicity and predict genomic variants potentially associated with TKI-induced cardiotoxicity. We conclude that mRNA expression profiles when integrated with publicly available genomic, pathway, and single cell transcriptomic datasets, provide multiscale signatures for cardiotoxicity that could be used for drug development and patient stratification.

Molecular Profiling Defines Three Subtypes of Synovial Sarcoma

Synovial Sarcomas (SS) are characterized by the presence of the SS18::SSX fusion gene, which protein product induce chromatin changes through remodeling of the BAF complex. To elucidate the genomic events that drive phenotypic diversity in SS, we performed RNA and targeted DNA sequencing on 91 tumors from 55 patients. Our results were verified by proteomic analysis, public gene expression cohorts and single-cell RNA sequencing. Transcriptome profiling identified three distinct SS subtypes resembling the known histological subtypes: SS subtype I and was characterized by hyperproliferation, evasion of immune detection and a poor prognosis. SS subtype II and was dominated by a vascular-stromal component and had a significantly better outcome. SS Subtype III was characterized by biphasic differentiation, increased genomic complexity and immune suppression mediated by checkpoint inhibition, and poor prognosis despite good responses to neoadjuvant therapy. Chromosomal abnormalities were an independent significant risk factor for metastasis. KRT8 was identified as a key component for epithelial differentiation in biphasic tumors, potentially controlled by OVOL1 regulation. Our findings explain the histological grounds for SS classification and indicate that a significantly larger proportion of patients have high risk tumors (corresponding to SS subtype I) than previously believed.

Insight into the therapeutic effects of artesunate in relieving metabolic-associated steatohepatitis from transcriptomic and lipidomics analyses

OBJECTIVES

Artesunate (ART) is a water-soluble derivative of artemisinin, which has shown anti-inflammatory, anti-tumor, and immunomodulating effects. We aimed to investigate the potential therapeutic effects and mechanisms of ART in metabolic dysfunction-associated steatohepatitis (MASH).

METHODS

The mice were randomly divided into the control group, high-fat, high-cholesterol diet-induced MASH group, and the MASH treated with ART (30 mg/kg once daily) group. Liver enzymes, lipids, and histological features were compared among groups. The molecular mechanisms were studied by transcriptomic and lipidomics analyses of liver tissues.

RESULTS

The mice of the MASH group had significantly increased hepatic fat deposition and inflammation in terms of biochemical indicators and pathological manifestations than the control group. The ART-treated group had improved plasma liver enzymes and hepatic cholesterol, especially at week 4 of intervention (p < 0.05). A total of 513 differentially expressed genes and 59 differentially expressed lipids were identified in the MASH group and the MASH+ART group. Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment test showed that ART regulated glycerolipid metabolism pathway and enhanced fatty acid degradation. Peroxisome proliferator-activated receptor (PPAR)-α acted as a key transcription factor in the treatment of MASH with ART, which was confirmed by cell experiment.

CONCLUSIONS

ART significantly improved fat deposition and inflammatory manifestations in MASH mice, with potential therapeutic effects. The mechanism of artemisinin treatment for MASH may involve extensive regulation of downstream genes by upstream transcription factors, such as PPAR-α, to restore hepatic lipid homeostasis.

Key Cell-in-Cell Related Genes are Identified by Bioinformatics and Experiments in Glioblastoma

Purpose

This study aimed to explore the roles of cell-in-cell (CIC)-related genes in glioblastoma (GBM) using bioinformatics and experimental strategies.

Patients and Methods

The ssGSEA algorithm was used to calculate the CIC score for each patient. Subsequently, differentially expressed genes (DEGs) between the CIClow and CIChigh groups and between the tumor and control samples were screened using the limma R package. Key CIC-related genes (CICRGs) were further filtered using univariate Cox and LASSO analyses, followed by the construction of a CIC-related risk score model. The performance of the risk score model in predicting GBM prognosis was evaluated using ROC curves and an external validation cohort. Moreover, their location and differentiation trajectory in GBM were analyzed at the single-cell level using the Seurat R package. Finally, the expression of key CICRGs in clinical samples was examined by qPCR.

Results

In the current study, we found that CIC scorelow group had a significantly better survival in the TCGA-GBM cohort, supporting the important role of CICRGs in GBM. Using univariate Cox and LASSO analyses, PTX3, TIMP1, IGFBP2, SNCAIP, LOXL1, SLC47A2, and LGALS3 were identified as key CICRGs. Based on this data, a CIC-related prognostic risk score model was built using the TCGA-GBM cohort and validated in the CGGA-GBM cohort. Further mechanistic analyses showed that the CIC-related risk score is closely related to immune and inflammatory responses. Interestingly, at the single-cell level, key CICRGs were expressed in the neurons and myeloids of tumor tissues and exhibited unique temporal dynamics of expression changes. Finally, the expression of key CICRGs was validated by qPCR using clinical samples from GBM patients.

Conclusion

We identified novel CIC-related genes and built a reliable prognostic prediction model for GBM, which will provide further basic clues for studying the exact molecular mechanisms of GBM pathogenesis from a CIC perspective.

Biological sex affects functional variation across the human genome

Humans display sexual dimorphism across many traits, but little is known about underlying genetic mechanisms and impacts on disease. We utilized single-cell RNA-seq of 480 lymphoblastoid cell lines to reveal that the vast majority (79%) of sex-biased genes are targets of transcription factors that display sex-biased expression. Further, we developed a two-step regression method that identified sex-biased expression quantitative trait loci (sb-eQTL) across the genome. In contrast to previous work, these sb-eQTL are abundant (n=10,754; FDR 5%) and reproducible (replication up to π1=0.56). These sb-eQTL are enriched in over 600 GWAS phenotypes, including 120 sb-eQTL associated with the female-biased autoimmune disease multiple sclerosis. Our results demonstrate widespread genetic impacts on sexual dimorphism and identify possible mechanisms and clinical targets for sex differences in diverse diseases.

Multi-organ transcriptome atlas of a mouse model of relative energy deficiency in sport

Insufficient energy intake to meet energy expenditure demands of physical activity can result in systemic neuroendocrine and metabolic abnormalities in activity-dependent anorexia and relative energy deficiency in sport (REDs). REDs affects >40% of athletes, yet the lack of underlying molecular changes has been a hurdle to have a better understanding of REDs and its treatment. To assess the molecular changes in response to energy deficiency, we implemented the "exercise-for-food" paradigm, in which food reward size is determined by wheel-running activity. By using this paradigm, we replicated several aspects of REDs in female and male mice with high physical activity and gradually reduced food intake, which results in weight loss, compromised bone health, organ-specific mass changes, and altered rest-activity patterns. By integrating transcriptomics of 19 different organs, we provide a comprehensive dataset that will guide future understanding of REDs and may provide important implications for metabolic health and (athletic) performance.

Hypoxia-induced cysteine metabolism reprogramming is crucial for the tumorigenesis of colorectal cancer

Metabolic reprogramming is a hallmark of human cancer, and cancer-specific metabolism provides opportunities for cancer diagnosis, prognosis, and treatment. However, the underlying mechanisms by which metabolic pathways affect the initiation and progression of colorectal cancer (CRC) remain largely unknown. Here, we demonstrate that cysteine is highly enriched in colorectal tumors compared to adjacent non-tumor tissues, thereby promoting tumorigenesis of CRC. Synchronously importing both cysteine and cystine in colorectal cancer cells is necessary to maintain intracellular cysteine levels. Hypoxia-induced reactive oxygen species (ROS) and ER stress regulate the co-upregulation of genes encoding cystine transporters (SLC7A11, SLC3A2) and genes encoding cysteine transporters (SLC1A4, SLC1A5) through the transcription factor ATF4. Furthermore, the metabolic flux from cysteine to reduced glutathione (GSH), which is critical to support CRC growth, is increased due to overexpression of glutathione synthetase GSS in CRC. Depletion of cystine/cysteine by recombinant cyst(e)inase effectively inhibits the growth of colorectal tumors by inducing autophagy in colorectal cancer cells through mTOR-ULK signaling axis. This study demonstrates the underlying mechanisms of cysteine metabolism in tumorigenesis of CRC, and evaluates the potential of cysteine metabolism as a biomarker or a therapeutic target for CRC.

Gene regulatory networks in disease and ageing

The precise control of gene expression is required for the maintenance of cellular homeostasis and proper cellular function, and the declining control of gene expression with age is considered a major contributor to age-associated changes in cellular physiology and disease. The coordination of gene expression can be represented through models of the molecular interactions that govern gene expression levels, so-called gene regulatory networks. Gene regulatory networks can represent interactions that occur through signal transduction, those that involve regulatory transcription factors, or statistical models of gene-gene relationships based on the premise that certain sets of genes tend to be coexpressed across a range of conditions and cell types. Advances in experimental and computational technologies have enabled the inference of these networks on an unprecedented scale and at unprecedented precision. Here, we delineate different types of gene regulatory networks and their cell-biological interpretation. We describe methods for inferring such networks from large-scale, multi-omics datasets and present applications that have aided our understanding of cellular ageing and disease mechanisms.

Neural Tissue-Like, not Supraphysiological, Electrical Conductivity Stimulates Neuronal Lineage Specification through Calcium Signaling and Epigenetic Modification

Electrical conductivity is a pivotal biophysical factor for neural interfaces, though optimal values remain controversial due to challenges isolating this cue. To address this issue, conductive substrates made of carbon nanotubes and graphene oxide nanoribbons, exhibiting a spectrum of conductivities from 0.02 to 3.2 S m-1, while controlling other surface properties is designed. The focus is to ascertain whether varying conductivity in isolation has any discernable impact on neural lineage specification. Remarkably, neural-tissue-like low conductivity (0.02-0.1 S m-1) prompted neural stem/progenitor cells to exhibit a greater propensity toward neuronal lineage specification (neurons and oligodendrocytes, not astrocytes) compared to high supraphysiological conductivity (3.2 S m-1). High conductivity instigated the apoptotic process, characterized by increased apoptotic fraction and decreased neurogenic morphological features, primarily due to calcium overload. Conversely, cells exposed to physiological conductivity displayed epigenetic changes, specifically increased chromatin openness with H3acetylation (H3ac) and neurogenic-transcription-factor activation, along with a more balanced intracellular calcium response. The pharmacological inhibition of H3ac further supported the idea that such epigenetic changes might play a key role in driving neuronal specification in response to neural-tissue-like, not supraphysiological, conductive cues. These findings underscore the necessity of optimal conductivity when designing neural interfaces and scaffolds to stimulate neuronal differentiation and facilitate the repair process.

Multi-omic lineage tracing predicts the transcriptional, epigenetic and genetic determinants of cancer evolution

Cancer is a highly heterogeneous disease, where phenotypically distinct subpopulations coexist and can be primed to different fates. Both genetic and epigenetic factors may drive cancer evolution, however little is known about whether and how such a process is pre-encoded in cancer clones. Using single-cell multi-omic lineage tracing and phenotypic assays, we investigate the predictive features of either tumour initiation or drug tolerance within the same cancer population. Clones primed to tumour initiation in vivo display two distinct transcriptional states at baseline. Remarkably, these states share a distinctive DNA accessibility profile, highlighting an epigenetic basis for tumour initiation. The drug tolerant niche is also largely pre-encoded, but only partially overlaps the tumour-initiating one and evolves following two genetically and transcriptionally distinct trajectories. Our study highlights coexisting genetic, epigenetic and transcriptional determinants of cancer evolution, unravelling the molecular complexity of pre-encoded tumour phenotypes.

Benchmarking of protein interaction databases for integration with manually reconstructed signalling network models

Protein interaction databases are critical resources for network bioinformatics and integrating molecular experimental data. Interaction databases may also enable construction of predictive computational models of biological networks, although their fidelity for this purpose is not clear. Here, we benchmark protein interaction databases X2K, Reactome, Pathway Commons, Omnipath and Signor for their ability to recover manually curated edges from three logic-based network models of cardiac hypertrophy, mechano-signalling and fibrosis. Pathway Commons performed best at recovering interactions from manually reconstructed hypertrophy (137 of 193 interactions, 71%), mechano-signalling (85 of 125 interactions, 68%) and fibroblast networks (98 of 142 interactions, 69%). While protein interaction databases successfully recovered central, well-conserved pathways, they performed worse at recovering tissue-specific and transcriptional regulation. This highlights a knowledge gap where manual curation is critical. Finally, we tested the ability of Signor and Pathway Commons to identify new edges that improve model predictions, revealing important roles of protein kinase C autophosphorylation and Ca2+/calmodulin-dependent protein kinase II phosphorylation of CREB in cardiomyocyte hypertrophy. This study provides a platform for benchmarking protein interaction databases for their utility in network model construction, as well as providing new insights into cardiac hypertrophy signalling. KEY POINTS: Protein interaction databases are used to recover signalling interactions from previously developed network models. The five protein interaction databases benchmarked recovered well-conserved pathways, but did poorly at recovering tissue-specific pathways and transcriptional regulation, indicating the importance of manual curation. We identify new signalling interactions not previously used in the network models, including a role for Ca2+/calmodulin-dependent protein kinase II phosphorylation of CREB in cardiomyocyte hypertrophy.

Potential regulation and prognostic model of colorectal cancer with extracellular matrix genes

Background

The tumor microenvironment (TME) of colorectal cancer (CRC) mainly comprises immune cells, stromal cells, tumor cells, as well as the extracellular matrix (ECM), which holds a pivotal position. The ECM affects cancer progression, but its regulatory roles and predictive potential in CRC are not fully understood.

Methods

We analyzed transcriptomes from CRC tumors and paired normal tissues to study ECM features. Up-regulated ECM components were examined through functional enrichment analysis, and single-cell sequencing identified cell types producing collagen, regulators, and secreted factors. Transcription factor analysis and cell-cell interaction studies were conducted to identify potential regulators of ECM changes. Additionally, a prognostic model was developed using TCGA-CRC cohort data, focusing on up-regulated core ECM components.

Results

Bulk RNA-seq analysis revealed a unique ECM pattern in tumors, with ECM abundance and composition significantly related to patient survival. Up-regulated ECM components were linked to various cancer-related pathways. Fibroblasts and non-fibroblasts interactions were crucial in forming the TME. Key potential regulators identified included ZNF469, PRRX2, TWIST1, and AEBP1. A prognostic model based on five ECM genes (THBS3, LAMB3, ESM1, SPRX, COL9A3) demonstrated strong associations with immune suppression and tumor angiogenesis.

Conclusions

The ECM components were involved in various cell-cell interactions and correlated with tumor development and poor survival outcomes. The ECM prognostic model components could be potential targets for novel therapeutic interventions in colorectal cancer.

Proteomics analysis of periplaque and chronic inactive multiple sclerosis lesions

Background

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system characterized by increased inflammation and immune responses, oxidative injury, mitochondrial dysfunction, and iron dyshomeostasis leading to demyelination and axonal damage. In MS, incomplete remyelination results in chronically demyelinated axons and degeneration coinciding with disability. This suggests a failure in the ability to remyelinate in MS, however, the precise underlying mechanisms remain unclear. We aimed to identify proteins whose expression was altered in chronic inactive white matter lesions and periplaque white matter in MS tissue to reveal potential pathophysiological mechanisms.

Methods

Laser capture microdissection coupled to proteomics was used to interrogate spatially altered changes in formalin-fixed paraffin-embedded brain tissue from three chronic MS individuals and three controls with no apparent neurological complications. Histopathological maps guided the capture of inactive lesions, periplaque white matter, and cortex from chronic MS individuals along with corresponding white matter and cortex from control tissue. Label free quantitation by liquid chromatography tandem mass spectrometry was used to discover differentially expressed proteins between the various brain regions.

Results

In addition to confirming loss of several myelin-associated proteins known to be affected in MS, proteomics analysis of chronic inactive MS lesions revealed alterations in myelin assembly, metabolism, and cytoskeletal organization. The top altered proteins in MS inactive lesions compared to control white matter consisted of PPP1R14A, ERMN, SIRT2, CARNS1, and MBLAC2.

Conclusion

Our findings highlight proteome changes in chronic inactive MS white matter lesions and periplaque white matter, which may be crucial for proper myelinogenesis, bioenergetics, focal adhesions, and cellular function. This study highlights the importance and feasibility of spatial approaches such as laser capture microdissection-based proteomics analysis of pathologically distinct regions of MS brain tissue. Identification of spatially resolved changes in the proteome of MS brain tissue should aid in the understanding of pathophysiological mechanisms and the development of novel therapies.

On the identification of differentially-active transcription factors from ATAC-seq data

ATAC-seq has emerged as a rich epigenome profiling technique, and is commonly used to identify Transcription Factors (TFs) underlying given phenomena. A number of methods can be used to identify differentially-active TFs through the accessibility of their DNA-binding motif, however little is known on the best approaches for doing so. Here we benchmark several such methods using a combination of curated datasets with various forms of short-term perturbations on known TFs, as well as semi-simulations. We include both methods specifically designed for this type of data as well as some that can be repurposed for it. We also investigate variations to these methods, and identify three particularly promising approaches (a chromVAR-limma workflow with critical adjustments, monaLisa and a combination of GC smooth quantile normalization and multivariate modeling). We further investigate the specific use of nucleosome-free fragments, the combination of top methods, and the impact of technical variation. Finally, we illustrate the use of the top methods on a novel dataset to characterize the impact on DNA accessibility of TRAnscription Factor TArgeting Chimeras (TRAFTAC), which can deplete TFs - in our case NFkB - at the protein level.

Multiomics2Targets identifies targets from cancer cohorts profiled with transcriptomics, proteomics, and phosphoproteomics

The availability of data from profiling of cancer patients with multiomics is rapidly increasing. However, integrative analysis of such data for personalized target identification is not trivial. Multiomics2Targets is a platform that enables users to upload transcriptomics, proteomics, and phosphoproteomics data matrices collected from the same cohort of cancer patients. After uploading the data, Multiomics2Targets produces a report that resembles a research publication. The uploaded matrices are processed, analyzed, and visualized using the tools Enrichr, KEA3, ChEA3, Expression2Kinases, and TargetRanger to identify and prioritize proteins, genes, and transcripts as potential targets. Figures and tables, as well as descriptions of the methods and results, are automatically generated. Reports include an abstract, introduction, methods, results, discussion, conclusions, and references and are exportable as citable PDFs and Jupyter Notebooks. Multiomics2Targets is applied to analyze version 3 of the Clinical Proteomic Tumor Analysis Consortium (CPTAC3) pan-cancer cohort, identifying potential targets for each CPTAC3 cancer subtype. Multiomics2Targets is available from https://multiomics2targets.maayanlab.cloud/.

scParser: sparse representation learning for scalable single-cell RNA sequencing data analysis

The rapid rise in the availability and scale of scRNA-seq data needs scalable methods for integrative analysis. Though many methods for data integration have been developed, few focus on understanding the heterogeneous effects of biological conditions across different cell populations in integrative analysis. Our proposed scalable approach, scParser, models the heterogeneous effects from biological conditions, which unveils the key mechanisms by which gene expression contributes to phenotypes. Notably, the extended scParser pinpoints biological processes in cell subpopulations that contribute to disease pathogenesis. scParser achieves favorable performance in cell clustering compared to state-of-the-art methods and has a broad and diverse applicability.

Multi-omic analysis reveals VEGFR2, PI3K, and JNK mediate the small molecule induction of human iPSC-derived cardiomyocyte proliferation

Mammalian hearts lose their regenerative potential shortly after birth. Stimulating the proliferation of preexisting cardiomyocytes is a potential therapeutic strategy for cardiac damage. In a previous study, we identified 30 compounds that induced the bona-fide proliferation of human iPSC-derived cardiomyocytes (hiPSC-CM). Here, we selected five active compounds with diverse targets, including ALK5 and CB1R, and performed multi-omic analyses to identify common mechanisms mediating the cell cycle progression of hiPSC-CM. Transcriptome profiling revealed the top enriched pathways for all compounds including cell cycle, DNA repair, and kinesin pathways. Functional proteomic arrays found that the compounds collectively activated multiple receptor tyrosine kinases including ErbB2, IGF1R, and VEGFR2. Network analysis integrating common transcriptomic and proteomic signatures predicted that MAPK/PI3K pathways mediated compound responses. Furthermore, VEGFR2 negatively regulated endoreplication, enabling the completion of cell division. Thus, in this study, we applied high-content imaging and molecular profiling to establish mechanisms linking pro-proliferative agents to mechanisms of cardiomyocyte cell cycling.

PURE-seq identifies Egr1 as a Potential Master Regulator in Murine Aging by Sequencing Long-Term Hematopoietic Stem Cells

Single-cell transcriptomics is valuable for uncovering individual cell properties, particularly in highly heterogeneous systems. However, this technique often results in the analysis of many well- characterized cells, increasing costs and diluting rare cell populations. To address this, we developed PURE-seq (PIP-seq for Rare-cell Enrichment and Sequencing) for scalable sequencing of rare cells. PURE-seq allows direct cell loading from FACS into PIP-seq reactions, minimizing handling and reducing cell loss. PURE-seq reliably captures rare cells, with 60 minutes of sorting capturing tens of cells at a rarity of 1 in 1,000,000. Using PURE-seq, we investigated murine long- term hematopoietic stem cells and their transcriptomes in the context of hematopoietic aging, identifying Egr1 as a potential master regulator of hematopoiesis in the aging context. PURE-seq offers an accessible and reliable method for isolating and sequencing cells that are currently too rare to capture successfully with existing methods.

PURE-seq identifies Egr1 as a Potential Master Regulator in Murine Aging by Sequencing Long-Term Hematopoietic Stem Cells

Single-cell transcriptomics is valuable for uncovering individual cell properties, particularly in highly heterogeneous systems. However, this technique often results in the analysis of many well-characterized cells, increasing costs and diluting rare cell populations. To address this, we developed PURE-seq (PIP-seq for Rare-cell Enrichment and Sequencing) for scalable sequencing of rare cells. PURE-seq allows direct cell loading from FACS into PIP-seq reactions, minimizing handling and reducing cell loss. PURE-seq reliably captures rare cells, with 60 minutes of sorting capturing tens of cells at a rarity of 1 in 1,000,000. Using PURE-seq, we investigated murine long-term hematopoietic stem cells and their transcriptomes in the context of hematopoietic aging, identifying Egr1 as a potential master regulator of hematopoiesis in the aging context. PURE-seq offers an accessible and reliable method for isolating and sequencing cells that are currently too rare to capture successfully with existing methods.

Multi-omics characterization of the monkeypox virus infection

Multiple omics analyzes of Vaccinia virus (VACV) infection have defined molecular characteristics of poxvirus biology. However, little is known about the monkeypox (mpox) virus (MPXV) in humans, which has a different disease manifestation despite its high sequence similarity to VACV. Here, we perform an in-depth multi-omics analysis of the transcriptome, proteome, and phosphoproteome signatures of MPXV-infected primary human fibroblasts to gain insights into the virus-host interplay. In addition to expected perturbations of immune-related pathways, we uncover regulation of the HIPPO and TGF-β pathways. We identify dynamic phosphorylation of both host and viral proteins, which suggests that MAPKs are key regulators of differential phosphorylation in MPXV-infected cells. Among the viral proteins, we find dynamic phosphorylation of H5 that influenced the binding of H5 to dsDNA. Our extensive dataset highlights signaling events and hotspots perturbed by MPXV, extending the current knowledge on poxviruses. We use integrated pathway analysis and drug-target prediction approaches to identify potential drug targets that affect virus growth. Functionally, we exemplify the utility of this approach by identifying inhibitors of MTOR, CHUK/IKBKB, and splicing factor kinases with potent antiviral efficacy against MPXV and VACV.

ABCG2-Expressing Clonal Repopulating Endothelial Cells Serve to Form and Maintain Blood Vessels

BACKGROUND

Most organs are maintained lifelong by resident stem/progenitor cells. During development and regeneration, lineage-specific stem/progenitor cells can contribute to the growth or maintenance of different organs, whereas fully differentiated mature cells have less regenerative potential. However, it is unclear whether vascular endothelial cells (ECs) are also replenished by stem/progenitor cells with EC-repopulating potential residing in blood vessels. It has been reported recently that some EC populations possess higher clonal proliferative potential and vessel-forming capacity compared with mature ECs. Nevertheless, a marker to identify vascular clonal repopulating ECs (CRECs) in murine and human individuals is lacking, and, hence, the mechanism for the proliferative, self-renewal, and vessel-forming potential of CRECs is elusive.

METHODS

We analyzed colony-forming, self-renewal, and vessel-forming potential of ABCG2 (ATP binding cassette subfamily G member 2)-expressing ECs in human umbilical vessels. To study the contribution of Abcg2-expressing ECs to vessel development and regeneration, we developed Abcg2CreErt2;ROSA TdTomato mice and performed lineage tracing during mouse development and during tissue regeneration after myocardial infarction injury. RNA sequencing and chromatin methylation chromatin immunoprecipitation followed by sequencing were conducted to study the gene regulation in Abcg2-expressing ECs.

RESULTS

In human and mouse vessels, ECs with higher ABCG2 expression (ABCECs) possess higher clonal proliferative potential and in vivo vessel-forming potential compared with mature ECs. These cells could clonally contribute to vessel formation in primary and secondary recipients after transplantation. These features of ABCECs meet the criteria of CRECs. Results from lineage tracing experiments confirm that Abcg2-expressing CRECs (AbcCRECs) contribute to arteries, veins, and capillaries in cardiac tissue development and vascular tissue regeneration after myocardial infarction. Transcriptome and epigenetic analyses reveal that a gene expression signature involved in angiogenesis and vessel development is enriched in AbcCRECs. In addition, various angiogenic genes, such as Notch2 and Hey2, are bivalently modified by trimethylation at the 4th and 27th lysine residue of histone H3 (H3K4me3 and H3K27me3) in AbcCRECs.

CONCLUSIONS

These results are the first to establish that a single prospective marker identifies CRECs in mice and human individuals, which holds promise to provide new cell therapies for repair of damaged vessels in patients with endothelial dysfunction.

Dual targeting of histone deacetylases and MYC as potential treatment strategy for H3-K27M pediatric gliomas

Diffuse midline gliomas (DMGs) are aggressive and fatal pediatric tumors of the central nervous system that are highly resistant to treatments. Lysine to methionine substitution of residue 27 on histone H3 (H3-K27M) is a driver mutation in DMGs, reshaping the epigenetic landscape of these cells to promote tumorigenesis. H3-K27M gliomas are characterized by deregulation of histone acetylation and methylation pathways, as well as the oncogenic MYC pathway. In search of effective treatment, we examined the therapeutic potential of dual targeting of histone deacetylases (HDACs) and MYC in these tumors. Treatment of H3-K27M patient-derived cells with Sulfopin, an inhibitor shown to block MYC-driven tumors in vivo, in combination with the HDAC inhibitor Vorinostat, resulted in substantial decrease in cell viability. Moreover, transcriptome and epigenome profiling revealed synergistic effect of this drug combination in downregulation of prominent oncogenic pathways such as mTOR. Finally, in vivo studies of patient-derived orthotopic xenograft models showed significant tumor growth reduction in mice treated with the drug combination. These results highlight the combined treatment with PIN1 and HDAC inhibitors as a promising therapeutic approach for these aggressive tumors.

EZH2 PROTACs target EZH2- and FOXM1-associated oncogenic nodes, suppressing breast cancer cell growth

Breast cancer (BC) remains the second leading cause of cancer-related mortalities in women. Resistance to hormone therapies such as tamoxifen, an estrogen receptor (ER) inhibitor, is a major hurdle in the treatment of BC. Enhancer of zeste homolog 2 (EZH2), the methyltransferase component of the Polycomb repressive complex 2 (PRC2), has been implicated in tamoxifen resistance. Evidence suggests that EZH2 often functions noncanonically, in a methyltransferase-independent manner, as a transcription coactivator through interacting with oncogenic transcription factors. Unlike methyltransferase inhibitors, proteolysis targeting chimeras (PROTAC) can suppress both activating and repressive functions of EZH2. Here, we find that EZH2 PROTACs, MS177 and MS8815, effectively inhibited the growth of BC cells, including those with acquired tamoxifen resistance, to a much greater degree when compared to methyltransferase inhibitors. Mechanistically, EZH2 associates with forkhead box M1 (FOXM1) and binds to the promoters of FOXM1 target genes. EZH2 PROTACs induce degradation of both EZH2 and FOXM1, leading to reduced expression of target genes involved in cell cycle progression and tamoxifen resistance. Together, this study supports that EZH2-targeted PROTACs represent a promising avenue of research for the future treatment of BC, including in the setting of tamoxifen resistance.

Paired Transcriptomic Analyses of Atheromatous and Control Vessels Reveal Novel Autophagy and Immunoregulatory Genes in Peripheral Artery Disease

Peripheral artery disease (PAD), a significant health burden worldwide, affects lower extremities due to atherosclerosis in peripheral vessels. Although the mechanisms of PAD have been well studied, the molecular milieu of the plaques localized within peripheral arteries are not well understood. Thus, to identify PAD-lesion-specific gene expression profiles precluding genetic, environmental, and dietary biases, we studied the transcriptomic profile of nine plaque tissues normalized to non-plaque tissues from the same donors. A total of 296 upregulated genes, 274 downregulated genes, and 186 non-coding RNAs were identified. STAG1, SPCC3, FOXQ1, and E2F3 were key downregulated genes, and CD93 was the top upregulated gene. Autophagosome assembly, cellular response to UV, cytoskeletal organization, TCR signaling, and phosphatase activity were the key dysregulated pathways identified. Telomerase regulation and autophagy were identified as novel interacting pathways using network analysis. The plaque tissue was predominantly composed of immune cells and dedifferentiated cell populations indicated by cell-specific marker-imputed gene expression analysis. This study identifies novel genes, non-coding RNAs, associated regulatory pathways, and the cell composition of the plaque tissue in PAD patients. The autophagy and immunoregulatory genes may drive novel mechanisms, resulting in atheroma. These novel interacting networks and genes have potential for PAD-specific therapeutic applications.

Optimized reporters for multiplexed detection of transcription factor activity

In any given cell type, dozens of transcription factors (TFs) act in concert to control the activity of the genome by binding to specific DNA sequences in regulatory elements. Despite their considerable importance in determining cell identity and their pivotal role in numerous disorders, we currently lack simple tools to directly measure the activity of many TFs in parallel. Massively parallel reporter assays (MPRAs) allow the detection of TF activities in a multiplexed fashion; however, we lack basic understanding to rationally design sensitive reporters for many TFs. Here, we use an MPRA to systematically optimize transcriptional reporters for 86 TFs and evaluate the specificity of all reporters across a wide array of TF perturbation conditions. We thus identified critical TF reporter design features and obtained highly sensitive and specific reporters for 60 TFs, many of which outperform available reporters. The resulting collection of "prime" TF reporters can be used to uncover TF regulatory networks and to illuminate signaling pathways.

HIGHLIGHTS

Systematic design and optimization of transcriptional reporters for 86 TFsCharacterization of TF-specific reporter design optimization rulesEvaluation of reporter TF-specificity across a wide array of TF perturbationsIdentification of a collection of 60 "prime" TF reporters with optimized performance.

Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets

This article provides an in-depth review of computational methods for predicting transcriptional regulators (TRs) with query gene sets. Identification of TRs is of utmost importance in many biological applications, including but not limited to elucidating biological development mechanisms, identifying key disease genes, and predicting therapeutic targets. Various computational methods based on next-generation sequencing (NGS) data have been developed in the past decade, yet no systematic evaluation of NGS-based methods has been offered. We classified these methods into two categories based on shared characteristics, namely library-based and region-based methods. We further conducted benchmark studies to evaluate the accuracy, sensitivity, coverage, and usability of NGS-based methods with molecular experimental datasets. Results show that BART, ChIP-Atlas, and Lisa have relatively better performance. Besides, we point out the limitations of NGS-based methods and explore potential directions for further improvement.

CRISPR-inhibition screen for lncRNAs linked to melanoma growth and metastasis

Melanoma being one of the most common and deadliest skin cancers, has been rising since the past decade. Patients at advanced stages of the disease have very poor prognoses, as opposed to at the earlier stages. Nowadays the standard-of-care of advanced melanoma is resection followed by immune checkpoint inhibition based immunotherapy. However, a substantial proportion of patients either do not respond or develop resistances. This underscores a need for novel approaches and therapeutic targets as well as a better understanding of the mechanisms of melanoma pathogenesis. Long non-coding RNAs (lncRNAs) comprise a poorly characterized class of functional players and promising targets in promoting malignancy. Certain lncRNAs have been identified to play integral roles in melanoma progression and drug resistances, however systematic screens to uncover novel functional lncRNAs are scarce. Here, we profile differentially expressed lncRNAs in patient derived short-term metastatic cultures and BRAF-MEK-inhibition resistant cells. We conduct a focused growth-related CRISPR-inhibition screen of overexpressed lncRNAs, validate and functionally characterize lncRNA hits with respect to cellular growth, invasive capacities and apoptosis in vitro as well as the transcriptomic impact of our lead candidate the novel lncRNA XLOC_030781. In sum, we extend the current knowledge of ncRNAs and their potential relevance on melanoma.

Significance

Previously considered as transcriptional noise, lncRNAs have emerged as novel players in regulating many cellular aspects in health and disease including melanoma. However, the number and as well as the extent of functional significance of most lncRNAs remains elusive. We provide a comprehensive strategy to identify functionally relevant lncRNAs in melanoma by combining expression profiling with CRISPR-inhibition growths screens lowering the experimental effort. We also provide a larger resource of differentially expressed lncRNAs with potential implications in melanoma growth and invasion. Our results broaden the characterized of lncRNAs as potential targets for future therapeutic applications.