Cistrome Data Browser: expanded datasets and new tools for gene regulatory analysis

TFTG: A comprehensive database for human transcription factors and their targets

Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.

CSE1L as a prognostic biomarker associated with pan cancer immune infiltration and drug sensitivity

BACKGROUND

Rising cancer-related mortality underscores the importance of biomarkers for treatment and prognosis, with Chromosome Segregation 1 Like (CSE1L) linked to various cancers yet its roles remain partially understood. This study investigates CSE1L's expression and oncogenic mechanisms in solid tumors.

RESEARCH DESIGN AND METHODS

We analyzed multi-omics data from 31 solid tumors, measured CSE1L in 41 head and neck carcinoma patients post-chemotherapy via qRT-PCR, and evaluated the impact of CSE1L knockdown on cell proliferation in A549 and HepG2 cells.

RESULTS

In this study, we observed significantly elevated levels of CSE1L RNA in 13 tumor tissues and protein levels in 8 tumor tissues compared to their corresponding adjacent normal tissues. Additionally, our investigation unveiled a correlation between heightened CSE1L expression in tumor tissues and worsened patient prognosis, poor response to immunotherapy, and diminished effectiveness of neoadjuvant chemotherapy. Through an analysis of CSE1L mechanisms, we discovered its potential involvement in promoting tumor cell proliferation, enhancing drug resistance, and influencing immune infiltration, thereby impacting patient prognosis and treatment outcomes. Finally, we delved into the potential mechanisms underlying upregulation of CSE1L in tumor tissues.

CONCLUSION

Our findings demonstrate that CSE1L promotes tumor development in various malignancies, highlighting its potential as both a therapeutic target and prognostic indicator.

Characterizing primary transcriptional responses to short term heat shock in Down syndrome

Heat shock stress induces genome-wide changes in transcription regulation, activating a coordinated cellular response to enable survival. We noticed many heat shock genes are up-regulated in blood samples from individuals with trisomy 21. We characterized the immediate transcriptional response to heat shock of two lymphoblastoid cell lines derived from brothers with and without trisomy 21. The trisomy 21 cells displayed a more robust heat shock response after just one hour at 42°C than the matched disomic cells.

CDK9 inhibition inhibits multiple oncogenic transcriptional and epigenetic pathways in prostate cancer

BACKGROUND

Cyclin-dependent kinase 9 (CDK9) stimulates oncogenic transcriptional pathways in cancer and CDK9 inhibitors have emerged as promising therapeutic candidates.

METHODS

The activity of an orally bioavailable CDK9 inhibitor, CDKI-73, was evaluated in prostate cancer cell lines, a xenograft mouse model, and patient-derived tumor explants and organoids. Expression of CDK9 was evaluated in clinical specimens by mining public datasets and immunohistochemistry. Effects of CDKI-73 on prostate cancer cells were determined by cell-based assays, molecular profiling and transcriptomic/epigenomic approaches.

RESULTS

CDKI-73 inhibited proliferation and enhanced cell death in diverse in vitro and in vivo models of androgen receptor (AR)-driven and AR-independent models. Mechanistically, CDKI-73-mediated inhibition of RNA polymerase II serine 2 phosphorylation resulted in reduced expression of BCL-2 anti-apoptotic factors and transcriptional defects. Transcriptomic and epigenomic approaches revealed that CDKI-73 suppressed signaling pathways regulated by AR, MYC, and BRD4, key drivers of dysregulated transcription in prostate cancer, and reprogrammed cancer-associated super-enhancers. These latter findings prompted the evaluation of CDKI-73 with the BRD4 inhibitor AZD5153, a combination that was synergistic in patient-derived organoids and in vivo.

CONCLUSION

Our work demonstrates that CDK9 inhibition disrupts multiple oncogenic pathways and positions CDKI-73 as a promising therapeutic agent for prostate cancer, particularly aggressive, therapy-resistant subtypes.

An endogenous retrovirus regulates tumor-specific expression of the immune transcriptional regulator SP140

Speckled Protein 140 (SP140) is a chromatin reader with critical roles regulating immune cell transcriptional programs, and SP140 splice variants are associated with immune diseases including Crohn's disease, multiple sclerosis, and chronic lymphocytic leukemia. SP140 expression is currently thought to be restricted to immune cells. However, by analyzing human transcriptomic datasets from a wide range of normal and cancer cell types, we found recurrent cancer-specific expression of SP140, driven by an alternative intronic promoter derived from an intronic endogenous retrovirus (ERV). The ERV belongs to the primate-specific LTR8B family and is regulated by oncogenic mitogen-activated protein kinase (MAPK) signaling. The ERV drives expression of multiple cancer-specific isoforms, including a nearly full-length isoform that retains all the functional domains of the full-length canonical isoform and is also localized within the nucleus, consistent with a role in chromatin regulation. In a fibrosarcoma cell line, silencing the cancer-specific ERV promoter of SP140 resulted in increased sensitivity to interferon-mediated cytotoxicity and dysregulation of multiple genes. Our findings implicate aberrant ERV-mediated SP140 expression as a novel mechanism contributing to immune gene dysregulation in a wide range of cancer cells.

Current genomic deep learning models display decreased performance in cell type-specific accessible regions

BACKGROUND

A number of deep learning models have been developed to predict epigenetic features such as chromatin accessibility from DNA sequence. Model evaluations commonly report performance genome-wide; however, cis regulatory elements (CREs), which play critical roles in gene regulation, make up only a small fraction of the genome. Furthermore, cell type-specific CREs contain a large proportion of complex disease heritability.

RESULTS

We evaluate genomic deep learning models in chromatin accessibility regions with varying degrees of cell type specificity. We assess two modeling directions in the field: general purpose models trained across thousands of outputs (cell types and epigenetic marks) and models tailored to specific tissues and tasks. We find that the accuracy of genomic deep learning models, including two state-of-the-art general purpose models-Enformer and Sei-varies across the genome and is reduced in cell type-specific accessible regions. Using accessibility models trained on cell types from specific tissues, we find that increasing model capacity to learn cell type-specific regulatory syntax-through single-task learning or high capacity multi-task models-can improve performance in cell type-specific accessible regions. We also observe that improving reference sequence predictions does not consistently improve variant effect predictions, indicating that novel strategies are needed to improve performance on variants.

CONCLUSIONS

Our results provide a new perspective on the performance of genomic deep learning models, showing that performance varies across the genome and is particularly reduced in cell type-specific accessible regions. We also identify strategies to maximize performance in cell type-specific accessible regions.

Bioinformatics tools and resources for cancer and application

ABSTRACT

Tumor bioinformatics plays an important role in cancer research and precision medicine. The primary focus of traditional cancer research has been molecular and clinical studies of a number of fundamental pathways and genes. In recent years, driven by breakthroughs in high-throughput technologies, large-scale cancer omics data have accumulated rapidly. How to effectively utilize and share these data is particularly important. To address this crucial task, many computational tools and databases have been developed over the past few years. To help researchers quickly learn and understand the functions of these tools, in this review, we summarize publicly available bioinformatics tools and resources for pan-cancer multi-omics analysis, regulatory analysis of tumorigenesis, tumor treatment and prognosis, immune infiltration analysis, immune repertoire analysis, cancer driver gene and driver mutation analysis, and cancer single-cell analysis, which may further help researchers find more suitable tools for their research.

Transitions in chromatin conformation shaped by fatty acids and the circadian clock underlie hepatic transcriptional reorganization in obese mice

The circadian clock system coordinates metabolic, physiological, and behavioral functions across a 24-h cycle, crucial for adapting to environmental changes. Disruptions in circadian rhythms contribute to major metabolic pathologies like obesity and Type 2 diabetes. Understanding the regulatory mechanisms governing circadian control is vital for identifying therapeutic targets. It is well characterized that chromatin remodeling and 3D structure at genome regulatory elements contributes to circadian transcriptional cycles; yet the impact of rhythmic chromatin topology in metabolic disease is largely unexplored. In this study, we explore how the spatial configuration of the genome adapts to diet, rewiring circadian transcription and contributing to dysfunctional metabolism. We describe daily fluctuations in chromatin contacts between distal regulatory elements of metabolic control genes in livers from lean and obese mice and identify specific lipid-responsive regions recruiting the clock molecular machinery. Interestingly, under high-fat feeding, a distinct interactome for the clock-controlled gene Dbp strategically promotes the expression of distal metabolic genes including Fgf21. Alongside, new chromatin loops between regulatory elements from genes involved in lipid metabolism control contribute to their transcriptional activation. These enhancers are responsive to lipids through CEBPβ, counteracting the circadian repressor REVERBa. Our findings highlight the intricate coupling of circadian gene expression to a dynamic nuclear environment under high-fat feeding, supporting a temporally regulated program of gene expression and transcriptional adaptation to diet.

Olanzapine suppresses mPFC activity-norepinephrine releasing to alleviate CLOCK-enhanced cancer stemness under chronic stress

BACKGROUND

Olanzapine (OLZ) reverses chronic stress-induced anxiety. Chronic stress promotes cancer development via abnormal neuro-endocrine activation. However, how intervention of brain-body interaction reverses chronic stress-induced tumorigenesis remains elusive.

METHODS

KrasLSL-G12D/WT lung cancer model and LLC1 syngeneic tumor model were used to study the effect of OLZ on cancer stemness and anxiety-like behaviors. Cancer stemness was evaluated by qPCR, western-blotting, immunohistology staining and flow-cytometry analysis of stemness markers, and cancer stem-like function was assessed by serial dilution tumorigenesis in mice and extreme limiting dilution analysis in primary tumor cells. Anxiety-like behaviors in mice were detected by elevated plus maze and open field test. Depression-like behaviors in mice were detected by tail suspension test. Anxiety and depression states in human were assessed by Hospital Anxiety and Depression Scale (HADS). Chemo-sensitivity of lung cancer was assessed by in vivo syngeneic tumor model and in vitro CCK-8 assay in lung cancer cell lines.

RESULTS

In this study, we found that OLZ reversed chronic stress-enhanced lung tumorigenesis in both KrasLSL-G12D/WT lung cancer model and LLC1 syngeneic tumor model. OLZ relieved anxiety and depression-like behaviors by suppressing neuro-activity in the mPFC and reducing norepinephrine (NE) releasing under chronic stress. NE activated ADRB2-cAMP-PKA-CREB pathway to promote CLOCK transcription, leading to cancer stem-like traits. As such, CLOCK-deficiency or OLZ reverses NE/chronic stress-induced gemcitabine (GEM) resistance in lung cancer. Of note, tumoral CLOCK expression is positively associated with stress status, serum NE level and poor prognosis in lung cancer patients.

CONCLUSION

We identify a new mechanism by which OLZ ameliorates chronic stress-enhanced tumorigenesis and chemoresistance. OLZ suppresses mPFC-NE-CLOCK axis to reverse chronic stress-induced anxiety-like behaviors and lung cancer stemness. Decreased NE-releasing prevents activation of ADRB2-cAMP-PKA-CREB pathway to inhibit CLOCK transcription, thus reversing lung cancer stem-like traits and chemoresistance under chronic stress.

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Identification and Validation of Diagnostic Model Based on Angiogenesis- and Epithelial Mesenchymal Transition-Related Genes in Myocardial Infarction

Background

Myocardial infarction (MI) is a chronic cardiovascular disease. This study aims to discern potentially angiogenesis- and epithelial mesenchymal transition (EMT)-related genes as biomarkers for MI diagnosis through bioinformatics.

Methods

All datasets and angiogenesis- and EMT-related genes were collected from the public database. The differentially expressed genes (DEGs) of MI and MI-related genes were acquired. DEGs, MI-related genes, and angiogenesis- and EMT-related genes were intersected to obtain hub genes. Functional enrichment, immune microenvironment, and transcription factors (TFs)-hub genes regulatory network analysis were performed. The diagnostic markers and models were developed and validated. Drug prediction and molecular docking were performed. Finally, diagnostic markers expressions were validated using RT-qPCR.

Results

A total of 224 angiogenesis- and EMT-related genes, 2,897 DEGs, 1,217 MI-related genes, and 9 hub genes were acquired. The immune infiltration levels of plasma cells, T cells CD4 memory activated, monocytes, macrophages M0, mast cells resting, and neutrophils were higher in patients with MI. LRPAP1, COLGALT1, QSOX1, THBD, VCAN, PLOD1, and PLAUR as the diagnostic markers were identified and used to construct diagnostic models, which can distinguish MI from controls well. Then, 9 drugs were screened, and the binding energies ranged from -7.08 to -5.21 kcal/mol. RT-qPCR results showed that the expression of LRPAP1, PLAUR, and PLOD1 was significantly increased in the MI group.

Conclusion

The 7 diagnostic markers may play potential roles in MI and could contribute to improved future diagnostics.

Endogenous retroviruses mediate transcriptional rewiring in response to oncogenic signaling in colorectal cancer

Cancer cells exhibit rewired transcriptional regulatory networks that promote tumor growth and survival. However, the mechanisms underlying the formation of these pathological networks remain poorly understood. Through a pan-cancer epigenomic analysis, we found that primate-specific endogenous retroviruses (ERVs) are a rich source of enhancers displaying cancer-specific activity. In colorectal cancer and other epithelial tumors, oncogenic MAPK/AP1 signaling drives the activation of enhancers derived from the primate-specific ERV family LTR10. Functional studies in colorectal cancer cells revealed that LTR10 elements regulate tumor-specific expression of multiple genes associated with tumorigenesis, such as ATG12 and XRCC4. Within the human population, individual LTR10 elements exhibit germline and somatic structural variation resulting from a highly mutable internal tandem repeat region, which affects AP1 binding activity. Our findings reveal that ERV-derived enhancers contribute to transcriptional dysregulation in response to oncogenic signaling and shape the evolution of cancer-specific regulatory networks.

Single-cell and spatial multiomic inference of gene regulatory networks using SCRIPro

MOTIVATION

The burgeoning generation of single-cell or spatial multiomic data allows for the characterization of gene regulation networks (GRNs) at an unprecedented resolution. However, the accurate reconstruction of GRNs from sparse and noisy single-cell or spatial multiomic data remains challenging.

RESULTS

Here, we present SCRIPro, a comprehensive computational framework that robustly infers GRNs for both single-cell and spatial multi-omics data. SCRIPro first improves sample coverage through a density clustering approach based on multiomic and spatial similarities. Additionally, SCRIPro scans transcriptional regulator (TR) importance by performing chromatin reconstruction and in silico deletion analyses using a comprehensive reference covering 1,292 human and 994 mouse TRs. Finally, SCRIPro combines TR-target importance scores derived from multiomic data with TR-target expression levels to ensure precise GRN reconstruction. We benchmarked SCRIPro on various datasets, including single-cell multiomic data from human B-cell lymphoma, mouse hair follicle development, Stereo-seq of mouse embryos, and Spatial-ATAC-RNA from mouse brain. SCRIPro outperforms existing motif-based methods and accurately reconstructs cell type-specific, stage-specific, and region-specific GRNs. Overall, SCRIPro emerges as a streamlined and fast method capable of reconstructing TR activities and GRNs for both single-cell and spatial multi-omic data.

AVAILABILITY

SCRIPro is available at https://github.com/wanglabtongji/SCRIPro.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Adenovirus small E1A directs activation of Alu transcription at YAP/TEAD- and AP-1-bound enhancers through interactions with the EP400 chromatin remodeler

Alu retrotransposons, which form the largest family of mobile DNA elements in the human genome, have recently come to attention as a potential source of regulatory novelties, most notably by participating in enhancer function. Even though Alu transcription by RNA polymerase III is subjected to tight epigenetic silencing, their expression has long been known to increase in response to various types of stress, including viral infection. Here we show that, in primary human fibroblasts, adenovirus small e1a triggered derepression of hundreds of individual Alus by promoting TFIIIB recruitment by Alu-bound TFIIIC. Epigenome profiling revealed an e1a-induced decrease of H3K27 acetylation and increase of H3K4 monomethylation at derepressed Alus, making them resemble poised enhancers. The enhancer nature of e1a-targeted Alus was confirmed by the enrichment, in their upstream regions, of the EP300/CBP acetyltransferase, EP400 chromatin remodeler and YAP1 and FOS transcription factors. The physical interaction of e1a with EP400 was critical for Alu derepression, which was abrogated upon EP400 ablation. Our data suggest that e1a targets a subset of enhancer Alus whose transcriptional activation, which requires EP400 and is mediated by the e1a-EP400 interaction, may participate in the manipulation of enhancer activity by adenoviruses.

Single-cell total-RNA profiling unveils regulatory hubs of transcription factors

Recent development of RNA velocity uses master equations to establish the kinetics of the life cycle of RNAs from unspliced RNA to spliced RNA (i.e., mature RNA) to degradation. To feed this kinetic analysis, simultaneous measurement of unspliced RNA and spliced RNA in single cells is greatly desired. However, the majority of single-cell RNA-seq chemistry primarily captures mature RNA species to measure gene expressions. Here, we develop a one-step total-RNA chemistry-based single-cell RNA-seq method: snapTotal-seq. We benchmark this method with multiple single-cell RNA-seq assays in their performance in kinetic analysis of cell cycle by RNA velocity. Next, with LASSO regression between transcription factors, we identify the critical regulatory hubs mediating the cell cycle dynamics. We also apply snapTotal-seq to profile the oncogene-induced senescence and identify the key regulatory hubs governing the entry of senescence. Furthermore, from the comparative analysis of unspliced RNA and spliced RNA, we identify a significant portion of genes whose expression changes occur in spliced RNA but not to the same degree in unspliced RNA, indicating these gene expression changes are mainly controlled by post-transcriptional regulation. Overall, we demonstrate that snapTotal-seq can provide enriched information about gene regulation, especially during the transition between cell states.

ETS1 and RBPJ transcriptionally regulate METTL14 to suppress TGF-β1-induced epithelial-mesenchymal transition in human bronchial epithelial cells

Asthma is a chronic respiratory disease characterized by airway inflammation and remodeling. Epithelial-mesenchymal transition (EMT) of bronchial epithelial cells is considered to be a crucial player in asthma. Methyltransferase-like 14 (METTL14), an RNA methyltransferase, is implicated in multiple pathological processes, including EMT, cell proliferation and migration. However, the role of METTL14 in asthma remains uncertain. This research aimed to explore the biological functions of METTL14 in asthma and its underlying upstream mechanisms. METTL14 expression was down-regulated in asthmatic from three GEO datasets (GSE104468, GSE165934, and GSE74986). Consistent with this trend, METTL14 was decreased in the lung tissues of OVA-induced asthmatic mice and transforming growth factor-β1 (TGF-β1)-stimulated human bronchial epithelial cells (Beas-2B) in this study. Overexpression of METTL14 caused reduction in mesenchymal markers (FN1, N-cad, Col-1 and α-SMA) in TGF-β1-treated cells, but caused increase in epithelial markers (E-cad), thus inhibiting EMT. Also, METTL14 suppressed the proliferation and migration ability of TGF-β1-treated Beas-2B cells. Two transcription factors, ETS1 and RBPJ, could both bind to the promoter region of METTL14 and drive its expression. Elevating METTL14 expression could reversed EMT, cell proliferation and migration promoted by ETS1 or RBPJ deficiency. These results indicate that the ETS1/METTL14 and RBPJ/METTL14 transcription axes exhibit anti-EMT, anti-proliferation and anti-migration functions in TGF-β1-induced bronchial epithelial cells, implying that METTL14 may be considered an alternative candidate target for the treatment of asthma.

Current genomic deep learning models display decreased performance in cell type specific accessible regions

Background

A number of deep learning models have been developed to predict epigenetic features such as chromatin accessibility from DNA sequence. Model evaluations commonly report performance genome-wide; however, cis regulatory elements (CREs), which play critical roles in gene regulation, make up only a small fraction of the genome. Furthermore, cell type specific CREs contain a large proportion of complex disease heritability.

Results

We evaluate genomic deep learning models in chromatin accessibility regions with varying degrees of cell type specificity. We assess two modeling directions in the field: general purpose models trained across thousands of outputs (cell types and epigenetic marks), and models tailored to specific tissues and tasks. We find that the accuracy of genomic deep learning models, including two state-of-the-art general purpose models - Enformer and Sei - varies across the genome and is reduced in cell type specific accessible regions. Using accessibility models trained on cell types from specific tissues, we find that increasing model capacity to learn cell type specific regulatory syntax - through single-task learning or high capacity multi-task models - can improve performance in cell type specific accessible regions. We also observe that improving reference sequence predictions does not consistently improve variant effect predictions, indicating that novel strategies are needed to improve performance on variants.

Conclusions

Our results provide a new perspective on the performance of genomic deep learning models, showing that performance varies across the genome and is particularly reduced in cell type specific accessible regions. We also identify strategies to maximize performance in cell type specific accessible regions.

Enhancing Disease Risk Gene Discovery by Integrating Transcription Factor-Linked Trans-located Variants into Transcriptome-Wide Association Analyses

Transcriptome-wide association studies (TWAS) have been successful in identifying disease susceptibility genes by integrating cis-variants predicted gene expression with genome-wide association studies (GWAS) data. However, trans-located variants for predicting gene expression remain largely unexplored. Here, we introduce transTF-TWAS, which incorporates transcription factor (TF)-linked trans-located variants to enhance model building. Using data from the Genotype-Tissue Expression project, we predict gene expression and alternative splicing and applied these models to large GWAS datasets for breast, prostate, and lung cancers. We demonstrate that transTF-TWAS outperforms other existing TWAS approaches in both constructing gene prediction models and identifying disease-associated genes, as evidenced by simulations and real data analysis. Our transTF-TWAS approach significantly contributes to the discovery of disease risk genes. Findings from this study have shed new light on several genetically driven key regulators and their associated regulatory networks underlying disease susceptibility.

Oncogenic fatty acid oxidation senses circadian disruption in sleep-deficiency-enhanced tumorigenesis

Circadian disruption predicts poor cancer prognosis, yet how circadian disruption is sensed in sleep-deficiency (SD)-enhanced tumorigenesis remains obscure. Here, we show fatty acid oxidation (FAO) as a circadian sensor relaying from clock disruption to oncogenic metabolic signal in SD-enhanced lung tumorigenesis. Both unbiased transcriptomic and metabolomic analyses reveal that FAO senses SD-induced circadian disruption, as illustrated by continuously increased palmitoyl-coenzyme A (PA-CoA) catalyzed by long-chain fatty acyl-CoA synthetase 1 (ACSL1). Mechanistically, SD-dysregulated CLOCK hypertransactivates ACSL1 to produce PA-CoA, which facilitates CLOCK-Cys194 S-palmitoylation in a ZDHHC5-dependent manner. This positive transcription-palmitoylation feedback loop prevents ubiquitin-proteasomal degradation of CLOCK, causing FAO-sensed circadian disruption to maintain SD-enhanced cancer stemness. Intriguingly, timed β-endorphin resets rhythmic Clock and Acsl1 expression to alleviate SD-enhanced tumorigenesis. Sleep quality and serum β-endorphin are negatively associated with both cancer development and CLOCK/ACSL1 expression in patients with cancer, suggesting dawn-supplemented β-endorphin as a potential chronotherapeutic strategy for SD-related cancer.

DUSP6 inhibition overcomes neuregulin/HER3-driven therapy tolerance in HER2+ breast cancer

Despite clinical benefits of tyrosine kinase inhibitors (TKIs) in cancer, most tumors can reactivate proliferation under TKI therapy. Here we present transcriptional profiling of HER2+ breast cancer cells transitioning from dormant drug tolerant cells to re-proliferating cells under continuous HER2 inhibitor (HER2i) therapy. Focusing on phosphatases, expression of dual-specificity phosphatase DUSP6 was found inhibited in dormant cells, but strongly induced upon regrowth. DUSP6 expression also selectively associated with poor patient survival in HER2+ breast cancers. DUSP6 overexpression conferred apoptosis resistance, whereas its pharmacological blockade prevented therapy tolerance development under HER2i therapy. DUSP6 targeting also synergized with clinically used HER2i combination therapies. Mechanistically DUSP6 is a positive regulator of HER3 expression, and its impact on HER2i tolerance was mediated by neuregulin-HER3 axis. In vivo, genetic targeting of DUSP6 reduced tumor growth in brain metastasis model, whereas its pharmacological targeting induced synthetic lethal therapeutic effect in combination with HER2i. Collectively this work demonstrates that DUSP6 drives escape from HER2i-induced dormancy, and that DUSP6 is a druggable target to overcome HER3-driven TKI resistance.

Fibroblast-like synoviocytes orchestrate daily rhythmic inflammation in arthritis

Rheumatoid arthritis is a chronic inflammatory disease that shows characteristic diurnal variation in symptom severity, where joint resident fibroblast-like synoviocytes (FLS) act as important mediators of arthritis pathology. We investigate the role of FLS circadian clock function in directing rhythmic joint inflammation in a murine model of inflammatory arthritis. We demonstrate FLS time-of-day-dependent gene expression is attenuated in arthritic joints, except for a subset of disease-modifying genes. The deletion of essential clock gene Bmal1 in FLS reduced susceptibility to collagen-induced arthritis but did not impact symptomatic severity in affected mice. Notably, FLS Bmal1 deletion resulted in loss of diurnal expression of disease-modulating genes across the joint, and elevated production of MMP3, a prognostic marker of joint damage in inflammatory arthritis. This work identifies the FLS circadian clock as an influential driver of daily oscillations in joint inflammation, and a potential regulator of destructive pathology in chronic inflammatory arthritis.

REUNION: transcription factor binding prediction and regulatory association inference from single-cell multi-omics data

MOTIVATION

Profiling of gene expression and chromatin accessibility by single-cell multi-omics approaches can help to systematically decipher how transcription factors (TFs) regulate target gene expression via cis-region interactions. However, integrating information from different modalities to discover regulatory associations is challenging, in part because motif scanning approaches miss many likely TF binding sites.

RESULTS

We develop REUNION, a framework for predicting genome-wide TF binding and cis-region-TF-gene "triplet" regulatory associations using single-cell multi-omics data. The first component of REUNION, Unify, utilizes information theory-inspired complementary score functions that incorporate TF expression, chromatin accessibility, and target gene expression to identify regulatory associations. The second component, Rediscover, takes Unify estimates as input for pseudo semi-supervised learning to predict TF binding in accessible genomic regions that may or may not include detected TF motifs. Rediscover leverages latent chromatin accessibility and sequence feature spaces of the genomic regions, without requiring chromatin immunoprecipitation data for model training. Applied to peripheral blood mononuclear cell data, REUNION outperforms alternative methods in TF binding prediction on average performance. In particular, it recovers missing region-TF associations from regions lacking detected motifs, which circumvents the reliance on motif scanning and facilitates discovery of novel associations involving potential co-binding transcriptional regulators. Newly identified region-TF associations, even in regions lacking a detected motif, improve the prediction of target gene expression in regulatory triplets, and are thus likely to genuinely participate in the regulation.

AVAILABILITY AND IMPLEMENTATION

All source code is available at https://github.com/yangymargaret/REUNION.

TFTF: An R-Based Integrative Tool for Decoding Human Transcription Factor-Target Interactions

Transcription factors (TFs) are crucial in modulating gene expression and sculpting cellular and organismal phenotypes. The identification of TF-target gene interactions is pivotal for comprehending molecular pathways and disease etiologies but has been hindered by the demanding nature of traditional experimental approaches. This paper introduces a novel web application and package utilizing the R program, which predicts TF-target gene relationships and vice versa. Our application integrates the predictive power of various bioinformatic tools, leveraging their combined strengths to provide robust predictions. It merges databases for enhanced precision, incorporates gene expression correlation for accuracy, and employs pan-tissue correlation analysis for context-specific insights. The application also enables the integration of user data with established resources to analyze TF-target gene networks. Despite its current limitation to human data, it provides a platform to explore gene regulatory mechanisms comprehensively. This integrated, systematic approach offers researchers an invaluable tool for dissecting the complexities of gene regulation, with the potential for future expansions to include a broader range of species.

RAD21 deficiency drives corneal to scleral differentiation fate switching via upregulating WNT9B

The cornea and sclera are distinct adjacent tissues, yet their stromal cells originate from common neural crest cells (NCCs). Sclerocornea is a disease characterized by an indistinguishable boundary between the cornea and sclera. Previously, we identified a RAD21 mutation in a sclerocornea pedigree. Here, we investigated the impacts of RAD21 on NCC activities during eye development. RAD21 deficiency caused upregulation of PCDHGC3. Both RAD21 knockdown and PCDHGC3 upregulation disrupted the migration of NCCs. Transcriptome analysis indicated that WNT9B had 190.9-fold higher expression in scleral stroma than in corneal stroma. WNT9B was also significantly upregulated by both RAD21 knockdown and PCDHGC3 overexpression, and knock down of WNT9B rescued the differentiation and migration of NCCs with RAD21 deficiency. Consistently, overexpressing wnt9b in Xenopus tropicalis led to ocular developmental abnormalities. In summary, WNT9B is a determinant factor during NCC differentiation into corneal keratocytes or scleral stromal cells and is affected by RAD21 expression.

Heterochromatin protein ERH represses alternative cell fates during early mammalian differentiation

During development, H3K9me3 heterochromatin is dynamically rearranged, silencing repeat elements and protein coding genes to restrict cell identity. Enhancer of Rudimentary Homolog (ERH) is an evolutionarily conserved protein originally characterized in fission yeast and recently shown to be required for H3K9me3 maintenance in human fibroblasts, but its function during development remains unknown. Here, we show that ERH is required for proper segregation of the inner cell mass and trophectoderm cell lineages during mouse development by repressing totipotent and alternative lineage programs. During human embryonic stem cell (hESC) differentiation into germ layer lineages, ERH is crucial for silencing naïve and pluripotency genes, transposable elements, and alternative lineage genes. Strikingly, ERH depletion in somatic cells reverts the H3K9me3 landscape to an hESC state and enables naïve and pluripotency gene and transposable element activation during iPSC reprogramming. Our findings reveal a role for ERH in initiation and maintenance of developmentally established gene repression.

Validated Negative Regions (VNRs) in the VISTA Database might be Truncated Forms of Bona Fide Enhancers

The VISTA enhancer database is a valuable resource for evaluating predicted enhancers in humans and mice. In addition to thousands of validated positive regions (VPRs) in the human and mouse genomes, the database also contains similar numbers of validated negative regions (VNRs). It is previously shown that the VPRs are on average half as long as predicted overlapping enhancers that are highly conserved and hypothesize that the VPRs may be truncated forms of long bona fide enhancers. Here, it is shown that like the VPRs, the VNRs also are under strong evolutionary constraints and overlap predicted enhancers in the genomes. The VNRs are also on average half as long as predicted overlapping enhancers that are highly conserved. Moreover, the VNRs and the VPRs display similar cell/tissue-specific modification patterns of key epigenetic marks of active enhancers. Furthermore, the VNRs and the VPRs show similar impact score spectra of in silico mutagenesis. These highly similar properties between the VPRs and the VNRs suggest that like the VPRs, the VNRs may also be truncated forms of long bona fide enhancers.

N6-methyladenosine-modified SENP1, identified by IGF2BP3, is a novel molecular marker in acute myeloid leukemia and aggravates progression by activating AKT signal via de-SUMOylating HDAC2

BACKGROUND

Elevated evidence suggests that the SENPs family plays an important role in tumor progression. However, the role of SENPs in AML remains unclear.

METHODS

We evaluated the expression pattern of SENP1 based on RNA sequencing data obtained from OHSU, TCGA, TARGET, and MILE datasets. Clinical samples were used to verify the expression of SENP1 in the AML cells. Lentiviral vectors shRNA and sgRNA were used to intervene in SENP1 expression in AML cells, and the effects of SENP1 on AML proliferation and anti-apoptosis were detected using in vitro and in vivo models. Chip-qPCR, MERIP-qPCR, CO-IP, RNA pulldown, and dual-luciferase reporter gene assays were used to explore the regulatory mechanisms of SNEP1 in AML.

RESULTS

SENP1 was significantly upregulated in high-risk AML patients and closely related to poor prognosis. The AKT/mTOR signaling pathway is a key downstream pathway that mediates SENP1's regulation of AML proliferation and anti-apoptosis. Mechanistically, the CO-IP assay revealed binding between SENP1 and HDAC2. SUMO and Chip-qPCR assays suggested that SENP1 can desumoylate HDAC2, which enhances EGFR transcription and activates the AKT pathway. In addition, we found that IGF2BP3 expression was upregulated in high-risk AML patients and was positively correlated with SENP1 expression. MERIP-qPCR and RIP-qPCR showed that IGF2BP3 binds SENP1 3-UTR in an m6A manner, enhances SENP1 expression, and promotes AKT pathway conduction.

CONCLUSIONS

Our findings reveal a distinct mechanism of SENP1-mediated HDAC2-AKT activation and establish the critical role of the IGF2BP3/SENP1signaling axis in AML development.

Flexible modeling of regulatory networks improves transcription factor activity estimation

Transcriptional regulation plays a crucial role in determining cell fate and disease, yet inferring the key regulators from gene expression data remains a significant challenge. Existing methods for estimating transcription factor (TF) activity often rely on static TF-gene interaction databases and cannot adapt to changes in regulatory mechanisms across different cell types and disease conditions. Here, we present a new algorithm - Transcriptional Inference using Gene Expression and Regulatory data (TIGER) - that overcomes these limitations by flexibly modeling activation and inhibition events, up-weighting essential edges, shrinking irrelevant edges towards zero through a sparse Bayesian prior, and simultaneously estimating both TF activity levels and changes in the underlying regulatory network. When applied to yeast and cancer TF knock-out datasets, TIGER outperforms comparable methods in terms of prediction accuracy. Moreover, our application of TIGER to tissue- and cell-type-specific RNA-seq data demonstrates its ability to uncover differences in regulatory mechanisms. Collectively, our findings highlight the utility of modeling context-specific regulation when inferring transcription factor activities.

Let-7 restrains an oncogenic epigenetic circuit in AT2 cells to prevent ectopic formation of fibrogenic transitional cell intermediates and pulmonary fibrosis

Analysis of lung alveolar type 2 (AT2) progenitor stem cells has highlighted fundamental mechanisms that direct their differentiation into alveolar type 1 cells (AT1s) in lung repair and disease. However, microRNA (miRNA) mediated post-transcriptional mechanisms which govern this nexus remain understudied. We show here that the let-7 miRNA family serves a homeostatic role in governance of AT2 quiescence, specifically by preventing the uncontrolled accumulation of AT2 transitional cells and by promoting AT1 differentiation to safeguard the lung from spontaneous alveolar destruction and fibrosis. Using mice and organoid models with genetic ablation of let-7a1/let-7f1/let-7d cluster (let-7afd) in AT2 cells, we demonstrate prevents AT1 differentiation and results in aberrant accumulation of AT2 transitional cells in progressive pulmonary fibrosis. Integration of enhanced AGO2 UV-crosslinking and immunoprecipitation sequencing (AGO2-eCLIP) with RNA-sequencing from AT2 cells uncovered the induction of direct targets of let-7 in an oncogene feed-forward regulatory network including BACH1/EZH2 which drives an aberrant fibrotic cascade. Additional analyses by CUT&RUN-sequencing revealed loss of let-7afd hampers AT1 differentiation by eliciting aberrant histone EZH2 methylation which prevents the exit of AT2 transitional cells into terminal AT1s. This study identifies let-7 as a key gatekeeper of post-transcriptional and epigenetic chromatin signals to prevent AT2-driven pulmonary fibrosis.

The response to influenza vaccination is associated with DNA methylation-driven regulation of T cell innate antiviral pathways

Background

The effect of vaccination on the epigenome remains poorly characterized. In previous research, we identified an association between seroprotection against influenza and DNA methylation at sites associated with the RIG-1 signaling pathway, which recognizes viral double-stranded RNA and leads to a type I interferon response. However, these studies did not fully account for confounding factors including age, gender, and BMI, along with changes in cell type composition.

Results

Here, we studied the influenza vaccine response in a longitudinal cohort vaccinated over two consecutive years (2019-2020 and 2020-2021), using peripheral blood mononuclear cells and a targeted DNA methylation approach. To address the effects of multiple factors on the epigenome, we designed a multivariate multiple regression model that included seroprotection levels as quantified by the hemagglutination-inhibition (HAI) assay test.

Conclusions

Our findings indicate that 179 methylation sites can be combined as potential signatures to predict seroprotection. These sites were not only enriched for genes involved in the regulation of the RIG-I signaling pathway, as found previously, but also enriched for other genes associated with innate immunity to viruses and the transcription factor binding sites of BRD4, which is known to impact T cell memory. We propose a model to suggest that the RIG-I pathway and BRD4 could potentially be modulated to improve immunization strategies.

Estrogen receptor 1 chromatin profiling in human breast tumors reveals high inter-patient heterogeneity with enrichment of risk SNPs and enhancer activity at most-conserved regions

Estrogen Receptor 1 (ESR1; also known as ERα, encoded by ESR1 gene) is the main driver and prime drug target in luminal breast cancer. ESR1 chromatin binding is extensively studied in cell lines and a limited number of human tumors, using consensi of peaks shared among samples. However, little is known about inter-tumor heterogeneity of ESR1 chromatin action, along with its biological implications. Here, we use a large set of ESR1 ChIP-seq data from 70 ESR1+ breast cancers to explore inter-patient heterogeneity in ESR1 DNA binding to reveal a striking inter-tumor heterogeneity of ESR1 action. Of note, commonly shared ESR1 sites show the highest estrogen-driven enhancer activity and are most engaged in long-range chromatin interactions. In addition, the most commonly shared ESR1-occupied enhancers are enriched for breast cancer risk SNP loci. We experimentally confirm SNVs to impact chromatin binding potential for ESR1 and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we can confirm these variations to associate with differences in expression for the target gene. Cumulatively, we reveal a natural hierarchy of ESR1-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ESR1 landscape, with the most common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.

Identification of key eRNAs for intervertebral disc degeneration by integrated multinomial bioinformatics analysis

BACKGROUND

Intervertebral disc degeneration (IVDD) is a common degenerative condition leading to abnormal stress distribution under load, causing intervertebral stenosis, facet joint degeneration, and foraminal stenosis. Very little is known about the molecular mechanism of eRNAs in IVDD.

METHODS

Gene expression profiles of 38 annulus disc samples composed of 27 less degenerated discs (LDs) and 11 more degenerated discs (MDs) were retrieved from the GEO database. Then, differentially expressed enhancer RNAs (DEeRNAs), differentially expressed target genes (DETGs), and differentially expressed transcription factors (DETFs), hallmark of cancer signalling pathways according to GSVA; the types and quantity of immune cells according to CIBERSORT; and immune gene sets according to ssGSEA were analysed to construct an IVDD-related eRNA network. Then, multidimensional validation was performed to explore the interactions among DEeRNAs, DETFs and DEGs in space.

RESULTS

A total of 53 components, 14 DETGs, 15 DEeRNAs, 3 DETFs, 5 immune cells, 9 hallmarks, and 7 immune gene sets, were selected to construct the regulatory network. After validation by online multidimensional databases, 21 interactive DEeRNA-DEG-DETF axes related to IVDD exacerbation were identified, among which the C1S-CTNNB1-CHD4 axis was the most significant.

CONCLUSION

Based upon the results of our study, we theorize that the C1S-CTNNB1-CHD4 axis plays a vital role in IVDD exacerbation. Specifically, C1S recruits CTNNB1 and upregulates the expression of CHD4 in IVDD, and subsequently, CHD4 suppresses glycolysis and activates oxidative phosphorylation, thus generating insoluble collagen fibre deposits and leading to the progression of IVDD. Overall, these DEeRNAs could comprise promising therapeutic targets for IVDD due to their high tissue specificity.

LATS1 controls CTCF chromatin occupancy and hormonal response of 3D-grown breast cancer cells

The cancer epigenome has been studied in cells cultured in two-dimensional (2D) monolayers, but recent studies highlight the impact of the extracellular matrix and the three-dimensional (3D) environment on multiple cellular functions. Here, we report the physical, biochemical, and genomic differences between T47D breast cancer cells cultured in 2D and as 3D spheroids. Cells within 3D spheroids exhibit a rounder nucleus with less accessible, more compacted chromatin, as well as altered expression of ~2000 genes, the majority of which become repressed. Hi-C analysis reveals that cells in 3D are enriched for regions belonging to the B compartment, have decreased chromatin-bound CTCF and increased fusion of topologically associating domains (TADs). Upregulation of the Hippo pathway in 3D spheroids results in the activation of the LATS1 kinase, which promotes phosphorylation and displacement of CTCF from DNA, thereby likely causing the observed TAD fusions. 3D cells show higher chromatin binding of progesterone receptor (PR), leading to an increase in the number of hormone-regulated genes. This effect is in part mediated by LATS1 activation, which favors cytoplasmic retention of YAP and CTCF removal.

Nuclear receptor corepressors non-canonically drive glucocorticoid receptor-dependent activation of hepatic gluconeogenesis

Nuclear receptor corepressors (NCoRs) function in multiprotein complexes containing histone deacetylase 3 (HDAC3) to alter transcriptional output primarily through repressive chromatin remodelling at target loci1-5. In the liver, loss of HDAC3 causes a marked hepatosteatosis largely because of de-repression of genes involved in lipid metabolism6,7; however, the individual roles and contribution of other complex members to hepatic and systemic metabolic regulation are unclear. Here we show that adult loss of both NCoR1 and NCoR2 (double knockout (KO)) in hepatocytes phenocopied the hepatomegalic fatty liver phenotype of HDAC3 KO. In addition, double KO livers exhibited a dramatic reduction in glycogen storage and gluconeogenic gene expression that was not observed with hepatic KO of individual NCoRs or HDAC3, resulting in profound fasting hypoglycaemia. This surprising HDAC3-independent activation function of NCoR1 and NCoR2 is due to an unexpected loss of chromatin accessibility on deletion of NCoRs that prevented glucocorticoid receptor binding and stimulatory effect on gluconeogenic genes. These studies reveal an unanticipated, non-canonical activation function of NCoRs that is required for metabolic health.

Activation of the FOXM1/ASF1B/PRDX3 axis confers hyperproliferative and antioxidative stress reactivity to gastric cancer

Nucleosome assembly during DNA replication is dependent on histone chaperones. Recent studies suggest that dysregulated histone chaperones contribute to cancer progression, including gastric cancer (GC). Further studies are required to explore the prognostic and therapeutic implications of histone chaperones and their mechanisms of action in GC progression. Here we identified histone chaperone ASF1B as a potential biomarker for GC proliferation and prognosis. ASF1B was significantly upregulated in GC, which was associated with poor prognosis. In vitro and in vivo experiments demonstrated that the inhibition of ASF1B suppressed the malignant characteristics of GC, while overexpression of ASF1B had the opposite effect. Mechanistically, transcription factor FOXM1 directly bound to the ASF1B-promoter region, thereby regulating its transcription. Treatment with thiostrepton, a FOXM1 inhibitor, not only suppressed ASF1B expression, but also inhibited GC progression. Furthermore, ASF1B regulated the mitochondrial protein peroxiredoxin 3 (PRDX3) transcription in a FOXM1-dependent manner. The crucial role of ASF1B-regulated PRDX3 in GC cell proliferation and oxidative stress balance was also elucidated. In summary, our study suggests that the FOXM1-ASF1B-PRDX3 axis is a potential therapeutic target for treating GC.

Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.

Key chromatin regulator-related genes associated with the risk of coronary artery disease regulate the expression of HCFC1, RNF8, TNP1 and SET

Chromatin regulators are indispensable upstream epigenetic regulators.The emergence and progression of atherosclerosis has been demonstrated to be influenced by smooth muscle-related chromatin regulators, such as ZEB2 and MAFF. However, specific chromatin regulators and their possible roles have not been clarified. Information was gathered from 51 patients diagnosed with coronary artery disease (CAD) and 50 individuals in good health from the GEO database. 440 genes were identified as having differential expression across the two datasets, and these genes were linked to cellular reactions. Enrichment of pathways related to histone modification and transcriptional regulatory factors was observed in GO and KEGG analyses. Four machine learning models (RF, SVM, GLM, and XGB) were developed using the expression profiles of 440 chromatin-associated genes in the CAD cohort to pinpoint genes with significant diagnostic potential. After evaluating residuals, root mean square errors, receiver operating characteristic curves, and immune-infiltration, four key genes (HCFC1, RNF8, TNP1, and SET) were identified. Gene expression in different blood vessel levels in atherosclerotic plaques in a mouse model of coronary artery disease showed significant variations. The gene expression levels in macrophages aligned with clinical data from the GEO database as expected. This discovery is crucial for future analysis and the prediction of drug and miRNA targets. In conclusion, we found that the four hub genes are important in the mechanism of CAD. These findings provide new ideas for the study of potential epigenetic predictive markers and therapeutic targets to be used in determining a treatment strategy for CAD.

OpenAnnotateApi: Python and R packages to efficiently annotate and analyze chromatin accessibility of genomic regions

Summary

Chromatin accessibility serves as a critical measurement of physical contact between nuclear macromolecules and DNA sequence, providing valuable insights into the comprehensive landscape of regulatory mechanisms, thus we previously developed the OpenAnnotate web server. However, as an increasing number of epigenomic analysis software tools emerged, web-based annotation often faced limitations and inconveniences when integrated into these software pipelines. To address these issues, we here develop two software packages named OpenAnnotatePy and OpenAnnotateR. In addition to web-based functionalities, these packages encompass supplementary features, including the capability for simultaneous annotation across multiple cell types, advanced searching of systems, tissues and cell types, and converting the result to the data structure of mainstream tools. Moreover, we applied the packages to various scenarios, including cell type revealing, regulatory element prediction, and integration into mainstream single-cell ATAC-seq analysis pipelines including EpiScanpy, Signac, and ArchR. We anticipate that OpenAnnotateApi will significantly facilitate the deciphering of gene regulatory mechanisms, and offer crucial assistance in the field of epigenomic studies.

Availability and implementation

OpenAnnotateApi for R is available at https://github.com/ZjGaothu/OpenAnnotateR and for Python is available at https://github.com/ZjGaothu/OpenAnnotatePy.

Interplay between B7-H3 and HLA class I in the clinical course of pancreatic ductal adenocarcinoma

Human leukocyte antigen (HLA) class I defects are associated with cancer progression. However, their prognostic significance is controversial and may be modulated by immune checkpoints. Here, we investigated whether the checkpoint B7-H3 modulates the relationship between HLA class I and pancreatic ductal adenocarcinoma (PDAC) prognosis. PDAC tumors were analyzed for the expression of B7-H3, HLA class I, HLA class II molecules, and for the presence of tumor-infiltrating immune cells. We observed defective HLA class I and HLA class II expressions in 75% and 59% of PDAC samples, respectively. HLA class I and B7-H3 expression were positively related at mRNA and protein level, potentially because of shared regulation by RELA, a sub-unit of NF-kB. High B7-H3 expression and low CD8+ T cell density were indicators of poor survival, while HLA class I was not. Defective HLA class I expression was associated with unfavorable survival only in patients with low B7-H3 expression. Favorable survival was observed only when HLA class I expression was high and B7-H3 expression low. Our results provide the rationale for targeting B7-H3 in patients with PDAC tumors displaying high HLA class I levels.

Intergenic sequences harboring potential enhancer elements contribute to Axenfeld-Rieger syndrome by regulating PITX2

Recent studies have uncovered that noncoding sequence variants may relate to Axenfeld-Rieger syndrome (ARS), a rare developmental anomaly with genetic heterogeneity. However, how these genomic regions are functionally and structurally associated with ARS is still unclear. In this study, we performed genome-wide linkage analysis and whole-genome sequencing in a Chinese family with ARS and identified a heterozygous deletion of about 570 kb (termed LOH-1) in the intergenic sequence between paired-like homeodomain transcription factor 2 (PITX2) and family with sequence similarity 241 member A. Knockout of LOH-1 homologous sequences caused ARS phenotypes in mice. RNA-Seq and real-time quantitative PCR revealed a significant reduction in Pitx2 gene expression in LOH-1-/- mice, while forkhead box C1 expression remained unchanged. ChIP-Seq and bioinformatics analysis identified a potential enhancer region (LOH-E1) within LOH-1. Deletion of LOH-E1 led to a substantial downregulation of the PITX2 gene. Mechanistically, we found a sequence (hg38 chr4:111,399,594-111,399,691) that is on LOH-E1 could regulate PITX2 by binding to RAD21, a critical component of the cohesin complex. Knockdown of RAD21 resulted in reduced PITX2 expression. Collectively, our findings indicate that a potential enhancer sequence that is within LOH-1 may regulate PITX2 expression remotely through cohesin-mediated loop domains, leading to ARS when absent.

Integrative analysis of DNA replication origins and ORC-/MCM-binding sites in human cells reveals a lack of overlap

Based on experimentally determined average inter-origin distances of ~100 kb, DNA replication initiates from ~50,000 origins on human chromosomes in each cell cycle. The origins are believed to be specified by binding of factors like the origin recognition complex (ORC) or CTCF or other features like G-quadruplexes. We have performed an integrative analysis of 113 genome-wide human origin profiles (from five different techniques) and five ORC-binding profiles to critically evaluate whether the most reproducible origins are specified by these features. Out of ~7.5 million union origins identified by all datasets, only 0.27% (20,250 shared origins) were reproducibly obtained in at least 20 independent SNS-seq datasets and contained in initiation zones identified by each of three other techniques, suggesting extensive variability in origin usage and identification. Also, 21% of the shared origins overlap with transcriptional promoters, posing a conundrum. Although the shared origins overlap more than union origins with constitutive CTCF-binding sites, G-quadruplex sites, and activating histone marks, these overlaps are comparable or less than that of known transcription start sites, so that these features could be enriched in origins because of the overlap of origins with epigenetically open, promoter-like sequences. Only 6.4% of the 20,250 shared origins were within 1 kb from any of the ~13,000 reproducible ORC-binding sites in human cancer cells, and only 4.5% were within 1 kb of the ~11,000 union MCM2-7-binding sites in contrast to the nearly 100% overlap in the two comparisons in the yeast, Saccharomyces cerevisiae. Thus, in human cancer cell lines, replication origins appear to be specified by highly variable stochastic events dependent on the high epigenetic accessibility around promoters, without extensive overlap between the most reproducible origins and currently known ORC- or MCM-binding sites.

Identification of arnicolide C as a novel chemosensitizer to suppress mTOR/E2F1/FANCD2 axis in non-small cell lung cancer

BACKGROUND AND PURPOSE

The mammalian target of rapamycin (mTOR) pathway plays critical roles in intrinsic chemoresistance by regulating Fanconi anaemia complementation group D2 (FANCD2) expression. However, the mechanisms by which mTOR regulates FANCD2 expression and related inhibitors are not clearly elucidated. Extracts of Centipeda minima (C. minima) showed promising chemosensitizing effects by inhibiting FANCD2 activity. Here, we have aimed to identify the bioactive chemosensitizer in C. minima extracts and elucidate its underlying mechanism.

EXPERIMENTAL APPROACH

The chemosensitizing effects of arnicolide C (ArC), a bioactive compound in C. minima, on non-small cell lung cancer (NSCLC) were investigated using immunoblotting, immunofluorescence, flow cytometry, the comet assay, small interfering RNA (siRNA) transfection and animal models. The online SynergyFinder software was used to determine the synergistic effects of ArC and chemotherapeutic drugs on NSCLC cells.

KEY RESULTS

ArC had synergistic cytotoxic effects with DNA cross-linking drugs such as cisplatin and mitomycin C in NSCLC cells. ArC treatment markedly decreased FANCD2 expression in NSCLC cells, thus attenuating cisplatin-induced FANCD2 nuclear foci formation, leading to DNA damage and apoptosis. ArC inhibited the mTOR pathway and attenuated mTOR-mediated expression of E2F1, a critical transcription factor of FANCD2. Co-administration of ArC and cisplatin exerted synergistic anticancer effects in the A549 xenograft mouse model by suppressing mTOR/FANCD2 signalling in tumour tissues.

CONCLUSION AND IMPLICATIONS

ArC suppressed DNA cross-linking drug-induced DNA damage response by inhibiting the mTOR/E2F1/FANCD2 signalling axis, serving as a chemosensitizing agent. This provides insight into the anticancer mechanisms of ArC and offers a potential combinatorial anticancer therapeutic strategy.

Senktide blocks aberrant RTN3 interactome to retard memory decline and tau pathology in social isolated Alzheimer's disease mice

Sporadic or late-onset Alzheimer's disease (LOAD) accounts for more than 95% of Alzheimer's disease (AD) cases without any family history. Although genome-wide association studies have identified associated risk genes and loci for LOAD, numerous studies suggest that many adverse environmental factors, such as social isolation, are associated with an increased risk of dementia. However, the underlying mechanisms of social isolation in AD progression remain elusive. In the current study, we found that 7 days of social isolation could trigger pattern separation impairments and presynaptic abnormalities of the mossy fibre-CA3 circuit in AD mice. We also revealed that social isolation disrupted histone acetylation and resulted in the downregulation of 2 dentate gyrus (DG)-enriched miRNAs, which simultaneously target reticulon 3 (RTN3), an endoplasmic reticulum protein that aggregates in presynaptic regions to disturb the formation of functional mossy fibre boutons (MFBs) by recruiting multiple mitochondrial and vesicle-related proteins. Interestingly, the aggregation of RTN3 also recruits the PP2A B subunits to suppress PP2A activity and induce tau hyperphosphorylation, which, in turn, further elevates RTN3 and forms a vicious cycle. Finally, using an artificial intelligence-assisted molecular docking approach, we determined that senktide, a selective agonist of neurokinin3 receptors (NK3R), could reduce the binding of RTN3 with its partners. Moreover, application of senktide in vivo effectively restored DG circuit disorders in socially isolated AD mice. Taken together, our findings not only demonstrate the epigenetic regulatory mechanism underlying mossy fibre synaptic disorders orchestrated by social isolation and tau pathology but also reveal a novel potential therapeutic strategy for AD.

ADNP modulates SINE B2-derived CTCF-binding sites during blastocyst formation in mice

CTCF is crucial for chromatin structure and transcription regulation in early embryonic development. However, the kinetics of CTCF chromatin occupation in preimplantation embryos have remained unclear. In this study, we used CUT&RUN technology to investigate CTCF occupancy in mouse preimplantation development. Our findings revealed that CTCF begins binding to the genome prior to zygotic genome activation (ZGA), with a preference for CTCF-anchored chromatin loops. Although the majority of CTCF occupancy is consistently maintained, we identified a specific set of binding sites enriched in the mouse-specific short interspersed element (SINE) family B2 that are restricted to the cleavage stages. Notably, we discovered that the neuroprotective protein ADNP counteracts the stable association of CTCF at SINE B2-derived CTCF-binding sites. Knockout of Adnp in the zygote led to impaired CTCF binding signal recovery, failed deposition of H3K9me3, and transcriptional derepression of SINE B2 during the morula-to-blastocyst transition, which further led to unfaithful cell differentiation in embryos around implantation. Our analysis highlights an ADNP-dependent restriction of CTCF binding during cell differentiation in preimplantation embryos. Furthermore, our findings shed light on the functional importance of transposable elements (TEs) in promoting genetic innovation and actively shaping the early embryo developmental process specific to mammals.

UCHL1 contributes to insensitivity to endocrine therapy in triple-negative breast cancer by deubiquitinating and stabilizing KLF5

BACKGROUND

Ubiquitin carboxyl-terminal hydrolase L1 (UCHL1) is a deubiquitinating enzyme that regulates ERα expression in triple-negative cancer (TNBC). This study aimed to explore the deubiquitination substrates of UCHL1 related to endocrine therapeutic responses and the mechanisms of UCHL1 dysregulation in TNBC.

METHODS

Bioinformatics analysis was conducted using online open databases. TNBC representative MDA-MB-468 and SUM149 cells were used for in vitro and in-vivo studies. Co-immunoprecipitation was used to explore the interaction between UCHL1 and KLF5 and UCHL1-mediated KIF5 deubiquitination. CCK-8, colony formation and animal studies were performed to assess endocrine therapy responses. The regulatory effect of TET1/3 on UCHL1 promoter methylation and transcription was performed by Bisulfite sequencing PCR and ChIP-qPCR.

RESULTS

UCHL1 interacts with KLF5 and stabilizes KLF5 by reducing its polyubiquitination and proteasomal degradation. The UCHL1-KLF5 axis collaboratively upregulates EGFR expression while downregulating ESR1 expression at both mRNA and protein levels in TNBC. UCHL1 knockdown slows the proliferation of TNBC cells and sensitizes the tumor cells to Tamoxifen and Fulvestrant. KLF5 overexpression partially reverses these trends. Both TET1 and TET3 can bind to the UCHL1 promoter region, reducing methylation of associated CpG sites and enhancing UCHL1 transcription in TNBC cell lines. Additionally, TET1 and TET3 elevates KLF5 protein level in a UCHL1-dependent manner.

CONCLUSION

UCHL1 plays a pivotal role in TNBC by deubiquitinating and stabilizing KLF5, contributing to endocrine therapy resistance. TET1 and TET3 promote UCHL1 transcription through promoter demethylation and maintain KLF5 protein level in a UCHL1-dependent manner, implying their potential as therapeutic targets in TNBC.

The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen

Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype.

SIGNIFICANCE

Standard treatments are related to loss of DNA methylation in IDHmut glioma, resulting in epigenetic activation of genes associated with tumor progression and alterations in the microenvironment that resemble treatment-naïve IDHwt glioma.

TSCRE: a comprehensive database for tumor-specific cis-regulatory elements

Cis-regulatory elements (CREs) and super cis-regulatory elements (SCREs) are non-coding DNA regions which influence the transcription of nearby genes and play critical roles in development. Dysregulated CRE and SCRE activities have been reported to alter the expression of oncogenes and tumor suppressors, thereby regulating cancer hallmarks. To address the strong need for a comprehensive catalogue of dysregulated CREs and SCREs in human cancers, we present TSCRE (http://tscre.zsqylab.com/), an open resource providing tumor-specific and cell type-specific CREs and SCREs derived from the re-analysis of publicly available histone modification profiles. Currently, TSCRE contains 1 864 941 dysregulated CREs and 68 253 dysregulated SCREs identified from 1366 human patient samples spanning 17 different cancer types and 9 histone marks. Over 95% of these elements have been validated in public resources. TSCRE offers comprehensive annotations for each element, including associated genes, expression patterns, clinical prognosis, somatic mutations, transcript factor binding sites, cancer-type specificity, and drug response. Additionally, TSCRE integrates pathway and transcript factor enrichment analyses for each study, enabling in-depth functional and mechanistic investigations. Furthermore, TSCRE provides an interactive interface for users to explore any CRE and SCRE of interest. We believe TSCRE will be a highly valuable platform for the community to discover candidate cancer biomarkers.

Id2 epigenetically controls CD8+ T-cell exhaustion by disrupting the assembly of the Tcf3-LSD1 complex

CD8+ T-cell exhaustion is a state of dysfunction that promotes tumor progression and is marked by the generation of Slamf6+ progenitor exhausted (Texprog) and Tim-3+ terminally exhausted (Texterm) subpopulations. Inhibitor of DNA binding protein 2 (Id2) has been shown to play important roles in T-cell development and CD8+ T-cell immunity. However, the role of Id2 in CD8+ T-cell exhaustion is unclear. Here, we found that Id2 transcriptionally and epigenetically regulates the generation of Texprog cells and their conversion to Texterm cells. Genetic deletion of Id2 dampens CD8+ T-cell-mediated immune responses and the maintenance of stem-like CD8+ T-cell subpopulations, suppresses PD-1 blockade and increases tumor susceptibility. Mechanistically, through its HLH domain, Id2 binds and disrupts the assembly of the Tcf3-Tal1 transcriptional regulatory complex, and thus modulates chromatin accessibility at the Slamf6 promoter by preventing the interaction of Tcf3 with the histone lysine demethylase LSD1. Therefore, Id2 increases the abundance of the permissive H3K4me2 mark on the Tcf3-occupied E-boxes in the Slamf6 promoter, modulates chromatin accessibility at the Slamf6 promoter and epigenetically regulates the generation of Slamf6+ Texprog cells. An LSD1 inhibitor GSK2879552 can rescue the Id2 knockout phenotype in tumor-bearing mice. Inhibition of LSD1 increases the abundance of Slamf6+Tim-3- Texprog cells in tumors and the expression level of Tcf1 in Id2-deleted CD8+ T cells. This study demonstrates that Id2-mediated transcriptional and epigenetic modification drives hierarchical CD8+ T-cell exhaustion, and the mechanistic insights gained may have implications for therapeutic intervention with tumor immune evasion.

Adaptive Selection of Cis-regulatory Elements in the Han Chinese

Cis-regulatory elements have an important role in human adaptation to the living environment. However, the lag in population genomic cohort studies and epigenomic studies, hinders the research in the adaptive analysis of cis-regulatory elements in human populations. In this study, we collected 4,013 unrelated individuals and performed a comprehensive analysis of adaptive selection of genome-wide cis-regulatory elements in the Han Chinese. In total, 12.34% of genomic regions are under the influence of adaptive selection, where 1.00% of enhancers and 2.06% of promoters are under positive selection, and 0.06% of enhancers and 0.02% of promoters are under balancing selection. Gene ontology enrichment analysis of these cis-regulatory elements under adaptive selection reveals that many positive selections in the Han Chinese occur in pathways involved in cell-cell adhesion processes, and many balancing selections are related to immune processes. Two classes of adaptive cis-regulatory elements related to cell adhesion were in-depth analyzed, one is the adaptive enhancers derived from neanderthal introgression, leads to lower hyaluronidase level in skin, and brings better performance on UV-radiation resistance to the Han Chinese. Another one is the cis-regulatory elements regulating wound healing, and the results suggest the positive selection inhibits coagulation and promotes angiogenesis and wound healing in the Han Chinese. Finally, we found that many pathogenic alleles, such as risky alleles of type 2 diabetes or schizophrenia, remain in the population due to the hitchhiking effect of positive selections. Our findings will help deepen our understanding of the adaptive evolution of genome regulation in the Han Chinese.