GTRD: a database on gene transcription regulation-2019 update

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.

A large-scale cancer-specific protein-DNA interaction network

Cancer development and progression are generally associated with gene dysregulation, often resulting from changes in the transcription factor (TF) sequence or expression. Identifying key TFs involved in cancer gene regulation provides a framework for potential new therapeutics. This study presents a large-scale cancer gene TF-DNA interaction network, as well as an extensive promoter clone resource for future studies. Highly connected TFs bind to promoters of genes associated with either good or poor cancer prognosis, suggesting that strategies aimed at shifting gene expression balance between these two prognostic groups may be inherently complex. However, we identified potential for oncogene-targeted therapeutics, with half of the tested oncogenes being potentially repressed by influencing specific activators or bifunctional TFs. Finally, we investigate the role of intrinsically disordered regions within the key cancer-related TF ESR1 in DNA binding and transcriptional activity, and found that these regions can have complex trade-offs in TF function. Altogether, our study broadens our knowledge of the TFs involved in cancer gene regulation and provides a valuable resource for future studies and therapeutics.

Transcription Factor Activity Regulating Macrophage Heterogeneity during Skin Wound Healing

Monocytes and macrophages (Mos/Mϕs) play diverse roles in wound healing by adopting a spectrum of functional phenotypes; however, the regulation of such heterogeneity remains poorly defined. We enhanced our previously published Bayesian inference TF activity model, incorporating both single-cell RNA sequencing and single-cell ATAC sequencing data to infer transcription factor (TF) activity in Mos/Mϕs during skin wound healing. We found that wound Mos/Mϕs clustered into early-stage Mos/Mϕs, late-stage Mϕs, and APCs, and that each cluster showed differential chromatin accessibility and differential predicted TF activity that did not always correlate with mRNA or protein expression. Network analysis revealed two highly connected large communities involving a total of 19 TFs, highlighting TF cooperation in regulating wound Mos/Mϕs. This analysis also revealed a small community populated by NR4A1 and NFKB1, supporting a proinflammatory link between these TFs. Importantly, we validated a proinflammatory role for NR4A1 activity during wound healing, showing that Nr4a1 knockout mice exhibit decreased inflammatory gene expression in early-stage wound Mos/Mϕs, along with delayed wound re-epithelialization and impaired granulation tissue formation. In summary, our study provides insight into TF activity that regulates Mo/Mϕ heterogeneity during wound healing and provides a rational basis for targeting Mo/Mϕ TF networks to alter phenotypes and improve healing.

SAFER: sub-hypergraph attention-based neural network for predicting effective responses to dose combinations

BACKGROUND

The potential benefits of drug combination synergy in cancer medicine are significant, yet the risks must be carefully managed due to the possibility of increased toxicity. Although artificial intelligence applications have demonstrated notable success in predicting drug combination synergy, several key challenges persist: (1) Existing models often predict average synergy values across a restricted range of testing dosages, neglecting crucial dose amounts and the mechanisms of action of the drugs involved. (2) Many graph-based models rely on static protein-protein interactions, failing to adapt to dynamic and higher-order relationships. These limitations constrain the applicability of current methods.

RESULTS

We introduce SAFER, a Sub-hypergraph Attention-based graph model, addressing these issues by incorporating complex relationships among biological knowledge networks and considering dosing effects on subject-specific networks. SAFER outperformed previous models on the benchmark and the independent test set. The analysis of subgraph attention weight for the lung cancer cell line highlighted JAK-STAT signaling pathway, PRDM12, ZNF781, and CDC5L that have been implicated in lung fibrosis.

CONCLUSIONS

SAFER presents an interpretable framework designed to identify drug-responsive signals. Tailored for comprehending dose effects on subject-specific molecular contexts, our model uniquely captures dose-level drug combination responses. This capability unlocks previously inaccessible avenues of investigation compared to earlier models. Furthermore, the SAFER framework can be leveraged by future inquiries to investigate molecular networks that uniquely characterize individual patients and can be applied to prioritize personalized effective treatment based on safe dose combinations.

CD74 is a functional MIF receptor on activated CD4+ T cells

Next to its classical role in MHC II-mediated antigen presentation, CD74 was identified as a high-affinity receptor for macrophage migration inhibitory factor (MIF), a pleiotropic cytokine and major determinant of various acute and chronic inflammatory conditions, cardiovascular diseases and cancer. Recent evidence suggests that CD74 is expressed in T cells, but the functional relevance of this observation is poorly understood. Here, we characterized the regulation of CD74 expression and that of the MIF chemokine receptors during activation of human CD4+ T cells and studied links to MIF-induced T-cell migration, function, and COVID-19 disease stage. MIF receptor profiling of resting primary human CD4+ T cells via flow cytometry revealed high surface expression of CXCR4, while CD74, CXCR2 and ACKR3/CXCR7 were not measurably expressed. However, CD4+ T cells constitutively expressed CD74 intracellularly, which upon T-cell activation was significantly upregulated, post-translationally modified by chondroitin sulfate and could be detected on the cell surface, as determined by flow cytometry, Western blot, immunohistochemistry, and re-analysis of available RNA-sequencing and proteomic data sets. Applying 3D-matrix-based live cell-imaging and receptor pathway-specific inhibitors, we determined a causal involvement of CD74 and CXCR4 in MIF-induced CD4+ T-cell migration. Mechanistically, proximity ligation assay visualized CD74/CXCR4 heterocomplexes on activated CD4+ T cells, which were significantly diminished after MIF treatment, pointing towards a MIF-mediated internalization process. Lastly, in a cohort of 30 COVID-19 patients, CD74 surface expression was found to be significantly upregulated on CD4+ and CD8+ T cells in patients with severe compared to patients with only mild disease course. Together, our study characterizes the MIF receptor network in the course of T-cell activation and reveals CD74 as a novel functional MIF receptor and MHC II-independent activation marker of primary human CD4+ T cells.

CDC7 inhibition drives an inflammatory response and a p53-dependent senescent-like state in breast epithelial cells

Drugs that block DNA replication prevent cell proliferation, which may result in anticancer activity. The latter is dependent on the drug's mode of action as well as on cell type-dependent responses to treatment. The inhibition of Cell division cycle 7-related protein kinase (CDC7), a key regulator of DNA replication, decreases the efficiency of origin firing and hampers the restarting of paused replication forks. Here, we show that upon prolonged CDC7 inhibition, breast-derived MCF10A cells progressively withdraw from the cell cycle and enter a reversible senescent-like state. This is characterised by the rewiring of the transcriptional programme with the induction of cytokine and chemokine expression and correlates with the accumulation of Cyclic GMP-AMP synthase (cGAS)-positive micronuclei. Importantly, cell fate depends on Cellular tumour antigen p53 (p53) function as cells no longer enter senescence but are funnelled into apoptosis upon p53 knockout. This work uncovers key features of the secondary response to CDC7 inhibitors, which could aid the development of these compounds as anticancer drugs.

DeepIMAGER: Deeply Analyzing Gene Regulatory Networks from scRNA-seq Data

Understanding the dynamics of gene regulatory networks (GRNs) across diverse cell types poses a challenge yet holds immense value in unraveling the molecular mechanisms governing cellular processes. Current computational methods, which rely solely on expression changes from bulk RNA-seq and/or scRNA-seq data, often result in high rates of false positives and low precision. Here, we introduce an advanced computational tool, DeepIMAGER, for inferring cell-specific GRNs through deep learning and data integration. DeepIMAGER employs a supervised approach that transforms the co-expression patterns of gene pairs into image-like representations and leverages transcription factor (TF) binding information for model training. It is trained using comprehensive datasets that encompass scRNA-seq profiles and ChIP-seq data, capturing TF-gene pair information across various cell types. Comprehensive validations on six cell lines show DeepIMAGER exhibits superior performance in ten popular GRN inference tools and has remarkable robustness against dropout-zero events. DeepIMAGER was applied to scRNA-seq datasets of multiple myeloma (MM) and detected potential GRNs for TFs of RORC, MITF, and FOXD2 in MM dendritic cells. This technical innovation, combined with its capability to accurately decode GRNs from scRNA-seq, establishes DeepIMAGER as a valuable tool for unraveling complex regulatory networks in various cell types.

Differential impact of sex on regulation of skeletal muscle mitochondrial function and protein homeostasis by hypoxia-inducible factor-1α in normoxia

Hypoxia-inducible factor (HIF)-1α is continuously synthesized and degraded in normoxia. During hypoxia, HIF1α stabilization restricts cellular/mitochondrial oxygen utilization. Cellular stressors can stabilize HIF1α even during normoxia. However, less is known about HIF1α function(s) and sex-specific effects during normoxia in the basal state. Since skeletal muscle is the largest protein store in mammals and protein homeostasis has high energy demands, we determined HIF1α function at baseline during normoxia in skeletal muscle. Untargeted multiomics data analyses were followed by experimental validation in differentiated murine myotubes with loss/gain of function and skeletal muscle from mice without/with post-natal muscle-specific Hif1a deletion (Hif1amsd). Mitochondrial oxygen consumption studies using substrate, uncoupler, inhibitor, titration protocols; targeted metabolite quantification by gas chromatography-mass spectrometry; and post-mitotic senescence markers using biochemical assays were performed. Multiomics analyses showed enrichment in mitochondrial and cell cycle regulatory pathways in Hif1a deleted cells/tissue. Experimentally, mitochondrial oxidative functions and ATP content were higher with less mitochondrial free radical generation with Hif1a deletion. Deletion of Hif1a also resulted in higher concentrations of TCA cycle intermediates and HIF2α proteins in myotubes. Overall responses to Hif1amsd were similar in male and female mice, but changes in complex II function, maximum respiration, Sirt3 and HIF1β protein expression and muscle fibre diameter were sex-dependent. Adaptive responses to hypoxia are mediated by stabilization of constantly synthesized HIF1α. Despite rapid degradation, the presence of HIF1α during normoxia contributes to lower mitochondrial oxidative efficiency and greater post-mitotic senescence in skeletal muscle. In vivo responses to HIF1α in skeletal muscle were differentially impacted by sex. KEY POINTS: Hypoxia-inducible factor -1α (HIF1α), a critical transcription factor, undergoes continuous synthesis and proteolysis, enabling rapid adaptive responses to hypoxia by reducing mitochondrial oxygen consumption. In mammals, skeletal muscle is the largest protein store which is determined by a balance between protein synthesis and breakdown and is sensitive to mitochondrial oxidative function. To investigate the functional consequences of transient HIF1α expression during normoxia in the basal state, myotubes and skeletal muscle from male and female mice with HIF1α knockout were studied using complementary multiomics, biochemical and metabolite assays. HIF1α knockout altered the electron transport chain, mitochondrial oxidative function, signalling molecules for protein homeostasis, and post-mitotic senescence markers, some of which were differentially impacted by sex. The cost of rapid adaptive responses mediated by HIF1α is lower mitochondrial oxidative efficiency and post-mitotic senescence during normoxia.

Aberrant DNA methylation distorts developmental trajectories in atypical teratoid/rhabdoid tumors

Atypical teratoid/rhabdoid tumors (AT/RTs) are pediatric brain tumors known for their aggressiveness and aberrant but still unresolved epigenetic regulation. To better understand their malignancy, we investigated how AT/RT-specific DNA hypermethylation was associated with gene expression and altered transcription factor binding and how it is linked to upstream regulation. Medulloblastomas, choroid plexus tumors, pluripotent stem cells, and fetal brain were used as references. A part of the genomic regions, which were hypermethylated in AT/RTs similarly as in pluripotent stem cells and demethylated in the fetal brain, were targeted by neural transcriptional regulators. AT/RT-unique DNA hypermethylation was associated with polycomb repressive complex 2 and linked to suppressed genes with a role in neural development and tumorigenesis. Activity of the several NEUROG/NEUROD pioneer factors, which are unable to bind to methylated DNA, was compromised via the suppressed expression or DNA hypermethylation of their target sites, which was also experimentally validated for NEUROD1 in medulloblastomas and AT/RT samples. These results highlight and characterize the role of DNA hypermethylation in AT/RT malignancy and halted neural cell differentiation.

SAFER: sub-hypergraph attention-based neural network for predicting effective responses to dose combinations

Background

The potential benefits of drug combination synergy in cancer medicine are significant, yet the risks must be carefully managed due to the possibility of increased toxicity. Although artificial intelligence applications have demonstrated notable success in predicting drug combination synergy, several key challenges persist: (1) Existing models often predict average synergy values across a restricted range of testing dosages, neglecting crucial dose amounts and the mechanisms of action of the drugs involved. (2) Many graph-based models rely on static protein-protein interactions, failing to adapt to dynamic and context-dependent networks. This limitation constrains the applicability of current methods.

Results

We introduced SAFER, a Sub-hypergraph Attention-based graph model, addressing these issues by incorporating complex relationships among biological knowledge networks and considering dosing effects on subject-specific networks. SAFER outperformed previous models on the benchmark and the independent test set. The analysis of subgraph attention weight for the lung cancer cell line highlighted JAK-STAT signaling pathway, PRDM12, ZNF781, and CDC5L that have been implicated in lung fibrosis.

Conclusions

SAFER presents an interpretable framework designed to identify drug-responsive signals. Tailored for comprehending dose effects on subject-specific molecular contexts, our model uniquely captures dose-level drug combination responses. This capability unlocks previously inaccessible avenues of investigation compared to earlier models. Finally, the SAFER framework can be leveraged by future inquiries to investigate molecular networks that uniquely characterize individual patients.

Microcephaly Gene Mcph1 Deficiency Induces p19ARF-Dependent Cell Cycle Arrest and Senescence

MCPH1 has been identified as the causal gene for primary microcephaly type 1, a neurodevelopmental disorder characterized by reduced brain size and delayed growth. As a multifunction protein, MCPH1 has been reported to repress the expression of TERT and interact with transcriptional regulator E2F1. However, it remains unclear whether MCPH1 regulates brain development through its transcriptional regulation function. This study showed that the knockout of Mcph1 in mice leads to delayed growth as early as the embryo stage E11.5. Transcriptome analysis (RNA-seq) revealed that the deletion of Mcph1 resulted in changes in the expression levels of a limited number of genes. Although the expression of some of E2F1 targets, such as Satb2 and Cdkn1c, was affected, the differentially expressed genes (DEGs) were not significantly enriched as E2F1 target genes. Further investigations showed that primary and immortalized Mcph1 knockout mouse embryonic fibroblasts (MEFs) exhibited cell cycle arrest and cellular senescence phenotype. Interestingly, the upregulation of p19ARF was detected in Mcph1 knockout MEFs, and silencing p19Arf restored the cell cycle and growth arrest to wild-type levels. Our findings suggested it is unlikely that MCPH1 regulates neurodevelopment through E2F1-mediated transcriptional regulation, and p19ARF-dependent cell cycle arrest and cellular senescence may contribute to the developmental abnormalities observed in primary microcephaly.

Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions

We report an approach for cancer phenotyping based on targeted sequencing of cell-free DNA (cfDNA) for small cell lung cancer (SCLC). In SCLC, differential activation of transcription factors (TFs), such as ASCL1, NEUROD1, POU2F3, and REST defines molecular subtypes. We designed a targeted capture panel that identifies chromatin organization signatures at 1535 TF binding sites and 13,240 gene transcription start sites and detects exonic mutations in 842 genes. Sequencing of cfDNA from SCLC patient-derived xenograft models captured TF activity and gene expression and revealed individual highly informative loci. Prediction models of ASCL1 and NEUROD1 activity using informative loci achieved areas under the receiver operating characteristic curve (AUCs) from 0.84 to 0.88 in patients with SCLC. As non-SCLC (NSCLC) often transforms to SCLC following targeted therapy, we applied our framework to distinguish NSCLC from SCLC and achieved an AUC of 0.99. Our approach shows promising utility for SCLC subtyping and transformation monitoring, with potential applicability to diverse tumor types.

Histone demethylase KDM1A promotes hepatic steatosis and inflammation by increasing chromatin accessibility in NAFLD

Nonalcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease without specific Food and Drug Administration-approved drugs. Recent advances suggest that chromatin remodeling and epigenetic alteration contribute to the development of NAFLD. The functions of the corresponding molecular modulator in NAFLD, however, are still elusive. KDM1A, commonly known as lysine-specific histone demethylase 1, has been reported to increase glucose uptake in hepatocellular carcinoma. In addition, a recent study suggests that inhibition of KDM1A reduces lipid accumulation in primary brown adipocytes. We here investigated the role of KDM1A, one of the most important histone demethylases, in NAFLD. In this study, we observed a significant upregulation of KDM1A in NAFLD mice, monkeys, and humans compared to the control group. Based on these results, we further found that the KDM1A can exacerbate lipid accumulation and inflammation in hepatocytes and mice. Mechanistically, KDM1A exerted its effects by elevating chromatin accessibility, subsequently promoting the development of NAFLD. Furthermore, the mutation of KDM1A blunted its capability to promote the development of NAFLD. In summary, our study discovered that KDM1A exacerbates hepatic steatosis and inflammation in NAFLD via increasing chromatin accessibility, further indicating the importance of harnessing chromatin remodeling and epigenetic alteration in combating NAFLD. KDM1A might be considered as a potential therapeutic target in this regard.

STAT6 mutations enriched at diffuse large B-cell lymphoma relapse reshape the tumor microenvironment

Diffuse large B-cell lymphoma (DLBCL) relapses in approximately 40% of patients following frontline therapy. We reported that STAT6D419 mutations are enriched in relapsed/refractory DLBCL (rrDLBCL) samples, suggesting that JAK/STAT signaling plays a role in therapeutic resistance. We hypothesized that STAT6D419 mutations can improve DLBCL cell survival by reprogramming the microenvironment to sustain STAT6 activation. Thus, we investigated the role of STAT6D419 mutations on DLBCL cell growth and its microenvironment. We found that phospho-STAT6D419N was retained in the nucleus longer than phospho-STAT6WT following IL-4 stimulation, and STAT6D419N recognized a more restricted DNA-consensus sequence than STAT6WT. Upon IL-4 induction, STAT6D419N expression led to a higher magnitude of gene expression changes, but in a more selective list of gene targets compared with STATWT. The most significantly expressed genes induced by STAT6D419N were those implicated in survival, proliferation, migration, and chemotaxis, in particular CCL17. This chemokine, also known as TARC, attracts helper T-cells to the tumor microenvironment, especially in Hodgkin's lymphoma. To this end, in DLBCL, phospho-STAT6+ rrDLBCL cells had a greater proportion of infiltrating CD4+ T-cells than phospho-STAT6- tumors. Our findings suggest that STAT6D419 mutations in DLBCL lead to cell autonomous changes, enhanced signaling, and altered composition of the tumor microenvironment.

A large-scale cancer-specific protein-DNA interaction network

Cancer development and progression are generally associated with dysregulation of gene expression, often resulting from changes in transcription factor (TF) sequence or expression. Identifying key TFs involved in cancer gene regulation provides a framework for potential new therapeutics. This study presents a large-scale cancer gene TF-DNA interaction network as well as an extensive promoter clone resource for future studies. Most highly connected TFs do not show a preference for binding to promoters of genes associated with either good or poor cancer prognosis, suggesting that emerging strategies aimed at shifting gene expression balance between these two prognostic groups may be inherently complex. However, we identified potential for oncogene targeted therapeutics, with half of the tested oncogenes being potentially repressed by influencing specific activator or bifunctional TFs. Finally, we investigate the role of intrinsically disordered regions within the key cancer-related TF estrogen receptor ɑ (ESR1) on DNA binding and transcriptional activity, and found that these regions can have complex trade-offs in TF function. Altogether, our study not only broadens our knowledge of TFs involved in the cancer gene regulatory network but also provides a valuable resource for future studies, laying a foundation for potential therapeutic strategies targeting TFs in cancer.

Single-Cell Transcriptome Analysis Reveals Development-Specific Networks at Distinct Synchronized Antral Follicle Sizes in Sheep Oocytes

The development of the ovarian antral follicle is a complex, highly regulated process. Oocytes orchestrate and coordinate the development of mammalian ovarian follicles, and the rate of follicular development is governed by a developmental program intrinsic to the oocyte. Characterizing oocyte signatures during this dynamic process is critical for understanding oocyte maturation and follicular development. Although the transcriptional signature of sheep oocytes matured in vitro and preovulatory oocytes have been previously described, the transcriptional changes of oocytes in antral follicles have not. Here, we used single-cell transcriptomics (SmartSeq2) to characterize sheep oocytes from small, medium, and large antral follicles. We characterized the transcriptomic landscape of sheep oocytes during antral follicle development, identifying unique features in the transcriptional atlas, stage-specific molecular signatures, oocyte-secreted factors, and transcription factor networks. Notably, we identified the specific expression of 222 genes in the LO, 8 and 6 genes that were stage-specific in the MO and SO, respectively. We also elucidated signaling pathways in each antral follicle size that may reflect oocyte quality and in vitro maturation competency. Additionally, we discovered key biological processes that drive the transition from small to large antral follicles, revealing hub genes involved in follicle recruitment and selection. Thus, our work provides a comprehensive characterization of the single-oocyte transcriptome, filling a gap in the mapping of the molecular landscape of sheep oogenesis. We also provide key insights into the transcriptional regulation of the critical sizes of antral follicular development, which is essential for understanding how the oocyte orchestrates follicular development.

MethMotif.Org 2024: a database integrating context-specific transcription factor-binding motifs with DNA methylation patterns

MethMotif (https://methmotif.org) is a publicly available database that provides a comprehensive repository of transcription factor (TF)-binding profiles, enriched with DNA methylation patterns. In this release, we have enhanced the platform, expanding our initial collection to over 700 position weight matrices (PWM), all of which include DNA methylation profiles. One of the key advancements in this release is the segregation of TF-binding motifs based on their cofactors and DNA methylation status. We have previously demonstrated that gene ontology (GO) enriched terms associated with TF target genes may differ based on their association with alternative cofactors and DNA methylation status. MethMotif provides precomputed GO annotations for each human TF of interest, as well as for TF-co-TF complexes, enabling a comprehensive analysis of TF functions in the context of their co-factors. Additionally, MethMotif has been updated to encompass data for two new species, Mus musculus and Arabidopsis thaliana, widening its applicability to a broader community. MethMotif stands out as the first and only TF-binding motifs database to incorporate context-specific PWM coupled with epigenetic information, thereby enlightening context-specific TF functions. This enhancement allows the community to explore and gain deeper insights into the regulatory mechanisms governing transcriptional processes.

Position-specific evolution in transcription factor binding sites, and a fast likelihood calculation for the F81 model

Transcription factor binding sites (TFBS), like other DNA sequence, evolve via mutation and selection relating to their function. Models of nucleotide evolution describe DNA evolution via single-nucleotide mutation. A stationary vector of such a model is the long-term distribution of nucleotides, unchanging under the model. Neutrally evolving sites may have uniform stationary vectors, but one expects that sites within a TFBS instead have stationary vectors reflective of the fitness of various nucleotides at those positions. We introduce 'position-specific stationary vectors' (PSSVs), the collection of stationary vectors at each site in a TFBS locus, analogous to the position weight matrix (PWM) commonly used to describe TFBS. We infer PSSVs for human TFs using two evolutionary models (Felsenstein 1981 and Hasegawa-Kishino-Yano 1985). We find that PSSVs reflect the nucleotide distribution from PWMs, but with reduced specificity. We infer ancestral nucleotide distributions at individual positions and calculate 'conditional PSSVs' conditioned on specific choices of majority ancestral nucleotide. We find that certain ancestral nucleotides exert a strong evolutionary pressure on neighbouring sequence while others have a negligible effect. Finally, we present a fast likelihood calculation for the F81 model on moderate-sized trees that makes this approach feasible for large-scale studies along these lines.

Specifying cellular context of transcription factor regulons for exploring context-specific gene regulation programs

Understanding the role of transcription and transcription factors in cellular identity and disease, such as cancer and autoimmunity, is essential. However, comprehensive data resources for cell line-specific transcription factor-to-target gene annotations are currently limited. To address this, we developed a straightforward method to define regulons that capture the cell-specific aspects of TF binding and transcript expression levels. By integrating cellular transcriptome and transcription factor binding data, we generated regulons for four common cell lines comprising both proximal and distal cell line-specific regulatory events. Through systematic benchmarking involving transcription factor knockout experiments, we demonstrated performance on par with state-of-the-art methods, with our method being easily applicable to other cell types of interest. We present case studies using three cancer single-cell datasets to showcase the utility of these cell-type-specific regulons in exploring transcriptional dysregulation. In summary, this study provides a valuable tool and a resource for systematically exploring cell line-specific transcriptional regulations, emphasizing the utility of network analysis in deciphering disease mechanisms.

GCparagon: evaluating and correcting GC biases in cell-free DNA at the fragment level

Analyses of cell-free DNA (cfDNA) are increasingly being employed for various diagnostic and research applications. Many technologies aim to increase resolution, e.g. for detecting early-stage cancer or minimal residual disease. However, these efforts may be confounded by inherent base composition biases of cfDNA, specifically the over - and underrepresentation of guanine (G) and cytosine (C) sequences. Currently, there is no universally applicable tool to correct these effects on sequencing read-level data. Here, we present GCparagon, a two-stage algorithm for computing and correcting GC biases in cfDNA samples. In the initial step, length and GC base count parameters are determined. Here, our algorithm minimizes the inclusion of known problematic genomic regions, such as low-mappability regions, in its calculations. In the second step, GCparagon computes weights counterbalancing the distortion of cfDNA attributes (correction matrix). These fragment weights are added to a binary alignment map (BAM) file as alignment tags for individual reads. The GC correction matrix or the tagged BAM file can be used for downstream analyses. Parallel computing allows for a GC bias estimation below 1 min. We demonstrate that GCparagon vastly improves the analysis of regulatory regions, which frequently show specific GC composition patterns and will contribute to standardized cfDNA applications.

Open MoA: revealing the mechanism of action (MoA) based on network topology and hierarchy

MOTIVATION

Many approaches in systems biology have been applied in drug repositioning due to the increased availability of the omics data and computational biology tools. Using a multi-omics integrated network, which contains information of various biological interactions, could offer a more comprehensive inspective and interpretation for the drug mechanism of action (MoA).

RESULTS

We developed a computational pipeline for dissecting the hidden MoAs of drugs (Open MoA). Our pipeline computes confidence scores to edges that represent connections between genes/proteins in the integrated network. The interactions showing the highest confidence score could indicate potential drug targets and infer the underlying molecular MoAs. Open MoA was also validated by testing some well-established targets. Additionally, we applied Open MoA to reveal the MoA of a repositioned drug (JNK-IN-5A) that modulates the PKLR expression in HepG2 cells and found STAT1 is the key transcription factor. Overall, Open MoA represents a first-generation tool that could be utilized for predicting the potential MoA of repurposed drugs and dissecting de novo targets for developing effective treatments.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/XinmengLiao/Open_MoA.

Gene signature reveals decreased SOX10-dependent transcripts in malignant cells from immune checkpoint inhibitor-resistant cutaneous melanomas

Evidence is mounting for cross-resistance between immune checkpoint and targeted kinase inhibitor therapies in cutaneous melanoma patients. Since the loss of the transcription factor, SOX10, causes tolerance to MAPK pathway inhibitors, we used bioinformatic techniques to determine if reduced SOX10 expression/activity is associated with immune checkpoint inhibitor resistance. We integrated SOX10 ChIP-seq, knockout RNA-seq, and knockdown ATAC-seq data from melanoma cell models to develop a robust SOX10 gene signature. We used computational methods to validate this signature as a measure of SOX10-dependent activity in independent single-cell and bulk RNA-seq SOX10 knockdown, cell line panel, and MAPK inhibitor drug-resistant datasets. Evaluation of patient single-cell RNA-seq data revealed lower levels of SOX10-dependent transcripts in immune checkpoint inhibitor-resistant tumors. Our results suggest that SOX10-deficient melanoma cells are associated with cross-resistance between targeted and immune checkpoint inhibitors and highlight the need to identify therapeutic strategies that target this subpopulation.

Ancistrocladinium A Induces Apoptosis in Proteasome Inhibitor-Resistant Multiple Myeloma Cells: A Promising Therapeutic Agent Candidate

The N,C-coupled naphthylisoquinoline alkaloid ancistrocladinium A belongs to a novel class of natural products with potent antiprotozoal activity. Its effects on tumor cells, however, have not yet been explored. We demonstrate the antitumor activity of ancistrocladinium A in multiple myeloma (MM), a yet incurable blood cancer that represents a model disease for adaptation to proteotoxic stress. Viability assays showed a potent apoptosis-inducing effect of ancistrocladinium A in MM cell lines, including those with proteasome inhibitor (PI) resistance, and in primary MM cells, but not in non-malignant blood cells. Concomitant treatment with the PI carfilzomib or the histone deacetylase inhibitor panobinostat strongly enhanced the ancistrocladinium A-induced apoptosis. Mass spectrometry with biotinylated ancistrocladinium A revealed significant enrichment of RNA-splicing-associated proteins. Affected RNA-splicing-associated pathways included genes involved in proteotoxic stress response, such as PSMB5-associated genes and the heat shock proteins HSP90 and HSP70. Furthermore, we found strong induction of ATF4 and the ATM/H2AX pathway, both of which are critically involved in the integrated cellular response following proteotoxic and oxidative stress. Taken together, our data indicate that ancistrocladinium A targets cellular stress regulation in MM and improves the therapeutic response to PIs or overcomes PI resistance, and thus may represent a promising potential therapeutic agent.

Genome-wide association studies and fine-mapping identify genomic loci for n-3 and n-6 polyunsaturated fatty acids in Hispanic American and African American cohorts

Omega-3 (n-3) and omega-6 (n-6) polyunsaturated fatty acids (PUFAs) play critical roles in human health. Prior genome-wide association studies (GWAS) of n-3 and n-6 PUFAs in European Americans from the CHARGE Consortium have documented strong genetic signals in/near the FADS locus on chromosome 11. We performed a GWAS of four n-3 and four n-6 PUFAs in Hispanic American (n = 1454) and African American (n = 2278) participants from three CHARGE cohorts. Applying a genome-wide significance threshold of P < 5 × 10-8, we confirmed association of the FADS signal and found evidence of two additional signals (in DAGLA and BEST1) within 200 kb of the originally reported FADS signal. Outside of the FADS region, we identified novel signals for arachidonic acid (AA) in Hispanic Americans located in/near genes including TMX2, SLC29A2, ANKRD13D and POLD4, and spanning a > 9 Mb region on chromosome 11 (57.5 Mb ~ 67.1 Mb). Among these novel signals, we found associations unique to Hispanic Americans, including rs28364240, a POLD4 missense variant for AA that is common in CHARGE Hispanic Americans but absent in other race/ancestry groups. Our study sheds light on the genetics of PUFAs and the value of investigating complex trait genetics across diverse ancestry populations.

Dynamic DNA 5-hydroxylmethylcytosine and RNA 5-methycytosine Reprogramming During Early Human Development

After implantation, complex and highly specialized molecular events render functionally distinct organ formation, whereas how the epigenome shapes organ-specific development remains to be fully elucidated. Here, nano-hmC-Seal, RNA bisulfite sequencing (RNA-BisSeq), and RNA sequencing (RNA-Seq) were performed, and the first multilayer landscapes of DNA 5-hydroxymethylcytosine (5hmC) and RNA 5-methylcytosine (m5C) epigenomes were obtained in the heart, kidney, liver, and lung of the human foetuses at 13-28 weeks with 123 samples in total. We identified 70,091 and 503 organ- and stage-specific differentially hydroxymethylated regions (DhMRs) and m5C-modified mRNAs, respectively. The key transcription factors (TFs), T-box transcription factor 20 (TBX20), paired box 8 (PAX8), krueppel-like factor 1 (KLF1), transcription factor 21 (TCF21), and CCAAT enhancer binding protein beta (CEBPB), specifically contribute to the formation of distinct organs at different stages. Additionally, 5hmC-enriched Alu elements may participate in the regulation of expression of TF-targeted genes. Our integrated studies reveal a putative essential link between DNA modification and RNA methylation, and illustrate the epigenetic maps during human foetal organogenesis, which provide a foundation for for an in-depth understanding of the epigenetic mechanisms underlying early development and birth defects.

Integrating massive RNA-seq data to elucidate transcriptome dynamics in Drosophila melanogaster

The volume of ribonucleic acid (RNA)-seq data has increased exponentially, providing numerous new insights into various biological processes. However, due to significant practical challenges, such as data heterogeneity, it is still difficult to ensure the quality of these data when integrated. Although some quality control methods have been developed, sample consistency is rarely considered and these methods are susceptible to artificial factors. Here, we developed MassiveQC, an unsupervised machine learning-based approach, to automatically download and filter large-scale high-throughput data. In addition to the read quality used in other tools, MassiveQC also uses the alignment and expression quality as model features. Meanwhile, it is user-friendly since the cutoff is generated from self-reporting and is applicable to multimodal data. To explore its value, we applied MassiveQC to Drosophila RNA-seq data and generated a comprehensive transcriptome atlas across 28 tissues from embryogenesis to adulthood. We systematically characterized fly gene expression dynamics and found that genes with high expression dynamics were likely to be evolutionarily young and expressed at late developmental stages, exhibiting high nonsynonymous substitution rates and low phenotypic severity, and they were involved in simple regulatory programs. We also discovered that human and Drosophila had strong positive correlations in gene expression in orthologous organs, revealing the great potential of the Drosophila system for studying human development and disease.

A renal YY1-KIM1-DR5 axis regulates the progression of acute kidney injury

Acute kidney injury (AKI) exhibits high morbidity and mortality. Kidney injury molecule-1 (KIM1) is dramatically upregulated in renal tubules upon injury, and acts as a biomarker for various renal diseases. However, the exact role and underlying mechanism of KIM1 in the progression of AKI remain elusive. Herein, we report that renal tubular specific knockout of Kim1 attenuates cisplatin- or ischemia/reperfusion-induced AKI in male mice. Mechanistically, transcription factor Yin Yang 1 (YY1), which is downregulated upon AKI, binds to the promoter of KIM1 and represses its expression. Injury-induced KIM1 binds to the ECD domain of death receptor 5 (DR5), which activates DR5 and the following caspase cascade by promoting its multimerization, thus induces renal cell apoptosis and exacerbates AKI. Blocking the KIM1-DR5 interaction with rationally designed peptides exhibit reno-protective effects against AKI. Here, we reveal a YY1-KIM1-DR5 axis in the progression of AKI, which warrants future exploration as therapeutic targets.

LINC01137/miR-186-5p/WWOX: a novel axis identified from WWOX-related RNA interactome in bladder cancer

Introduction: The discovery of non-coding RNA (ncRNA) dates back to the pre-genomics era, but the progress in this field is still dynamic and leverages current post-genomics solutions. WWOX is a global gene expression modulator that is scarcely investigated for its role in regulating cancer-related ncRNAs. In bladder cancer (BLCA), the link between WWOX and ncRNA remains unexplored. The description of AP-2α and AP-2γ transcription factors, known as WWOX-interacting proteins, is more commonplace regarding ncRNA but still merits investigation. Therefore, this in vitro and in silico study aimed to construct an ncRNA-containing network with WWOX/AP-2 and to investigate the most relevant observation in the context of BLCA cell lines and patients. Methods: RT-112, HT-1376, and CAL-29 cell lines were subjected to two stable lentiviral transductions. High-throughput sequencing of cellular variants (deposited in the Gene Expression Omnibus database under the GSE193659 record) enabled the investigation of WWOX/AP-2-dependent differences using various bioinformatics tools (e.g., limma-voom, FactoMineR, multiple Support Vector Machine Recursive Feature Elimination (mSVM-RFE), miRDB, Arena-Idb, ncFANs, RNAhybrid, TargetScan, Protein Annotation Through Evolutionary Relationships (PANTHER), Gene Transcription Regulation Database (GTRD), or Evaluate Cutpoints) and repositories such as The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia. The most relevant observations from cap analysis gene expression sequencing (CAGE-seq) were confirmed using real-time PCR, whereas TCGA data were validated using the GSE31684 cohort. Results: The first stage of the whole study justified focusing solely on WWOX rather than on WWOX combined with AP-2α/γ. The most relevant observation of the developed ncRNA-containing network was LINC01137, i.e., long non-coding RNAs (lncRNAs) that unraveled the core network containing UPF1, ZC3H12A, LINC01137, WWOX, and miR-186-5p, the last three being a novel lncRNA/miRNA/mRNA axis. Patients' data confirmed the LINC01137/miR-186-5p/WWOX relationship and provided a set of dependent genes (i.e., KRT18, HES1, VCP, FTH1, IFITM3, RAB34, and CLU). Together with the core network, the gene set was subjected to survival analysis for both TCGA-BLCA and GSE31684 patients, which indicated that the increased expression of WWOX or LINC01137 is favorable, similar to their combination with each other (WWOX↑ and LINC01137↑) or with MIR186 (WWOX↑/LINC01137↑ but MIR186↓). Conclusion: WWOX is implicated in the positive feedback loop with LINC01137 that sponges WWOX-targeting miR-186-5p. This novel WWOX-containing lncRNA/miRNA/mRNA axis should be further investigated to depict its relationships in a broader context, which could contribute to BLCA research and treatment.

A natural variation-based screen in mouse cells reveals USF2 as a regulator of the DNA damage response and cellular senescence

Cellular senescence is a program of cell cycle arrest, apoptosis resistance, and cytokine release induced by stress exposure in metazoan cells. Landmark studies in laboratory mice have characterized a number of master senescence regulators, including p16INK4a, p21, NF-κB, p53, and C/EBPβ. To discover other molecular players in senescence, we developed a screening approach to harness the evolutionary divergence between mouse species. We found that primary cells from the Mediterranean mouse Mus spretus, when treated with DNA damage to induce senescence, produced less cytokine and had less-active lysosomes than cells from laboratory Mus musculus. We used allele-specific expression profiling to catalog senescence-dependent cis-regulatory variation between the species at thousands of genes. We then tested for correlation between these expression changes and interspecies sequence variants in the binding sites of transcription factors. Among the emergent candidate senescence regulators, we chose a little-studied cell cycle factor, upstream stimulatory factor 2 (USF2), for molecular validation. In acute irradiation experiments, cells lacking USF2 had compromised DNA damage repair and response. Longer-term senescent cultures without USF2 mounted an exaggerated senescence regulatory program-shutting down cell cycle and DNA repair pathways, and turning up cytokine expression, more avidly than wild-type. We interpret these findings under a model of pro-repair, anti-senescence regulatory function by USF2. Our study affords new insights into the mechanisms by which cells commit to senescence, and serves as a validated proof of concept for natural variation-based regulator screens.

EGFR + lung adenocarcinomas coopt alveolar macrophage metabolism and function to support EGFR signaling and growth

The limited efficacy of currently approved immunotherapies in EGFR-mutant lung adenocarcinoma (LUAD) underscores the need to better understand mechanisms governing local immunosuppression. Elevated surfactant and GM-CSF secretion from the transformed epithelium induces tumor-associated alveolar macrophages (TA-AM) to proliferate and support tumor growth by rewiring inflammatory functions and lipid metabolism. TA-AM properties are driven by increased GM-CSF-PPARγ signaling and inhibition of airway GM-CSF or PPARγ in TA-AMs suppresses cholesterol efflux to tumor cells, which impairs EGFR phosphorylation and restrains LUAD progression. In the absence of TA-AM metabolic support, LUAD cells compensate by increasing cholesterol synthesis, and blocking PPARγ in TA-AMs simultaneous with statin therapy further suppresses tumor progression and increases T cell effector functions. These results reveal new therapeutic combinations for immunotherapy resistant EGFR-mutant LUADs and demonstrate how such cancer cells can metabolically co-opt TA-AMs through GM-CSF-PPARγ signaling to provide nutrients that promote oncogenic signaling and growth.

Nucleosome Patterns in Circulating Tumor DNA Reveal Transcriptional Regulation of Advanced Prostate Cancer Phenotypes

Advanced prostate cancers comprise distinct phenotypes, but tumor classification remains clinically challenging. Here, we harnessed circulating tumor DNA (ctDNA) to study tumor phenotypes by ascertaining nucleosome positioning patterns associated with transcription regulation. We sequenced plasma ctDNA whole genomes from patient-derived xenografts representing a spectrum of androgen receptor active (ARPC) and neuroendocrine (NEPC) prostate cancers. Nucleosome patterns associated with transcriptional activity were reflected in ctDNA at regions of genes, promoters, histone modifications, transcription factor binding, and accessible chromatin. We identified the activity of key phenotype-defining transcriptional regulators from ctDNA, including AR, ASCL1, HOXB13, HNF4G, and GATA2. To distinguish NEPC and ARPC in patient plasma samples, we developed prediction models that achieved accuracies of 97% for dominant phenotypes and 87% for mixed clinical phenotypes. Although phenotype classification is typically assessed by IHC or transcriptome profiling from tumor biopsies, we demonstrate that ctDNA provides comparable results with diagnostic advantages for precision oncology.

SIGNIFICANCE

This study provides insights into the dynamics of nucleosome positioning and gene regulation associated with cancer phenotypes that can be ascertained from ctDNA. New methods for classification in phenotype mixtures extend the utility of ctDNA beyond assessments of somatic DNA alterations with important implications for molecular classification and precision oncology. This article is highlighted in the In This Issue feature, p. 517.

ESCCdb: A Comprehensive Database and Key Regulator Exploring Platform Based on Cross Dataset Comparisons for Esophageal Squamous Cell Carcinoma

Esophageal cancer is the seventh most prevalent and the sixth most lethal cancer. Esophageal squamous cell carcinoma (ESCC) is one of the major esophageal cancer subtypes that accounts for 87 % of the total cases. However, its molecular mechanism remains unclear. Here, we present an integrated database for ESCC called ESCCdb, which includes a total of 56 datasets and published studies from the GEO, Xena or SRA databases and related publications. It helps users to explore a particular gene with multiple graphical and interactive views with one click. The results comprise expression changes across 20 datasets, copy number alterations in 11 datasets, somatic mutations from 12 papers, related drugs derived from DGIdb, related pathways, and gene correlations. ESCCdb enables directly cross-dataset comparison of a gene's mutations, expressions and copy number changes in multiple datasets. This allows users to easily assess the alterations in ESCC. Furthermore, survival analysis, drug-gene relationships, and results from whole-genome CRISPR/Cas9 screening can help users determine the clinical relevance, derive functional inferences, and identify potential drugs. Notably, ESCCdb also enables the exploration of the correlation structure and identification of potential key regulators for a process. Finally, we identified 789 consistently differential expressed genes; we summarized recurrently mutated genes and genes affected by significant copy number alterations. These genes may be stable biomarkers or important players during ESCC development. ESCCdb fills the gap between massive omics data and users' needs for integrated analysis and can promote basic and clinical ESCC research. The database is freely accessible at http://cailab.labshare.cn/ESCCdb.

FT-6876, a Potent and Selective Inhibitor of CBP/p300, is Active in Preclinical Models of Androgen Receptor-Positive Breast Cancer

BACKGROUND

Patients with triple-negative breast cancer (TNBC) expressing the androgen receptor (AR) respond poorly to neoadjuvant chemotherapy, although AR antagonists have shown promising clinical activity, suggesting these tumors are AR-dependent. cAMP responsive element binding protein (CREB)-binding protein (CBP) and p300 are transcriptional co-activators for the AR, a key driver of AR+ breast and prostate cancer, and may provide a novel therapeutic target in AR+ TNBC.

OBJECTIVES

The aim of this study was to determine the therapeutic potential of FT-6876, a new CBP/p300 bromodomain inhibitor, in breast cancer models with a range of AR levels in vitro and in vivo.

METHODS

Effects of FT-6876 on the CBP/p300 pathway were determined by combining chromatin immunoprecipitation (ChIP) with precision run-on sequencing (PRO-seq) complemented with H3K27 acetylation (Ac) and transcriptional profiling. The antiproliferative effect of FT-6876 was also measured in vitro and in vivo.

RESULTS

We describe the discovery of FT-6876, a potent and selective CBP/p300 bromodomain inhibitor. The combination of ChIP and PRO-seq confirmed the reduction in H3K27Ac at specific promoter sites concurrent with a decrease in CBP/p300 on the chromatin and a reduction in nascent RNA and enhancer RNA. This was associated with a time- and concentration-dependent reduction in H3K37Ac associated with a decrease in AR and estrogen receptor (ER) target gene expression. This led to a time-dependent growth inhibition in AR+ models, correlated with AR expression. Tumor growth inhibition was also observed in AR+ tumor models of TNBC and ER+ breast cancer subtypes with consistent pharmacokinetics and pharmacodynamics.

CONCLUSION

Our findings demonstrate FT-6876 as a promising new CBP/p300 bromodomain inhibitor, with efficacy in preclinical models of AR+ breast cancer.

Expression Profiles of Long Noncoding RNAs and Messenger RNAs in a Rat Model of Spinal Cord Injury

Spinal cord injury (SCI) is a serious disorder of the central nervous system with a high disability rate. Long noncoding RNAs (lncRNAs) are reported to mediate many biological processes. The aim of this study was to explore lncRNA and mRNA expression profiles and functional networks after SCI. Differentially expressed genes between SCI model rats and sham controls were identified by microarray assays and analyzed by functional enrichment. Key lncRNAs were identified using a support vector machine- (SVM-) recursive feature elimination (RFE) algorithm. A trans and cis regulation model was used to analyze the regulatory relationships between lncRNAs and their targets. An lncRNA-related ceRNA network was established. We identified 5465 differentially expressed lncRNAs (DE lncRNAs) and 8366 differentially expressed mRNAs (DE mRNAs) in the SCI group compared with the sham group (fold change > 2.0, p < 0.05). Four genes were confirmed by qRT-PCR which were consistent with the microarray data. GSEA analysis showed that most marked changes occurred in pathways related to immune inflammation and nerve cell function, including cytokine-cytokine receptor interaction, neuroactive ligand-receptor interaction, and GABAergic synapse. Enrichment analysis identified 30 signaling pathways, including those associated with immune inflammation response. A total of 40 key lncRNAs were identified using the SVM-RFE algorithm. A key lncRNA-mRNAs coexpression network was generated for 230 951 lncRNA-mRNA pairs with half showing positive correlations. Several key DE lncRNAs were predicted to have "cis"- or "trans"-regulated target genes. The transcription factors, Sp1, JUN, and SOX10, may regulate the interaction between XR_001837123.1 and ETS 1. In addition, five pairs of ceRNA regulatory sequences were constructed. Many mRNAs and lncRNAs were found to be dysregulated after SCI. Bioinformatic analysis showed that DE lncRNAs may play crucial roles in SCI. It is anticipated that these findings will provide new insights into the underlying mechanisms and potential therapeutic targets for SCI.

A novel, conserved and possibly functional motif "WHWGHTW" in mitochondrial transcription across Bilateria

The animal mitogenomes which undergone a reductive evolution has an obvious loss of coding capacity compared to their known closest relatives, but it has not yet been fully investigated why and how the intergenic regions do not encode protein and have no known functions, are stably maintained, replicated, and transmitted by the genome. These relatively small intergenic regions may not be under neutral evolution and they may have functional and/or regulatory roles that have yet to be identified. Here, the distribution pattern, sequence content and location of a novel sequence motif of 'WWWGHTW' were bioinformatically investigated and characterised by constructing a sampling mitogenome dataset of 1889 species from 14 phyla representing the clade of Bilateria. This motif is reverse complementary of the previously described DmTTF binding sequence and found in the nd4L- (X) -trnT gene cluster. This cluster commonly exhibits a strand displacement region and an intergenic region among the bilaterian superphylums, particularly in Ecdysozoa. This motif may be accepted as a substrate providing binding sites for the specific interaction with transcription factors because of (i) its reverse complementarity of previously described DmTTF binding sequence, and (ii) the possession of G and T nucleotides in the fourth and sixth positions, (iii) the bias on T and G nucleotides instead of C and A in the degenerated positions. This suggestion is also supported by the presence of a strand displacement region in the nd4L- (X) -trnT gene cluster, particularly in Ecdysozoa consisting of the most rearranged mitogenomes among the bilaterian superphylums.

CISD1 Is a Breast Cancer Prognostic Biomarker Associated with Diabetes Mellitus

Women with diabetes mellitus are believed to have increased risk of developing breast cancer and lower life expectancies. This study aims to depict the association between the CISD1, the co-expressed genes, and diabetes mellitus to offer potential therapeutic targets for further mechanical research. The TCGA-BRCA RNAseq data is acquired. All the data and analyzed using R packages and web-based bioinformatics tools. CISD1 gene expression was evaluated between tumor bulk and adjacent tissue. Immune cell infiltration evaluation was performed. CISD1 expressed significantly higher in tumor tissue than that of the normal tissue, indicating poor overall survival rates. High expression level of CISD1 in tumor shows less pDC and NK cells penetration. There are 138 genes shared between CISD1 co-expressed gene pool in BRCA and diabetes mellitus related genes using "diabetes" as the term for text mining. These shared genes enrich in "cell cycle" and other pathways. MCODE analysis demonstrates that p53-independent G1/S DNA damage checkpoint, p53-independent DNA damage response, and ubiquitin mediated degradation of phosphorylated cdc25A are top-ranked than other terms. CISD1 and co-expressed genes, especially shared ones with diabetes mellitus, can be the focused genes considered when addressing clinical problems in breast cancer with a diabetes mellitus background.

Age- and Stage-Dependent Prostate Cancer Aggressiveness Associated with Differential Notch Signaling

Prostate cancer (PC) remains a worldwide challenge, as does the question of how to distinguish its indolent from its aggressive form to reconcile proper management of the disease with age-related life expectations. This study aimed to differentiate the Notch-driven course of PC regarding patients’ ages and stage of their disease. We analyzed 397 PC samples split into age subgroups of ≦55, 60−70, and >70 years old, as well as early vs. late stage. The clinical association of Notch signaling was evaluated by DFS and UpSet analyses. The clustering of downstream effectors was performed with ExpressCluster. Finally, for the most relevant findings, functional networks were constructed with MCODE and stringApp. The results have been validated with an independent cohort. We identified specific patterns of Notch expression associated with unfavorable outcomes, which were reflected by entering into a hybrid epithelial/mesenchymal state and thus reaching tumor plasticity with its all consequences. We characterized the molecular determinants of the age-related clinical behavior of prostate tumors that stem from different invasive properties depending on the route of the EMT program. Of the utmost relevance is the discovery of age- and stage-specific combinations of the Notch molecules predicting unfavorable outcomes and constituting a new prognostic and therapeutic approach for PCs.

Evolutionary analysis of endogenous intronic retroviruses in primates reveals an enrichment in transcription binding sites associated with key regulatory processes

Background

Endogenous retroviruses (ERVs) are the result of the integration of retroviruses into host DNA following germline infection. Endogenous retroviruses are made up of three main genes: gag, pol, and env, each of which encodes viral proteins that can be conserved or not. ERVs have been observed in a wide range of vertebrate genomes and their functions are associated with viral silencing and gene regulation.

Results

In this work, we studied the evolutionary history of endogenous retroviruses associated with five human genes (INPP5B, DET1, PSMA1, USH2A, and MACROD2), which are located within intron sections. To verify the retroviral origin of the candidates, several approaches were used to detect and locate ERV elements. Both orthologous and paralogous genes were identified by Ensembl and then analyzed for ERV presence using RetroTector. A phylogenetic tree was reconstructed to identify the minimum time point of ERV acquisition. From that search, we detected ERVs throughout the primate lineage and in some other groups. Also, we identified the minimum origin of the ERVs from the parvorder Catarrhini to the Homininae subfamily.

Conclusions

With the data collected, and by observing the transcription factors annotated inside ERVs, we propose that these elements play a relevant role in gene expression regulation and they probably possess important features for tumorigenesis control.

A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA

Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we develop Griffin, a framework for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing data. Griffin employs a GC correction procedure tailored to variable cfDNA fragment sizes, which generates a better representation of chromatin accessibility and improves the accuracy of cancer detection and tumor subtype classification. We demonstrate estrogen receptor subtyping from cfDNA in metastatic breast cancer. We predict estrogen receptor subtype in 139 patients with at least 5% detectable circulating tumor DNA with an area under the receive operator characteristic curve (AUC) of 0.89 and validate performance in independent cohorts (AUC = 0.96). In summary, Griffin is a framework for accurate tumor subtyping and can be generalizable to other cancer types for precision oncology applications.

Lineage-specific rearrangement of chromatin loops and epigenomic features during adipocytes and osteoblasts commitment

Human mesenchymal stem cells (hMSCs) can be differentiated into adipocytes and osteoblasts. The processes are driven by the rewiring of chromatin architectures and transcriptomic/epigenomic changes. Here, we induced hMSCs to adipogenic and osteogenic differentiation, and performed 2 kb resolution Hi-C experiments for chromatin loops detection. We also generated matched RNA-seq, ChIP-seq and ATAC-seq data for integrative analysis. After comprehensively comparing adipogenesis and osteogenesis, we quantitatively identified lineage-specific loops and screened out lineage-specific enhancers and open chromatin. We reveal that lineage-specific loops can activate gene expression and facilitate cell commitment through combining enhancers and accessible chromatin in a lineage-specific manner. We finally proposed loop-mediated regulatory networks and identified the controlling factors for adipocytes and osteoblasts determination. Functional experiments validated the lineage-specific regulation networks towards IRS2 and RUNX2 that are associated with adipogenesis and osteogenesis, respectively. These results are expected to help better understand the chromatin conformation determinants of hMSCs fate commitment.

T3 and glucose increase expression of phosphoenolpyruvate carboxykinase (PCK1) leading to increased β-cell proliferation

OBJECTIVES

Thyroid hormone (T3) and high glucose concentrations are critical components of β-cell maturation and function. In the present study, we asked whether T3 and glucose signaling pathways coordinately regulate transcription of genes important for β-cell function and proliferation.

METHODS

RNA-seq analysis was performed on cadaveric human islets from five different donors in response to low and high glucose concentrations and in the presence or absence of T3. Gene expression was also studies in sorted human β-cells, mouse islets and Ins-1 cells by RT-qPCR. Silencing of the thyroid hormone receptors (THR) was conducted using lentiviruses. Proliferation was assessed by ki67 immunostaining in primary human/mouse islets. Chromatin immunoprecipitation and proximity ligation assay were preformed to validate interactions of ChREBP and THR.

RESULTS

We found glucose-mediated expression of carbohydrate response element binding protein alpha and beta (ChREBPα and ChREBPβ) mRNAs and their target genes are highly dependent on T3 concentrations in rodent and human β-cells. In β-cells, T3 and glucose coordinately regulate the expression of ChREBPβ and PCK1 (phosphoenolpyruvate carboxykinase-1) among other important genes for β-cell maturation. Additionally, we show the thyroid hormone receptor (THR) and ChREBP interact, and their relative response elements are located near to each other on mutually responsive genes. In FACS-sorted adult human β-cells, we found that high concentrations of glucose and T3 induced the expression of PCK1. Next, we show that overexpression of Pck1 together with dimethyl malate (DMM), a substrate precursor, significantly increased β-cell proliferation in human islets. Finally, using a Cre-Lox approach, we demonstrated that ChREBPβ contributes to Pck1-dependent β-cell proliferation in mouse β-cells.

CONCLUSIONS

We conclude that T3 and glucose act together to regulate ChREBPβ, leading to increased expression and activity of Pck1, and ultimately increased β-cell proliferation.

Aging is associated with a systemic length-associated transcriptome imbalance

Aging is among the most important risk factors for morbidity and mortality. To contribute toward a molecular understanding of aging, we analyzed age-resolved transcriptomic data from multiple studies. Here, we show that transcript length alone explains most transcriptional changes observed with aging in mice and humans. We present three lines of evidence supporting the biological importance of the uncovered transcriptome imbalance. First, in vertebrates the length association primarily displays a lower relative abundance of long transcripts in aging. Second, eight antiaging interventions of the Interventions Testing Program of the National Institute on Aging can counter this length association. Third, we find that in humans and mice the genes with the longest transcripts enrich for genes reported to extend lifespan, whereas those with the shortest transcripts enrich for genes reported to shorten lifespan. Our study opens fundamental questions on aging and the organization of transcriptomes.

Evolution and function of developmentally dynamic pseudogenes in mammals

BACKGROUND

Pseudogenes are excellent markers for genome evolution, which are emerging as crucial regulators of development and disease, especially cancer. However, systematic functional characterization and evolution of pseudogenes remain largely unexplored.

RESULTS

To systematically characterize pseudogenes, we date the origin of human and mouse pseudogenes across vertebrates and observe a burst of pseudogene gain in these two lineages. Based on a hybrid sequencing dataset combining full-length PacBio sequencing, sample-matched Illumina sequencing, and public time-course transcriptome data, we observe that abundant mammalian pseudogenes could be transcribed, which contribute to the establishment of organ identity. Our analyses reveal that developmentally dynamic pseudogenes are evolutionarily conserved and show an increasing weight during development. Besides, they are involved in complex transcriptional and post-transcriptional modulation, exhibiting the signatures of functional enrichment. Coding potential evaluation suggests that 19% of human pseudogenes could be translated, thus serving as a new way for protein innovation. Moreover, pseudogenes carry disease-associated SNPs and conduce to cancer transcriptome perturbation.

CONCLUSIONS

Our discovery reveals an unexpectedly high abundance of mammalian pseudogenes that can be transcribed and translated, and these pseudogenes represent a novel regulatory layer. Our study also prioritizes developmentally dynamic pseudogenes with signatures of functional enrichment and provides a hybrid sequencing dataset for further unraveling their biological mechanisms in organ development and carcinogenesis in the future.

Transcriptional targets of senataxin and E2 promoter binding factors are associated with neuro-degenerative pathways during increased autophagic flux

Autophagy is an intracellular recycling process that degrades harmful molecules and enables survival during starvation, with implications for diseases including dementia, cancer and atherosclerosis. Previous studies demonstrate how a limited number of transcription factors (TFs) can increase autophagy. However, this knowledge has not resulted in translation into therapy, thus, to gain understanding of more suitable targets, we utilized a systems biology approach. We induced autophagy by amino acid starvation and mTOR inhibition in HeLa, HEK 293 and SH-SY5Y cells and measured temporal gene expression using RNA-seq. We observed 456 differentially expressed genes due to starvation and 285 genes due to mTOR inhibition (P_FDR < 0.05 in every cell line). Pathway analyses implicated Alzheimer's and Parkinson's diseases (P_FDR ≤ 0.024 in SH-SY5Y and HeLa) and amyotrophic lateral sclerosis (ALS, P_FDR < 0.05 in mTOR inhibition experiments). Differential expression of the Senataxin (SETX) target gene set was predicted to activate multiple neurodegenerative pathways (P_FDR ≤ 0.04). In the SH-SY5Y cells of neuronal origin, the E2F transcription family was predicted to activate Alzheimer's disease pathway (P_FDR ≤ 0.0065). These exploratory analyses suggest that SETX and E2F may mediate transcriptional regulation of autophagy and further investigations into their possible role in neuro-degeneration are warranted.

Graph attention network for link prediction of gene regulations from single-cell RNA-sequencing data

MOTIVATION

Single-cell RNA sequencing (scRNA-seq) data provides unprecedented opportunities to reconstruct gene regulatory networks (GRNs) at fine-grained resolution. Numerous unsupervised or self-supervised models have been proposed to infer GRN from bulk RNA-seq data, but few of them are appropriate for scRNA-seq data under the circumstance of low signal-to-noise ratio and dropout. Fortunately, the surging of TF-DNA binding data (e.g. ChIP-seq) makes supervised GRN inference possible. We regard supervised GRN inference as a graph-based link prediction problem that expects to learn gene low-dimensional vectorized representations to predict potential regulatory interactions.

RESULTS

In this paper, we present GENELink to infer latent interactions between transcription factors (TFs) and target genes in GRN using graph attention network. GENELink projects the single-cell gene expression with observed TF-gene pairs to a low-dimensional space. Then, the specific gene representations are learned to serve for downstream similarity measurement or causal inference of pairwise genes by optimizing the embedding space. Compared to eight existing GRN reconstruction methods, GENELink achieves comparable or better performance on seven scRNA-seq datasets with four types of ground-truth networks. We further apply GENELink on scRNA-seq of human breast cancer metastasis and reveal regulatory heterogeneity of Notch and Wnt signalling pathways between primary tumour and lung metastasis. Moreover, the ontology enrichment results of unique lung metastasis GRN indicate that mitochondrial oxidative phosphorylation (OXPHOS) is functionally important during the seeding step of the cancer metastatic cascade, which is validated by pharmacological assays.

AVAILABILITY AND IMPLEMENTATION

The code and data are available at https://github.com/zpliulab/GENELink.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RUNX1/CEBPA Mutation in Acute Myeloid Leukemia Promotes Hypermethylation and Indicates for Demethylation Therapy

Acute myeloid leukemia (AML) is a rapidly progressing heterogeneous disease with a high mortality rate, which is characterized by hyperproliferation of atypical immature myeloid cells. The number of AML patients is expected to increase in the near future, due to the old-age-associated nature of AML and increased longevity in the human population. RUNX1 and CEBPA, key transcription factors (TFs) of hematopoiesis, are frequently and independently mutated in AML. RUNX1 and CEBPA can bind TET2 demethylase and attract it to their binding sites (TFBS) in cell lines, leading to DNA demethylation of the regions nearby. Since TET2 does not have a DNA-binding domain, TFs are crucial for its guidance to target genomic locations. In this paper, we show that RUNX1 and CEBPA mutations in AML patients affect the methylation of important regulatory sites that resulted in the silencing of several RUNX1 and CEBPA target genes, most likely in a TET2-dependent manner. We demonstrated that hypermethylation of TFBS in AML cells with RUNX1 mutations was associated with resistance to anticancer chemotherapy. Demethylation therapy restored expression of the RUNX1 target gene, BIK, and increased sensitivity of AML cells to chemotherapy. If our results are confirmed, mutations in RUNX1 could be an indication for prescribing the combination of cytotoxic and demethylation therapies.

TFLink: an integrated gateway to access transcription factor-target gene interactions for multiple species

Analysis of transcriptional regulatory interactions and their comparisons across multiple species are crucial for progress in various fields in biology, from functional genomics to the evolution of signal transduction pathways. However, despite the rapidly growing body of data on regulatory interactions in several eukaryotes, no databases exist to provide curated high-quality information on transcription factor-target gene interactions for multiple species. Here, we address this gap by introducing the TFLink gateway, which uniquely provides experimentally explored and highly accurate information on transcription factor-target gene interactions (∼12 million), nucleotide sequences and genomic locations of transcription factor binding sites (∼9 million) for human and six model organisms: mouse, rat, zebrafish, fruit fly, worm and yeast by integrating 10 resources. TFLink provides user-friendly access to data on transcription factor-target gene interactions, interactive network visualizations and transcription factor binding sites, with cross-links to several other databases. Besides containing accurate information on transcription factors, with a clear labelling of the type/volume of the experiments (small-scale or high-throughput), the source database and the original publications, TFLink also provides a wealth of standardized regulatory data available for download in multiple formats. The database offers easy access to high-quality data for wet-lab researchers, supplies data for gene set enrichment analyses and facilitates systems biology and comparative gene regulation studies. Database URL https://tflink.net/.

P2Y12 inhibitor clopidogrel inhibits renal fibrosis by blocking macrophage-to-myofibroblast transition

Clopidogrel, a P2Y12 inhibitor, is a novel anti-fibrosis agent for chronic kidney disease (CKD), but its mechanisms remain unclear, which we investigated by silencing P2Y12 or treating unilateral ureteral obstruction (UUO) in LysM-Cre/Rosa Tomato mice with clopidogrel in vivo and in vitro. We found that P2Y12 was significantly increased and correlated with progressive renal fibrosis in CKD patients and UUO mice. Phenotypically, up to 82% of P2Y12-expressing cells within the fibrosing kidney were of macrophage origin, identified by co-expressing CD68/F4/80 antigens or a macrophage-lineage-tracing marker Tomato. Unexpectedly, more than 90% of P2Y12-expressing macrophages were undergoing macrophage-to-myofibroblast transition (MMT) by co-expressing alpha smooth muscle actin (α-SMA), which was also confirmed by single-cell RNA sequencing. Functionally, clopidogrel improved the decline rate of the estimated glomerular filtration rate (eGFR) in patients with CKD and significantly inhibited renal fibrosis in UUO mice. Mechanistically, P2Y12 expression was induced by transforming growth factor β1 (TGF-β1) and promoted MMT via the Smad3-dependent mechanism. Thus, silencing or pharmacological inhibition of P2Y12 was capable of inhibiting TGF-β/Smad3-mediated MMT and progressive renal fibrosis in vivo and in vitro. In conclusion, P2Y12 is highly expressed by macrophages in fibrosing kidneys and mediates renal fibrosis by promoting MMT via TGF-β/Smad3 signaling. Thus, P2Y12 inhibitor maybe a novel and effective anti-fibrosis agent for CKD.

FOXR2 Is an Epigenetically Regulated Pan-Cancer Oncogene That Activates ETS Transcriptional Circuits

Forkhead box R2 (FOXR2) is a forkhead transcription factor located on the X chromosome whose expression is normally restricted to the testis. In this study, we performed a pan-cancer analysis of FOXR2 activation across more than 10,000 adult and pediatric cancer samples and found FOXR2 to be aberrantly upregulated in 70% of all cancer types and 8% of all individual tumors. The majority of tumors (78%) aberrantly expressed FOXR2 through a previously undescribed epigenetic mechanism that involves hypomethylation of a novel promoter, which was functionally validated as necessary for FOXR2 expression and proliferation in FOXR2-expressing cancer cells. FOXR2 promoted tumor growth across multiple cancer lineages and co-opted ETS family transcription circuits across cancers. Taken together, this study identifies FOXR2 as a potent and ubiquitous oncogene that is epigenetically activated across the majority of human cancers. The identification of hijacking of ETS transcription circuits by FOXR2 extends the mechanisms known to active ETS transcription factors and highlights how transcription factor families cooperate to enhance tumorigenesis.

SIGNIFICANCE

This work identifies a novel promoter that drives aberrant FOXR2 expression and delineates FOXR2 as a pan-cancer oncogene that specifically activates ETS transcriptional circuits across human cancers. See related commentary by Liu and Northcott, p. 2977.

ASCL2 Maintains Stemness Phenotype through ATG9B and Sensitizes Gliomas to Autophagy Inhibitor

Autophagy is a highly conserved process that is vital for tumor progression and treatment response. Although autophagy is proposed to maintain the stemness phenotype in adult diffuse glioma, the molecular basis of the link between autophagy and stemness is poorly understood, which makes it impossible to effectively screen for the population that will benefit from autophagy-targeted treatment. Here, ATG9B as essential for self-renewal capacity and tumor-propagation potential is identified. Notably, ASCL2 transcriptionally regulates the expression of ATG9B to maintain stemness properties. The ASCL2-ATG9B axis is an independent prognostic biomarker and indicator of autophagic activity. Furthermore, the highly effective blood-brain barrier (BBB)-permeable autophagy inhibitor ROC-325, which can significantly inhibit the progression of ASCL2-ATG9B axis^High gliomas as a single agent is investigated. These data demonstrate that a new ASCL2-ATG9B signaling axis is crucial for maintaining the stemness phenotype and tumor progression, revealing a potential autophagy inhibition strategy for adult diffuse gliomas.