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PubMed2025

Nucleosome stability safeguards cell identity, stress resilience and healthy aging.

Nucleosomes are the minimal repeating units of chromatin. Their dynamic assembly and disassembly underpins chromatin organization and genome regulation. However, it remains unclear how intrinsic nucleosome stability contributes to higher-level yet fundamental cellular and organismal properties-such as preservation of cell identity, lineage specification, stress resilience and ultimately healthy aging. To address this, we tested the impact of decreased intrinsic nucleosome stability across multiple cell, tissue and organismal models by introducing histone mutants that weaken histone-histone interactions. While nucleosome instability did not broadly alter global chromatin accessibility, DNA damage, cell proliferation or viability, it impaired lineage-specific gene expression programs, altered lineage specification and activated intrinsic inflammatory and stress pathways in a manner reminiscent of aging in mouse tissues and human cells. Consistently, nucleosome instability accelerated the onset of age-associated transcriptional alterations and functional decline in Caenorhabditis elegans and Drosophila melanogaster, and reduced cellular resilience to exogenous perturbations-including environmental, epigenetic and mitotic stress-in human cells and Saccharomyces cerevisiae. These cross-species findings identify nucleosome stability as an evolutionarily conserved epigenetic safeguard that preserves cell identity and stress resilience and supports organismal function and healthy aging.

Journal Article↗

PubMed2025

Transcription factor 4 maintains endothelial cell identity by inhibiting endothelial to mesenchymal transition.

Endothelial to mesenchymal transition (EndoMT) is essential for embryonic heart development and contributes to many pathological processes. It is unclear how the balance between endothelial cell (EC) identity and EndoMT mediators is regulated to drive this transition. This study identifies transcription factor 4 (TCF4; also known as ITF2) as a critical EC identity gene. TCF4 knockdown impairs EC phenotype and function, and induces a transition towards a mesenchymal-like state. This discovery suggests that TCF4 safeguards EC identity against EndoMT. Mechanistically, TCF4 directly binds to the promoter of multiple key genes in the transforming growth factor-β (TGFβ) signaling pathway, thereby repressing their expression. TCF4 expression is consistently down-regulated in three EndoMT models. TCF4 down-regulation diminishes its inhibitory effect on the TGFβ signaling pathway, leading to pathway activation and subsequently enhancing EndoMT. This, in turn, further suppresses TCF4 expression. Consequently, the TCF4-TGFβ feedback loop is formed to intensify the EndoMT process. We demonstrate that introducing exogenous TCF4 disrupts this TCF4-TGFβ feedback loop of EndoMT, rescuing the EC phenotype and function under TGFβ stimulation, as well as ECs from human patients with heart failure. Our results reveal a key role for TCF4 in safeguarding EC identity and preventing EndoMT, suggesting a therapeutic potential of targeting TCF4 for EndoMT-related cardiovascular diseases.

Humans↗

PubMed2025

Tribus: semi-automated discovery of cell identities and phenotypes from multiplexed imaging and proteomic data.

MOTIVATION: Multiplexed imaging and single-cell analysis are increasingly applied to investigate the tissue spatial ecosystems in cancer and other complex diseases. Accurate single-cell phenotyping based on marker combinations is a critical but challenging task due to (i) low reproducibility across experiments with manual thresholding, and, (ii) labor-intensive ground-truth expert annotation required for learning-based methods. RESULTS: We developed Tribus, an interactive knowledge-based classifier for multiplexed images and proteomic datasets that avoids hard-set thresholds and manual labeling. We demonstrated that Tribus recovers fine-grained cell types, matching the gold standard annotations by human experts. Additionally, Tribus can target ambiguous populations and discover phenotypically distinct cell subtypes. Through benchmarking against three similar methods in four public datasets with ground truth labels, we show that Tribus outperforms other methods in accuracy and computational efficiency, reducing runtime by an order of magnitude. Finally, we demonstrate the performance of Tribus in rapid and precise cell phenotyping with two large in-house whole-slide imaging datasets. AVAILABILITY AND IMPLEMENTATION: Tribus is available at https://github.com/farkkilab/tribus as an open-source Python package.

Proteomics↗

PubMed2024

DKK1-SE recruits AP1 to activate the target gene DKK1 thereby promoting pancreatic cancer progression.

Super-enhancers are a class of DNA cis-regulatory elements that can regulate cell identity, cell fate, stem cell pluripotency, and even tumorigenesis. Increasing evidence shows that epigenetic modifications play an important role in the pathogenesis of various types of cancer. However, the current research is far from enough to reveal the complex mechanism behind it. This study found a super-enhancer enriched with abnormally active histone modifications in pancreatic ductal adenocarcinoma (PDAC), called DKK1-super-enhancer (DKK1-SE). The major active component of DKK1-SE is component enhancer e1. Mechanistically, AP1 induces chromatin remodeling in component enhancer e1 and activates the transcriptional activity of DKK1. Moreover, DKK1 was closely related to the malignant clinical features of PDAC. Deletion or knockdown of DKK1-SE significantly inhibited the proliferation, colony formation, motility, migration, and invasion of PDAC cells in vitro, and these phenomena were partly mitigated upon rescuing DKK1 expression. In vivo, DKK1-SE deficiency not only inhibited tumor proliferation but also reduced the complexity of the tumor microenvironment. This study identifies that DKK1-SE drives DKK1 expression by recruiting AP1 transcription factors, exerting oncogenic effects in PDAC, and enhancing the complexity of the tumor microenvironment.

Humans↗

PubMed2025

NANOG is repurposed after implantation to repress Sox2 and begin pluripotency extinction.

Loss of pluripotency is an essential step in post-implantation development that facilitates the emergence of somatic cell identities essential for gastrulation. Before implantation, pluripotent cell identity is governed by a gene regulatory network that includes the key transcription factors SOX2 and NANOG. However, it is unclear how the pluripotency gene regulatory network is dissolved to enable lineage restriction. Here, we show that SOX2 is required for post-implantation pluripotent identity in the mouse, and cells that lose SOX2 expression in the posterior epiblast are no longer pluripotent. Using in vitro and in vivo analyses, we demonstrate anticorrelated expression of NANOG and SOX2 preceding gastrulation, culminating in an early disappearance of pluripotent identity from posterior NANOGhigh/SOX2low epiblast. Surprisingly, Sox2 expression is repressed by NANOG and embryos with post-implantation deletion of Nanog maintain posterior SOX2 expression. Our results demonstrate that the distinctive features of post-implantation pluripotency are underpinned by altered functionality of pluripotency transcription factors, ensuring correct spatio-temporal loss of embryonic pluripotency.

Animals↗

PubMed2026

Interplay between DNA and RNA methylation shapes cancer cell plasticity.

Cellular plasticity refers to the ability of healthy cells to shift between phenotypic states and modify their characteristics to maintain tissue homeostasis and integrity. In the tumor context, cancer stem cells (CSCs) exploit this flexibility to withstand stress, facilitate tumor dissemination, and evade therapeutic interventions. Epigenetic regulation, particularly DNA methylation at CpG sites, is recognized as a well-known driver of tumor plasticity by repressing differentiation programs through modulation of chromatin accessibility. More recently, RNA modifications (epitranscriptomics) have emerged as crucial post-transcriptional regulators of gene expression that shape RNA fate and function. Among these, N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), and N7-methylguanosine (m7G) contribute to the regulation of cell identity by modulating stemness-differentiation balance, stress adaptation, and epithelial-to-mesenchymal transition (EMT). Notably, dysregulation of both DNA and RNA methylation signatures is frequently observed in tumors, suggesting potential functional interactions between these regulatory layers. Emerging evidence indicates that DNA CpG methylation and RNA methylation pathways may cooperate to influence stemness, survival, and EMT-associated signaling, thereby supporting CSCs' plasticity. Although the molecular mechanisms underlying this crosstalk remain incompletely understood, accumulating studies suggest that DNA and RNA methylation could converge within interconnected regulatory networks that contribute to the control of cancer cell identity. A deeper understanding of these interactions may uncover novel vulnerabilities for targeting tumor plasticity. In this review, we summarize the current knowledge on the interplay between DNA and RNA methylation in regulating tumor plasticity, highlighting emerging mechanistic insights, functional interactions, and potential implications for future epigenetic and epitranscriptomic therapeutic strategies.

Humans↗

PubMed2023

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis.

Large single-cell RNA datasets have contributed to unprecedented biological insight. Often, these take the form of cell atlases and serve as a reference for automating cell labeling of newly sequenced samples. Yet, classification algorithms have lacked the capacity to accurately annotate cells, particularly in complex datasets. Here we present SIMS (Scalable, Interpretable Machine Learning for Single-Cell), an end-to-end data-efficient machine learning pipeline for discrete classification of single-cell data that can be applied to new datasets with minimal coding. We benchmarked SIMS against common single-cell label transfer tools and demonstrated that it performs as well or better than state of the art algorithms. We then use SIMS to classify cells in one of the most complex tissues: the brain. We show that SIMS classifies cells of the adult cerebral cortex and hippocampus at a remarkably high accuracy. This accuracy is maintained in trans-sample label transfers of the adult human cerebral cortex. We then apply SIMS to classify cells in the developing brain and demonstrate a high level of accuracy at predicting neuronal subtypes, even in periods of fate refinement, shedding light on genetic changes affecting specific cell types across development. Finally, we apply SIMS to single cell datasets of cortical organoids to predict cell identities and unveil genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. When cell types are obscured by stress signals, label transfer from primary tissue improves the accuracy of cortical organoid annotations, serving as a reliable ground truth. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Brain organoids↗

PubMed2024

SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.

Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-efficient pipeline for single-cell RNA classification. We benchmark SIMS against datasets from different tissues and species. We demonstrate SIMS's efficacy in classifying cells in the brain, achieving high accuracy even with small training sets (<3,500 cells) and across different samples. SIMS accurately predicts neuronal subtypes in the developing brain, shedding light on genetic changes during neuronal differentiation and postmitotic fate refinement. Finally, we apply SIMS to single-cell RNA datasets of cortical organoids to predict cell identities and uncover genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Single-Cell Analysis↗

PubMed2026

Asynchronous transitions from high-risk hepatoblastoma to carcinoma.

BACKGROUND & AIMS: Most pediatric hepatocellular tumors are classified as hepatoblastoma (HB) or hepatocellular carcinoma (HCC), yet a subset exhibits mixed histological and molecular features. These hepatoblastomas with carcinoma features (HBCs) include cases provisionally designated as hepatocellular neoplasm-not otherwise specified (HCN-NOS). Their biology remains poorly understood, with unresolved questions about their cellular composition and outcomes. It is unclear whether HBCs comprise hybrid cells with combined HB and HCC characteristics (HBC cells) or admixtures of distinct HB and HCC cells. We characterized the biology, etiology, cellular composition, and evolutionary dynamics of HBCs. METHODS: We performed multi-omics profiling - including single-nucleus RNA sequencing, single-nucleus DNA sequencing, and multi-region longitudinal bulk RNA and DNA sequencing - to characterize HBC composition, evolution, and treatment response. Two-thirds of our samples were post-chemotherapy resections. RESULTS: HBCs comprise heterogeneous mixtures of HB-like, HBC-like, and HCC-like molecular cell types. Outcomes in HBC are significantly worse than in HB, and HBC cells are more chemoresistant than HB cells, with resistance shaped by their cell identity, genetic alterations, and embryonic differentiation stage. HBC cells originate from HB cells that were arrested at early hepatic stem cell development stages because of aberrant WNT signaling activation. Inhibition of WNT signaling promoted differentiation and enhanced sensitivity to chemotherapy. Furthermore, each analyzed HBC reflected a dynamic process of multiple HB-to-HBC and HBC-to-HCC transitions, underscoring their evolutionary complexity. A limitation of our study is our inability to pinpoint the role of chemotherapy-induced genome modifications. CONCLUSIONS: Multi-omics profiling of HBCs revealed key insights into their biology and composition, demonstrating that they originate from HB precursors at early hepatic stem cell development stages and that their differentiation arrest depends on sustained aberrant WNT signaling activity. IMPACT AND IMPLICATIONS: Hepatoblastomas with carcinoma features (HBCs) represent a poorly understood subset of pediatric liver tumors with mixed characteristics of hepatoblastoma (HB) and hepatocellular carcinoma (HCC). Using multi-omics profiling, we show that HBCs comprise heterogeneous mixtures of HB-like, intermediate HBC-like, and HCC-like cell populations that arise from HB precursors arrested at early hepatic stem cell developmental stages due to aberrant WNT signaling. This differentiation arrest contributes to chemoresistance and poorer clinical outcomes compared with HB. Importantly, pharmacologic inhibition of WNT signaling promoted differentiation and increased chemotherapy sensitivity, suggesting a potential therapeutic strategy. These findings refine the biological classification of HBCs and highlight differentiation-based treatment approaches for this aggressive tumor subtype.

Multiomics↗

PubMed2025

Scalable screening of ternary-code DNA methylation dynamics associated with human traits.

Epigenome-wide association studies (EWASs) are transforming our understanding of the interplay between epigenetics and complex human traits. We introduce the methylation screening array (MSA) to enable scalable and quantitative screening of trait-associated DNA cytosine modifications in large human populations. The MSA integrates EWASs and cell-type-linked methylation signatures, covering diverse traits and diseases. Using the MSA to profile the ternary-code DNA methylations-dissecting 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC), and unmodified cytosine-revealed a previously unappreciated role of 5hmC in mediating human trait associations and epigenetic clocks. We demonstrated that 5hmCs complement 5mCs in defining epigenetic cell identities. In-depth analyses highlighted the cell-type context of EWAS and genome-wide association study (GWAS) hits. Targeting aging, we uncovered shared and tissue-specific 5hmC aging dynamics and tissue-specific rates of mitotic hyper- and hypomethylation. These findings chart a landscape of the complex interplay of the two forms of cytosine modifications in diverse human tissues and their roles in health and disease.

Humans↗

PubMed2026

Single nucleus multiomics reveals an early inflammatory response to high-fat diet in mouse islets.

In periods of sustained hyper-nutrition, pancreatic β-cells undergo functional compensation through transcriptional upregulation of gene programs driving insulin secretion. This adaptation is essential for maintaining systemic glucose homeostasis and metabolic health. Using single nuclei multiomics, we have mapped the early transcriptional adaptive mechanisms in murine islets of Langerhans exposed to high-fat diet (HFD) for 1 and 3 wk. We show that β-cells exhibit the largest transcriptional response to HFD, characterized by early activation of pro-inflammatory eRegulons and down-regulation of β-cell identity genes, particularly in a distinct subset of β-cells. These observations extend to humans, where the prevalence of an β-cells with a high inflammatory signature is increased in diabetes. Collectively, these observations point to cellular crosstalk through pro-inflammatory signaling as a central and early driver of β-cell dysfunction that limits the compensatory capacity of β-cells, which is closely linked to the development of diabetes.

Animals↗

PubMed2026

Aging and DNA damage are associated with the development of endothelial cell clonal expansion.

Endothelial dysfunction is a hallmark of vascular aging and a key contributor to cardiovascular disease. Although senescence has been widely studied as a terminal endothelial cell fate, recent evidence suggests that clonal expansion, the proliferative expansion of genetically identical cells, may also occur in aged tissues. We sought to determine whether endothelial clonal expansion increases with age, specifically at the atheroprone regions of the aorta, and to evaluate whether DNA damage promotes endothelial cell clonal expansion. Tamoxifen-inducible, endothelial-specific Cdh5-CreERT2 male and female mice were used to quantify clonal expansion in endothelial cells (ECs) across the aortic region in both young (4 mo) and aged (24 mo) mice. We further examined the effect of DNA damage by administering systemic doxorubicin (DOXO) to assess clonal dynamics in different aortic regions. Aging significantly increased EC clone size and the percentage of clonal ECs in atheroprone regions, particularly the minor arch, whereas only clone size increased in nonatheroprone regions. Systemic DOXO administration increased clone size across the aortic region without altering clonal recruitment, indicating selective amplification of preexisting clones. These findings suggest that clonal expansion is promoted by both aging and DNA damage. Clonal expansion may represent an underrecognized mechanism contributing to endothelial homogeneity and vascular remodeling during aging and in response to sublethal genomic stress.NEW & NOTEWORTHY Aging reshapes the vascular endothelium in unexpected ways. Using lineage tracing in mice, we show that endothelial cells undergo age-dependent clonal expansion, particularly in atheroprone regions exposed to disturbed blood flow. This process is amplified by DNA damage and reflects the selective expansion of preexisting clones rather than increased recruitment. Endothelial clonal expansion may represent an underrecognized mechanism driving vascular remodeling during aging and genotoxic stress.

Animals↗

PubMed2026

Transcriptome-Proteome Analysis of Human Naive and Memory B Cell Subsets Reveals Isotype and Subclass-Specific Phenotypes.

Antibodies produced by B cells aid in the recognition and clearance of pathogens and are the cornerstone of vaccination strategies. Humans produce nine different antibody isotypes, and their effector functions differ according to the type of antigen and route of exposure. Phenotypic variation between isotype-switched B cell subsets is expected but not studied in detail. To obtain a molecular definition of isotype-defined cell identity, we performed proteomics and transcriptomics on isotype-defined populations of human naive and memory B cells (MBCs): CD27-IgM+IgD+, CD27+CD38lo/-IgM+IgD+, CD27+CD38lo/-IgM+IgD-, and IgA1, IgA2, IgG1, IgG2, IgG3, and IgG4 MBCs (CD27+CD38lo/-Ig+). Combined proteome and transcriptome analysis revealed that mRNA and protein expression profiles separate isotype-defined B cell subsets according to their differentiation status. mRNA and protein expression levels correlated reasonably well for many genes. IgG4-switched B cells were most distinct from naive B cells in terms of mRNA as well as protein expression profiles. Besides a distinct expression profile of cytokine and Fc receptors, we identified a high expression of IgE-coding mRNA in IgG4-switched B cells. SDR16C5 was identified as uniquely upregulated in IgG4-switched B cells. Taken together, this study highlights the distinct phenotypic profile of IgG4-switched B cells.

Humans↗

PubMed2025

Mapping early PRC2 nucleation sites upon Suz12 reintroduction reveals features of de novo Polycomb recruitment.

Polycomb domains safeguard cell identity by maintaining lineage-specific chromatin states enriched in repressive histone modifications, preserving the epigenetic memory of cell lineages. While Polycomb Repressive Complex 2 (PRC2) can re-establish its occupancy after perturbation, the mechanisms that guide de novo Polycomb recruitment remain unclear. To address this, we engineered an auxin-inducible degradation system to reversibly deplete and reintroduce the endogenous PRC2 core subunit Suz12 in mouse embryonic stem cells (mESCs). Genome-wide profiling at an early recovery time point revealed ~1,100 PRC2 nucleation sites, characterized by rapid Suz12 and histone H3K27me3 re-accumulation with strong signal, with minimal impact on gene expression. These sites were significantly enriched at bivalent promoters, coinciding with unmethylated CpG islands and chromatin states associated with developmental regulation, and were largely conserved in differentiated cells. Motif analysis identified G/C-rich DNA sequences associated with E2F and zinc-finger proteins, alongside strong co-occupancy with MTF2 and JARID2, two PRC2 cofactors previously implicated in Polycomb targeting. Notably, a subset of nucleation sites overlapped with long-range chromatin interaction anchors in histone H3K27me3 HiChIP datasets. These findings reveal that PRC2 de novo nucleation sites are associated with a combination of chromatin states, DNA sequence features, cofactor co-occupancy and spatial genome organization, suggesting that epigenetic memory can be re-established through defined genomic and chromatin features.

Epigenetic memory↗

PubMed2025

CUT&TIME captures the history of open chromatin in developing neurons.

Chromatin structure plays a central role in defining cell identity by regulating gene expression. During development, shifts in chromatin structure facilitate changes in gene expression needed to specify distinct cell types. To understand how changes in chromatin structure influence the developmental trajectory of neural progenitor cells, we developed CUT&TIME, a technique that uses a hyperactive 6-methyl adenosine (6mA) methyltransferase pulsed in living cells to map historical chromatin accessibility genome-wide in single cells. We show that CUT&TIME produces a record of the chromatin landscape during neurogenesis in the developing retina, specifically as neural progenitors produce the major projection neuron type, retinal ganglion cells (RGCs). We further show that this method is compatible with single cell profiling technologies, which allows us to visualize and capture the diversity of chromatin states that produce RGCs. Additionally, we identify changes in promoter accessibility associated with the transition from progenitor to RGC. Together, these data demonstrate that CUT&TIME captures a historical record of chromatin structure, which can be used to identify early changes in accessibility associated with cell-fate commitment.

Journal Article↗

PubMed2025

Scalable single-cell total RNA-seq reveals non-coding programs in immunity, infection, and brain development.

Non-coding RNAs represent a widespread and diverse layer of post-transcriptional regulation across cell types and states, yet much of their diversity remains uncharted at single-cell resolution. This gap stems from the limitations of widely used single-cell RNA-sequencing protocols, which focus on polyadenylated transcripts and miss many short or non-polyadenylated RNAs. Here, we adapted single-cell RNA-sequencing on the 10x Genomics platform to capture a broad complement of coding and non-coding RNAs-including miRNAs, tRNAs, lncRNAs, histone RNAs, and non-adenylated viral transcripts. This approach enabled the discovery of rich, dynamic non-coding RNA programs across immune cells, virally infected hepatocytes, and the developing human brain. In dengue virus-infected hepatocytes, we detect non-adenylated viral transcripts and distinguish active from transcriptionally quiescent infected states, each with distinct host regulatory signatures. In brain tissue, we identify biotype-specific, cell-type-restricted non-coding RNAs, including miRNAs whose expression anticorrelates with predicted targets, consistent with post-transcriptional regulatory relationships. We show that MIR137, one of the strongest GWAS loci associated with schizophrenia and intellectual disability, is expressed specifically in Cajal-Retzius cells, an early-born but transient population that guides subsequent cortical neuron migration. These findings demonstrate the importance of non-coding RNAs in defining cell identity and state, and show how expanded transcriptome coverage can reveal additional layers of gene control-now accessible through practical and scalable single-cell profiling.

Journal Article↗

PubMed2025

Selective targeting of TBXT with DARPins identifies regulatory networks and therapeutic vulnerabilities in chordoma.

The embryonic transcription factor TBXT (brachyury) drives chordoma, a spinal neoplasm without effective drug therapies. TBXT's regulatory network is poorly understood, and strategies to disrupt its activity for therapeutic purposes are lacking. We developed designed ankyrin repeat proteins that block TBXT-DNA binding (T-DARPins). In chordoma cells, T-DARPins reduced cell cycle progression, spheroid formation, and tumor growth in mice and induced signs of senescence and differentiation. Transcriptomic and proteomic analyses identified gene networks involved in cell cycle regulation, embryonic cell identity, and interferon response and revealed features of regulome components, such as susceptibility to pharmacologic inhibition and the fine-tuning of TBXT downstream effectors through IGFBP3. Finally, we found high interferon signaling in chordoma cell lines and patient tumors, which was promoted by TBXT and associated with sensitivity to JAK2 inhibitors. These findings demonstrate the potential of DARPins for probing nuclear proteins to understand the regulatory networks of transcription factor-driven cancers, including entry points for therapies that warrant testing in patients.

Humans↗

PubMed2026

Driver genomic lesions in MDM2, CDK4, and JUN co-opt targetable super-enhancer networks to impose liposarcomagenic core regulatory circuitry.

INTRODUCTION: Amplification of chromosome 12q13-15 spanning MDM2 and CDK4 genes serves as a molecular diagnostic hallmark of dedifferentiated liposarcoma (DDLPS), an aggressive soft-tissue sarcoma. Epigenetic activation of master transcription factors (RUNX proteins, FOSL2, and MYC) establishes a self-reinforcing oncogenic transcriptional circuitry in DDLPS. Nevertheless, the collaborative interplay between genomic alterations and epigenetic dysregulation in defining DDLPS cell identity remains elusive. OBJECTIVES: This work aimed to elucidate the primary genetic drivers and mechanistic basis of DDLPS-specific core transcriptional regulatory circuitry. METHODS: We performed integrative chromatin profiling analysis of DDLPS clinical specimens and cell lines to map cis-regulatory landscapes. Cistromes of MDM2, JUN, and E2F1 were delineated through chromatin immunoprecipitation sequencing in two DDLPS models. Essential driver functions and transcriptional regulatory effects of key regulators were assessed via various genetic manipulation approaches. Synergistic interactions between BET-targeting agents and MDM2/p53 or CDK4 inhibitors were quantified by cell viability assays. In vivo xenograft assays evaluated the oncogenic potential of key regulators and the therapeutic efficacy of novel strategies. RESULTS: Co-amplification of MDM2, CDK4, and JUN during sarcomagenesis converges with BET protein-dependent chromatin remodeling to fuel feed-forward transcriptional circuits among master transcription factors. Mechanistically, excessively expressed MDM2 stabilizes the core regulatory circuitry by forming chromatin-bound complexes with JUN/FOSL2 at cis-regulatory elements, especially super-enhancers across DDLPS genome. Concurrently, CDK4 maintains expression of E2F1 which further fosters transcriptional output of master transcription factors in DDLPS cells. Leveraging DDLPS-selective overexpression of MDM2 and its E3 ligase activity, targeted degradation of BET proteins by MDM2-recruiting proteolysis targeting chimera selectively disrupted the core regulatory circuitry, suppressing DDLPS growth and exhibiting strong synergy with CDK4 inhibitor. CONCLUSION: DDLPS-associated genomic lesions collaborate with BET-dependent chromatin regulation to establish disease-sustaining transcriptional circuitry. Our findings also provide a mechanistic rationale for harnessing MDM2's E3 ligase activity to therapeutically degrade oncoproteins in MDM2-amplified malignancies.

Core transcriptional regulatory circuitry↗