The PTM profiling of CTCF reveals the regulation of 3D chromatin structure by O-GlcNAcylation.

CCCTC-binding factor (CTCF), a ubiquitously expressed and highly conserved protein, is known to play a critical role in chromatin structure. Post-translational modifications (PTMs) diversify the functions of protein to regulate numerous cellular processes. However, the effects of PTMs on the genome-wide binding of CTCF and the organization of three-dimensional (3D) chromatin structure have not been fully understood. In this study, we uncovered the PTM profiling of CTCF and demonstrated that CTCF can be O-GlcNAcylated and arginine methylated. Functionally, we demonstrated that O-GlcNAcylation inhibits CTCF binding to chromatin. Meanwhile, deficiency of CTCF O-GlcNAcylation results in the disruption of loop domains and the alteration of chromatin loops associated with cellular development. Furthermore, the deficiency of CTCF O-GlcNAcylation increases the expression of developmental genes and negatively regulates maintenance and establishment of stem cell pluripotency. In conclusion, these results provide key insights into the role of PTMs for the 3D chromatin structure.

SEPDB: a database of secreted proteins.

Detecting changes in the dynamics of secreted proteins in serum has been a challenge for proteomics. Enter secreted protein database (SEPDB), an integrated secretory proteomics database offering human, mouse and rat secretory proteomics datasets collected from serum, exosomes and cell culture media. SEPDB compiles secreted protein information from secreted protein database, UniProt and Human Protein Atlas databases to annotate secreted proteomics data based on protein subcellular localization and disease markers. SEPDB integrates the latest predictive modeling techniques to measure deviations in the distribution of signal peptide structures of secreted proteins, extends signal peptide sequence prediction by excluding transmembrane structural domain proteins and updates the validation analysis pipeline for secreted proteins. To establish tissue-specific profiles, we have also created secreted proteomics datasets associated with different human tissues. In addition, we provide information on heterogeneous receptor network organizational relationships, reflective of the complex functional information inherent in the molecular structures of secreted proteins that serve as ligands. Users can take advantage of the Refreshed Search, Analyze, Browse and Download functions of SEPDB, which is available online at https://sysomics.com/SEPDB/. Database URL:  https://sysomics.com/SEPDB/.

Ablation alone is noninferior to radiotherapy plus ablation in the patients with early-stage hepatocellular carcinoma: a population-based study.

Recently, the efficacy of two low-invasive treatments, ablation, and radiotherapy, has been fully compared for the patients with the early-stage hepatocellular carcinoma (HCC). However, the comparison between radiotherapy plus ablation and ablation alone has been less frequently reported. Data from the Surveillance, Epidemiology, and End Results (SEER) database were searched for early-stage HCC patients treated with ablation plus radiotherapy or ablation alone. The outcome measures were overall survival (OS) and cancer-specific survival (CSS). The propensity score matching (PSM) was used to reduce selection bias. We included 240 and 6619 patients in the radiotherapy plus ablation group and ablation group before the PSM. After PSM, 240 pairs of patients were included. The median OS (mOS) and median CSS (mCSS) of patients receiving ablation alone were longer than that of receiving radiotherapy plus ablation (mOS: 47 vs. 34 months, P = 0.019; mCSS: 77 vs. 40 months, P = 0.018, after PSM) before and after PSM. The multivariate analysis indicated that radiotherapy plus ablation independent risk factor for OS and CSS before PSM, but the significance disappeared after PSM. The detailed subgroup analyses indicated ablation alone brought more benefit in very early-stage HCC and older patients. In addition, we found different types of radiotherapy might lead to different outcomes when combined with ablation. In conclusion, ablation alone is noninferior to radiotherapy plus ablation in patients with early-stage HCC. The additional radiation prior to ablation may bring survival benefits in the patients with higher tumor stage. However, due to the risk of selection bias in that study, the results should be interpreted cautiously.

Dual-Layer Spectral Detector Computed Tomography Quantitative Parameters: A Potential Tool for Lymph Node Activity Determination in Lymphoma Patients.

Dual-energy CT has shown promising results in determining tumor characteristics and treatment effectiveness through spectral data by assessing normalized iodine concentration (nIC), normalized effective atomic number (nZeff), normalized electron density (nED), and extracellular volume (ECV). This study explores the value of quantitative parameters in contrast-enhanced dual-layer spectral detector CT (SDCT) as a potential tool for detecting lymph node activity in lymphoma patients. A retrospective analysis of 55 lymphoma patients with 289 lymph nodes, assessed through 18FDG-PET/CT and the Deauville five-point scale, revealed significantly higher values of nIC, nZeff, nED, and ECV in active lymph nodes compared to inactive ones (p < 0.001). Generalized linear mixed models showed statistically significant fixed-effect parameters for nIC, nZeff, and ECV (p < 0.05). The area under the receiver operating characteristic curve (AUROC) values of nIC, nZeff, and ECV reached 0.822, 0.845, and 0.811 for diagnosing lymph node activity. In conclusion, the use of g nIC, nZeff, and ECV as alternative imaging biomarkers to PET/CT for identifying lymph node activity in lymphoma holds potential as a reliable diagnostic tool that can guide treatment decisions.

CLIC3 interacts with NAT10 to inhibit N4-acetylcytidine modification of p21 mRNA and promote bladder cancer progression.

Chromatin accessibility plays important roles in revealing the regulatory networks of gene expression, while its application in bladder cancer is yet to be fully elucidated. Chloride intracellular channel 3 (CLIC3) protein has been reported to be associated with the progression of some tumors, whereas the specific mechanism of CLIC3 in tumor remains unclear. Here, we screened for key genes in bladder cancer through the identification of transcription factor binding site clustered region (TFCR) on the basis of chromatin accessibility and TF motif. CLIC3 was identified by joint profiling of chromatin accessibility data with TCGA database. Clinically, CLIC3 expression was significantly elevated in bladder cancer and was negatively correlated with patient survival. CLIC3 promoted the proliferation of bladder cancer cells by reducing p21 expression in vitro and in vivo. Mechanistically, CLIC3 interacted with NAT10 and inhibited the function of NAT10, resulting in the downregulation of ac4C modification and stability of p21 mRNA. Overall, these findings uncover an novel mechanism of mRNA ac4C modification and CLIC3 may act as a potential therapeutic target for bladder cancer.

Comparative study on genomic and epigenomic profiles of retinoblastoma or tuberous sclerosis complex via nanopore sequencing and a joint screening framework.

Recurrence and extraocular metastasis in advanced intraocular retinoblastoma (RB) are still major obstacles for successful treatment of Chinese children. Tuberous sclerosis complex (TSC) is a very rare, multisystemic genetic disorder characterized by hamartomatous growth. In this study, we aimed to compare genomic and epigenomic profiles with human RB or TSC using recently developed nanopore sequencing, and to identify disease-associated variations or genes. Peripheral blood samples were collected from either RB or RB/TSC patients plus their normal siblings, followed by nanopore sequencing and identification of disease-specific structural variations (SVs) and differentially methylated regions (DMRs) by a systematic biology strategy named as multiomics-based joint screening framework. In total, 316 RB- and 1295 TSC-unique SVs were identified, as well as 1072 RB- and 1114 TSC-associated DMRs, respectively. We eventually identified 6 key genes for RB for further functional validation. Knockdown of CDK19 with specific siRNAs significantly inhibited Y79 cellular proliferation and increased sensitivity to carboplatin, whereas downregulation of AHNAK2 promoted the cell growth as well as drug resistance. Those two genes might serve as potential diagnostic markers or therapeutic targets of RB. The systematic biology strategy combined with functional validation might be an effective approach for rare pediatric malignances with limited samples and challenging collection process.

Application and development of Deuterium Metabolic Imaging in tumor glucose metabolism: visualization of different metabolic pathways.

Cancer metabolism has emerged as a pivotal area of research recently. The ability to visualize and comprehend the metabolic processes of cancer holds immense clinical value, particularly in the diagnosis of malignant tumors and the assessment of treatment responses. Deuterium Metabolic Imaging (DMI), as a robust, simple, and versatile MR spectroscopic imaging tool, demonstrates promise in tumor diagnosis and treatment efficacy assessment. This review explored the latest developments and applications of DMI in oncology across various tumor metabolic axes, with a specific emphasis on its potential for clinical translation. DMI offers invaluable insights into tumor biology, treatment responses, and prognostic outcomes. Notably, DMI can identify early responses to immunotherapy, a prominent area of current research interest. In conclusion, DMI harbors the potential to evolve into a convenient and efficient imaging technique in clinical practice, thereby advancing precision medicine and improving the diagnosis and evaluation of cancer treatments.

Study on tumour cell-derived hybrid exosomes as dasatinib nanocarriers for pancreatic cancer therapy.

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death. Therefore, we intend to explore novel strategies against PDAC. The exosomes-based biomimetic nanoparticle is an appealing candidate served as a drug carrier in cancer treatment, due to its inherit abilities. In the present study, we designed dasatinib-loaded hybrid exosomes by fusing human pancreatic cancer cells derived exosomes with dasatinib-loaded liposomes, followed by characterization for particle size (119.9 ± 6.10 nm) and zeta potential (-11.45 ± 2.24 mV). Major protein analysis from western blot techniques reveal the presence of exosome marker proteins CD9 and CD81. PEGylated hybrid exosomes showed pH-sensitive drug release in acidic condition, benefiting drug delivery to acidic cancer environment. Dasatinib-loaded hybrid exosomes exhibited significantly higher uptake rates and cytotoxicity to parent PDAC cells by two-sample t-test or by one-way ANOVA analysis of variance, as compared to free drug or liposomal formulations. The results from our computational analysis demonstrated that the drug-likeness, ADMET, and protein-ligand binding affinity of dasatinib are verified successfully. Cancer derived hybrid exosomes may serve as a potential therapeutic candidate for pancreatic cancer treatment.

Correction of Arterial-Phase Motion Artifacts in Gadoxetic Acid-Enhanced Liver MRI Using an Innovative Unsupervised Network.

This study aims to propose and evaluate DR-CycleGAN, a disentangled unsupervised network by introducing a novel content-consistency loss, for removing arterial-phase motion artifacts in gadoxetic acid-enhanced liver MRI examinations. From June 2020 to July 2021, gadoxetic acid-enhanced liver MRI data were retrospectively collected in this center to establish training and testing datasets. Motion artifacts were semi-quantitatively assessed using a five-point Likert scale (1 = no artifact, 2 = mild, 3 = moderate, 4 = severe, and 5 = non-diagnostic) and quantitatively evaluated using the structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR). The datasets comprised a training dataset (308 examinations, including 58 examinations with artifact grade = 1 and 250 examinations with artifact grade ≥ 2), a paired test dataset (320 examinations, including 160 examinations with artifact grade = 1 and paired 160 examinations with simulated motion artifacts of grade ≥ 2), and an unpaired test dataset (474 examinations with artifact grade ranging from 1 to 5). The performance of DR-CycleGAN was evaluated and compared with a state-of-the-art network, Cycle-MedGAN V2.0. As a result, in the paired test dataset, DR-CycleGAN demonstrated significantly higher SSIM and PSNR values and lower motion artifact grades compared to Cycle-MedGAN V2.0 (0.89 ± 0.07 vs. 0.84 ± 0.09, 32.88 ± 2.11 vs. 30.81 ± 2.64, and 2.7 ± 0.7 vs. 3.0 ± 0.9, respectively; p < 0.001 each). In the unpaired test dataset, DR-CycleGAN also exhibited a superior motion artifact correction performance, resulting in a significant decrease in motion artifact grades from 2.9 ± 1.3 to 2.0 ± 0.6 compared to Cycle-MedGAN V2.0 (to 2.4 ± 0.9, p < 0.001). In conclusion, DR-CycleGAN effectively reduces motion artifacts in the arterial phase images of gadoxetic acid-enhanced liver MRI examinations, offering the potential to enhance image quality.

CTCF coordinates cell fate specification via orchestrating regulatory hubs with pioneer transcription factors.

CCCTC-binding factor (CTCF), a ubiquitously expressed architectural protein, has emerged as a key regulator of cell identity gene transcription. However, the precise molecular mechanism underlying specialized functions of CTCF remains elusive. Here, we investigate the mechanism through integrative analyses of primary hepatocytes, myocytes, and B cells from mouse and human. We demonstrate that CTCF cooperates with lineage-specific pioneer transcription factors (TFs), including MyoD, FOXA, and PU.1, to control cell identity at 1D and 3D levels. At the 1D level, pioneer TFs facilitate lineage-specific CTCF occupancy via opening chromatin. At the 3D level, CTCF and pioneer TFs form regulatory hubs to govern the expression of cell identity genes. This mechanism is validated using MyoD-null mice, CTCF knockout mice, and CRISPR editing during myogenic differentiation. Collectively, these findings uncover a general mechanism whereby CTCF acts as a cell identity cofactor to control cell identity genes via orchestrating regulatory hubs with pioneer TFs.

TimeTalk uses single-cell RNA-seq datasets to decipher cell-cell communication during early embryo development.

Early embryonic development is a dynamic process that relies on proper cell-cell communication to form a correctly patterned embryo. Early embryo development-related ligand-receptor pairs (eLRs) have been shown to guide cell fate decisions and morphogenesis. However, the scope of eLRs and their influence on early embryo development remain elusive. Here, we developed a computational framework named TimeTalk from integrated public time-course mouse scRNA-seq datasets to decipher the secret of eLRs. Extensive validations and analyses were performed to ensure the involvement of identified eLRs in early embryo development. Process analysis identified that eLRs could be divided into six temporal windows corresponding to sequential events in the early embryo development process. With the interpolation strategy, TimeTalk is powerful in revealing paracrine settings and studying cell-cell communication during early embryo development. Furthermore, by using TimeTalk in the blastocyst and blastoid models, we found that the blastoid models share the core communication pathways with the epiblast and primitive endoderm lineages in the blastocysts. This result suggests that TimeTalk has transferability to other bio-dynamic processes. We also curated eLRs recognized by TimeTalk, which may provide valuable clues for understanding early embryo development and relevant disorders.

Association between genetic predisposition and disease burden of stroke in China: a genetic epidemiological study.

Background: Stroke ranks second worldwide and first in China as a leading cause of death and disability. It has a polygenic architecture and is influenced by environmental and lifestyle factors. However, it remains unknown as to whether and how much the genetic predisposition of stroke is associated with disease burden. Methods: Allele frequency from the whole genome sequencing data in the Chinese Millionome Database of 141,418 individuals and trait-specific polygenic risk score models were applied to estimate the provincial genetic predisposition to stroke, stroke-related risk factors and stroke-related drug response. Disease burden including mortality, disability-adjusted life years (DALYs), years of life lost(YLLs), years lived with disability (YLDs) and prevalence in China was collected from the Global Burden Disease study. The association between stroke genetic predisposition and the epidemiological burden was assessed and then quantified in both regression-based models and machine learning-based models at a provincial resolution. Findings: Among the 30 administrative divisions in China, the genetic predisposition of stroke was characterized by a north-higher-than-south gradient (p < 0.0001). Genetic predisposition to stroke, blood pressure, body mass index, and alcohol use were strongly intercorrelated (rho >0.6; p < 0.05 after Bonferroni correction for each comparison). Genetic risk imposed an independent effect of approximately 1-6% on mortality, DALYs and YLLs. Interpretation: The distribution pattern of stroke genetic predisposition is different at a macroscopic level, and it subtly but significantly impacts the epidemiological burden. Further research is warranted to identify the detailed aetiology and potential translation into public health measures. Funding: Beijing Municipal Science and Technology Commission (Z191100006619106), CAMS Innovation Fund for Medical Sciences (CAMS-I2M, 2023-I2M-1-001), the National High Level Hospital Clinical Research Funding (2022-GSP-GG-17), National Natural Science Foundation of China (32000398, 32171441 to X.J.), Natural Science Foundation of Guangdong Province, China (2017A030306026 to X.J.), and National Key R&D Program of China (2022YFC2502402).

A transcriptome-based single-cell biological age model and resource for tissue-specific aging measures.

Accurately measuring biological age is crucial for improving healthcare for the elderly population. However, the complexity of aging biology poses challenges in how to robustly estimate aging and interpret the biological significance of the traits used for estimation. Here we present SCALE, a statistical pipeline that quantifies biological aging in different tissues using explainable features learned from literature and single-cell transcriptomic data. Applying SCALE to the "Mouse Aging Cell Atlas" (Tabula Muris Senis) data, we identified tissue-level transcriptomic aging programs for more than 20 murine tissues and created a multitissue resource of mouse quantitative aging-associated genes. We observe that SCALE correlates well with other age indicators, such as the accumulation of somatic mutations, and can distinguish subtle differences in aging even in cells of the same chronological age. We further compared SCALE with other transcriptomic and methylation "clocks" in data from aging muscle stem cells, Alzheimer's disease, and heterochronic parabiosis. Our results confirm that SCALE is more generalizable and reliable in assessing biological aging in aging-related diseases and rejuvenating interventions. Overall, SCALE represents a valuable advancement in our ability to measure aging accurately, robustly, and interpretably in single cells.

A semiautomated radiomics model based on multimodal dual-layer spectral CT for preoperative discrimination of the invasiveness of pulmonary ground-glass nodules.

Background: In recent years, spectral computed tomography (CT) has shown excellent performance in the diagnosis of ground-glass nodules (GGNs) invasiveness; however, no research has combined spectral multimodal data and radiomics analysis for comprehensive analysis and exploration. Therefore, this study goes a step further on the basis of the previous research: to investigate the value of dual-layer spectral CT-based multimodal radiomics in accessing the invasiveness of lung adenocarcinoma manifesting as GGNs. Methods: In this study, 125 GGNs with pathologically confirmed preinvasive adenocarcinoma (PIA) and lung adenocarcinoma were divided into a training set (n=87) and a test set (n=38). Each lesion was automatically detected and segmented by the pre-trained neural networks, and 63 multimodal radiomic features were extracted. The least absolute shrinkage and selection operator (LASSO) was used to select target features, and a rad-score was constructed in the training set. Logistic regression analysis was conducted to establish a joint model which combined age, gender, and the rad-score. The diagnostic performance of the two models was compared by the receiver operating characteristic (ROC) curve and precision-recall curve. The difference between the two models was compared by the ROC analysis. The test set was used to evaluate the predictive performance and calibrate the model. Results: Five radiomic features were selected. In the training and test sets, the area under the curve (AUC) of the radiomics model was 0.896 (95% CI: 0.830-0.962) and 0.881 (95% CI: 0.777-0.985) respectively, and the AUC of the joint model was 0.932 (95% CI: 0.882-0.982) and 0.887 (95% CI: 0.786-0.988) respectively. There was no significant difference in AUC between the radiomics model and joint model in the training and test sets (0.896 vs. 0.932, P=0.088; 0.881 vs. 0.887, P=0.480). Conclusions: Multimodal radiomics based on dual-layer spectral CT showed good predictive performance in differentiating the invasiveness of GGNs, which could assist in the decision of clinical treatment strategies.

A gadoxetic-acid enhancement flux analysis of small liver nodules (≤2 cm) in patients at high risk of hepatocellular carcinoma.

PURPOSE: To discriminate between benignities and hepatocellular carcinomas (HCCs) in patients at high risk of HCC using a novel enhancement flux analysis for gadoxetic-acid enhanced MRI. METHOD: This study retrospectively collected 181 liver nodules in 156 patients at high risk of HCC who underwent gadoxetic acid-enhanced MRI examinations with following surgical resection from 1st August 2017 to 31st December 2021 as the training set; another 42 liver nodules in 36 patients were prospectively collected from 1st January 2022 to 1st October 2022 as the test set. The time-intensity curves (TICs) of liver nodules were formed with consecutive time points: 0 s, 20 s, 1 min, 2 min, 5 min, 10 min, 15 min, and 20 min since contrast injection. A novel enhancement flux analysis was applied by using a biexponential function fitting to distinguish benignities and HCC. Besides, previously published models including maximum enhancement ratio (ERmax), percentage signal ratio (PSR), and ERmax+PSR were compared. The areas under the receiver operating characteristic curves (AUCs) were compared among these methods. RESULTS: The novel enhancement flux analysis showed the highest AUCs in the training set (0.897, 95%CI: 0.833-0.960) and the test set (0.859, 95%CI: 0.747-0.970) among all models. The AUCs of PSR, ERmax and ERmax+PSR were 0.801 (95%CI: 0.710-0.891), 0.620 (95%CI: 0.510-0.729), and 0.799 (95%CI: 0.709-0.889) in the training set, and were 0.701 (95%CI: 0.539-0.863), 0.529 (95%CI: 0.342-0.717), and 0.708 (95%CI: 0.549-0.867) in the test set. CONCLUSIONS: The biexponential flux analysis for gadoxetic-acid enhanced MRI presents a better potential in accurate diagnosis of small HCC nodules.

Prognosis prediction of icotinib as targeted therapy for advanced EGFR-positive non-small cell lung cancer patients.

Clinical trials on icotinib, a first-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), have shown promising results as targeted therapy for non-small cell lung cancer (NSCLC). This study aimed to establish an effective scoring system to predict the one-year progression-free survival (PFS) of advanced NSCLC patients with EGFR mutations treated with icotinib as targeted therapy. A total of 208 consecutive patients with advanced EGFR-positive NSCLC treated with icotinib were enrolled in this study. Baseline characteristics were collected within 30 days before icotinib treatment. PFS was taken as the primary endpoint and the response rate as the secondary endpoint. Least absolute shrinkage and selection operator (LASSO) regression analysis and Cox proportional hazards regression analysis were used to select the optimal predictors. We evaluated the scoring system using a five-fold cross-validation. PFS events occurred in 175 patients, with a median PFS of 9.9 months (interquartile range, 6.8-14.5). The objective response rate (ORR) was 36.1%, and the disease control rate (DCR) was 67.3%. The final ABC-Score consisted of three predictors: age, bone metastases and carbohydrate antigen 19-9 (CA19-9). Upon comparison of all three factors, the combined ABC-score (area under the curve (AUC)= 0.660) showed a better predictive accuracy than age (AUC = 0.573), bone metastases (AUC = 0.615), and CA19-9 (AUC = 0.608) individually. A five-fold cross-validation showed good discrimination with AUC = 0.623. The ABC-score developed in this study was significantly effective as a prognostic tool for icotinib in advanced NSCLC patients with EGFR mutations.

A graph neural network-based interpretable framework reveals a novel DNA fragility-associated chromatin structural unit.

BACKGROUND: DNA double-strand breaks (DSBs) are among the most deleterious DNA lesions, and they can cause cancer if improperly repaired. Recent chromosome conformation capture techniques, such as Hi-C, have enabled the identification of relationships between the 3D chromatin structure and DSBs, but little is known about how to explain these relationships, especially from global contact maps, or their contributions to DSB formation. RESULTS: Here, we propose a framework that integrates graph neural network (GNN) to unravel the relationship between 3D chromatin structure and DSBs using an advanced interpretable technique GNNExplainer. We identify a new chromatin structural unit named the DNA fragility-associated chromatin interaction network (FaCIN). FaCIN is a bottleneck-like structure, and it helps to reveal a universal form of how the fragility of a piece of DNA might be affected by the whole genome through chromatin interactions. Moreover, we demonstrate that neck interactions in FaCIN can serve as chromatin structural determinants of DSB formation. CONCLUSIONS: Our study provides a more systematic and refined view enabling a better understanding of the mechanisms of DSB formation under the context of the 3D genome.

Decitabine priming increases anti-PD-1 antitumor efficacy by promoting CD8+ progenitor exhausted T cell expansion in tumor models.

CD8+ exhausted T cells (Tex) are heterogeneous. PD-1 inhibitors reinvigorate progenitor Tex, which subsequently differentiate into irresponsive terminal Tex. The ability to maintain a capacity for durable proliferation of progenitor Tex is important, but the mechanism remains unclear. Here, we showed CD8+ progenitor Tex pretreated with decitabine, a low-dose DNA demethylating agent, had enhanced proliferation and effector function against tumors after anti-PD-1 treatment in vitro. Treatment with decitabine plus anti-PD-1 promoted the activation and expansion of tumor-infiltrated CD8+ progenitor Tex and efficiently suppressed tumor growth in multiple tumor models. Transcriptional and epigenetic profiling of tumor-infiltrated T cells demonstrated that the combination of decitabine plus anti-PD-1 markedly elevated the clonal expansion and cytolytic activity of progenitor Tex compared with anti-PD-1 monotherapy and restrained CD8+ T cell terminal differentiation. Strikingly, decitabine plus anti-PD-1 sustained the expression and activity of the AP-1 transcription factor JunD, which was reduced following PD-1 blockade therapy. Downregulation of JunD repressed T cell proliferation, and activation of JNK/AP-1 signaling in CD8+ T cells enhanced the antitumor capacity of PD-1 inhibitors. Together, epigenetic agents remodel CD8+ progenitor Tex populations and improve responsiveness to anti-PD-1 therapy.

Mapping nucleolus-associated chromatin interactions using nucleolus Hi-C reveals pattern of heterochromatin interactions.

As the largest substructures in the nucleus, nucleoli are the sites of ribosome biogenesis. Increasing evidence indicates that nucleoli play a key role in the organization of 3D genome architecture, but systematic studies of nucleolus-associated chromatin interactions are lacking. Here, we developed a nucleolus Hi-C (nHi-C) experimental technique to enrich nucleolus-associated chromatin interactions. Using the nHi-C experiment, we identify 264 high-confidence nucleolus-associated domains (hNADs) that form strong heterochromatin interactions associated with the nucleolus and consist of 24% of the whole genome in HeLa cells. Based on the global hNAD inter-chromosomal interactions, we find five nucleolar organizer region (NOR)-bearing chromosomes formed into two clusters that show different interaction patterns, which is concordant with their epigenetic states and gene expression levels. hNADs can be divided into three groups that display distinct cis/trans interaction signals, interaction frequencies associated with nucleoli, distance from the centromeres, and overlap percentage with lamina-associated domains (LADs). Nucleolus disassembly caused by Actinomycin D (ActD) significantly decreases the strength of hNADs and affects compartment/TAD strength genome-wide. In summary, our results provide a global view of heterochromatin interactions organized around nucleoli and demonstrate that nucleoli act as an inactive inter-chromosomal hub to shape both compartments and TADs.

Ionizing radiation damage and repair from 3D-genomic perspective.

Ionizing radiation (IR)-induced DNA damage and repair are complex and occur at hierarchical chromatin structures; radiobiology needs to be studied from a 3D-genomic perspective. Differences in IR damage and repair throughout the 3D genome may help to explain differences in radiosensitivity.