Super enhancers (SEs), characterized by clusters of enhancers, are instrumental in shaping cellular identity and function. Given this crucial involvement of SEs in cell lineage commitment, and considering the pivotal position of surface ectoderm in differentiating into a wide array of cell types, the study of these SEs holds immense promise for advancing cell-based therapeutic applications. In this study, we profiled the SE landscape in surface ectoderm cells derived from pluripotent stem cell differentiation. By leveraging 3D genomic data, we discerned active histone modifications and frequent chromatin interactions of SEs with target genes. Notably, perturbing specific SE using a CRISPR-dCas9-mediated approach resulted in decreased expression of the connected gene. Subsequently, we constructed a regulatory network of core transcription factors (TFs) operating on SEs and uncovered their control over the differentiation process by forming regulatory network with key TFs, such as TEAD1. Knocking down TEADs attenuated the differentiation process and target gene activation, whereas YAP-TEAD activation expedited the differentiation process by promoting the early establishment of SEs. Collectively, our findings shed light on the crucial role of SEs and identify YAP-TEAD as vital regulators controlling surface ectoderm commitment, thereby providing a novel insight into lineage commitment and stem cell-based epithelial regeneration.

Objective·To investigate the changes in transcriptome and chromatin accessibility during the differentiation of human embryonic stem cells (hESCs) into neural progenitor cells (NPCs) using in vitro differentiation models and high-throughput multi-omics sequencing technologies.Methods·hESCs were first induced to differentiate into NPCs in vitro using the embryoid body formation method, and cells at both stages were collected. The cell phenotypes were identified by reverse transcription-quantitative real-time PCR (RT-qPCR) and immunofluorescence (IF) staining. Transcriptome sequencing (RNA-seq) was conducted to detect and analyze the differentially expressed genes (DEGs) between hESCs and NPCs. The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) was employed to assess chromatin accessibility changes between hESCs and NPCs. Motif enrichment analysis was performed on differentially accessible chromatin regions to discover potential regulatory transcription factors. Finally, an integrated analysis of RNA-seq and ATAC-seq data and the protein-protein interaction (PPI) network were performed to identify key genes and regulatory pathways involved in the early stages of neural differentiation in vitro.Results·Both RT-qPCR and IF results indicated that the expression levels of pluripotency markers (NANOG and POU5F1) were high at the hESC stage but significantly decreased at the NPC stage, while early neural differentiation markers (PAX6, SOX1, and NES) were minimally expressed at the hESC stage but markedly upregulated at the NPC stage. RNA-seq analysis revealed that compared to the hESC stage, there were 5 597 genes upregulated and 3 654 genes downregulated at the NPC stage. Gene function enrichment analysis showed that the upregulated genes at the NPC stage were enriched in the functions related to neural development. ATAC-seq analysis demonstrated a total of 27 491 genomic regions had significant changes in chromatin accessibility during the differentiation from hESC to NPC, with 12 381 regions showing increased accessibility and 15 110 regions showing decreased accessibility. Motif enrichment analysis revealed that transcription factor genes such as DLX1 and LHX2 might play an important role in the differentiation process from hESCs into NPCs. Integrated analysis of RNA-seq and ATAC-seq data revealed that overlapping genes with high expression at the NPC stage were mainly enriched in axon guidance, forebrain development, and neuron migration. After neural differentiation, the expression levels of CTNND2 and LHX2 genes increased, and the chromatin accessibility of related genomic regions also increased. PPI network analysis indentified candidate downstream genes including PRKACA, CDH2, and ERBB4.Conclusion·The in vitro differentiation model of hESCs combined with high-throughput multi-omics sequencing technologies can be used to depict the changes in transcriptome and chromatin accessibility during the differentiation of hESCs into NPCs. In this process, the expression levels of genes related to axon guidance, forebrain development, and neuronal migration pathways increase and related chromatin accessibility is enhanced.

The effect of immunotherapy for colorectal cancer (CRC) is limited due to anti-tumor immunosuppression. Circular RNAs (circRNAs) are also associated with tumor immunity. The aim of this study was to clarify the regulatory relationship between circRNA and anti-tumor immunosuppression in CRC. CircRNAs associated with CRC were identified using bioinformatic analysis and subsequently confirmed in clinical samples using qRT-PCR and in situ hybridization. The expression, clinical relevance, functional significance and clinical properties of circMVP in CRC specimens and cells were evaluated in vitro and in vivo. RNA pull-down, single-cell RNA sequencing, EMSA, RNA immunoprecipitation, chromatin immunoprecipitation, and polysome profiling assay were performed to confirm the underlying mechanism of circRNA. CircMVP (hsa_circ_0000688) expression was increased in CRC and correlated with poor prognosis in CRC patients. Increased circMVP expression activates proliferation, invasion, and tumorigenesis of CRC. In addition, we found that circMVP, by interacting with METTL3, stabilizes its expression in the nucleus and significantly enhances its mediated N6-methyladenosine (m6A) modification. Specifically, circMVP/METTL3 promoted the expression of (3-catenin by directly acting on CTNNB1 mRNA. CircMVP/METTL3 further enhanced the expression of B7-H3 through the (3-catenin signaling pathway. Notably, inhibition of circMVP expression significantly improved the efficacy of anti-B7-H3 immunotherapy in in vivo and in vitro models. CircMVP mediated CTNNB1 m6A modification by promoting METTL3 activation and inhibited B7-H3-dependent anti-tumor immune response in CRC. In conclusion, circMVP may be a predictor of CRC immune evasion and a potential therapeutic target.

Manzufei decoction (MZFD) effectively treats COPD, but its mechanisms are unclear. Combining network pharmacology and experimental validation, we identified 168 bioactive components in MZFD and 265 potential targets. Network analysis pinpointed 4 core compounds. Comparing 1167 COPD-related targets revealed 114 overlapping therapeutic targets. Enrichment analysis implicated key pathways, notably AKT signaling. Molecular docking confirmed strong binding of quercetin to AKT and MUC5AC. Animal studies demonstrated that MZFD inhibits AKT signaling pathway activation, reduces MUC5AC protein expression in lung tissue and lung inflammation, thereby alleviating lung injury in AECOPD model rats.

Single-modality neuroimaging data often provide limited information and are constrained by technical issues such as signal-to-noise ratio, and resolution limitations, potentially leading to biases and an incomplete understanding of brain complexities. This can hinder the development of diagnostic and therapeutic strategies for brain disorders. To address these challenges, this paper presents the Multimodal Graph Neural Network Model based on Feature Fusion (MMP-DGNN), which leverages sMRI and PET data. The model employs an algorithm to extract and accurately describe sample features using an autoencoder. During feature fusion, a shared adjacency matrix based on feature similarity and phenotypic data is constructed for graph representation. A dual-layer graph neural network then classifies the features, with the results fused at the decision layer for final classification. Experimental results show that MMP-DGNN achieves superior classification performance of 98.17%, outperforming other methods in multimodal neuroimaging data classification.

The dynamics of chromatin conformation involve continuous and reversible changes within the nucleus of a cell, which participate in regulating processes such as gene expression, DNA replication, and damage repair. Here, SEE is introduced, an artificial intelligence (AI) method that utilizes autoencoder and transformer techniques to analyze chromatin dynamics using single-cell RNA sequencing data and a limited number of single-cell Hi-C maps. SEE is employed to investigate chromatin dynamics across different scales, enabling the detection of (i) rearrangements in topologically associating domains (TADs), and (ii) oscillations in chromatin interactions at gene loci. Additionally, SEE facilitates the interpretation of disease-associated single-nucleotide polymorphisms (SNPs) by leveraging the dynamic features of chromatin conformation. Overall, SEE offers a single-cell, high-resolution approach to analyzing chromatin dynamics in both developmental and disease contexts.

ABSTRACTPowassan virus (POWV) is a tick-borne flavivirus known for causing fatal neuroinvasive diseases in humans. Recently, there has been a noticeable increase in POWV infections, emphasizing the urgency of understanding viral replication, pathogenesis, and developing interventions. Notably, there are no approved vaccines or therapeutics for POWV, and its classification as a biosafety level-3 (BSL-3) agent hampers research. To overcome these obstacles, we developed a replicon system, a self-replicating RNA lacking structural proteins, making it safe to operate in a BSL-2 environment. We constructed a POWV replicon carrying the Gaussia luciferase (Gluc) reporter gene and blasticidin (BSD) selectable marker. Continuous BSD selection led to obtain a stable POWV replicon-carrying Huh7 cell lines. We identified cell culture adaptive mutations G4079A, G4944T and G6256A, resulting in NS2AR195K, NS3G122G, and NS3V560M, enhancing RNA replication. We demonstrated the utility of the POWV replicon system for high-throughput screening (HTS) assay to identify promising antivirals against POWV replication. We further explored the applications of the POWV replicon system, generating single-round infectious particles (SRIPs) by transfecting Huh7-POWV replicon cells with plasmids encoding viral capsid (C), premembrane (prM), and envelope (E) proteins, and revealed the distinct antigenic profiles of POWV with ZIKV. In summary, the POWV replicon and SRIP systems represent crucial platforms for genetic and functional analysis of the POWV life cycle and facilitating the discovery of antiviral drugs.IMPORTANCEIn light of the recent surge in human infections caused by POWV, a biosafety level-3 (BSL-3) classified virus, there is a pressing need to understand the viral life cycle and the development of effective countermeasures. To address this, we have pioneered the establishment of a POWV RNA replicon system and a replicon-based POWV SRIP system. Importantly, these systems are operable in BSL-2 laboratories, enabling comprehensive investigations into the viral life cycle and facilitating antiviral screening. In summary, these useful tools are poised to advance our understanding of the POWV life cycle and expedite the development of antiviral interventions.

Therapy‐induced senescence can regulate both the innate and adaptive immune systems, thereby affecting therapeutic efficacy. Bleomycin is a major component of combined chemotherapy regimens, utilized for the treatment of multiple tumors, whereas pulmonary toxicity severely restricts its clinical benefits. As a member of the bleomycin family, boningmycin (BON) exhibits potent anticancer activity with minimal pulmonary toxicity, making it a potential alternative to bleomycin. Low concentrations of BON can induce senescence, but the impact of BON‐induced senescence on anticancer immunity remains unclear. This study investigates the effects of BON‐induced senescence on PD‐L1 expression and the underlying mechanisms in human cancer cells. Firstly, the elevation of PD‐L1 protein during BON‐induced senescence was confirmed by a senescence β‐galactosidase staining assay, detection of the senescence‐associated secretory phenotype (SASP), western blot and flow cytometry in human lung cancer NCI‐H460 cells and breast cancer MDA‐MB‐231 cells. Subsequently, it was shown that the increase in PD‐L1 protein is mediated by SASP, as evidenced by the use of conditional media, knockdown of cyclic GMP‐AMP synthase and inhibition of stimulator of interferon genes. Ultimately, it was demonstrated that SASP‐mediated PD‐L1 up‐regulation is dependent on the activation of the JAK/STAT pathway through the use of specific inhibitors and siRNAs. These findings clarify the impact of BON‐induced senescence on PD‐L1 expression and may contribute to the optimization of the therapeutic efficacy of bleomycin‐related compounds and the clinical transformation of BON.

Despite intense research on mice, the transcriptional regulation of neocortical neurogenesis remains limited in humans and non-human primates. Cortical development in rhesus macaque is known to recapitulate multiple facets of cortical development in humans, including the complex composition of neural stem cells and the thicker supragranular layer. To characterize temporal shifts in transcriptomic programming responsible for differentiation from stem cells to neurons, we sampled parietal lobes of rhesus macaque at E40, E50, E70, E80, and E90, spanning the full period of prenatal neurogenesis. Single-cell RNA sequencing produced a transcriptomic atlas of developing parietal lobe in rhesus macaque neocortex. Identification of distinct cell types and neural stem cells emerging in different developmental stages revealed a terminally bifurcating trajectory from stem cells to neurons. Notably, deep-layer neurons appear in the early stages of neurogenesis, while upper-layer neurons appear later. While these different lineages show overlap in their differentiation program, cell fates are determined post-mitotically. Trajectories analysis from ventricular radial glia (vRGs) to outer radial glia (oRGs) revealed dynamic gene expression profiles and identified differential activation of BMP, FGF, and WNT signaling pathways between vRGs and oRGs. These results provide a comprehensive overview of the temporal patterns of gene expression leading to different fates of radial glial progenitors during neocortex layer formation.

For many years, multi-scale models of chromatin domains, such as A/B compartments, sub-compartments, topologically associated domains (TADs), sub-TADs, and loops have been popular. However, existing methods can only identify structures at a single scale and cannot partition multi-scale structures. In this paper, we proposed a method (TORNADOES) for chromatin domain partitioning based on hypergraph clustering. First, we use a density clustering algorithm to identify TADs at different scales based on Hi-C data with different resolutions. Then, by combining ChIP-seq data features and TAD results at different scales, we generate a hypergraph based on these TADs. Finally, we partition the chromatin domain structure at different scales, including A/B, A1, A2, B1, B2, and B3 based on the Laplacian matrix feature of the hypergraph. Similarity comparison experiments and ChIP-seq signal enrichment analysis are performed on the A/B region and sub-TAD levels, respectively, demonstrating that our method can identify chromatin domains with distinct features and provide a deeper understanding of the organizational patterns and functional differences in TADs at the genomic hierarchical structure. Comparative analysis of multiple cell line data shows that TORNADOES can better classify different numbers and types of compartments by changing the factors ChIP-seq data and clustering number used to characterize TAD compared to other methods. Source code for the TORNADOES method can be found at https://github.com/ghaiyan/TORNADOES.

Metastasis continues to negatively impact individuals diagnosed with colorectal cancer (CRC). Research has revealed the important role of long noncoding RNAs (lncRNAs) in CRC metastasis, but the underlying mechanisms remain unclear. Here, we revealed that the lncRNA small nucleolar RNA host gene 1 (SNHG1) is expressed at higher levels in metastatic CRC tissues than in primary CRC tissues, and that high lncRNA SNHG1 expression indicates poor patient outcomes. We found that lncRNA SNHG1 promotes the migration and invasion of tumor cells both in vivo and in vitro. Moreover, lncRNA SNHG1 increases serpin family A member 3 (SERPINA3) mRNA stability by interacting with the heterogeneous nuclear ribonucleoprotein D (HNRNPD) protein, and subsequently upregulates SERPINA3 expression. Moreover, HNRNPD and SERPINA3 reversed the effects of lncRNA SNHG1 knockdown on CRC cell metastasis. In conclusion, we report that the lncRNA SNHG1 recruits HNRNPD, in turn upregulating SERPINA3 expression and ultimately facilitating CRC cell migration and invasion. Targeting the lncRNA SNHG1/HNRNPD/SERPINA3 signaling pathway might be a therapeutic option for preventing CRC metastasis.

Deciphering cell-type-specific 3D structures of chromatin is challenging. Here, we present InferLoop, a novel method for inferring the strength of chromatin interaction using single-cell chromatin accessibility data. The workflow of InferLoop is, first, to conduct signal enhancement by grouping nearby cells into bins, and then, for each bin, leverage accessibility signals for loop signals using a newly constructed metric that is similar to the perturbation of the Pearson correlation coefficient. In this study, we have described three application scenarios of InferLoop, including the inference of cell-type-specific loop signals, the prediction of gene expression levels and the interpretation of intergenic loci. The effectiveness and superiority of InferLoop over other methods in those three scenarios are rigorously validated by using the single-cell 3D genome structure data of human brain cortex and human blood, the single-cell multi-omics data of human blood and mouse brain cortex, and the intergenic loci in the GWAS Catalog database as well as the GTEx database, respectively. In addition, InferLoop can be applied to predict loop signals of individual spots using the spatial chromatin accessibility data of mouse embryo. InferLoop is available at https://github.com/jumphone/inferloop.

In Asia, the proportion of patients with irritable bowel syndrome (IBS) with abdominal discomfort alone is significantly higher than that in western countries. The purposes of this study are to understand the cognition of abdominal pain and abdominal discomfort in Chinese patients with IBS and to compare the clinical characteristics of patients with abdominal pain alone and with abdominal discomfort alone. Patients with IBS with diarrhea (IBS-D) who met the Rome III diagnostic criteria and had episodes of at least one day/week were consecutively enrolled. The cognition of abdominal pain and abdominal discomfort were investigated through face-to-face unstructured interview. Patients were divided into a pain group and a discomfort group according to the cognition interviews, then the characteristics and severity of symptoms (IBS symptom severity scale, IBS-SSS), IBS quality of life (IBS-QOL) and psychological state were compared between groups. A total of 88 patients with IBS-D were enrolled. Most of the patients with self-reported abdominal pain described their pain as spasm/cramping; patients with self-reported abdominal discomfort had as many as 24 different descriptions of discomfort. Most patients having abdominal pain and discomfort could accurately distinguish the two symptoms. The degree of abdominal pain in the pain group was higher than abdominal discomfort in the discomfort group (P = 0.002). There was no significant difference in IBS-SSS, extra-intestinal pain, IBS-QOL, and psychological state between the two groups. For Chinese patients with IBS-D, abdominal pain and abdominal discomfort are two different symptoms, but they have similar clinical features. ChiCTR, ChiCTR1900028082. Registered 11 December 2019 - Retrospectively registered, http://www.chictr.org.cn .

Abstract. Background:. Exercise, as the cornerstone of pulmonary rehabilitation, is recommended to chronic obstructive pulmonary disease (COPD) patients. The underlying molecular basis and metabolic process were not fully elucidated. Methods:. Sprague-Dawley rats were classified into five groups: non-COPD/rest (n = 8), non-COPD/exercise (n = 7), COPD/rest (n = 7), COPD/medium exercise (n = 10), and COPD/intensive exercise (n = 10). COPD animals were exposed to cigarette smoke and lipopolysaccharide instillation for 90 days, while the non-COPD control animals were exposed to room air. Non-COPD/exercise and COPD/medium exercise animals were trained on a treadmill at a decline of 5° and a speed of 15 m/min while animals in the COPD/intensive exercise group were trained at a decline of 5° and a speed of 18 m/min. After eight weeks of exercise/rest, we used ultrasonography, immunohistochemistry, transmission electron microscopy, oxidative capacity of mitochondria, airflow-assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI), and transcriptomics analyses to assess rectal femoris (RF). Results:. At the end of 90 days, COPD rats’ weight gain was smaller than control by 59.48 ± 15.33 g (P = 0.0005). The oxidative muscle fibers proportion was lower (P < 0.0001). At the end of additional eight weeks of exercise/rest, compared to COPD/rest, COPD/medium exercise group showed advantages in weight gain, femoral artery peak flow velocity (Δ58.22 mm/s, 95% CI: 13.85–102.60 mm/s, P = 0.0104), RF diameters (Δ0.16 mm, 95% CI: 0.04–0.28 mm, P = 0.0093), myofibrils diameter (Δ0.06 μm, 95% CI: 0.02–0.10 μm, P = 0.006), oxidative muscle fiber percentage (Δ4.84%, 95% CI: 0.15–9.53%, P = 0.0434), mitochondria oxidative phosphorylate capacity (P < 0.0001). Biomolecules spatial distribution in situ and bioinformatic analyses of transcriptomics suggested COPD-related alteration in metabolites and gene expression, which can be impacted by exercise. Conclusion:. COPD rat model had multi-level structure and function impairment, which can be mitigated by exercise.

Stress-elevated glucocorticoids cause circadian disturbances and gut-brain axis (GBA) disorders, including irritable bowel syndrome (IBS). We hypothesized that the glucocorticoid receptor (GR/NR3C1) might cause chromatin circadian misalignment in the colon epithelium. We observed significantly decreased core circadian gene Nr1d1 in water avoidance stressed (WAS) BALB/c colon epithelium, like in IBS patients. WAS decreased GR binding at the Nr1d1 promoter E-box (enhancer box), and GR could suppress Nr1d1 via this site. Stress also altered GR binding at the E-box sites along the Ikzf3-Nr1d1 chromatin and remodeled circadian chromatin 3D structures, including Ikzf3-Nr1d1 super-enhancer, Dbp, and Npas2. Intestinal deletion of Nr3c1 specifically abolished these stress-induced transcriptional alternations relevant to IBS phenotypes in BALB/c mice. GR mediated Ikzf3-Nr1d1 chromatin disease related circadian misalignment in stress-induced IBS animal model. This animal model dataset suggests that regulatory SNPs of human IKZF3-NR1D1 transcription through conserved chromatin looping have translational potential based on the GR-mediated circadian-stress crosstalk.

Here, we present a protocol for calculating the spatial density of regulatory chromatin interactions (SD-RCI) using Hi-C, ATAC-seq, and ChIP-seq datasets from the same cell line. We describe steps for selecting and preprocessing datasets, training and predicting a model to obtain regulatory chromatin interactions, and evaluating model performance. We then detail calculation of SD-RCI and visualization of the correlation between SD-RCI and gene expression. This protocol is applicable to Hi-C, ATAC-seq, and ChIP-seq data from the human cell line. For complete details on the use and execution of this protocol, please refer to Gong et al. (2023).1

Chromatin interactions play essential roles in chromatin conformation and gene expression. However, few tools exist to analyze the spatial density of regulatory chromatin interactions (SD-RCI). Here, we present the multi-modal network (MINE) toolkit, including MINE-Loop, MINE-Density, and MINE-Viewer. The MINE-Loop network aims to enhance the detection of RCIs, MINE-Density quantifies the SD--RCI, and MINE-Viewer facilitates 3D visualization of the density of chromatin interactions and participating regulatory factors (e.g., transcription factors). We applied MINE to investigate the relationship between the SD-RCI and chromatin volume change in HeLa cells before and after liquid-liquid phase separation. Changes in SD-RCI before and after treating the HeLa cells with 1,6-hexanediol suggest that changes in chromatin organization was related to the degree of activation or repression of genes. Together, the MINE toolkit enables quantitative studies on different aspects of chromatin conformation and regulatory activity.

Background: As parts of the cis-regulatory mechanism of the human genome, interactions between distal enhancers and proximal promoters play a crucial role. Enhancers, promoters, and enhancer-promoter interactions (EPIs) can be detected using many sequencing technologies and computation models. However, a systematic review that summarizes these EPI identification methods and that can help researchers apply and optimize them is still needed. Results: In this review, we first emphasize the role of EPIs in regulating gene expression and describe a generic framework for predicting enhancer-promoter interaction. Next, we review prediction methods for enhancers, promoters, loops, and enhancer-promoter interactions using different data features that have emerged since 2010, and we summarize the websites available for obtaining enhancers, promoters, and enhancer-promoter interaction datasets. Finally, we review the application of the methods for identifying EPIs in diseases such as cancer. Conclusions: The advance of computer technology has allowed traditional machine learning, and deep learning methods to be used to predict enhancer, promoter, and EPIs from genetic, genomic, and epigenomic features. In the past decade, models based on deep learning, especially transfer learning, have been proposed for directly predicting enhancer-promoter interactions from DNA sequences, and these models can reduce the parameter training time required of bioinformatics researchers. We believe this review can provide detailed research frameworks for researchers who are beginning to study enhancers, promoters, and their interactions.

The quantification of developmental potential is critical for determining developmental stages and identifying essential molecular signatures in single-cell studies. Here, we present FitDevo, a novel method for inferring developmental potential using scRNA-seq data. The main idea of FitDevo is first to generate sample-specific gene weight (SSGW) and then infer developmental potential by calculating the correlation between SSGW and gene expression. SSGW is generated using a generalized linear model that combines sample-specific information and gene weight learned from a training dataset covering scRNA-seq data of 17 previously published datasets. We have rigorously validated FitDevo's effectiveness using a testing dataset with scRNA-seq data from 28 existing datasets and have also demonstrated its superiority over current methods. Furthermore, FitDevo's broad application scope has been illustrated using three practical scenarios: deconvolution analysis of epidermis, spatial transcriptomic data analysis of hearts and intestines, and developmental potential analysis of breast cancer. The source code and related data are available at https://github.com/jumphone/ fitdevo.

MicroRNAs (miRNAs) participate in the comprehensive biological process of several cancer types. In our former study, we found that hsa-microRNA- (miR-)28-5p was downregulated, but tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activating protein zeta (14-3-3ζ or YWHAZ) was upregulated in diffuse large B-cell lymphoma (DLBCL) tissues. We predicted that YWHAZ was a target gene for hsa-miR- 28-5p using bioinformatics analysis. Our goal was to reveal the role of hsa-miR-28-5p in DLBCL. YWHAZ was tested by immunohistochemistry (IHC) in formalin-fixed paraffin-embedded (FFPE) tissues of 137 DLBCL tissues, and the expression of hsa-miR-28-5p and YWHAZ was examined by quantitative real-time polymerase chain reaction (qRT-PCR) in 15 fresh and frozen DLBCL tissues. To study the functional roles of the downregulated hsa-miR-28-5p in DLBCL, a Cell Counting Kit-8 assay was conducted to estimate cell proliferation. Transient transfection of miRNA mimics was performed to overexpress hsa-miR-28-5p, and flow cytometry was performed to examine cell apoptosis and cell cycle progression. A dual-luciferase reporter assay was employed to explore the relationship between hsa-miR-28-5p and YWHAZ. Western blotting and qRT-PCR were used to investigate the function of hsa-miR-28-5p in YWHAZ expression. hsa-miR-28-5p was found to be significantly downregulated in DLBCL tissues and cell lines. Functional studies showed that hsa-miR-28-5p overexpression inhibited cell viability and proliferation, and YWHAZ was predicted to be a target of hsa-miR-28-5p. Dual-luciferase reporter assay, Western blotting, and qRT-PCR verified that hsa-miR-28-5p negatively regulated YWHAZ expression by directly targeting its 3′ untranslated regions in DLBCL cells. hsa-miR-28-5p may suppress the growth of DLBCL cells by inhibiting YWHAZ expression. These findings could provide novel targets for DLBCL diagnosis and therapy.