Universal subunit vaccine protects against multiple SARS-CoV-2 variants and SARS-CoV.

Although Omicron RBD of SARS-CoV-2 accumulates many mutations, the backbone region (truncated RBD) of spike protein is highly conserved. Here, we designed several subunit vaccines by keeping the conserved spike backbone region of SARS-CoV-2 Omicron BA.1 subvariant (S-6P-no-RBD), or inserting the RBD of Delta variant (S-6P-Delta-RBD), Omicron (BA.5) variant (S-6P-BA5-RBD), or ancestral SARS-CoV-2 (S-6P-WT-RBD) to the above backbone construct, and evaluated their ability to induce immune responses and cross-protective efficacy against various SARS-CoV-2 variants and SARS-CoV. Among the four subunit vaccines, S-6P-Delta-RBD protein elicited broad and potent neutralizing antibodies against all SARS-CoV-2 variants tested, including Alpha, Beta, Gamma, and Delta variants, the BA.1, BA.2, BA.2.75, BA.4.6, and BA.5 Omicron subvariants, and the ancestral strain of SARS-CoV-2. This vaccine prevented infection and replication of SARS-CoV-2 Omicron, and completely protected immunized mice against lethal challenge with the SARS-CoV-2 Delta variant and SARS-CoV. Sera from S-6P-Delta-RBD-immunized mice protected naive mice against challenge with the Delta variant, with significantly reduced viral titers and without pathological effects. Protection correlated positively with the serum neutralizing antibody titer. Overall, the designed vaccine has potential for development as a universal COVID-19 vaccine and/or a pan-sarbecovirus subunit vaccine that will prevent current and future outbreaks caused by SARS-CoV-2 variants and SARS-related CoVs.

A lactate-responsive gene signature predicts the prognosis and immunotherapeutic response of patients with triple-negative breast cancer.

Background: Increased glycolytic activity and lactate production are characteristic features of triple-negative breast cancer (TNBC). The aim of this study was to determine whether a subset of lactate-responsive genes (LRGs) could be used to classify TNBC subtypes and predict patient outcomes. Methods: Lactate levels were initially measured in different breast cancer (BC) cell types. Subsequently, MDA-MB-231 cells treated with 2-Deoxy-d-glucose or l-lactate were subjected to RNA sequencing (RNA-seq). The gene set variation analysis algorithm was utilized to calculate the lactate-responsive score, conduct a differential analysis, and establish an association with the extent of immune infiltration. Consensus clustering was then employed to classify TNBC patients. Tumor immune dysfunction and exclusion, cibersort, single-sample gene set enrichment analysis, and EPIC, were used to compare the tumor-infiltrating immune cells between TNBC subtypes and predict the response to immunotherapy. Furthermore, a prognostic model was developed by combining 98 machine learning algorithms, to assess the predictive significance of the LRG signature. The predictive value of immune infiltration and the immunotherapy response was also assessed. Finally, the association between lactate and various anticancer drugs was examined based on expression profile similarity principles. Results: We found that the lactate levels of TNBC cells were significantly higher than those of other BC cell lines. Through RNA-seq, we identified 14 differentially expressed LRGs in TNBC cells under varying lactate levels. Notably, this LRG signature was associated with interleukin-17 signaling pathway dysregulation, suggesting a link between lactate metabolism and immune impairment. Furthermore, the LRG signature was used to categorize TNBC into two distinct subtypes, whereby Subtype A was characterized by immunosuppression, whereas Subtype B was characterized by immune activation. Conclusion: We identified an LRG signature in TNBC, which could be used to predict the prognosis of patients with TNBC and gauge their response to immunotherapy. Our findings may help guide the precision treatment of patients with TNBC.

A Unique mRNA Vaccine Elicits Protective Efficacy against the SARS-CoV-2 Omicron Variant and SARS-CoV.

The highly pathogenic coronaviruses SARS-CoV-2 and SARS-CoV have led to the COVID-19 pandemic and SARS outbreak, respectively. The receptor-binding domain (RBD) of the spike (S) protein of SARS-CoV-2, particularly the Omicron variant, has frequent mutations, resulting in the reduced efficiency of current COVID-19 vaccines against new variants. Here, we designed two lipid nanoparticle-encapsulated mRNA vaccines by deleting the mutant RBD of the SARS-CoV-2 Omicron variant (SARS2-S (RBD-del)) or by replacing this mutant RBD with the conserved and potent RBD of SARS-CoV (SARS2-S (SARS-RBD)). Both mRNA vaccines were stable at various temperatures for different time periods. Unlike SARS2-S (RBD-del) mRNA, SARS2-S (SARS-RBD) mRNA elicited effective T-cell responses and potent antibodies specific to both SARS-CoV-2 S and SARS-CoV RBD proteins. It induced strong neutralizing antibodies against pseudotyped SARS-CoV-2 and SARS-CoV infections and protected immunized mice from the challenge of the SARS-CoV-2 Omicron variant and SARS-CoV by significantly reducing the viral titers in the lungs after Omicron challenge and by completely preventing SARS-CoV-induced weight loss and death. SARS2-S (SARS-RBD)-immunized serum antibodies protected naïve mice from the SARS-CoV challenge, with its protective efficacy positively correlating with the neutralizing antibody titers. These findings indicate that this mRNA vaccine has the potential for development as an effective vaccine against current and future SARS-CoV-2 variants and SARS-CoV.

Data-mining framework for in-depth quantitative study of influences on low-wind-velocity area from morphological parameters of cuboid-form buildings.

Wind environment is important in architectural sustainable design, as existing studies show that it can be considerably influenced by building morphologies. This study aimed to develop a data-mining framework to quantitatively evaluate and compare influences on Low-Wind-Velocity Area (LWVA) of common cuboid-form buildings with typical morphological parameters. The data-mining framework was originally developed by integrating multiple computational methods for rapid in-depth iterative analyses, including the generation of building models using parametric modelling, the big data generation based on hybrid model, and the statistical metric analysis method. The hybrid model was created by combining the CFD model and machine learning model. The accuracy and efficiency of the framework were fully demonstrated through the comprehensive validation and analyses of different models. The data of more than fifty thousand building cases with different morphological parameters and relevant wind conditions were generated and analyzed. Influences on LWVA of morphological parameters of cuboid-form building was comprehensively evaluated, including the visualization of multiple parameters, calculation and comparison of several correlation coefficients. It suggested that the reduction of height and width on the windward side would significantly decrease the LWVA and promote the outdoor ventilation. The change of depth would have relatively limited influence on the LWVA. Multivariate regression model-fit and variance analyses were further implemented, and it was found that there was a relatively significant linear correlation between the LWVA and morphological parameters. The equation of multivariate regression model was provided for extra rapid prediction. The study outcome could contribute to efficient evaluation of LWVA and provide useful information for sustainable design.

METTL3 orchestrates glycolysis by stabilizing the c-Myc/WDR5 complex in triple-negative breast cancer.

BACKGROUND: The carcinogenic transcription factor c-Myc is the most aggressive oncogene, which drive malignant transformation and dissemination of triple-negative breast cancer (TNBC). Recruitment of many cofactors, especially WDR5, a protein that nucleates H3K4me chromatin modifying complexes, play a pivotal role in regulating c-Myc-dependent gene transcription, a critical process for c-Myc signaling to function in a variety of biological and pathological contexts. For this reason, interrupting the interaction between c-Myc and the transcription cofactor WDR5 may become the most promising new strategy for treating c-Myc driven TNBC. METHODS: Immunoprecipitation and mass spectrometry (IP-MS) is used to screen proteins that bind c-Myc/WDR5 interactions. The interaction of METTL3 with c-Myc/WDR5 in breast cancer tissues and TNBC cells was detected by Co-IP and immunofluorescence. Subsequently, we further analyzed the influence of METTL3 expression on c-Myc/WDR5 protein expression and its interaction stability by Western blot and Co-IP. The correlation between METTL3 and c-Myc pathway was analyzed by ChIP-seq sequencing and METTL3 knockdown transcriptome data. The effect of METTL3 expression on c-Myc transcriptional activity was detected by ChIP-qPCR and Dual Luciferase Reporter. At the same time, the overexpression vector METTL3-MUT (m6A) was constructed, which mutated the methyltransferase active site (Aa395-398, DPPW/APPA), and further explored whether the interaction between METTL3 and c-Myc/WDR5 was independent of methyltransferase activity. In addition, we also detected the changes of METTL3 expression on TNBC's sensitivity to small molecule inhibitors such as JQ1 and OICR9429 by CCK8, Transwell and clonal formation assays. Finally, we further verified our conclusions in spontaneous tumor formation mouse MMTV-PyMT and nude mouse orthotopic transplantation tumor models. RESULTS: METTL3 was found to bind mainly to c-Myc/WDR5 protein in the nucleus. It enhances the stability of c-Myc/WDR5 interaction through its methyltransferase independent mechanism, thereby enhancing the transcriptional activity of c-Myc on downstream glucose metabolism genes. Notably, the study also confirmed that METTL3 can directly participate in the transcription of glucose metabolism genes as a transcription factor, and knockdown METTL3 enhances the drug sensitivity of breast cancer cells to small molecule inhibitors JQ1 and OICR9429. The study was further confirmed by spontaneous tumor formation mouse MMTV-PyMT and nude mouse orthotopic transplantation tumor models. CONCLUSION: METTL3 binds to the c-Myc/WDR5 protein complex and promotes glycolysis, which plays a powerful role in promoting TNBC progression. Our findings further broaden our understanding of the role and mechanism of action of METTL3, and may open up new therapeutic avenues for effective treatment of TNBC with high c-Myc expression.

Associations of pyrethroid exposure with bone mineral density and osteopenia in adults.

INTRODUCTION: This study was to investigate the correlations between pyrethroid exposure and bone mineral density (BMD) and osteopenia. MATERIALS AND METHODS: This cross-sectional study included 1389 participants over 50 years of age drawn from the 2007-2010 and 2013-2014 National Health and Nutrition Examination Survey (NHANES). Three pyrethroid metabolites, 3-phenoxybenzoic acid (3-PBA), trans-3-(2,2-dichlorovinyl)-2,2-dimethyl-cyclopropane-1-carboxylic acid (trans-DCCA), and 4-fluoro-3-phenoxybenzoic acid (4-F-3PBA) were used as indicators of pyrethroid exposure. Low BMD was defined as T-score < - 1.0, including osteopenia. Weighted multivariable linear regression analysis or logistic regression analysis was utilized to evaluate the correlation between pyrethroid exposure and BMD and low BMD. Bayesian kernel machine regression (BKMR) model was utilized to analyze the correlation between pyrethroids mixed exposure and low BMD. RESULTS: There were 648 (48.41%) patients with low BMD. In individual pyrethroid metabolite analysis, both tertile 2 and tertile 3 of trans-DCCA were negatively related to total femur, femur neck, and total spine BMD [coefficient (ß) = - 0.041 to - 0.028; all P < 0.05]. Both tertile 2 and tertile 3 of 4-F-3PBA were negatively related to total femur BMD (P < 0.05). Only tertile 2 [odds ratio (OR) = 1.63; 95% CI = 1.07, 2.48] and tertile 3 (OR = 1.65; 95% CI = 1.10, 2.50) of trans-DCCA was correlated with an increased risk of low BMD. The BKMR analysis indicated that there was a positive tendency between mixed pyrethroids exposure and low BMD. CONCLUSION: In conclusion, pyrethroids exposure was negatively correlated with BMD levels, and the associations of pyrethroids with BMD and low BMD varied by specific pyrethroids, pyrethroid concentrations, and bone sites.

A T cell-based SARS-CoV-2 spike protein vaccine provides protection without antibodies.

SARS-CoV-2 spike-based vaccines are used to control the COVID-19 pandemic. However, emerging variants have become resistant to antibody neutralization and further mutations may lead to full resistance. We tested whether T cells alone could provide protection without antibodies. We designed a T cell-based vaccine in which SARS-CoV-2 spike sequences were rearranged and attached to ubiquitin. Immunization of mice with the vaccine induced no specific antibodies, but strong specific T cell responses. We challenged mice with SARS-CoV-2 wild-type strain or an Omicron variant after the immunization and monitored survival or viral titers in the lungs. The mice were significantly protected against death and weight loss caused by the SARS-CoV-2 wild-type strain, and the viral titers in the lungs of mice challenged with the SARS-CoV-2 wild-type strain or the Omicron variant were significantly reduced. Importantly, depletion of CD4+ or CD8+ T cells led to significant loss of the protection. Our analyses of spike protein sequences of the variants indicated that fewer than one-third presented by dominant HLA alleles were mutated and that most of the mutated epitopes were in the subunit 1 region. As the subunit 2 region is conservative, the vaccines targeting spike protein are expected to protect against future variants due to the T cell responses.

Blocking Ubiquitin-Specific Protease 7 Induces Ferroptosis in Gastric Cancer via Targeting Stearoyl-CoA Desaturase.

Gastric cancer (GC) presents a formidable global health challenge, and conventional therapies face efficacy limitations. Ubiquitin-specific protease 7 (USP7) plays pivotal roles in GC development, immune response, and chemo-resistance, making it a promising target. Various USP7 inhibitors have shown selectivity and efficacy in preclinical studies. However, the mechanistic role of USP7 has not been fully elucidated, and currently, no USP7 inhibitors have been approved for clinical use. In this study, DHPO is identified as a potent USP7 inhibitor for GC treatment through in silico screening. DHPO demonstrates significant anti-tumor activity in vitro, inhibiting cell viability and clonogenic ability, and preventing tumor migration and invasion. In vivo studies using orthotopic gastric tumor mouse models validate DHPO's efficacy in suppressing tumor growth and metastasis without significant toxicity. Mechanistically, DHPO inhibition triggers ferroptosis, evidenced by mitochondrial alterations, lipid Reactive Oxygen Species (ROS), Malondialdehyde (MDA) accumulation, and iron overload. Further investigations unveil USP7's regulation of Stearoyl-CoA Desaturase (SCD) through deubiquitination, linking USP7 inhibition to SCD degradation and ferroptosis induction. Overall, this study identifies USP7 as a key player in ferroptosis of GC, elucidates DHPO's inhibitory mechanisms, and highlights its potential for GC treatment by inducing ferroptosis through SCD regulation.

XYA-2: a marine-derived compound targeting apoptosis and multiple signaling pathways in pancreatic cancer.

Background: Pancreatic cancer is a highly aggressive and fatal disease with limited treatment options and poor prognosis for patients. This study aimed to investigate the impact of XYA-2 {N-(3,7-dimethyl-2,6-octadienyl)-2-aza-2-deoxychaetoviridin A}, a nitrogenated azaphilon previously reported from a deep-sea-derived fungus on the progression of pancreatic cancer cells. Methods: The inhibitory effects of XYA-2 on cell proliferation, clonogenic potential, cell cycle progression, apoptosis, migration, and invasion were assessed using various assays. The CCK-8 assay, clone formation assay, flow cytometry assay, wound healing assay, and transwell assay were employed to evaluate cell proliferation, clonogenic potential, cell cycle progression, apoptosis, migration, and invasion, respectively. Moreover, we employed RNA-seq and bioinformatics analyses to uncover the underlying mechanism by which XYA-2 influences pancreatic cancer cells. The revealed mechanism was subsequently validated through qRT-PCR. Results: Our results demonstrated that XYA-2 dose-dependently inhibited the proliferation of pancreatic cancer cells and induced cell cycle arrest and apoptosis. Additionally, XYA-2 exerted a significant inhibitory effect on the invasion and migration of cancer cells. Moreover, XYA-2 was found to regulate the expression of genes involved in multiple cancer-related pathways based on our RNA-seq and bioinformatics analysis. Conclusion: These findings highlight the potential of XYA-2 as a promising therapeutic option for the treatment of pancreatic cancer.

An Uncertainty-Guided Deep Learning Method Facilitates Rapid Screening of CYP3A4 Inhibitors.

Cytochrome P450 3A4 (CYP3A4), a prominent member of the P450 enzyme superfamily, plays a crucial role in metabolizing various xenobiotics, including over 50% of clinically significant drugs. Evaluating CYP3A4 inhibition before drug approval is essential to avoiding potentially harmful pharmacokinetic drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Despite the development of several CYP inhibitor prediction models, the primary approach for screening CYP inhibitors still relies on experimental methods. This might stem from the limitations of existing models, which only provide deterministic classification outcomes instead of precise inhibition intensity (e.g., IC50) and often suffer from inadequate prediction reliability. To address this challenge, we propose an uncertainty-guided regression model to accurately predict the IC50 values of anti-CYP3A4 activities. First, a comprehensive data set of CYP3A4 inhibitors was compiled, consisting of 27,045 compounds with classification labels, including 4395 compounds with explicit IC50 values. Second, by integrating the predictions of the classification model trained on a larger data set and introducing an evidential uncertainty method to rank prediction confidence, we obtained a high-precision and reliable regression model. Finally, we use the evidential uncertainty values as a trustworthy indicator to perform a virtual screening of an in-house compound set. The in vitro experiment results revealed that this new indicator significantly improved the hit ratio and reduced false positives among the top-ranked compounds. Specifically, among the top 20 compounds ranked with uncertainty, 15 compounds were identified as novel CYP3A4 inhibitors, and three of them exhibited activities less than 1 µM. In summary, our findings highlight the effectiveness of incorporating uncertainty in compound screening, providing a promising strategy for drug discovery and development.

Research progress on antitumor mechanisms and molecular targets of Inula sesquiterpene lactones.

The pharmacological effects of natural product therapy have received sigificant attention, among which terpenoids such as sesquiterpene lactones stand out due to their biological activity and pharmacological potential as anti-tumor drugs. Inula sesquiterpene lactones are a kind of sesquiterpene lactones extracted from Inula species. They have many pharmacological activities such as anti-inflammation, anti-asthma, anti-tumor, neuroprotective and anti-allergic. In recent years, more and more studies have proved that they are important candidate drugs for the treatment of a variety of cancers because of its good anti-tumor activity. In this paper, the structure, structure-activity relationship, antitumor activities, mechanisms and targets of Inula sesquiterpene lactones reported in recent years were reviewed in order to provide clues for the development of novel anticancer drugs.

A benzochalcone derivative synchronously induces apoptosis and ferroptosis in pancreatic cancer cells.

Background: Pancreatic cancer is a highly aggressive and lethal disease with limited treatment options. In this study, we investigated the potential therapeutic effects of compound KL-6 on pancreatic cancer cells. Methods: The study involved assessing the inhibitory effects of KL-6 on cell proliferation, clonogenic potential, cell cycle progression, apoptosis, migration, and invasion. Additionally, we examined the action mechanism of KL-6 by RNA-seq and bioinformatic analysis and validated by qRT-PCR and western blot in pancreatic cancer cells. Results: Our results demonstrated that KL-6 effectively inhibited the growth of pancreatic cancer cells in a dose-dependent manner. It induced G2/M phase cell cycle arrest and apoptosis, disrupting the cell cycle progression and promoting cell death. KL-6 also exhibited inhibitory effects on cell migration and invasion, suggesting its potential to suppress the metastatic properties of pancreatic cancer cells. Furthermore, KL-6 modulated the expression of genes involved in various cancer-related pathways including apoptosis and ferroptosis. Conclusion: These findings collectively support the potential of KL-6 as a promising therapeutic option for pancreatic cancer treatment. Further research is needed to fully understand the underlying mechanisms and evaluate the clinical efficacy of KL-6 in pancreatic cancer patients.

Causal association of physical activity with low back pain, intervertebral disc degeneration and sciatica: a two-sample mendelian randomization analysis study.

Objective: Previous studies are insufficient to confirm a causal association between physical activity (PA) and low back pain (LBP), intervertebral disc degeneration (IDD), and sciatica. The present study used a two-sample Mendelian randomization (MR) analysis method to demonstrate whether or not there was a causal connection. Methods: First, four PA phenotypes were selected [accelerometer-based PA (average acceleration), accelerometer-based PA (acceleration fraction >425 mg), self-reported moderate-to-vigorous PA, and self-reported vigorous PA], setting thresholds for single nucleotide polymorphisms (SNPs) significantly concerned with PA p < 5 × 10-8, linkage disequilibrium (LD) r 2 < 0.01, genetic distance >5,000 kb, and F-value >10. SNPs associated with the outcome and confounding factors were then excluded using the PhenoScanncer database. Finally, after coordinating the genetic instruments from genome-wide association studies (GWAS) effect alleles for exposure and outcomes, multiplicative random effects inverse variance weighting (IVW), MR-Egger, weighted median method (WMM), and weighted mode method were used to assess exposure-outcome causality and perform sensitivity analysis on the estimated results. Results: The current study's IVW findings revealed proof of a causal connection between PA and LBP. While there was a positive causal tie between accelerometer-based PA (acceleration fraction >425 mg) and LBP [OR: 1.818, 95% CI:1.129-2.926, p = 0.012], there was a negative causal link between accelerometer-based PA (average acceleration) and LBP [OR: 0.945, 95% CI: 0.909-0.984, p = 0.005]. However causal relationship between PA and IDD or sciatica was not found. Conclusion: Increasing average PA but needing to avoid high-intensity PA may be an effective means of preventing low back pain. Although PA is not directly causally related to disc degeneration and sciatica, it can act through indirect pathways.

Glycosylated Delta-receptor-binding domain mucosal vaccine elicits broadly neutralizing antibodies with protection against SARS-CoV-2 challenge.

Mucosal COVID-19 vaccines are needed to block SARS-CoV-2 infection at the mucosal site. Intranasal delivery of a glycosylated Delta variant receptor-binding domain (Delta-RBD) mucosal vaccine elicited potent and balanced systemic antibody titers comparable to those induced by the intramuscular injection of the same vaccine or Omicron-S subunit vaccine, as well as high mucosal IgA antibody responses. It elicited broadly neutralizing antibodies against the original SARS-CoV-2 strain, Delta and Omicron BA1/BA2 variants, completely protecting transgenic mice from lethal challenge with a Delta variant, including complete absence of weight loss. Of note, intramuscular priming with the Omicron-S protein followed by intranasal boosting with the Delta-RBD protein improved the vaccine's ability to generate broad-spectrum neutralizing antibodies against recent BA5 and XBB Omicron variants. Overall, this vaccine has the potential to prevent the SARS-CoV-2 infection of the respiratory mucosa, while the i.m. priming and i.n. boosting vaccination strategy may offer protection against known and emerging SARS-CoV-2 variants.

GeoDILI: A Robust and Interpretable Model for Drug-Induced Liver Injury Prediction Using Graph Neural Network-Based Molecular Geometric Representation.

Drug-induced liver injury (DILI) is a significant cause of drug failure and withdrawal due to liver damage. Accurate prediction of hepatotoxic compounds is crucial for safe drug development. Several DILI prediction models have been published, but they are built on different data sets, making it difficult to compare model performance. Moreover, most existing models are based on molecular fingerprints or descriptors, neglecting molecular geometric properties and lacking interpretability. To address these limitations, we developed GeoDILI, an interpretable graph neural network that uses a molecular geometric representation. First, we utilized a geometry-based pretrained molecular representation and optimized it on the DILI data set to improve predictive performance. Second, we leveraged gradient information to obtain high-precision atomic-level weights and deduce the dominant substructure. We benchmarked GeoDILI against recently published DILI prediction models, as well as popular GNN models and fingerprint-based machine learning models using the same data set, showing superior predictive performance of our proposed model. We applied the interpretable method in the DILI data set and derived seven precise and mechanistically elucidated structural alerts. Overall, GeoDILI provides a promising approach for accurate and interpretable DILI prediction with potential applications in drug discovery and safety assessment. The data and source code are available at GitHub repository (https://github.com/CSU-QJY/GeoDILI).

SMYD2 regulates vascular smooth muscle cell phenotypic switching and intimal hyperplasia via interaction with myocardin.

The SET and MYND domain-containing protein 2 (SMYD2) is a histone lysine methyltransferase that has been reported to regulate carcinogenesis and inflammation. However, its role in vascular smooth muscle cell (VSMC) homeostasis and vascular diseases has not been determined. Here, we investigated the role of SMYD2 in VSMC phenotypic modulation and vascular intimal hyperplasia and elucidated the underlying mechanism. We observed that SMYD2 expression was downregulated in injured carotid arteries in mice and phenotypically modulated VSMCs in vitro. Using an SMC-specific SMYD2 knockout mouse model, we found that SMYD2 ablation in VSMCs exacerbated neointima formation after vascular injury in vivo. Conversely, SMYD2 overexpression inhibited VSMC proliferation and migration in vitro and attenuated arterial narrowing in injured vessels in mice. SMYD2 downregulation promoted VSMC phenotypic switching accompanied with enhanced proliferation and migration. Mechanistically, genome-wide transcriptome analysis and loss/gain-of-function studies revealed that SMYD2 up-regulated VSMC contractile gene expression and suppressed VSMC proliferation and migration, in part, by promoting expression and transactivation of the master transcription cofactor myocardin. In addition, myocardin directly interacted with SMYD2, thereby facilitating SMYD2 recruitment to the CArG regions of SMC contractile gene promoters and leading to an open chromatin status around SMC contractile gene promoters via SMYD2-mediated H3K4 methylation. Hence, we conclude that SMYD2 is a novel regulator of VSMC contractile phenotype and intimal hyperplasia via a myocardin-dependent epigenetic regulatory mechanism.

IGF2BP2-modified UBE2D1 interacts with Smad2/3 to promote the progression of breast cancer.

Recent studies have suggested that ubiquitin-conjugating enzyme E2D1 (UBE2D1) is involved in tumor progression. In this study, we found that UBE2D1 expression was upregulated in breast cancer (BC) and was related to the prognosis of BC patients. Through in vitro and in vivo experiments, we demonstrated the aberrant expression of UBE2D1 promoted the proliferation and migration of BC cells, and the IGF2BP2-mediated N6-methyladenosine (m6A) modification increased the stability of UBE2D1 mRNA. Mechanistically, UBE2D1 expression regulated the activity of TGF-ß signaling through modulating the expression and the phosphorylation level of Smad2/3. Furthermore, UBE2D1 directly bound to Smad2/3 and affected the subsequent binding of Smad2 and Smad3, which is a necessary step for TGF-ß signaling activation. Thus, our study reveals a pro-oncogenic role of UBE2D1 in the progression of BC and may provide novel strategies for BC treatment.

Mettl3 synergistically regulates TGF-ß/SMAD2/3 to promote proliferation and metastasis of gastric cancer.

Transforming Growth factor-ß (TGF-ß)/Smad signaling is a complex regulatory network that both inhibits and promotes tumorigenesis. However, the mechanisms underlying the function of TGF-ß/Smad signaling pathway remain to be fully elucidated. As a methyltransferase, METTL3 is closely related to tumor development, but the role of METTL3 in the proliferation and metastasis of TGF-ß/Smad-activated gastric cancer (GC) is unclear. In this study, we identified TGF-ß/Smad2/3 axis as an important carcinogenic pathway in GC, which significantly promoted the proliferation and metastasis of GC. Furthermore, we found that Smad3 mRNA could be modified by m6A, which was subsequently recognized and stabilized by IGF2BP2, thereby enhancing Smad3 protein expression and promoting the activation of TGF-ß/Smad pathway. Importantly, we also found that METTL3 could combine with p-Smad3 to regulate the transcription of downstream target genes. Therefore, this study revealed a novel mechanism by which METTL3 synergistically regulates TGF-ß/Smad2/3 signaling and provide a new potential therapeutic target for the treatment of GC.

MERS-CoV RBD-mRNA vaccine induces potent and broadly neutralizing antibodies with protection against MERS-CoV infection.

Middle East respiratory syndrome coronavirus (MERS-CoV), a highly pathogenic coronavirus in the same Betacoronavirus genus and Coronaviridae family as SARS-CoV-2, continues to post a threat to human health. Mortality remains high; therefore, there is a need to develop effective vaccines to prevent MERS-CoV infection. The receptor-binding domain (RBD) within the MERS-CoV spike (S) protein is a critical vaccine target. The latest mRNA technology has enabled rapid development of much-needed vaccines with high efficiency and scalable manufacturing capacity. Here, we designed a mRNA vaccine encoding the RBD of MERS-CoV S protein (RBD-mRNA) and evaluated its immunogenicity and protective efficacy in a mouse model. The data showed that nucleoside-modified RBD-mRNA, but not RBD-mRNA lacking the nucleoside modification, was stable and elicited broadly and durable neutralizing antibody and cellular immune responses, which neutralized the original strain and multiple MERS-CoV variants. Among all immunization routes tested, the intradermal route was appropriate for this RBD-mRNA to induce strong B-cell responses and the highest neutralizing antibody titers. Importantly, injection of nucleoside-modified RBD-mRNA through the intradermal route protected immunized mice against challenge with MERS-CoV. This protection correlated with serum neutralizing antibody titers. Overall, we have developed an effective MERS-CoV RBD-based mRNA vaccine (with potential for further development) that prevents infection by divergent strains of MERS-CoV.

Immunogenic cell death-related classifications guide prognosis and immunotherapy in osteosarcoma.

Immunogenic cell death (ICD) is a form of cell death that stimulates the immune system to produce an immune response by releasing tumour-associated antigens and tumour-specific antigens and is considered to play an important role in tumour immunotherapy. In the present study, we identified two ICD-related subtypes in osteosarcoma (OS) by consensus clustering. The ICD-low subtype was associated with favourable clinical outcomes, abundant immune cell infiltration, and high activity of immune response signalling. We also established and validated an ICD-related prognostic model, which could not only be used to predict the overall survival of OS patients but was also found to be closely related to the tumour immune microenvironment of OS patients. Overall, we established a new classification system for OS based on ICD-related genes, which can be used to predict the prognosis of OS patients and to select appropriate immunotherapy drugs.