Genetic determinants of IgG antibody response to COVID-19 vaccination.

Human humoral immune responses to SARS-CoV-2 vaccines exhibit substantial inter-individual variability and have been linked to vaccine efficacy. To elucidate the underlying mechanism behind this variability, we conducted a genome-wide association study (GWAS) on the anti-spike IgG serostatus of UK Biobank participants who were previously uninfected by SARS-CoV-2 and had received either the first dose (n = 54,066) or the second dose (n = 46,232) of COVID-19 vaccines. Our analysis revealed significant genome-wide associations between the IgG antibody serostatus following the initial vaccine and human leukocyte antigen (HLA) class II alleles. Specifically, the HLA-DRB1∗13:02 allele (MAF = 4.0%, OR = 0.75, p = 2.34e-16) demonstrated the most statistically significant protective effect against IgG seronegativity. This protective effect was driven by an alteration from arginine (Arg) to glutamic acid (Glu) at position 71 on HLA-DRß1 (p = 1.88e-25), leading to a change in the electrostatic potential of pocket 4 of the peptide binding groove. Notably, the impact of HLA alleles on IgG responses was cell type specific, and we observed a shared genetic predisposition between IgG status and susceptibility/severity of COVID-19. These results were replicated within independent cohorts where IgG serostatus was assayed by two different antibody serology tests. Our findings provide insights into the biological mechanism underlying individual variation in responses to COVID-19 vaccines and highlight the need to consider the influence of constitutive genetics when designing vaccination strategies for optimizing protection and control of infectious disease across diverse populations.

Searching across-cohort relatives in 54,092 GWAS samples via encrypted genotype regression.

Explicitly sharing individual level data in genomics studies has many merits comparing to sharing summary statistics, including more strict QCs, common statistical analyses, relative identification and improved statistical power in GWAS, but it is hampered by privacy or ethical constraints. In this study, we developed encG-reg, a regression approach that can detect relatives of various degrees based on encrypted genomic data, which is immune of ethical constraints. The encryption properties of encG-reg are based on the random matrix theory by masking the original genotypic matrix without sacrificing precision of individual-level genotype data. We established a connection between the dimension of a random matrix, which masked genotype matrices, and the required precision of a study for encrypted genotype data. encG-reg has false positive and false negative rates equivalent to sharing original individual level data, and is computationally efficient when searching relatives. We split the UK Biobank into their respective centers, and then encrypted the genotype data. We observed that the relatives estimated using encG-reg was equivalently accurate with the estimation by KING, which is a widely used software but requires original genotype data. In a more complex application, we launched a finely devised multi-center collaboration across 5 research institutes in China, covering 9 cohorts of 54,092 GWAS samples. encG-reg again identified true relatives existing across the cohorts with even different ethnic backgrounds and genotypic qualities. Our study clearly demonstrates that encrypted genomic data can be used for data sharing without loss of information or data sharing barrier.

Genetic basis of pregnancy-associated decreased platelet counts and gestational thrombocytopenia.

ABSTRACT: Platelet count reduction occurs throughout pregnancy, with 5% to 12% of pregnant women being diagnosed with gestational thrombocytopenia (GT), characterized by a more marked decrease in platelet count during pregnancy. However, the underlying biological mechanism behind these phenomena remains unclear. Here, we used sequencing data from noninvasive prenatal testing of 100 186 Chinese pregnant individuals and conducted, to our knowledge, the hitherto largest-scale genome-wide association studies on platelet counts during 5 periods of pregnancy (the first, second, and third trimesters, delivery, and the postpartum period) as well as 2 GT statuses (GT platelet count < 150 × 109/L and severe GT platelet count < 100 × 109/L). Our analysis revealed 138 genome-wide significant loci, explaining 10.4% to 12.1% of the observed variation. Interestingly, we identified previously unknown changes in genetic effects on platelet counts during pregnancy for variants present in PEAR1 and CBL, with PEAR1 variants specifically associated with a faster decline in platelet counts. Furthermore, we found that variants present in PEAR1 and TUBB1 increased susceptibility to GT and severe GT. Our study provides insight into the genetic basis of platelet counts and GT in pregnancy, highlighting the critical role of PEAR1 in decreasing platelet counts during pregnancy and the occurrence of GT. Those with pregnancies carrying specific variants associated with declining platelet counts may experience a more pronounced decrease, thereby elevating the risk of GT. These findings lay the groundwork for further investigation into the biological mechanisms and causal implications of GT.

The DNA Methylcytosine Dioxygenase Tet2 Sustains Immunosuppressive Function of Tumor-Infiltrating Myeloid Cells to Promote Melanoma Progression.

Ten-Eleven-Translocation-2 (Tet2) is a DNA methylcytosine dioxygenase that functions as a tumor suppressor in hematopoietic malignancies. We examined the role of Tet2 in tumor-tissue myeloid cells and found that Tet2 sustains the immunosuppressive function of these cells. We found that Tet2 expression is increased in intratumoral myeloid cells both in mouse models of melanoma and in melanoma patients and that this increased expression is dependent on an IL-1R-MyD88 pathway. Ablation of Tet2 in myeloid cells suppressed melanoma growth in vivo and shifted the immunosuppressive gene expression program in tumor-associated macrophages to a proinflammatory one, with a concomitant reduction of the immunosuppressive function. This resulted in increased numbers of effector T cells in the tumor, and T cell depletion abolished the reduced tumor growth observed upon myeloid-specific deletion of Tet2. Our findings reveal a non-cell-intrinsic, tumor-promoting function for Tet2 and suggest that Tet2 may present a therapeutic target for the treatment of non-hematologic malignancies.

Predicting lncRNA-disease associations based on combining selective similarity matrix fusion and bidirectional linear neighborhood label propagation.

Recent studies have revealed that long noncoding RNAs (lncRNAs) are closely linked to several human diseases, providing new opportunities for their use in detection and therapy. Many graph propagation and similarity fusion approaches can be used for predicting potential lncRNA-disease associations. However, existing similarity fusion approaches suffer from noise and self-similarity loss in the fusion process. To address these problems, a new prediction approach, termed SSMF-BLNP, based on organically combining selective similarity matrix fusion (SSMF) and bidirectional linear neighborhood label propagation (BLNP), is proposed in this paper to predict lncRNA-disease associations. In SSMF, self-similarity networks of lncRNAs and diseases are obtained by selective preprocessing and nonlinear iterative fusion. The fusion process assigns weights to each initial similarity network and introduces a unit matrix that can reduce noise and compensate for the loss of self-similarity. In BLNP, the initial lncRNA-disease associations are employed in both lncRNA and disease directions as label information for linear neighborhood label propagation. The propagation was then performed on the self-similarity network obtained from SSMF to derive the scoring matrix for predicting the relationships between lncRNAs and diseases. Experimental results showed that SSMF-BLNP performed better than seven other state of-the-art approaches. Furthermore, a case study demonstrated up to 100% and 80% accuracy in 10 lncRNAs associated with hepatocellular carcinoma and 10 lncRNAs associated with renal cell carcinoma, respectively. The source code and datasets used in this paper are available at: https://github.com/RuiBingo/SSMF-BLNP.

TarKG: a comprehensive biomedical knowledge graph for target discovery.

MOTIVATION: Target discovery is a crucial step in drug development, as it directly affects the success rate of clinical trials. Knowledge graphs (KGs) offer unique advantages in processing complex biological data and inferring new relationships. Existing biomedical KGs primarily focus on tasks such as drug repositioning and drug-target interactions, leaving a gap in the construction of KGs tailored for target discovery. RESULTS: We established a comprehensive biomedical KG focusing on target discovery, termed TarKG, by integrating seven existing biomedical KGs, nine public databases, and traditional Chinese medicine knowledge databases. TarKG consists of 1 143 313 entities and 32 806 467 relations across 15 entity categories and 171 relation types, all centered around 3 core entity types: Disease, Gene, and Compound. TarKG provides specialized knowledges for the core entities including chemical structures, protein sequences, or text descriptions. By using different KG embedding algorithms, we assessed the knowledge completion capabilities of TarKG, particularly for disease-target link prediction. In case studies, we further examined TarKG's ability to predict potential protein targets for Alzheimer's disease (AD) and to identify diseases potentially associated with the metallo-deubiquitinase CSN5, using literature analysis for validation. Furthermore, we provided a user-friendly web server (https://tarkg.ddtmlab.org) that enables users to perform knowledge retrieval and relation inference using TarKG. AVAILABILITY AND IMPLEMENTATION: TarKG is accessible at https://tarkg.ddtmlab.org.

MeDBA: the Metalloenzyme Data Bank and Analysis platform.

Metalloenzymes are attractive research targets in fields of chemistry, biology, and medicine. Given that metalloenzymes can manifest conservation of metal-coordination and ligand binding modes, the excavation and expansion of metalloenzyme-specific knowledge is of interest in bridging metalloenzyme-related fields. Building on our previous metalloenzyme-ligand association database, MeLAD, we have expanded the scope of metalloenzyme-specific knowledge and services, by forming a versatile platform, termed the Metalloenzyme Data Bank and Analysis (MeDBA). The MeDBA provides: (i) manual curation of metalloenzymes into different categories, that this M-I, M-II and M-III; (ii) comprehensive information on metalloenzyme activities, expression profiles, family and disease links; (iii) structural information on metalloenzymes, in particular metal binding modes; (iv) metalloenzyme substrates and bioactive molecules acting on metalloenzymes; (v) excavated metal-binding pharmacophores and (vi) analysis tools for structure/metal active site comparison and metalloenzyme profiling. The MeDBA is freely available at https://medba.ddtmlab.org.

Wearable device-measured moderate to vigorous physical activity and risk of degenerative aortic valve stenosis.

BACKGROUND AND AIMS: Physical activity has proven effective in preventing atherosclerotic cardiovascular disease, but its role in preventing degenerative valvular heart disease (VHD) remains uncertain. This study aimed to explore the dose-response association between moderate to vigorous physical activity (MVPA) volume and the risk of degenerative VHD among middle-aged adults. METHODS: A full week of accelerometer-derived MVPA data from 87 248 UK Biobank participants (median age 63.3, female: 56.9%) between 2013 and 2015 were used for primary analysis. Questionnaire-derived MVPA data from 361 681 UK Biobank participants (median age 57.7, female: 52.7%) between 2006 and 2010 were used for secondary analysis. The primary outcome was the diagnosis of incident degenerative VHD, including aortic valve stenosis (AS), aortic valve regurgitation (AR), and mitral valve regurgitation (MR). The secondary outcome was VHD-related intervention or mortality. RESULTS: In the accelerometer-derived MVPA cohort, 555 incident AS, 201 incident AR, and 655 incident MR occurred during a median follow-up of 8.11 years. Increased MVPA volume showed a steady decline in AS risk and subsequent AS-related intervention or mortality risk, levelling off beyond approximately 300 min/week. In contrast, its association with AR or MR incidence was less apparent. The adjusted rates of AS incidence (95% confidence interval) across MVPA quartiles (Q1-Q4) were 11.60 (10.20, 13.20), 7.82 (6.63, 9.23), 5.74 (4.67, 7.08), and 5.91 (4.73, 7.39) per 10 000 person-years. The corresponding adjusted rates of AS-related intervention or mortality were 4.37 (3.52, 5.43), 2.81 (2.13, 3.71), 1.93 (1.36, 2.75), and 2.14 (1.50, 3.06) per 10 000 person-years, respectively. Aortic valve stenosis risk reduction was also observed with questionnaire-based MVPA data [adjusted absolute difference Q4 vs. Q1: AS incidence, -1.41 (-.67, -2.14) per 10 000 person-years; AS-related intervention or mortality, -.38 (-.04, -.88) per 10 000 person-years]. The beneficial association remained consistent in high-risk populations for AS, including patients with hypertension, obesity, dyslipidaemia, and chronic kidney disease. CONCLUSIONS: Higher MVPA volume was associated with a lower risk of developing AS and subsequent AS-related intervention or mortality. Future research needs to validate these findings in diverse populations with longer durations and repeated periods of activity monitoring.

Uric acid-lowering effect of harpagoside and its protective effect against hyperuricemia-induced renal injury in mice.

Hyperuricemia (HUA) is caused by increased synthesis and/or insufficient excretion of uric acid (UA). Long-lasting HUA may lead to a number of diseases including gout and kidney injury. Harpagoside (Harp) is a bioactive compound with potent anti-inflammatory activity from the roots of Scrophularia ningpoensis. Nevertheless, its potential effect on HUA was not reported. The anti-HUA and nephroprotective effects of Harp on HUA mice were assessed by biochemical and histological analysis. The proteins responsible for UA production and transportation were investigated to figure out its anti-HUA mechanism, while proteins related to NF-κB/NLRP3 pathway were evaluated to reveal its nephroprotective mechanism. The safety was evaluated by testing its effect on body weight and organ coefficients. The results showed that Harp significantly reduced the SUA level and protected the kidney against HUA-induced injury but had no negative effect on safety. Mechanistically, Harp significantly reduced UA production by acting as inhibitors of xanthine oxidase (XOD) and adenosine deaminase (ADA) and decreased UA excretion by acting as activators of ABCG2, OAT1 and inhibitors of GLUT9 and URAT1. Moreover, Harp markedly reduced infiltration of inflammatory cells and down-regulated expressions of TNF-α, NF-κB, NLRP3 and IL-1ß in the kidney. Harp was a promising anti-HUA agent.

TBK1, a prioritized drug repurposing target for amyotrophic lateral sclerosis: evidence from druggable genome Mendelian randomization and pharmacological verification in vitro.

BACKGROUND: There is a lack of effective therapeutic strategies for amyotrophic lateral sclerosis (ALS); therefore, drug repurposing might provide a rapid approach to meet the urgent need for treatment. METHODS: To identify therapeutic targets associated with ALS, we conducted Mendelian randomization (MR) analysis and colocalization analysis using cis-eQTL of druggable gene and ALS GWAS data collections to determine annotated druggable gene targets that exhibited significant associations with ALS. By subsequent repurposing drug discovery coupled with inclusion criteria selection, we identified several drug candidates corresponding to their druggable gene targets that have been genetically validated. The pharmacological assays were then conducted to further assess the efficacy of genetics-supported repurposed drugs for potential ALS therapy in various cellular models. RESULTS: Through MR analysis, we identified potential ALS druggable genes in the blood, including TBK1 [OR 1.30, 95%CI (1.19, 1.42)], TNFSF12 [OR 1.36, 95%CI (1.19, 1.56)], GPX3 [OR 1.28, 95%CI (1.15, 1.43)], TNFSF13 [OR 0.45, 95%CI (0.32, 0.64)], and CD68 [OR 0.38, 95%CI (0.24, 0.58)]. Additionally, we identified potential ALS druggable genes in the brain, including RESP18 [OR 1.11, 95%CI (1.07, 1.16)], GPX3 [OR 0.57, 95%CI (0.48, 0.68)], GDF9 [OR 0.77, 95%CI (0.67, 0.88)], and PTPRN [OR 0.17, 95%CI (0.08, 0.34)]. Among them, TBK1, TNFSF12, RESP18, and GPX3 were confirmed in further colocalization analysis. We identified five drugs with repurposing opportunities targeting TBK1, TNFSF12, and GPX3, namely fostamatinib (R788), amlexanox (AMX), BIIB-023, RG-7212, and glutathione as potential repurposing drugs. R788 and AMX were prioritized due to their genetic supports, safety profiles, and cost-effectiveness evaluation. Further pharmacological analysis revealed that R788 and AMX mitigated neuroinflammation in ALS cell models characterized by overly active cGAS/STING signaling that was induced by MSA-2 or ALS-related toxic proteins (TDP-43 and SOD1), through the inhibition of TBK1 phosphorylation. CONCLUSIONS: Our MR analyses provided genetic evidence supporting TBK1, TNFSF12, RESP18, and GPX3 as druggable genes for ALS treatment. Among the drug candidates targeting the above genes with repurposing opportunities, FDA-approved drug-R788 and AMX served as effective TBK1 inhibitors. The subsequent pharmacological studies validated the potential of R788 and AMX for treating specific ALS subtypes through the inhibition of TBK1 phosphorylation.

4 mC site recognition algorithm based on pruned pre-trained DNABert-Pruning model and fused artificial feature encoding.

DNA 4 mC plays a crucial role in the genetic expression process of organisms. However, existing deep learning algorithms have shortcomings in the ability to represent DNA sequence features. In this paper, we propose a 4 mC site identification algorithm, DNABert-4mC, based on a fusion of the pruned pre-training DNABert-Pruning model and artificial feature encoding to identify 4 mC sites. The algorithm prunes and compresses the DNABert model, resulting in the pruned pre-training model DNABert-Pruning. This model reduces the number of parameters and removes redundancy from output features, yielding more precise feature representations while upholding accuracy.Simultaneously, the algorithm constructs an artificial feature encoding module to assist the DNABert-Pruning model in feature representation, effectively supplementing the information that is missing from the pre-trained features. The algorithm also introduces the AFF-4mC fusion strategy, which combines artificial feature encoding with the DNABert-Pruning model, to improve the feature representation capability of DNA sequences in multi-semantic spaces and better extract 4 mC sites and the distribution of nucleotide importance within the sequence. In experiments on six independent test sets, the DNABert-4mC algorithm achieved an average AUC value of 93.81%, outperforming seven other advanced algorithms with improvements of 2.05%, 5.02%, 11.32%, 5.90%, 12.02%, 2.42% and 2.34%, respectively.

The Garden of Forking Paths: Reinterpreting Haseman-Elston Regression for a Genotype-by-Environment Model.

Haseman-Elston regression (HE-reg) has been known as a classic tool for detecting an additive genetic variance component. However, in this study we find that HE-reg can capture GxE under certain conditions, so we derive and reinterpret the analytical solution of HE-reg. In the presence of GxE, it leads to a natural discrepancy between linkage and association results, the latter of which is not able to capture GxE if the environment is unknown. Considering linkage and association as symmetric designs, we investigate how the symmetry can and cannot hold in the absence and presence of GxE, and consequently we propose a pair of statistical tests, Symmetry Test I and Symmetry Test II, both of which can be tested using summary statistics. Test statistics, and their statistical power issues are also investigated for Symmetry Tests I and II. Increasing the number of sib pairs is important to improve statistical power for detecting GxE.

Application of clustering strategy for automatic segmentation of tissue regions in mass spectrometry imaging.

RATIONALE: Mass spectrometry imaging (MSI) has been widely used in biomedical research fields. Each pixel in MSI consists of a mass spectrum that reflects the molecule feature of the tissue spot. Because MSI contains high-dimensional datasets, it is highly desired to develop computational methods for data mining and constructing tissue segmentation maps. METHODS: To visualize different tissue regions based on mass spectrum features and improve the efficiency in processing enormous data, we proposed a computational strategy that consists of four procedures including preprocessing, data reduction, clustering, and quantitative validation. RESULTS: In this study, we examined the combination of t-distributed stochastic neighbor embedding (t-SNE) and hierarchical clustering (HC) for MSI data analysis. Using publicly available MSI datasets, one dataset of mouse urinary bladder, and one dataset of human colorectal cancer, we demonstrated that the generated tissue segmentation maps from this combination were superior to other data reduction and clustering algorithms. Using the staining image as a reference, we assessed the performance of clustering algorithms with external and internal clustering validation measures, including purity, adjusted Rand index (ARI), Davies-Bouldin index (DBI), and spatial aggregation index (SAI). The result indicated that SAI delivered excellent performance for automatic segmentation of tissue regions in MSI. CONCLUSIONS: We used a clustering algorithm to construct tissue automatic segmentation in MSI datasets. The performance was evaluated by comparing it with the stained image and calculating clustering validation indexes. The results indicated that SAI is important for automatic tissue segmentation in MSI, different from traditional clustering validation measures. Compared to the reports that used internal clustering validation measures such as DBI, our method offers more effective evaluation of clustering results for MSI segmentation. We envision that the proposed automatic image segmentation strategy can facilitate deep learning in molecular feature extraction and biomarker discovery for the biomedical applications of MSI.

High-Resolution Depth-Discrete Analysis of PFAS Distribution and Leaching for a Vadose-Zone Source at an AFFF-Impacted Site.

The long-term leaching of polyfluoroalkyl substances (PFAS) within the vadose zone of an AFFF application site for which the depth to groundwater is approximately 100 m was investigated by characterizing the vertical distribution of PFAS in a high spatial resolution. The great majority (99%) of PFAS mass resides in the upper 3 m of the vadose zone. The depths to which each PFAS migrated, quantified by moment analysis, is an inverse function of molar volume, demonstrating chromatographic separation. The PFAS were operationally categorized into three chain-length groups based on the three general patterns of retention observed. The longest-chain (>∼335 cm3/mol molar volume) PFAS remained within the uppermost section of the core, exhibiting minimal leaching. Conversely, the shortest-chain (<∼220 cm3/mol) PFAS accumulated at the bottom of the interval, which coincides with the onset of a calcic horizon. PFAS with intermediate-chain lengths were distributed along the length of the core, exhibiting differential magnitudes of leaching. The minimal or differential leaching observed for the longest- and intermediate-chain-length PFAS, respectively, demonstrates that retention processes significantly impacted migration. The accumulation of shorter-chain PFAS at the bottom of the core is hypothesized to result from limited deep infiltration and potential-enhanced retention associated with the calcic horizon.

An analysis of differences in Carbapenem-resistant Enterobacterales in different regions: a multicenter cross-sectional study.

OBJECTIVE: This study aimed to explore the characteristics of carbapenem-resistant Enterobacterales (CRE) patients in the intensive care unit (ICU) in different regions of Henan Province to provide evidence for the targeted prevention and treatment of CRE. METHODS: This was a cross-sectional study. CRE screening was conducted in the ICUs of 78 hospitals in Henan Province, China, on March 10, 2021. The patients were divided into provincial capital hospitals and nonprovincial capital hospitals for comparative analysis. RESULTS: This study involved 1009 patients in total, of whom 241 were CRE-positive patients, 92 were in the provincial capital hospital and 149 were in the nonprovincial capital hospital. Provincial capital hospitals had a higher rate of CRE positivity, and there was a significant difference in the rate of CRE positivity between the two groups. The body temperature; immunosuppressed state; transfer from the ICU to other hospitals; and use of enemas, arterial catheters, carbapenems, or tigecycline at the provincial capital hospital were greater than those at the nonprovincial capital hospital (P < 0.05). However, there was no significant difference in the distribution of carbapenemase strains or enzymes between the two groups. CONCLUSIONS: The detection rate of CRE was significantly greater in provincial capital hospitals than in nonprovincial capital hospitals. The source of the patients, invasive procedures, and use of advanced antibiotics may account for the differences. Carbapenem-resistant Klebsiella pneumoniae (CR-KPN) was the most prevalent strain. Klebsiella pneumoniae carbapenemase (KPC) was the predominant carbapenemase enzyme. The distributions of carbapenemase strains and enzymes were similar in different regions.

13-Oxyingenol-dodecanoate inhibits the growth of non-small cell lung cancer cells by targeting ULK1.

Lung cancer is the leading cause of cancer deaths worldwide. Non-small cell lung cancer (NSCLC) accounts for 80-85% of all lung cancers. Euphorbia kansui yielded 13-oxyingenol-dodecanoate (13OD), an ingenane-type diterpenoid, which had a strong cytotoxic effect on NSCLC cells. The underlying mechanism and potential target, however, remained unknown. The study found that 13OD effectively inhibited the cell proliferation and colony formation of NSCLC cells (A549 and H460 cells), with less toxicity in normal human lung epithelial BEAS-2B cells. Moreover, 13OD can cause mitochondrial dysfunction, and apoptosis in NSCLC cells. Mechanistically, the transcriptomics results showed that differential genes were mainly enriched in the mTOR and AMPK signaling pathways, which are closely related to cellular autophagy, the related indicators were subsequently validated. Additionally, bafilomycin A1 (Baf A1), an autophagy inhibitor, reversed the mitochondrial damage caused by 13OD. Furthermore, the Omics and Text-based Target Enrichment and Ranking (OTTER) method predicted ULK1 as a potential target of 13OD against NSCLC cells. This hypothesis was further confirmed using molecular docking, the cellular thermal shift assay (CETSA), and Western blot analysis. Remarkably, ULK1 siRNA inhibited 13OD's toxic activity in NSCLC cells. In line with these findings, 13OD was potent and non-toxic in the tumor xenograft model. Our findings suggested a possible mechanism for 13OD's role as a tumor suppressor and laid the groundwork for identifying targets for ingenane-type diterpenoids.

Integrative epigenetic analysis reveals AP-1 promotes activation of tumor-infiltrating regulatory T cells in HCC.

Regulatory T (Treg) cells that infiltrate human tumors exhibit stronger immunosuppressive activity compared to peripheral blood Treg cells (PBTRs), thus hindering the induction of effective antitumor immunity. Previous transcriptome studies have identified a set of genes that are conserved in tumor-infiltrating Treg cells (TITRs). However, epigenetic profiles of TITRs have not yet been completely deciphered. Here, we employed ATAC-seq and CUT&Tag assays to integrate transcriptome profiles and identify functional regulatory elements in TITRs. We observed a global difference in chromatin accessibility and enhancer landscapes between TITRs and PBTRs. We identified two types of active enhancer formation in TITRs. The H3K4me1-predetermined enhancers are poised to be activated in response to tumor microenvironmental stimuli. We found that AP-1 family motifs are enriched at the enhancer regions of TITRs. Finally, we validated that c-Jun binds at regulatory regions to regulate signature genes of TITRs and AP-1 is required for Treg cells activation in vitro. High c-Jun expression is correlated with poor survival in human HCC. Overall, our results provide insights into the mechanism of AP-1-mediated activation of TITRs and can hopefully be used to develop new therapeutic strategies targeting TITRs in liver cancer treatment.

Trident cold atmospheric plasma blocks three cancer survival pathways to overcome therapy resistance.

Therapy resistance is responsible for most cancer-related death and is mediated by the unique ability of cancer cells to leverage metabolic conditions, signaling molecules, redox status, and other pathways for their survival. Interestingly, many cancer survival pathways are susceptible to disturbances in cellular reactive oxygen species (ROS) and may therefore be disrupted by exogenous ROS. Here, we explore whether trident cold atmospheric plasma (Tri-CAP), a gas discharge with exceptionally low-level ROS, could inhibit multiple cancer survival pathways together in a murine cell line model of therapy-resistant chronic myeloid leukemia (CML). We show that Tri-CAP simultaneously disrupts three cancer survival pathways of redox deregulation, glycolysis, and proliferative AKT/mTOR/HIF-1α signaling in this cancer model. Significantly, Tri-CAP blockade induces a very high rate of apoptotic death in CML cell lines and in primary CD34+ hematopoietic stem and progenitor cells from CML patients, both harboring the therapy-resistant T315I mutation. In contrast, nonmalignant controls are minimally affected by Tri-CAP, suggesting it selectively targets resistant cancer cells. We further demonstrate that Tri-CAP elicits similar lethality in human melanoma, breast cancer, and CML cells with disparate, resistant mechanisms and that it both reduces tumor formation in two mouse models and improves survival of tumor-bearing mice. For use in patients, administration of Tri-CAP may be extracorporeal for hematopoietic stem cell transplantation therapy, transdermal, or through its activated solution for infusion therapy. Collectively, our results suggest that Tri-CAP represents a potent strategy for disrupting cancer survival pathways and overcoming therapy resistance in a variety of malignancies.

Ursolic acid alleviates chronic prostatitis via regulating NLRP3 inflammasome-mediated Caspase-1/GSDMD pyroptosis pathway.

Ursolic acid (UA) is a naturally occurring pentacyclic triterpenoid widely found in fruits and vegetables. It has been reported that UA has anti-inflammatory effects. However, its efficacy and mechanism of action in the treatment of chronic prostatitis (CP) remain unclear. This study aimed to investigate the efficacy of UA treatment in CP and further explore the underlying mechanism. CP rat and pyroptosis cell models were established in vivo and in vitro, respectively. The efficacy of UA in inhibiting CP was evaluated via haematoxylin-eosin (HE) staining and measurement of inflammatory cytokines. RNA sequencing and molecular docking were used to predict the therapeutic targets of UA in CP. The expression of pyroptosis-related proteins was examined using various techniques, including immunohistochemistry, immunofluorescence, and flow cytometry. UA significantly ameliorated pathological damage and reduced the levels of proinflammatory cytokines in the CP model rats. RNA sequencing analysis and molecular docking suggested that NLRP3, Caspase-1, and GSDMD may be key targets. We also found that UA decreased ROS levels, alleviated oxidative stress, and inhibited p-NF-κB protein expression both in vivo and in vitro. UA improved pyroptosis morphology as indicated by electron microscope and inhibited the expression of the pyroptosis-related proteins NLRP3, Caspase-1, ASC, and GSDMD, reversed the levels of IL-1ß, IL-18, and lactate dehydrogenase in vivo and in vitro. UA can mitigate CP by regulating the NLRP3 inflammasome-mediated Caspase-1/GSDMD pathway. Therefore, UA may be a potential for the treatment of CP.

Phomopsterone B Alleviates Liver Fibrosis through mTOR-Mediated Autophagy and Apoptosis Pathway.

Liver fibrosis is the initial pathological process of many chronic liver diseases. Targeting hepatic stellate cell (HSC) activation is an available strategy for the therapy of liver fibrosis. We aimed to explore the anti-liver fibrosis activity and potential mechanism of phomopsterone B (PB) in human HSCs. The results showed that PB effectively attenuated the proliferation of TGF-ß1-stimulated LX-2 cells in a concentration-dependent manner at doses of 1, 2, and 4 µM. Quantitative real-time PCR and Western blot assays displayed that PB significantly reduced the expression levels of α-SMA and collagen I/III. AO/EB and Hoechst33342 staining and flow cytometry assays exhibited that PB promoted the cells' apoptosis. Meanwhile, PB diminished the number of autophagic vesicles and vacuolated structures, and the LC3B fluorescent spots indicated that PB could effectively inhibit the accretion of autophagosomes in LX-2 cells. Moreover, rapamycin and MHY1485 were utilized to further investigate the effect of mTOR in autophagy and apoptosis. The results demonstrated that PB regulated autophagy and apoptosis via the mTOR-dependent pathway in LX-2 cells. In summary, this is the first evidence that PB effectively alleviates liver fibrosis in TGF-ß1-stimulated LX-2 cells, and PB may be a promising candidate for the prevention of liver fibrosis.