COIMMR: a computational framework to reveal the contribution of herbal ingredients against human cancer via immune microenvironment and metabolic reprogramming.

Immune evasion and metabolism reprogramming have been regarded as two vital hallmarks of the mechanism of carcinogenesis. Thus, targeting the immune microenvironment and the reprogrammed metabolic processes will aid in developing novel anti-cancer drugs. In recent decades, herbal medicine has been widely utilized to treat cancer through the modulation of the immune microenvironment and reprogrammed metabolic processes. However, labor-based herbal ingredient screening is time consuming, laborious and costly. Luckily, some computational approaches have been proposed to screen candidates for drug discovery rapidly. Yet, it has been challenging to develop methods to screen drug candidates exclusively targeting specific pathways, especially for herbal ingredients which exert anti-cancer effects by multiple targets, multiple pathways and synergistic ways. Meanwhile, currently employed approaches cannot quantify the contribution of the specific pathway to the overall curative effect of herbal ingredients. Hence, to address this problem, this study proposes a new computational framework to infer the contribution of the immune microenvironment and metabolic reprogramming (COIMMR) in herbal ingredients against human cancer and specifically screen herbal ingredients targeting the immune microenvironment and metabolic reprogramming. Finally, COIMMR was applied to identify isoliquiritigenin that specifically regulates the T cells in stomach adenocarcinoma and cephaelin hydrochloride that specifically targets metabolic reprogramming in low-grade glioma. The in silico results were further verified using in vitro experiments. Taken together, our approach opens new possibilities for repositioning drugs targeting immune and metabolic dysfunction in human cancer and provides new insights for drug development in other diseases. COIMMR is available at https://github.com/LYN2323/COIMMR.

Exploring pharmacological active ingredients of traditional Chinese medicine by pharmacotranscriptomic map in ITCM.

With the emergence of high-throughput technologies, computational screening based on gene expression profiles has become one of the most effective methods for drug discovery. More importantly, profile-based approaches remarkably enhance novel drug-disease pair discovery without relying on drug- or disease-specific prior knowledge, which has been widely used in modern medicine. However, profile-based systematic screening of active ingredients of traditional Chinese medicine (TCM) has been scarcely performed due to inadequate pharmacotranscriptomic data. Here, we develop the largest-to-date online TCM active ingredients-based pharmacotranscriptomic platform integrated traditional Chinese medicine (ITCM) for the effective screening of active ingredients. First, we performed unified high-throughput experiments and constructed the largest data repository of 496 representative active ingredients, which was five times larger than the previous one built by our team. The transcriptome-based multi-scale analysis was also performed to elucidate their mechanism. Then, we developed six state-of-art signature search methods to screen active ingredients and determine the optimal signature size for all methods. Moreover, we integrated them into a screening strategy, TCM-Query, to identify the potential active ingredients for the special disease. In addition, we also comprehensively collected the TCM-related resource by literature mining. Finally, we applied ITCM to an active ingredient bavachinin, and two diseases, including prostate cancer and COVID-19, to demonstrate the power of drug discovery. ITCM was aimed to comprehensively explore the active ingredients of TCM and boost studies of pharmacological action and drug discovery. ITCM is available at http://itcm.biotcm.net.

Signature Search Polestar: a comprehensive drug repurposing method evaluation assistant for customized oncogenic signature.

SUMMARY: The burgeoning high-throughput technologies have led to a significant surge in the scale of pharmacotranscriptomic datasets, especially for oncology. Signature search methods (SSMs), utilizing oncogenic signatures formed by differentially expressed genes through sequencing, have been instrumental in anti-cancer drug screening and identifying mechanisms of action without relying on prior knowledge. However, various studies have found that different SSMs exhibit varying performance across pharmacotranscriptomic datasets. In addition, the size of the oncogenic signature can also significantly impact the result of drug repurposing. Therefore, finding the optimal SSMs and customized oncogenic signature for a specific disease remains a challenge. To address this, we introduce Signature Search Polestar (SSP), a webserver integrating the largest pharmacotranscriptomic datasets of anti-cancer drugs from LINCS L1000 with five state-of-the-art SSMs (XSum, CMap, GSEA, ZhangScore, XCos). SSP provides three main modules: Benchmark, Robustness, and Application. Benchmark uses two indices, Area Under the Curve and Enrichment Score, based on drug annotations to evaluate SSMs at different oncogenic signature sizes. Robustness, applicable when drug annotations are insufficient, uses a performance score based on drug self-retrieval for evaluation. Application provides three screening strategies, single method, SS_all, and SS_cross, allowing users to freely utilize optimal SSMs with tailored oncogenic signature for drug repurposing. AVAILABILITY AND IMPLEMENTATION: SSP is free at https://web.biotcm.net/SSP/. The current version of SSP is archived in https://doi.org/10.6084/m9.figshare.26524741.v1, allowing users to directly use or customize their own SSP webserver.

Effects of processing on the efficacy and metabolites of Cistanche tubulosa using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.

Cistanche tubulosa (CT), a well-known traditional Chinese medicine, has always been processed with rice wine for the treatment of kidney-yang deficiency syndrome (KYDS) since time immemorial. To explore the effect of processing on the efficacy and metabolites of CT in vivo, a comprehensive method using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was established for the analysis of the altered endogenous metabolites in response to the intervention of the raw and processed CT in KYDS model and the metabolites of the absorbed compounds in rats after gastric perfusion. It was shown that CT could improve KYDS, and the effect of the processed product was more significant. A total of 47 differential metabolites were identified in urine. Pathway analysis proved that purine metabolism; alanine, aspartate, and glutamate metabolism; and citrate cycle were the main pathways. Furthermore, 53 prototypes and 48 metabolites have been detected in rats. This was the first systematic research focus on the metabolites of raw and processed CT in vivo, which could provide a scientific basis for explaining the increasing efficiency of the processed CT. Moreover, it provides a valuable strategy for analyzing the chemical components and metabolites of other TCM prescriptions.

Single cell study of cellular diversity and mutual communication in chronic heart failure and drug repositioning.

Non-cardiomyocytes (non-CMs) play an important role in the process of cardiac remodeling of chronic heart failure. The mechanism of non-CMs transit and interact with each other remains largely unknown. Here, we try to characterize the cellular landscape of non-CMs in mice with chronic heart failure by using single-cell RNA sequencing (scRNA-seq) and provide potential therapeutic hunts. Cellular and molecular analysis revealed that the most affected cellular types are mainly fibroblasts and endothelial cells. Specially, Fib_0 cluster, the most abundant cluster in fibroblasts, was the only increased one, enriched for collagen synthesis genes such as Adamts4 and Crem, which might be responsible for the fibrosis in cardiac remodeling. End_0 cluster in endothelial cells was also the most abundant and only increased one, which has an effect of blood vessel morphogenesis. Cell communication further confirmed that fibroblasts and endothelial cells are the driving hubs in chronic heart failure. Furthermore, using fibroblasts and endothelial cells as the entry point of CMap technology, histone deacetylation (HDAC) inhibitors and HSP inhibitors were identified as potential anti-heart failure new drugs, which should be evaluated in the future. The combined application of scRNA-seq and CMap might be an effective way to achieve drug repositioning.

Comprehensive bioinformatics analysis reveals kinase activity profiling associated with heart failure.

Heart failure is a complex clinical syndrome originating from cardiac injury, which leads to considerable morbidity and mortality. Among the dynamic molecular adaptations occurring in heart failure development, aggravation of the disease is often attributed to global or local abnormality of the kinase. Therefore, the overall monitoring of kinase activity is indispensable. In this study, a bioinformatics analysis method was developed to conduct deep mining of transcriptome and phosphoproteome in failing heart tissue. A total of 982 differentially expressed genes and 9781 phosphorylation sites on 3252 proteins were identified. Via upstream regulator relations and kinase-substrate relations, a dendrogram of kinases can be constructed to monitor its abnormality. The results show that, on the dendrogram, the distribution of kinases demonstrated complex kinase activity changes and certain rules that occur during heart failure. Finally, we also identified the hub kinases in heart failure and verified the expression of these kinases by reverse-transcription polymerase chain reaction and Western blot analysis. In conclusion, for the first time, we have systematically analyzed the differences in kinases during heart failure and provided an unprecedented breadth of multi-omics data. These results can bring about a sufficient data foundation and novel research perspectives.

Exploring the mechanism of TCM formulae in the treatment of different types of coronary heart disease by network pharmacology and machining learning.

Traditional Chinese medicine (TCM) has long been used in the clinical treatment of coronary heart disease (CHD). TCM is characterized by syndrome-based medication, which is, using different TCM formulae for different syndromes. However, the underlying mode of action remains unclear. In this work, we utilized network pharmacology and machine learning to explore the mechanism of eight classic TCM formulae in the treatment of different types of CHD. First, by integrating multiple databases, a total of 669 potential bioactive compounds and 581 targets of the eight formulae were screened. Then, the effectiveness of these formulae on CHD was evaluated using two network-based indicators. The results showed that each formula's targets were significantly correlated with CHD associated genes and overlapped with the targets of 9 classes of drugs for cardio vascular diseases (CVD) to some degree. Next, from 5 different levels, i.e., herb, symptom, compound, target, and pathway level, we systematically compared the eight formulae using network clustering and hierarchical clustering. We found that all the formulae could be grouped into five clusters and the clustering results were approximately consistent at different levels. All the formulae were involved in 7 pathways closely related to CHD and may exhibit the common effect of relieving angina. Formulae in the same group collectively regulated some unique pathways and suggest further specific indications. For example, the three formulae used for Qi stagnation and blood stasis, Qi deficiency and blood stasis, and Qi-Yin deficiency syndromes acted on two special pathways (TNF signaling pathway, NF-kappa B signaling pathway) and may exert anti-inflammatory and immune-enhancing effects; the two formulae for Yin deficiency of heart and kidney, and Yang deficiency of heart and kidney syndromes regulated two special pathways (PPAR signaling pathway, thyroid hormone signaling pathway) in endocrine system and could improve renal function. Subsequently, we designed a rank algorithm, which integrated network topology with biological function, to identify important targets of these formulae. The results were consistent with the multi-level clustering results. At last, our literature mining validated about 20 % putative targets, as well as clustering results and effects of the formulae by experimental evidences. This study explained the medication patterns and scientific significance of TCM formulae on different types of CHD from perspective of systems biology. It may facilitate the understanding of different types of CHD described by traditional Chinese medicine from the perspectives of modern biology.

Chemical profiling of Honghua Xiaoyao tablet and simultaneous determination of its quality markers by liquid chromatography-tandem mass spectrometry combined with chemometrics methods.

Discovering marker components of traditional Chinese medicine formulas is challenging because of the hundreds of components they inherently contain. This study first proposed a reliable and validated method for the comprehensive profiling of chemical constituents in Honghua Xiaoyao tablet by using high-performance liquid chromatography coupled with mass spectrometry. After searching within the in-house library, a total of 55 constituents were unambiguously characterized or tentatively identified through reference standards and by comparing mass spectrometry data with literature values. Quantitative analysis of 14 compounds, which were selected as the quality marker components based on a serum pharmacochemistry study, has been performed by triple-quardrupole mass spectrometry technique. Multiple chemometric methods, including principal components analysis and hierarchical cluster analysis, were subsequently used to analyze the quantitative results, classify samples from three manufacturers, and distinguish the analytical markers. In method validation results, 14 quality marker compounds have shown good linearity (R2 ≥ 0.9965) with a relative wide concentration range and acceptable recovery at 98.39-102.46%. The proposed approach provides the chemical evidence for revealing the material basis of Honghua Xiaoyao tablet, and establishes a reliable statistical analysis-based strategy of quality marker investigation for controlling its quality.

Computational systems pharmacology reveals an antiplatelet and neuroprotective mechanism of Deng-Zhan-Xi-Xin injection in the treatment of ischemic stroke.

Herbs are typically prescribed in traditional Chinese medicine (TCM) to treat complex diseases. The multicomponent nature of herbal drug ingredients makes it difficult to readily understand their mode of action. To decipher their molecular mechanisms, here we proposed a novel computational systems pharmacology based approach, which consisted of transcriptome profiling, data collection, statistical analysis, network algorithm, bioinformatics analysis and pharmacological validation. The network algorithm called signed random walk with restart (SRWR) was used to simulate the propagation of drugs' effects on networks. This algorithm could identify proteins either positively or negatively regulated (activated or inhibited) by drugs on human signaling networks. To establish proof of principle, the herbal product Deng-Zhan-Xi-Xin injection (DZXXI), which exhibits pharmacological effects in ischemic stroke but its mechanism was unclear, was analyzed. Eighty-three targets were predicted with high confidence for DZXXI's active compounds in plasma, and 87 differentially expressed genes (DEGs) were identified in MCF7 cells treated with DZXXI. These target genes were further found to be associated with pathways involved in neuronal apoptosis in ischemic stroke, such as NF-κB signaling, TNF signaling, and PI3K-Akt signaling. Intersection analysis between DZXXI's putative targets with ischemic stroke-associated genes identified two important targets (PTGS1, PTGS2) corresponding to four DZXXI compounds, which were further validated using in silico and in vitro/vivo models. The most inhibited genes identified by the SRWR algorithm were significantly enriched with ischemic stroke-associated disease genes, antiplatelet associated pathways, and their encoded proteins were enriched in brain, vascular endothelium and platelets. The CMAP analysis based on DEGs suggested that DZXXI could function as both an anti-inflammatory and anti-platelet agent. Taken together, the computational analysis suggested that DZXXI exhibited anti-platelet and neuroprotective effects in the treatment of ischemic stroke. These deductions were preliminarily confirmed by subsequent in vitro/vivo studies. This approach provides a systems perspective to study the relevance between herbal drugs and disease processes, and can reveal possible pharmacological effects of multiple ingredients within herbal product.

Rapid characterization of chemical constituents and metabolites of Qi-Jing-Sheng-Bai granule by using UHPLC-Q-TOF-MS.

Qi-Jing-Sheng-Bai granule is an effective traditional Chinese medicine formula that has been widely used for the treatment of leukopenia post radiotherapy or chemotherapy. However, its chemical constituents were still unclear, which hindered interpreting bioactive constituents and studying integrative mechanisms. In this study, we developed a three-step strategy to characterize the chemical constituents and metabolites of Qi-Jing-Sheng-Bai by using ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. As a result, a total of 143 compounds, including 56 flavonoids, 51 saponins, and 36 other compounds, of which contained six pairs of isomers, were tentatively identified and characterized via reference standards and by comparing mass spectrometry data with literature. After oral administration of 15 g/kg Qi-Jing-Sheng-Bai, a number of 42 compounds including 24 prototype compounds and 18 metabolites have been detected in the serum of rats. This work serves as the first reference for Qi-Jing-Sheng-Bai chemical components and metabolites. Moreover, it provided a rapid and valid analytical strategy for characterization of the chemical compounds and metabolites of traditional Chinese medicine formula.

[Application of network biology on study of traditional Chinese medicine].

With the completion of the human genome project, people have gradually recognized that the functions of the biological system are fulfilled through network-type interaction between genes, proteins and small molecules, while complex diseases are caused by the imbalance of biological processes due to a number of gene expression disorders. These have contributed to the rise of the concept of the "multi-target" drug discovery. Treatment and diagnosis of traditional Chinese medicine are based on holism and syndrome differentiation. At the molecular level, traditional Chinese medicine is characterized by multi-component and multi-target prescriptions, which is expected to provide a reference for the development of multi-target drugs. This paper reviews the application of network biology in traditional Chinese medicine in six aspects, in expectation to provide a reference to the modernized study of traditional Chinese medicine.

Integrated immunogenomic analysis of single-cell and bulk profiling reveals novel tumor antigens and subtype-specific therapeutic agents in lung adenocarcinoma.

Background: In recent years, mRNA-based vaccines with promising safety and functional characteristics have gained significant momentum in cancer immunotherapy. However, stable immunological molecular subtypes of lung adenocarcinoma (LUAD) and novel tumor antigens for LUAD mRNA vaccine development remain elusive. Therefore, a novel approach is urgently needed to identify suitable LUAD subtypes and potential tumor antigens. Methods: The Cancer Genome Atlas (TCGA), the Genotype Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases were utilized to retrieve gene expression data. The LUAD Immunological Multi-Omics Classification (LIMOC) system was developed using seven machine learning (ML) algorithms by performing integrative immunogenomic analysis of single-cell and bulk tissue transcriptome profiling. Subsequently, a panel of approaches was applied to identify novel tumor antigens. Results: First, the LIMOC system was construct to identify three subtypes: LIMOC1, LIMOC2, and LIMOC3. Second, we identified CHIT1, LILRA4, and MEP1A as novel tumor antigens in LUAD; these genes were up-regulated, amplified, and mutated, and showed a positive association with APC infiltration, making them promising candidates for designing mRNA vaccines. Notably, the LIMOC2 subtype had the worst prognosis and could benefit most from mRNA immunization. Furthermore, we performed a comprehensive in silico screening of approximately 2000 compounds and identified Sorafenib and Azacitidine as potential subtype-specific therapeutic agents. Conclusions: Overall, our study established a robust LIMOC system and identified CHIT1, LILRA4, and MEP1A as promising tumor antigen candidates for development of anti-LUAD mRNA vaccines, particularly for the LIMOC2 subtype.

Exploring the anti-ovarian aging mechanism of He's Yangchao formula: Insights from multi-omics analysis in naturally aged mice.

BACKGROUND: The rapid acceleration of female reproductive aging has become a major public health concern. He's Yangchao formula (HSYC), a compound comprising eight herbs, has demonstrated efficacy in enhancing ovarian function. Thus, an in-depth study of its anti-ovarian aging mechanism is required. PURPOSE: To evaluate the anti-ovarian aging effect of HSYC in naturally aged mice and investigate the underlying mechanism by analyzing the gut microbiota (GM), metabolome, and transcriptome. METHODS: Young and advanced maternal age (AMA) mice were selected for this study. Hematoxylin and eosin staining, fluorescence staining, western blotting, and qPCR analyses were used to detect the phenotypes associated with ovarian aging. Subsequently, analyses of the GM, transcriptome, and metabolome analyses were performed to explore the potential mechanisms of action of HSYC. Finally, in vivo and in vitro experiments were performed to verify potential therapeutic mechanisms. RESULTS: HSYC promoted follicular development in AMA mice and ameliorated age-related mitochondrial dysfunction, apoptosis, and defects in DNA damage repair. GM analysis revealed that HSYC treatment significantly increased the abundance of Akkermansia and Turicibacter. Transcriptome and metabolome analyses showed that HSYC might mitigate ovarian aging by regulating metabolic pathways, amino acid metabolism, glutathione metabolism, and the synthesis of pantothenic acid and coenzyme A. Combined transcriptomic and metabolomic analyses identified the glutathione metabolic pathway as the key pathway through which HSYC counteracts ovarian aging. Additional experimental verification confirmed that HSYC upregulated the glutathione metabolic genes GPX8, GSTA1, and GSTA4, increased glutathione-related products (GSH), and reduced ROS levels. CONCLUSIONS: HSYC exerts beneficial therapeutic effects on ovarian aging by regulating multiple endogenous metabolites, targets, and metabolic pathways, with an emphasis on its anti-ovarian aging effects through the glutathione metabolic pathway. These findings underscore the innovative potential of HSYC in addressing ovarian aging and offer a novel therapeutic approach that targets multiple biological pathways to improve the reproductive health of women with AMA..

Network Medicine-Based Strategy Identifies Maprotiline as a Repurposable Drug by Inhibiting PD-L1 Expression via Targeting SPOP in Cancer.

Immune checkpoint inhibitors (ICIs) are drugs that inhibit immune checkpoint (ICP) molecules to restore the antitumor activity of immune cells and eliminate tumor cells. Due to the limitations and certain side effects of current ICIs, such as programmed death protein-1, programmed cell death-ligand 1, and cytotoxic T lymphocyte-associated antigen 4 (CTLA4) antibodies, there is an urgent need to find new drugs with ICP inhibitory effects. In this study, a network-based computational framework called multi-network algorithm-driven drug repositioning targeting ICP (Mnet-DRI) is developed to accurately repurpose novel ICIs from ≈3000 Food and Drug Administration-approved or investigational drugs. By applying Mnet-DRI to PD-L1, maprotiline (MAP), an antidepressant drug is repurposed, as a potential PD-L1 modifier for colorectal and lung cancers. Experimental validation revealed that MAP reduced PD-L1 expression by targeting E3 ubiquitin ligase speckle-type zinc finger structural protein (SPOP), and the combination of MAP and anti-CTLA4 in vivo significantly enhanced the antitumor effect, providing a new alternative for the clinical treatment of colorectal and lung cancer.

Benzosceptrin C induces lysosomal degradation of PD-L1 and promotes antitumor immunity by targeting DHHC3.

Programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) blockade has become a mainstay of cancer immunotherapy. Targeting the PD-1/PD-L1 axis with small molecules is an attractive approach to enhance antitumor immunity. Here, we identified a natural marine product, benzosceptrin C (BC), that enhances the cytotoxicity of T cells to cancer cells by reducing the abundance of PD-L1. Furthermore, BC exerts its antitumor effect in mice bearing MC38 tumors by activating tumor-infiltrating T cell immunity. Mechanistic studies suggest that BC can prevent palmitoylation of PD-L1 by inhibiting DHHC3 enzymatic activity. Subsequently, PD-L1 is transferred from the membrane to the cytoplasm and cannot return to the membrane via recycling endosomes, triggering lysosome-mediated degradation of PD-L1. Moreover, the combination of BC and anti-CTLA4 effectively enhances antitumor T cell immunity. Our findings reveal a previously unrecognized antitumor mechanism of BC and represent an alternative immune checkpoint blockade (ICB) therapeutic strategy to enhance the efficacy of cancer immunotherapy.

Multi-omics and network pharmacology study reveals the effects of Dengzhan Shengmai capsule against neuroinflammatory injury and thrombosis induced by ischemic stroke.

ETHNOPHARMACOLOGICAL RELEVANCE: Dengzhan Shengmai capsule (DZSM) is a traditional herb medicine used by Dai, an ethnic-minority community living in Xishuang banna tropical rainforest in Southwest of China. It was originally intended to treat disorders caused by insufficient brain function, characterized by gibberish, unresponsiveness, or confusion. Accumulating clinical evidences exhibited that it is effective on treating ischemic stroke (IS). However, the action of DZSM against IS needs to be further elucidated. AIM OF THE STUDY: To investigate the effect of DZSM and its active components against IS and the way of its action by multi-omics and network pharmacology. MATERIALS AND METHODS: A middle cerebral artery occlusion/reperfusion (MCAO/R) rat model was established to investigate the effect of DZSM on the focal cerebral ischemia/reperfusion injury. An integrated strategy combining metabolomics, network pharmacology and transcriptomics was performed to systematically clarify the underlying mechanism of action of DZSM against IS. AutoDock Vina was applied to conduct molecular docking simulation for the binding between the potential active compounds and targets. Arachidonic acid (AA) induced platelet aggregation and lipopolysaccharide (LPS) stimulated microglial cells BV2 inflammation models were applied for the in vitro validation of effects of DZSM and its potential active compounds. RESULTS: In MCAO/R rats, DZSM could significantly reduce the infarct volume. Putative target prediction and functional enrichment analysis based on network pharmacological indicated that the key targets and the potential active compounds played important roles in DZSM's treatment to IS. The targets included four common genes (PTGS1, PTGS2, NFKB1 and NR1I2) and five key TFs (NFKB1, RELA, HIF1A, ESR1 and HDAC1), whilst 22 potential active compounds were identified. Molecular docking indicated that good binding affinity have been seen between those compounds and NR1I2, NFKB1, and RELA. Multi-omics study revealed that DZSM could regulate glutamate by influencing citrate cycle and glutamate involved pathways, and have showed neuroprotection activity and anti-inflammation activity by inhibiting NF-κB pathway. Neuroprotective effects of DZSM was validated by regulating of NF-κB signaling pathway and its downstream NO, TNF-α and IL-6 cytokines contributed to the activity of DZSM and its active compounds of scutellarin, quercetin 3-O-glucuronide, ginsenoside Rb1, schizandrol A and 3, 5-diCQA, whilst the antithrombotic activity of DZSM and its active compounds of schisanhenol, apigenin and schisantherin B were screened out by anti-platelet aggregation experiment. CONCLUSION: DZSM could against IS via regulating its downstream NO, TNF-α and IL-6 cytokines through NF-κB signaling pathway and alleviating thrombosis.

Astragaloside IV derivative HHQ16 ameliorates infarction-induced hypertrophy and heart failure through degradation of lncRNA4012/9456.

Reversing ventricular remodeling represents a promising treatment for the post-myocardial infarction (MI) heart failure (HF). Here, we report a novel small molecule HHQ16, an optimized derivative of astragaloside IV, which effectively reversed infarction-induced myocardial remodeling and improved cardiac function by directly acting on the cardiomyocyte to reverse hypertrophy. The effect of HHQ16 was associated with a strong inhibition of a newly discovered Egr2-affiliated transcript lnc9456 in the heart. While minimally expressed in normal mouse heart, lnc9456 was dramatically upregulated in the heart subjected to left anterior descending coronary artery ligation (LADL) and in cardiomyocytes subjected to hypertrophic stimulation. The critical role of lnc9456 in cardiomyocyte hypertrophy was confirmed by specific overexpression and knockout in vitro. A physical interaction between lnc9456 and G3BP2 increased NF-κB nuclear translocation, triggering hypertrophy-related cascades. HHQ16 physically bound to lnc9456 with a high-affinity and induced its degradation. Cardiomyocyte-specific lnc9456 overexpression induced, but knockout prevented LADL-induced, cardiac hypertrophy and dysfunction. HHQ16 reversed the effect of lnc9456 overexpression while lost its protective role when lnc9456 was deleted, further confirming lnc9456 as the bona fide target of HHQ16. We further identified the human ortholog of lnc9456, also an Egr2-affiliated transcript, lnc4012. Similarly, lnc4012 was significantly upregulated in hypertrophied failing hearts of patients with dilated cardiomyopathy. HHQ16 also specifically bound to lnc4012 and caused its degradation and antagonized its hypertrophic effects. Targeted degradation of pathological increased lnc4012/lnc9456 by small molecules might serve as a novel promising strategy to regress infarction-induced cardiac hypertrophy and HF.

Cytokine Storm in Acute Viral Respiratory Injury: Role of Qing-Fei-Pai-Du Decoction in Inhibiting the Infiltration of Neutrophils and Macrophages through TAK1/IKK/NF-[Formula: see text]B Pathway.

COVID-19 has posed unprecedented challenges to global public health since its outbreak. The Qing-Fei-Pai-Du decoction (QFPDD), a Chinese herbal formula, is widely used in China to treat COVID-19. It exerts an impressive therapeutic effect by inhibiting the progression from mild to critical disease in the clinic. However, the underlying mechanisms remain obscure. Both SARS-CoV-2 and influenza viruses elicit similar pathological processes. Their severe manifestations, such as acute respiratory distress syndrome (ARDS), multiple organ failure (MOF), and viral sepsis, are correlated with the cytokine storm. During flu infection, QFPDD reduced the lung indexes and downregulated the expressions of MCP-1, TNF-[Formula: see text], IL-6, and IL-1[Formula: see text] in broncho-alveolar lavage fluid (BALF), lungs, or serum samples. The infiltration of neutrophils and inflammatory monocytes in lungs was decreased dramatically, and lung injury was ameliorated in QFPDD-treated flu mice. In addition, QFPDD also inhibited the polarization of M1 macrophages and downregulated the expressions of IL-6, TNF-[Formula: see text], MIP-2, MCP-1, and IP-10, while also upregulating the IL-10 expression. The phosphorylated TAK1, IKK[Formula: see text]/[Formula: see text], and I[Formula: see text]B[Formula: see text] and the subsequent translocation of phosphorylated p65 into the nuclei were decreased by QFPDD. These findings indicated that QFPDD reduces the intensity of the cytokine storm by inhibiting the NF-[Formula: see text]B signaling pathway during severe viral infections, thereby providing theoretical and experimental support for its clinical application in respiratory viral infections.

Systematic Understanding of Anti-Aging Effect of Coenzyme Q10 on Oocyte Through a Network Pharmacology Approach.

Background: Maternal oocyte aging is strongly contributing to age-related decline in female fertility. Coenzyme Q10 (CoQ10) exerts positive effects in improving aging-related deterioration of oocyte quality, but the exact mechanism is unclear. Objective: To reveal the system-level mechanism of CoQ10's anti-aging effect on oocytes based on network pharmacology. Methods: This study adopted a systems network pharmacology approach, including target identification, data integration, network and module construction, bioinformatics analysis, molecular docking, and molecular dynamics simulation. Result: A total of 27 potential therapeutic targets were screened out. Seven hub targets (PPARA, CAT, MAPK14, SQSTM1, HMOX1, GRB2, and GSR) were identified. Functional and pathway enrichment analysis indicated that these 27 putative targets exerted therapeutic effects on oocyte aging by regulating signaling pathways (e.g., PPAR, TNF, apoptosis, necroptosisn, prolactin, and MAPK signaling pathway), and are involved oxidation-reduction process, mitochondrion, enzyme binding, reactive oxygen species metabolic process, ATP binding, among others. In addition, five densely linked functional modules revealed the potential mechanisms of CoQ10 in improving aging-related deterioration of oocyte quality are closely related to antioxidant, mitochondrial function enhancement, autophagy, anti-apoptosis, and immune and endocrine system regulation. The molecular docking study reveals that seven hub targets have a good binding affinity towards CoQ10, and molecular dynamics simulation confirms the stability of the interaction between the hub targets and the CoQ10 ligand. Conclusion: This network pharmacology study revealed the multiple mechanisms involved in the anti-aging effect of CoQ10 on oocytes. The molecular docking and molecular dynamics simulation provide evidence that CoQ10 may act on these hub targets to fight against oocytes aging.

Integrated hepatic single-cell RNA sequencing and untargeted metabolomics reveals the immune and metabolic modulation of Qing-Fei-Pai-Du decoction in mice with coronavirus-induced pneumonia.

BACKGROUND: Although Qing-Fei-Pai-Du decoction (QFPDD) is extensively used clinically to treat COVID-19 patients, the mechanism by which it modulates the immunological and metabolic functions of liver tissue remains unknown. PURPOSE: The purpose of this study is to investigate the mechanism of action of QFPDD in the treatment of mice with coronavirus-induced pneumonia by combining integrated hepatic single-cell RNA sequencing and untargeted metabolomics. METHODS: We developed a human coronavirus pneumonia model in BALB/c mice by infecting them with human coronavirus HCoV-229E with stimulating them with cold-damp environment. We initially assessed the status of inflammation and immunity in model mice treated with or without QFPDD by detecting peripheral blood lymphocytes and inflammatory cytokines. Then, single-cell RNA sequencing and untargeted metabolomics were performed on mouse liver tissue. RESULTS: HCoV-229E infection in combination with exposure to a cold-damp environment significantly decreased the percentage of peripheral blood lymphocytes (CD4+ and CD8+ T cells, B cells) in mice, which was enhanced by QFPDD therapy. Meanwhile, the levels of inflammatory cytokines such as IL-6, TNF-α, and IFN-γ were significantly increased in mouse models but significantly decreased by QFPDD treatment. Single-cell RNA sequencing analysis showed that QFPDD could attenuate disease-associated alterations in gene expression, core transcriptional regulatory networks, and cell-type composition. Computational predictions indicated that QFPDD rectified the observed aberrant patterns of cell-cell communication. Additionally, the metabolic profiles of liver tissue in the Model group were distinct from mice in the Control group, and QFPDD significantly regulated hepatic purine metabolism. CONCLUSION: To the best of our knowledge, this study is the first to integrate hepatic single-cell RNA sequencing and untargeted metabolomics into a TCM formula and these valuable findings indicate that QFPDD can improve immune function and reduce liver injury and inflammation.