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.

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.

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.

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.

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.

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.

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.

Integrated microbiome and metabolome analysis reveals the potential therapeutic mechanism of Qing-Fei-Pai-Du decoction in mice with coronavirus-induced pneumonia.

Current studies have shown that gut microbiota may be closely related to the severity of coronavirus disease 2019 (COVID-19) by regulating the host immune response. Qing-Fei-Pai-Du decoction (QFPDD) is the recommended drug for clinical treatment of patients with COVID-19 in China, but whether it exerts a therapeutic effect by modulating the immune response through gut microbiota remains unclear. In this study, we evaluated the therapeutic effects of QFPDD in pneumonia model mice and performed 16S rRNA sequencing and serum and lung tissue metabolomic analysis to explore the underlying mechanisms during the treatment. Then, Spearman correlation analysis was performed on gut microbiome, serum metabolome, and immune-inflammation-related indicators. Our results suggest that QFPDD can restore the richness and diversity of gut microbiota, and multiple gut microbiota (including Alistipes, Odoribacter, Staphylococcus, Lachnospiraceae_NK4A136_group Enterorhabdus, and unclassified_f_Lachnospiraceae) are significantly associated with immune-inflammation-related indicators. In addition, various types of lipid metabolism changes were observed in serum and lung tissue metabolome, especially glycerophospholipids and fatty acids. A total of 27 differential metabolites (DMs) were significantly correlated with immune-inflammation-related indicators, including 9 glycerophospholipids, 7 fatty acids, 3 linoleic acid, 2 eicosanoids, 2 amino acids, 2 bile acids, and 2 others. Interestingly, these DMs showed a good correlation with the gut microbiota affected by QFPDD. The above results suggest that QFPDD can improve the immune function and reduce inflammation in pneumonia model mice by remodeling gut microbiota and host metabolism.

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.

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.

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.

Identification of a DNA Methylation-Driven Genes-Based Prognostic Model and Drug Targets in Breast Cancer: In silico Screening of Therapeutic Compounds and in vitro Characterization.

DNA methylation is a vital epigenetic change that regulates gene transcription and helps to keep the genome stable. The deregulation hallmark of human cancer is often defined by aberrant DNA methylation which is critical for tumor formation and controls the expression of several tumor-associated genes. In various cancers, methylation changes such as tumor suppressor gene hypermethylation and oncogene hypomethylation are critical in tumor occurrences, especially in breast cancer. Detecting DNA methylation-driven genes and understanding the molecular features of such genes could thus help to enhance our understanding of pathogenesis and molecular mechanisms of breast cancer, facilitating the development of precision medicine and drug discovery. In the present study, we retrospectively analyzed over one thousand breast cancer patients and established a robust prognostic signature based on DNA methylation-driven genes. Then, we calculated immune cells abundance in each patient and lower immune activity existed in high-risk patients. The expression of leukocyte antigen (HLA) family genes and immune checkpoints genes were consistent with the above results. In addition, more mutated genes were observed in the high-risk group. Furthermore, a in silico screening of druggable targets and compounds from CTRP and PRISM databases was performed, resulting in the identification of five target genes (HMMR, CCNB1, CDC25C, AURKA, and CENPE) and five agents (oligomycin A, panobinostat, (+)-JQ1, voxtalisib, and arcyriaflavin A), which might have therapeutic potential in treating high-risk breast cancer patients. Further in vitro evaluation confirmed that (+)-JQ1 had the best cancer cell selectivity and exerted its anti-breast cancer activity through CENPE. In conclusion, our study provided new insights into personalized prognostication and may inspire the integration of risk stratification and precision therapy.

A Comprehensive Investigation to Reveal the Relationship Between Plasmacytoid Dendritic Cells and Breast Cancer by Multiomics Data Analysis.

Plasmacytoid dendritic cells (pDC) are an essential immune microenvironment component. They have been reported for crucial roles in linking the adaptive and immune systems. However, the prognostic role of the pDC in breast cancer (BRCA) was controversial. In this work, we collected large sample cohorts and did a comprehensive investigation to reveal the relationship between pDC and BRCA by multiomics data analysis. Elevated pDC levels were correlated with prolonged survival outcomes in BRCA patients. The distinct mutation landscape and lower burden of somatic copy number alterations (SCNA) and lower intratumoral heterogeneity were observed in the high pDC abundance group. Additionally, a more sensitive immune response and chemotherapies response were observed in the high pDC group, which implicates that patients with high pDC abundance can be benefited from the combination of chemotherapy and immunotherapy. In conclusion, the correlation between pDC abundance and BRCA patients' overall survival (OS) was found to be positive. We identified the molecular profiles of BRCA patients with pDC abundance. Our findings may be beneficial in aiding in the development of immunotherapy and elucidating on the precision treatment for BRCA.

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.

Ferroptosis-Related Gene Model to Predict Overall Survival of Ovarian Carcinoma.

BACKGROUND: Ovarian cancer (OC) is the eighth most common cause of cancer death and the second cause of gynecologic cancer death in women around the world. Ferroptosis, an iron-dependent regulated cell death, plays a vital role in the development of many cancers. Applying expression of ferroptosis-related gene to forecast the cancer progression is helpful for cancer treatment. However, the relationship between ferroptosis-related genes and OC patient prognosis is still vastly unknown, making it still a challenge for developing ferroptosis therapy for OC. METHODS: The Cancer Genome Atlas (TCGA) data of OC were obtained and the datasets were randomly divided into training and test datasets. A novel ferroptosis-related gene signature associated with overall survival (OS) was constructed according to the training cohort. The test dataset and ICGC dataset were used to validate this signature. RESULTS: We constructed a model containing nine ferroptosis-related genes, namely, LPCAT3, ACSL3, CRYAB, PTGS2, ALOX12, HSBP1, SLC1A5, SLC7A11, and ZEB1, and predicted the OS of OC in TCGA. At a suitable cutoff, patients were divided into low risk and high risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics (ROCs) were as high as 0.664, respectively. Then, the test dataset and the ICGC dataset were used to evaluate our model, and the ROCs of test dataset were 0.667 and 0.777, respectively. In addition, functional analysis and correlation analysis showed that immune-related pathways were significantly enriched. Meanwhile, we also integrated with other clinical factors and we found the synthesized clinical factors and ferroptosis-related gene signature improved prognostic accuracy relative to the ferroptosis-related gene signature alone. CONCLUSION: The ferroptosis-related gene signature could predict the OS of OC patients and improve therapeutic decision-making.

Quantitative proteomics reveals Shexiang Baoxin Pill exerts cardioprotective effects by preserving energy metabolism in a rat model of myocardial infarction.

ETHNOPHARMACOLOGICAL RELEVANCE: Shexiang Baoxin Pill (SBP) is a composite formula of traditional Chinese medicine used to treat cardiovascular disease (CVD) in the clinic. However, the mechanism of its therapeutic effect on CVD has not been clearly elucidated yet. AIM OF THE STUDY: The aim of this study was to investigate the potential cardioprotective mechanism of SBP in the treatment of myocardial infarction (MI) model rats by applying proteomic approach. MATERIALS AND METHODS: The rat model of MI was generated by ligating the left anterior descending coronary artery. Eighteen rats were randomly divided into three groups (n = 6 each): the MI group, MI group treated with SBP (SBP), and sham-operated group (SOG). Cardiac function in the experimental groups was assessed by echocardiography analyses after 15 days of treatment. A label-free quantitative proteomic approach was utilized to investigate the whole proteomes of heart tissues from the groups above on the day of the operation (Day 0) and 15 days later (Day 15). The differentially expressed proteins were subsequently analyzed with bioinformatic methods. Additionally, the expression levels of two promising proteins were validated by Western blotting. RESULTS: The echocardiography analyses showed that SBP treatment significantly preserved the cardiac function of MI rats. Additionally, quantitative proteomics identified 389 differentially expressed proteins, and 15 proteins were considered as logical candidates for explaining the cardioprotective effect of SBP. Bioinformatic analysis of these differentially expressed proteins revealed that the proteins involved in cellular mitochondrial energy metabolism processes, such as fatty acid beta-oxidation and aerobic respiration, were significantly regulated under SBP treatment, of which fatty acid-binding protein 3 (FABP3) and myoglobin (MB) were significantly downregulated in the MI model group compared with the SOG group and returned to the basal level with SBP treatment, confirmed by Western blotting. CONCLUSIONS: The results of our study suggest that the cardioprotective effects of SBP are achieved through the preservation of energy metabolism in the heart tissue of MI rats.

Systems pharmacological study illustrates the immune regulation, anti-infection, anti-inflammation, and multi-organ protection mechanism of Qing-Fei-Pai-Du decoction in the treatment of COVID-19.

BACKGROUND: The traditional Chinese medicine (TCM) formula Qing-Fei-Pai-Du decoction (QFPDD) was the most widely used prescription in China's campaign to contain COVID-19, which has exhibited positive effects. However, the underlying mode of action is largely unknown. PURPOSE: A systems pharmacology strategy was proposed to investigate the mechanisms of QFPDD against COVID-19 from molecule, pathway and network levels. STUDY DESIGN AND METHODS: The systems pharmacological approach consisted of text mining, target prediction, data integration, network study, bioinformatics analysis, molecular docking, and pharmacological validation. Especially, we proposed a scoring method to measure the confidence of targets identified by prediction and text mining, while a novel scheme was used to identify important targets from 4 aspects. RESULTS: 623 high-confidence targets of QFPDD's 12 active compounds were identified, 88 of which were overlapped with genes affected by SARS-CoV-2 infection. These targets were found to be involved in biological processes related with the development of COVID-19, such as pattern recognition receptor signaling, interleukin signaling, cell growth and death, hemostasis, and injuries of the nervous, sensory, circulatory, and digestive systems. Comprehensive network and pathway analysis were used to identify 55 important targets, which regulated 5 functional modules corresponding to QFPDD's effects in immune regulation, anti-infection, anti-inflammation, and multi-organ protection, respectively. Four compounds (baicalin, glycyrrhizic acid, hesperidin, and hyperoside) and 7 targets (AKT1, TNF-α, IL6, PTGS2, HMOX1, IL10, and TP53) were key molecules related to QFPDD's effects. Molecular docking verified that QFPDD's compounds may bind to 6 host proteins that interact with SARS-CoV-2 proteins, further supported the anti-virus effect of QFPDD. At last, in intro experiments validated QFPDD's important effects, including the inhibition of IL6, CCL2, TNF-α, NF-κB, PTGS1/2, CYP1A1, CYP3A4 activity, the up-regulation of IL10 expression, and repressing platelet aggregation. CONCLUSION: This work illustrated that QFPDD could exhibit immune regulation, anti-infection, anti-inflammation, and multi-organ protection. It may strengthen the understanding of QFPDD and facilitate more application of this formula in the campaign to SARS-CoV-2.

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.

Integrated Bioinformatics Analysis Reveals Key Candidate Genes and Pathways Associated With Clinical Outcome in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) accounts for approximately 85-90% of all liver cancer cases and has poor relapse-free survival. There are many gene expression studies that have been performed to elucidate the genetic landscape and driver pathways leading to HCC. However, existing studies have been limited by the sample size and thus the pathogenesis of HCC is still unclear. In this study, we performed an integrated characterization using four independent datasets including 320 HCC samples and 270 normal liver tissues to identify the candidate genes and pathways in the progression of HCC. A total of 89 consistent differentially expression genes (DEGs) were identified. Gene-set enrichment analysis revealed that these genes were significantly enriched for cellular response to zinc ion in biological process group, collagen trimer in the cellular component group, extracellular matrix (ECM) structural constituent conferring tensile strength in the molecular function group, protein digestion and absorption, mineral absorption and ECM-receptor interaction. Network system biology based on the protein-protein interaction (PPI) network was also performed to identify the most connected and important genes based on our DEGs. The top five hub genes including osteopontin (SPP1), Collagen alpha-2(I) chain (COL1A2), Insulin-like growth factor I (IGF1), lipoprotein A (LPA), and Galectin-3 (LGALS3) were identified. Western blot and immunohistochemistry analysis were employed to verify the differential protein expression of hub genes in HCC patients. More importantly, we identified that these five hub genes were significantly associated with poor disease-free survival and overall survival. In summary, we have identified a potential clinical significance of these genes as prognostic biomarkers for HCC patients who would benefit from experimental approaches to obtain optimal outcome.