Prognostic factors for invasive mucinous adenocarcinoma of the lung: systematic review and meta-analysis.

BACKGROUND: Invasive mucinous adenocarcinoma of the lung (IMA) is a unique and rare subtype of lung adenocarcinoma with poorly defined prognostic factors and highly controversial studies. Hence, this study aimed to comprehensively identify and summarize the prognostic factors associated with IMA. METHODS: A comprehensive search of relevant literature was conducted in the PubMed, Embase, Cochrane, and Web of Science databases from their inception until June 2023. The pooled hazard ratio (HR) and corresponding 95% confidence intervals (CI) of overall survival (OS) and/or disease-free survival (DFS) were obtained to evaluate potential prognostic factors. RESULTS: A total of 1062 patients from 11 studies were included. In univariate analysis, we found that gender, age, TNM stage, smoking history, lymph node metastasis, pleural metastasis, spread through air spaces (STAS), tumor size, pathological grade, computed tomography (CT) findings of consolidative-type morphology, pneumonia type, and well-defined heterogeneous ground-glass opacity (GGO) were risk factors for IMA, and spiculated margin sign was a protective factor. In multivariate analysis, smoking history, lymph node metastasis, pathological grade, STAS, tumor size, and pneumonia type sign were found to be risk factors. There was not enough evidence that epidermal growth factor receptor (EGFR) mutations, anaplastic lymphoma kinase (ALK) mutations, CT signs of lobulated margin, and air bronchogram were related to the prognosis for IMA. CONCLUSION: In this study, we comprehensively analyzed prognostic factors for invasive mucinous adenocarcinoma of the lung in univariate and multivariate analyses of OS and/or DFS. Finally, 12 risk factors and 1 protective factor were identified. These findings may help guide the clinical management of patients with invasive mucinous adenocarcinoma of the lung.

Evaluation of Clinical Efficacy of Acupuncture and Moxibustion for Asthma: Systematic Review and Meta-Analysis.

Objective: The effectiveness of manual acupuncture for treating bronchial asthma is still debatable and broad, and the effects of different acupuncture points, treatment durations, or illness trajectories have never been rigorously assessed. The objective of this revised systematic review and subgroup meta-analysis of randomized controlled trials (RCTs) is to ascertain the clinical efficacy of manual acupuncture on bronchial asthma and whether these effects varied depending on the acupuncture points, length of treatment, or course of the disease. Materials and methods: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria were followed for creating a systematic review and meta-analysis. From the beginning through March 25, 2022, six electronic databases were checked. For the treatment of asthma, all RCTs contrasting acupuncture therapy along with conventional treatment against conventional treatment alone were chosen. The information was examined using Review Manager version 5.3 and Comprehensive Meta-Analysis version 3. Clinical efficacy (including the effective rate and the recurrence rate) was the primary outcome, and pulmonary function (including FEV1%, PEF) and The secondary results were T-lymphocyte immunity (containing CD3+, CD4+, and CD8+). Based on the acupuncture points, length of therapy, and nature of the condition, subgroup analyses were carried out. Results: There were a total of 21 RCTs that enrolled 2510 individuals. According to the meta-findings, analysis's manual acupuncture in addition to conventional treatment significantly increased the effective rate when compared to conventional treatment alone [OR = 5.14 95% CI 3.58-7.38, P < .00001], lung functions [FEV1% (MD = 6.18, 95% CI 2.40-9.96, P = .001) and PEF (MD = 0.45 95% CI 0.18-0.73, P = .001)], immune functions [CD3+ T lymphocytes (MD = 7.55 95% CI 6.55-8.56, P < .00001), CD4+ T-lymphocytes (MD = 5.11 95% CI 4.09-6.13, P < .00001), T-lymphocyte CD8+ (MD = -0.37.11 95% CI -3.62--2.51, P < .00001)] and noteworthy reduction in the recurrence rate (OR = 0.19 95% CI 0.10-0.38, P < .00001). Results from the subgroup analysis were consistent. Conclusion: Manual acupuncture combined with Western Medicine is more effective than conventional treatment alone for bronchial asthma. Combination therapy can significantly improve clinical efficacy, lung function, and immune function while reducing the relapse rate. But to further support the results of this investigation, high-quality RCTs with long-term outcomes are still required, taking into account the inherent limitations of the included studies. Registration number: PROSPERO (no. CRD42022357805) (https://www.crd.york.ac.uk/prospero/).

The Extraction, Determination, and Bioactivity of Curcumenol: A Comprehensive Review.

Curcuma wenyujin is a member of the Curcuma zedoaria (zedoary, Zingiberaceae) family, which has a long history in traditional Chinese medicine (TCM) due to its abundant biologically active constituents. Curcumenol, a component of Curcuma wenyujin, has several biological activities. At present, despite different pharmacological activities being reported, the clinical usage of curcumenol remains under investigation. To further determine the characteristics of curcumenol, the extraction, determination, and bioactivity of the compound are summarized in this review. Existing research has reported that curcumenol exerts different pharmacological effects in regard to a variety of diseases, including anti-inflammatory, anti-oxidant, anti-bactericidal, anti-diabetic, and anti-cancer activity, and also ameliorates osteoporosis. This review of curcumenol provides a theoretical basis for further research and clinical applications.

Discovery of Novel Noncovalent KRAS G12D Inhibitors through Structure-Based Virtual Screening and Molecular Dynamics Simulations.

The development of effective inhibitors targeting the Kirsten rat sarcoma viral proto-oncogene (KRASG12D) mutation, a prevalent oncogenic driver in cancer, represents a significant unmet need in precision medicine. In this study, an integrated computational approach combining structure-based virtual screening and molecular dynamics simulation was employed to identify novel noncovalent inhibitors targeting the KRASG12D variant. Through virtual screening of over 1.7 million diverse compounds, potential lead compounds with high binding affinity and specificity were identified using molecular docking and scoring techniques. Subsequently, 200 ns molecular dynamics simulations provided critical insights into the dynamic behavior, stability, and conformational changes of the inhibitor-KRASG12D complexes, facilitating the selection of lead compounds with robust binding profiles. Additionally, in silico absorption, distribution, metabolism, excretion (ADME) profiling, and toxicity predictions were applied to prioritize the lead compounds for further experimental validation. The discovered noncovalent KRASG12D inhibitors exhibit promises as potential candidates for targeted therapy against KRASG12D-driven cancers. This comprehensive computational framework not only expedites the discovery of novel KRASG12D inhibitors but also provides valuable insights for the development of precision treatments tailored to this oncogenic mutation.

Crosstalk and plasticity driving between cancer-associated fibroblasts and tumor microenvironment: significance of breast cancer metastasis.

Cancer-associated fibroblasts (CAFs) are the most abundant stromal cell population in breast tumors. A functionally diverse population of CAFs increases the dynamic complexity of the tumor microenvironment (TME). The intertwined network of the TME facilitates the interaction between activated CAFs and breast cancer cells, which can lead to the proliferation and invasion of breast cells. Considering the special transmission function of CAFs, the aim of this review is to summarize and highlight the crosstalk between CAFs and breast cancer cells in the TME as well as the relationship between CAFs and extracellular matrix (ECM), soluble cytokines, and other stromal cells in the metastatic state. The crosstalk between cancer-associated fibroblasts and tumor microenvironment also provides a plastic therapeutic target for breast cancer metastasis. In the course of the study, the inhibitory effects of different natural compounds on targeting CAFs and the advantages of different drug combinations were summarized. CAFs are also widely used in the diagnosis and treatment of breast cancer. The cumulative research on this phenomenon supports the establishment of a targeted immune microenvironment as a possible breakthrough in the prevention of invasive metastasis of breast cancer.

CERS4 predicts positive anti-PD-1 response and promotes immunomodulation through Rhob-mediated suppression of CD8+Tim3+ exhausted T cells in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is one of the main malignant tumors with high mortality and short survival time. Immunotherapy has become the standard treatment for advanced NSCLC, but it has the problems of drug resistance and low response rate. Therefore, obtaining effective biomarkers to predict and enhance immune checkpoint inhibitors (ICIs) efficacy in NSCLC is important. Sphingolipid metabolism is recently found to be closely involved in tumor immunotherapy. CERS4, an important sphingolipid metabolizing enzyme, is positively correlated with the efficacy of anti-PD-1 therapy for NSCLC. Upregulation of CERS4 expression could improve the efficacy of anti-PD-1 therapy for NSCLC. High expression of CERS4 could downregulate the expression of Rhob in tumor. Significantly, the ratio of CD4+/CD8+ T cell increased and the ratio of Tim-3+/CD8+ T cell decreased in spleen and peripheral blood cells. When Rhob was knocked out, the efficacy of PD-1 mAb treatment increased, and the frequency of Tim-3+ CD8+ T cell decreased. This finding further confirmed the role of sphingolipid metabolites in regulating the immunotherapeutic function of NSCLC. These metabolites may improve the efficacy of PD-1 mAb in NSCLC by regulating the CERS4/Rhob/Tim-3 axis. Overall, this study provided a potential and effective target for predicting and improving the efficacy of ICIs for NSCLC. It also provided a new perspective for the study on the mechanisms of ICIs resistance for NSCLC.

ß-Elemene enhances erlotinib sensitivity through induction of ferroptosis by upregulating lncRNA H19 in EGFR-mutant non-small cell lung cancer.

Nearly half of all Asian non-small cell lung cancer (NSCLC) patients harbour epidermal growth factor receptor (EGFR) mutations, and first-generation EGFR tyrosine kinase inhibitors (TKIs) are one of the first-line treatments that have improved the outcomes of these patients. Unfortunately, 20% of these patients can not benefit from the treatment. The basis of this primary resistance is poorly understood. Therefore, overcoming EGFR-TKI primary resistance and maintaining the efficacy of TKIs has become a key issue. ß-Elemene, a sesquiterpene compound extracted from Curcuma aromatica Salisb. (wenyujing), has shown potent antitumor effects. In this research, we found that ß-elemene combined with erlotinib enhanced the cytotoxicity of erlotinib to primary EGFR-TKI-resistant NSCLC cells with EGFR mutations and that ferroptosis was involved in the antitumor effect of the combination treatment. We found that lncRNA H19 was significantly downregulated in primary EGFR-TKI-resistant NSCLC cell lines and was upregulated by the combination treatment. Overexpression or knockdown of H19 conferred sensitivity or resistance to erlotinib, respectively, in both in vitro and in vivo studies. The high level of H19 enhanced the cytotoxicity of erlotinib by inducing ferroptosis. In conclusion, our data showed that ß-elemene combined with erlotinib could enhance sensitivity to EGFR-TKIs through induction of ferroptosis via H19 in primary EGFR-TKI-resistant lung cancer, providing a promising strategy to overcome EGFR-TKI resistance in NSCLC patients.

Evaluating Machine Learning Methods of Analyzing Multiclass Metabolomics.

Multiclass metabolomic studies have become popular for revealing the differences in multiple stages of complex diseases, various lifestyles, or the effects of specific treatments. In multiclass metabolomics, there are multiple data manipulation steps for analyzing raw data, which consist of data filtering, the imputation of missing values, data normalization, marker identification, sample separation, classification, and so on. In each step, several to dozens of machine learning methods can be chosen for the given data set, with potentially hundreds or thousands of method combinations in the whole data processing chain. Therefore, a clear understanding of these machine learning methods is helpful for selecting an appropriate method combination for obtaining stable and reliable analytical results of specific data. However, there has rarely been an overall introduction or evaluation of these methods based on multiclass metabolomic data. Herein, detailed descriptions of these machine learning methods in multiple data manipulation steps are reviewed. Moreover, an assessment of these methods was performed using a benchmark data set for multiclass metabolomics. First, 12 imputation methods for imputing missing values were evaluated based on the PSS (Procrustes statistical shape analysis) and NRMSE (normalized root-mean-square error) values. Second, 17 normalization methods for processing multiclass metabolomic data were evaluated by applying the PMAD (pooled median absolute deviation) value. Third, different methods of identifying markers of multiclass metabolomics were evaluated based on the CWrel (relative weighted consistency) value. Fourth, nine classification methods for constructing multiclass models were assessed using the AUC (area under the curve) value. Performance evaluations of machine learning methods are highly recommended to select the most appropriate method combination before performing the final analysis of the given data. Overall, detailed descriptions and evaluation of various machine learning methods are expected to improve analyses of multiclass metabolomic data.

Ginseng polysaccharides alter the gut microbiota and kynurenine/tryptophan ratio, potentiating the antitumour effect of antiprogrammed cell death 1/programmed cell death ligand 1 (anti-PD-1/PD-L1) immunotherapy.

OBJECTIVE: Programmed death 1 and its ligand 1 (PD-1/PD-L1) immunotherapy is promising for late-stage lung cancer treatment, however, the response rate needs to be improved. Gut microbiota plays a crucial role in immunotherapy sensitisation and Panax ginseng has been shown to possess immunomodulatory potential. In this study, we aimed to investigate whether the combination treatment of ginseng polysaccharides (GPs) and αPD-1 monoclonal antibody (mAb) could sensitise the response by modulating gut microbiota. DESIGN: Syngeneic mouse models were administered GPs and αPD-1 mAb, the sensitising antitumour effects of the combination therapy on gut microbiota were assessed by faecal microbiota transplantation (FMT) and 16S PacBio single-molecule real-time (SMRT) sequencing. To assess the immune-related metabolites, metabolomics analysis of the plasma samples was performed. RESULTS: We found GPs increased the antitumour response to αPD-1 mAb by increasing the microbial metabolites valeric acid and decreasing L-kynurenine, as well as the ratio of Kyn/Trp, which contributed to the suppression of regulatory T cells and induction of Teff cells after combination treatment. Besides, the microbial analysis indicated that the abundance of Parabacteroides distasonis and Bacteroides vulgatus was higher in responders to anti-PD-1 blockade than non-responders in the clinic. Furthermore, the combination therapy sensitised the response to PD-1 inhibitor in the mice receiving microbes by FMT from six non-responders by reshaping the gut microbiota from non-responders towards that of responders. CONCLUSION: Our results demonstrate that GPs combined with αPD-1 mAb may be a new strategy to sensitise non-small cell lung cancer patients to anti-PD-1 immunotherapy. The gut microbiota can be used as a novel biomarker to predict the response to anti-PD-1 immunotherapy.

Andrographolide suppresses non-small-cell lung cancer progression through induction of autophagy and antitumor immune response.

Despite recent advances in diagnosis and therapeutic strategies, treatment of non-small-cell lung cancer (NSCLC) remains unsatisfactory in terms of prognosis. Andrographolide (AD), a principal active component of Andrographis paniculata (Burm.f.) Nees, exerts anti-cancer therapeutic properties. AD has been used for centuries in China for clinical treatment of viral infections. However, the pharmacological biology of AD in NSCLC remains unknown. In this study, AD regulated autophagy and PD-L1 expression in NSCLC. Molecular dynamics simulations indicated that AD bound directly to signal transducer and activator of transcription-3 (STAT3) with high affinity. Proteomics analysis indicated that AD reduced the expression of tumour PD-L1 in NSCLC by suppressing JAK2/STAT3 signalling. AD modulated the P62-dependent selective autophagic degradation of PD-L1 by inhibiting STAT3 phosphorylation. In vivo study revealed that AD suppressed tumour growth in H1975 xenograft mice and Lewis lung carcinoma cell models, and better efficacy was obtained at higher concentrations. AD prolonged the survival time of the mice and enhanced the treatment efficacy of anti-PD-1 mAb immunotherapy by stimulating CD8+ T cell infiltration and function. This work elucidated the specific mechanism by which AD inhibited NSCLC. Treatment with the combination of AD and anti-PD-1 mAb immunotherapy could be a potential strategy for patients with NSCLC.

Potential prognostic factors in progression-free survival for patients with cervical cancer.

BACKGROUND: Cervical cancer continues to be one of the leading causes of cancer deaths among females in low and middle-income countries. In this study, we aimed to assess the independent prognostic value of clinical and potential prognostic factors in progression-free survival (PFS) in cervical cancer. METHODS: We conducted a retrospective study on 92 cervical cancer patients treated from 2017 to 2019 at the Zhuhai Hospital of Traditional Chinese and Western Medicine. Tumor characteristics, treatment options, progression-free survival and follow-up information were collected. Kaplan-Meier method was used to assess the PFS. RESULTS: Results showed that the number of retrieved lymph nodes had a statistically significant effect on PFS of cervical cancer patients (P = 0.002). Kaplan-Meier survival curve analysis showed that cervical cancer patients with initial symptoms age 25-39 had worse survival prognoses (P = 0.020). And the using of uterine manipulator in laparoscopic treatment showed a better prognosis (P < 0.001). A novel discovery of our study was to verify the prognostic values of retrieved lymph nodes count combining with FIGO staging system, which had never been investigated in cervical cancer before. According to the Kaplan-Meier survival curve analysis and receiver operating characteristic (ROC) curve analysis, significant improvements were found after the combination of retrieved lymph nodes count and FIGO stage in predicting PFS for cervical cancer patients (P < 0.001, AUC = 0.826, 95% CI: 0.689-0.962). CONCLUSION: Number of retrieved lymph nodes, initial symptoms age, uterine manipulator, and retrieved lymph nodes count combining with FIGO staging system could be potential prognostic factors for cervical cancer patients.

Plumbagin suppresses non-small cell lung cancer progression through downregulating ARF1 and by elevating CD8+ T cells.

Non-small cell lung cancer (NSCLC) is one of the most frequently diagnosed cancers and the leading causes of cancer death worldwide. Therefore, new therapeutic agents are urgently needed to improve patient outcomes. Plumbagin (PLB), a natural sesquiterpene present in many Chinese herbal medicines, has been reported for its anti-cancer activity in various cancer cells. In this study, the effects and underlying mechanisms of PLB on the tumorigenesis of NSCLC were investigated. PLB dose-dependently inhibited the growth of NSCLC cell lines. PLB promoted ROS production, activated the endoplasmic reticulum (ER) stress pathway, and induced cell apoptosis, accompanied by the decreased expression level of ADP-ribosylation factor 1 (ARF1) in NSCLC cancer cells, and those effects of PLB could be reversed by the pretreatment with N-acetyl-L-cysteine (NAC). More importantly, the calcium chelator (BM) significantly reversed PLB-induced cell apoptosis. Furthermore, PLB significantly inhibited the growth of both H1975 xenograft and LLC1 tumors and exhibited antitumor activity by enhancing the number and the effector function of CD8+ T cells in KRASLA2 mice model and the LLC1 xenograft. Our findings suggest that PLB exerts potent antitumor activity against NSCLC in vitro and in vivo through ARF1 downregulation and induction of antitumor immune response, indicating that PLB is a new novel therapeutic candidate for the treatment of patients with NSCLC.

In vivo CRISPR screening unveils histone demethylase UTX as an important epigenetic regulator in lung tumorigenesis.

Lung cancer is the leading cause of cancer-related death worldwide. Inactivation of tumor suppressor genes (TSGs) promotes lung cancer malignant progression. Here, we take advantage of the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-mediated somatic gene knockout in a KrasG12D/+ mouse model to identify bona fide TSGs. From individual knockout of 55 potential TSGs, we identify five genes, including Utx, Ptip, Acp5, Acacb, and Clu, whose knockout significantly promotes lung tumorigenesis. These candidate genes are frequently down-regulated in human lung cancer specimens and significantly associated with survival in patients with lung cancer. Through crossing the conditional Utx knockout allele to the KrasG12D/+ mouse model, we further find that Utx deletion dramatically promotes lung cancer progression. The tumor-promotive effect of Utx knockout in vivo is mainly mediated through an increase of the EZH2 level, which up-regulates the H3K27me3 level. Moreover, the Utx-knockout lung tumors are preferentially sensitive to EZH2 inhibitor treatment. Collectively, our study provides a systematic screening of TSGs in vivo and identifies UTX as an important epigenetic regulator in lung tumorigenesis.

Discovery of a Potent Degrader for Fibroblast Growth Factor Receptor 1/2.

Aberrant activation of FGFR signaling occurs in many cancers, and ATP-competitive FGFR inhibitors have received regulatory approval. Despite demonstrating clinical efficacy, these inhibitors exhibit dose-limiting toxicity, potentially due to a lack of selectivity amongst the FGFR family and are poorly tolerated. Here, we report the discovery and characterization of DGY-09-192, a bivalent degrader that couples the pan-FGFR inhibitor BGJ398 to a CRL2VHL E3 ligase recruiting ligand, which preferentially induces FGFR1&2 degradation while largely sparing FGFR3&4. DGY-09-192 exhibited two-digit nanomolar DC50 s for both wildtype FGFR2 and several FGFR2-fusions, resulting in degradation-dependent antiproliferative activity in representative gastric cancer and cholangiocarcinoma cells. Importantly, DGY-09-192 induced degradation of a clinically relevant FGFR2 fusion protein in a xenograft model. Taken together, we demonstrate that DGY-09-192 has potential as a prototype FGFR degrader.

Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.

In personalized medicine, many factors influence the choice of compounds. Hence, the selection of suitable medicine for patients with non-small-cell lung cancer (NSCLC) is expensive. To shorten the decision-making process for compounds, we propose a computationally efficient and cost-effective collaborative filtering method with ensemble learning. The ensemble learning is used to handle small-sample sizes in drug response datasets as the typical number of patients in a cancer dataset is very small. Moreover, the proposed method can be used to identify the most suitable compounds for patients without genetic data. To the best of our knowledge, this is the first method to provide effective recommendations without genetic data. We also constructed a reliable dataset that includes eight NSCLC cell lines and ten compounds that have been approved by the Food and Drug Administration. With the new dataset, the experimental results demonstrated that the dataset shift phenomenon that commonly occurs in practical biomedical data does not occur in this problem. The experimental results demonstrated that our proposed method can outperform two state-of-the-art recommender system techniques on both the NCI60 dataset and our new dataset. Our model can be applied to the prediction of drug sensitivity with less labor-intensive experiments in the future.

Chelidonine selectively inhibits the growth of gefitinib-resistant non-small cell lung cancer cells through the EGFR-AMPK pathway.

Tyrosine kinase inhibitors (TKIs) have been widely used for the clinical treatment of patients with non-small cell lung cancer (NSCLC) harboring mutations in the EGFR. Unfortunately, due to the secondary mutation in EGFR, eventual drug-resistance is inevitable. Therefore, to overcome the resistance, new agent is urgently required. Chelidonine, extracted from the roots of Chelidonium majus, was proved to effectively suppress the growth of NSCLC cells with EGFR double mutation. Proteomics analysis indicated that mitochondrial respiratory chain was significantly inhibited by chelidonine, and inhibitor of AMPK effectively blocked the apoptosis induced by chelidonine. Molecular dynamics simulations indicated that chelidonine could directly bind to EGFR and showed a much higher binding affinity to EGFRL858R/T790M than EGFRWT, which demonstrated that chelidonine could selectively inhibit the phosphorylation of EGFR in cells with EGFR double-mutation. In vivo study revealed that chelidonine has a similar inhibitory effect like second generation TKI Afatinib. In conclusion, targeting EGFR and inhibition of mitochondrial function is a promising anti-cancer therapeutic strategy for inhibiting NSCLC with EGFR mutation and TKI resistance.

Potent Antagonists of RORγt, Cardenolides from Calotropis gigantea, Exhibit Discrepant Effects on the Differentiation of T Lymphocyte Subsets.

RORγt is the master transcription factor of IL-17 cytokine expression and Th17 lymphocyte differentiation, which are responsible for the induction of many autoimmune diseases. Recently, RORγt has become an attractive target for drug development to treat these types of diseases, and the field of RORγt antagonist research is now extremely competitive. In our current study, molecular docking was applied to demonstrate that cardenolides, including uscharin, calactin, and calotropin derived from Calotropis gigantea, probably directly bind to RORγt. Therefore, the inhibitory effect was further validated using a luciferase reporter assay. Because RORγt is the key transcriptional factor for Th17 differentiation, the effects of these compounds on Th17 differentiation were studied by flow cytometry. The results showed that uscharin, calactin, and calotropin inhibited Th17 differentiation from 100 to 500 nM. Furthermore, uscharin had a better effect than digoxin, a well-known inverse agonist of RORγt, in reducing Th17 polarization. Additionally, the effects of the cardenolides on the differentiation of other Th lineages, including Th1, Th2, and Treg, were investigated. Uscharin suppressed Th1, Th2, and Treg cell differentiation, while calactin suppressed the differentiation of Th1 cells, and calotropin did not influence the other T cell subsets, indicating that calactin suppressed Th1 and Th17 differentiation, and calotropin selectively quenched Th17 polarization. Structural analysis of the three compounds showed that the selectivity of uscharin, calactin, and calotropin on the suppression of the different subsets of T cells is correlated to the minor differences in their chemical structures. Collectively, calactin and calotropin have greater potential to be developed as lead compounds than uscharin to treat autoimmune diseases mediated by Th17 and/or Th1 cells.

Identification of an IKKß inhibitor for inhibition of inflammation in vivo and in vitro.

Targeting on the IKKß to discover anti-inflammatory drugs has been launched for ten years, due to its predominant role in canonical NF-κB signaling. In the current study, we identified a novel IKKß inhibitor, ellipticine (ELL), an alkaloid isolated from Ochrosia elliptica and Rauvolfia sandwicensis. We found that ELL reduced the secretion and mRNA expression of TNF-α and IL-6 and decreased the protein expression of cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) in bone marrow derived macrophages (BMDMs) stimulated with LPS. In coincided with the results, ELL suppressed PGE2 and NO production in BMDMs. Underlying mechanistic study showed that ELL inhibited IκBα phosphorylation and degradation as well as NF-κB nuclear translocation, which was attributed to suppression of IKKα/ß activation. Furthermore, kinase assay and binding assay results indicated that ELL inhibited IKKß activity via directly binding to IKKß and in turn resulted in suppression of NF-κB signaling. To identify the binding sites of ELL on IKKß, IKKßC46A plasmid was prepared and the kinase assay was performed. The results demonstrated that the inhibitory effect of ELL on IKKß activity was impaired in the mutation, implying that anti-inflammatory effect of ELL was partially attributed to binding on cysteine 46. Furthermore, ELL up-regulated LC3 II expression and reduced p62 expression, suggesting that autophagy induction contributed to the anti-inflammatory effect of ELL as well. In coincided with the in vitro results, ELL increased the survival and antagonized the hypothermia in the mice with LPS-induced septic shock. Consistently, ELL reduced TNF-α and IL-6 production in the serum of the mice treated with LPS. Collectively, our study provides evidence that ELL is an IKKß inhibitor and has potential to be developed as a lead compound for treatment inflammatory diseases in the future.

Long-term macrolides for non-cystic fibrosis bronchiectasis: a systematic review and meta-analysis.

Long-term macrolides are increasingly being prescribed for stable bronchiectasis. This meta-analysis assessed the clinical effect of this treatment in bronchiectasis. A systematic review and meta-analysis were carried out. All randomized, controlled trials (RCT) comparing long-term macrolides with placebo and/or usual medical care, with outcome measures relating to efficacy and safety were selected. Nine RCT recruiting 530 patients were included. Compared with placebo and/or usual medical care, long-term macrolides significantly reduced the risk of the exacerbations (number of participants with exacerbations (relative risk = 0.70, 95% confidence interval (CI) 0.60-0.82, P < 0.00001); average exacerbations per participant (weighted mean difference = -1.01, 95% CI -1.35 to -0.67, P < 0.00001)), the St George's Respiratory Questionnaire total scores (weighted mean difference = -5.39 95% CI -9.89 to -0.88, P = 0.02), dyspnoea scale (weighted mean difference = -0.31 95% CI -0.42 to -0.20, P < 0.00001), 24-h sputum volume (P < 0.00001), and attenuated the decline of forced expiratory volume in 1 s (weighted mean difference 0.02 L, 95% CI 0.00-0.04, P = 0.01). Eradication of pathogens (P = 0.06), overall rate of adverse events (P = 0.61), and emergence of new pathogens (P = 0.61) were not elevated, while gastrointestinal events increased significantly with macrolides (P = 0.0001). Macrolide resistance increased, but a meta-analysis was not possible due to the diversity of parameters. Long-term use of macrolides appears to be a treatment option for stable bronchiectasis. The results of this review justify further investigation about adding this intervention to the treatment regimens of bronchiectasis.