Wenhua Xue

Association between metformin and the risk of gastric cancer in patients with type 2 diabetes mellitus: a meta-analysis of cohort studies

Objectives The objective of this study was to evaluate the association between metformin therapy and the incidence of gastric cancer (GC) in patients with type 2 diabetes mellitus (T2DM). Methods We systemically searched the following databases for studies published between the databases’ dates of inception and Nov. 2016: PubMed, Embase, the Cochrane Library, the Web of Science, and the China National Knowledge Infrastructure (CNKI). Hazard ratios (HR)and corresponding 95% confidence intervals (CIs) for the association between metformin therapy and the incidence of GC in patients with T2DM were the outcome measures assessed in this study. STATA 12.0 (Stata Corporation, College Station, Texas, USA) was used to conduct the statistical analysis. Results A total of seven cohort studies including 591,077 patients met all the criteria for inclusion in the analysis. Our data showed that metformin therapy was associated with a significantly lower incidence of GC in patients with T2DM than other types of therapy (HR=0.763, 95% CI: 0.642˜0.905). Subgroup analysis showed that patients living in Taiwan benefitted more from metformin therapy than patients living in any other region, as metformin significantly decreased the risk of GC in patients living in Taiwan but did not significantly decrease the risk of GC in patients living in other regions (HR=0.514, 95% CI: 0.384-0.688). The results of the present analysis support the idea that metformin facilitates reductions in the risk of T2DM-related GC. Conclusions The risk of GC among patients with T2DM is lower in patients receiving metformin therapy than in patients not receiving metformin therapy.

Rapid determination of 30 bioactive constituents in XueBiJing injection using ultra high performance liquid chromatography-high resolution hybrid quadrupole-orbitrap mass spectrometry coupled with principal component analysis

&NA; Xuebijing injection (XBJ) is a traditional Chinese herbal prescription widely used in the treatment of sepsis. Extensive chemical studies revealed that XBJ injection contains amino acids, phenolic acids, flavonoid glycosides, terpeneglycosides and phthalides. In this study, the applicability of ultra high performance liquid chromatography coupled with high resolution hybrid quadruple‐orbitrap mass spectrometry (UHPLC‐Q‐Orbitrap MS) for the simultaneous quantitative analysis of 30 bioactive constituents in XueBiJing injection (XBJ) was investigated. The mass spectrometer was operated in full MS scan mode. The use of 70,000 FWHM mass resolution and narrow mass windows (5 ppm) could effectively improve the selectivity of the method. Separation was achieved on a Waters ACQUITY UPLC® HSS C18 column (2.1 mm × 100 mm, 1.8 &mgr;m) with a gradient mobile phase consisting of acetonitrile‐water (containing 10 mM ammonium acetate) at a flow rate of 0.2 mL/min. Satisfactory linearity was achieved within wide linear range and all correlation coefficients (r) of analytes were more than 0.9996. The limits of detection (LODs) were in the range of 0.1180–27.82 ng/mL for different analytes. The relative standard deviations (RSDs) of inter‐ and intra‐day precisions were less than 3.0% and the recoveries of the assay were in the range of 98.5%–101.5%. The validated method was successfully applied for simultaneous determination of 30 bioactive compounds in XueBiJing injection from 10 batches samples by UHPLC‐Q‐Orbitrap MS within 10 min. Moreover, the results were evaluated principal component analysis and two compounds might be the most important chemical markers for chemical quality control of XBJ injection. The novel Q‐Orbitrap mass spectrometry has been proved to be a very promising and powerful tool for routine screening of bioactive compounds in traditional Chinese medicine injection, ensuring drug safety and public health. Graphical abstract Figure. No caption available. HighlightsThe report describes the validation with high precision and accuracy of an UHPLC‐Q‐orbitrap MS method for the determination of 30 bioactive constituents in XueBiJing injection for the first time.The high resolution hybrid quadrupole‐orbitrap mass spectrometry possess high accuracy and stability, and so the full MS scan mode with positive/negative ion swing was performed.This method was simple and time saving.The determination results were analyzed by multivariate analysis in order to discover the markers for quality control of XBJ injection.

Target of obstructive sleep apnea syndrome merge lung cancer: based on big data platform

Based on our hospital database, the incidence of lung cancer diagnoses was similar in obstructive sleep apnea Syndrome (OSAS) and hospital general population; among individual with a diagnosis of lung cancer, the presence of OSAS was associated with an increased risk for mortality. In the gene expression and network-level information, we revealed significant alterations of molecules related to HIF1 and metabolic pathways in the hypoxic-conditioned lung cancer cells. We also observed that GBE1 and HK2 are downstream of HIF1 pathway important in hypoxia-conditioned lung cancer cell. Furthermore, we used publicly available datasets to validate that the late-stage lung adenocarcinoma patients showed higher expression HK2 and GBE1 than early-stage ones. In terms of prognostic features, a survival analysis revealed that the high GBE1 and HK2 expression group exhibited poorer survival in lung adenocarcinoma patients. By analyzing and integrating multiple datasets, we identify molecular convergence between hypoxia and lung cancer that reflects their clinical profiles and reveals molecular pathways involved in hypoxic-induced lung cancer progression. In conclusion, we show that OSAS severity appears to increase the risk of lung cancer mortality.

‘Repair’ Treg Cells in Tissue Injury

Studies in mice and humans have elucidated an important role for Tregs in promoting tissue repair and restoring tissue integrity. Emerging evidence has revealed that Tregs promoted wound healing and repair processes at multiple tissue sites, such as the heart, liver, kidney, muscle, lung, bone and central nervous system. The localization of repair Tregs in the lung, muscle and liver exhibited unique phenotypes and functions. Epidermal growth factor receptor, amphiregulin, CD73/CD39 and keratinocyte growth factor are important repair factors that are produced or expressed by repair Tregs; these factors coordinate with parenchymal cells to limit injury and promote repair. In addition, repair Tregs can be modulated by IL-33/ST2, TCR signals and other cytokines in the context of injured microenvironment cues. In this review, we provide an overview of the emerging knowledge about Treg-mediated repair in damaged tissues and organs.

Metformin-Induced Reduction of CD39 and CD73 Blocks Myeloid-Derived Suppressor Cell Activity in Patients with Ovarian Cancer

Metformin is a broadly prescribed drug for type 2 diabetes that exerts antitumor activity, yet the mechanisms underlying this activity remain unclear. We show here that metformin treatment blocks the suppressive function of myeloid-derived suppressor cells (MDSC) in patients with ovarian cancer by downregulating the expression and ectoenzymatic activity of CD39 and CD73 on monocytic and polymononuclear MDSC subsets. Metformin triggered activation of AMP-activated protein kinase α and subsequently suppressed hypoxia-inducible factor α, which was critical for induction of CD39/CD73 expression in MDSC. Furthermore, metformin treatment correlated with longer overall survival in diabetic patients with ovarian cancer, which was accompanied by a metformin-induced reduction in the frequency of circulating CD39+CD73+ MDSC and a concomitant increase in the antitumor activities of circulating CD8+ T cells. Our results highlight a direct effect of metformin on MDSC and suggest that metformin may yield clinical benefit through improvement of antitumor T-cell immunity by dampening CD39/CD73-dependent MDSC immunosuppression in ovarian cancer patients.Significance: The antitumor activity of an antidiabetes drug is attributable to reduced immunosuppressive activity of myeloid-derived tumor suppressor cells. Cancer Res; 78(7); 1779-91. ©2018 AACR.

Integrated analysis profiles of long non-coding RNAs reveal potential biomarkers of drug resistance in lung cancer

Lung cancer is one of the leading causes of cancer-related death. Resistance to chemotherapy and molecularly targeted therapies is a major problem that can contribute substantially to high mortality. The roles of long non-coding RNAs (lncRNAs) in drug resistance of lung cancer are insufficiently understood. Here, we identified a distinct drug resistance-related transcriptional signature and constructed a functional lncRNA-mRNA co-expression network. We found that 34 lncRNAs and 103 mRNAs have differential expression in drug resistance of lung cancer, in which 10 lncRNAs were down regulated and 24 up regulated; 49 mRNAs were down regulated and 54 up regulated. LncRNAs-mRNAs expression network analysis revealed a role for lncRNAs in modulating cancer-related pathways. We also found that two pair lncRNAs and their subnetworks were highly related to drug resistance. NR_028502.1/NR_028505.1 were found differentially co-expressed with nine mRNAs, and highly correlated with better clinical outcome. NR_030725.1/NR_030726.1 co-expressed with eleven mRNAs, and were associated with poor survival in patients with lung cancer. Our work comprehensively identified expression signature of resistance-associated lncRNAs and their inter-regulated mRNAs in lung cancer.Lung cancer is one of the leading causes of cancer-related death. Resistance to chemotherapy and molecularly targeted therapies is a major problem that can contribute substantially to high mortality. The roles of long non-coding RNAs (lncRNAs) in drug resistance of lung cancer are insufficiently understood. Here, we identified a distinct drug resistance-related transcriptional signature and constructed a functional lncRNA-mRNA co-expression network. We found that 34 lncRNAs and 103 mRNAs have differential expression in drug resistance of lung cancer, in which 10 lncRNAs were down regulated and 24 up regulated; 49 mRNAs were down regulated and 54 up regulated. LncRNAs-mRNAs expression network analysis revealed a role for lncRNAs in modulating cancer-related pathways. We also found that two pair lncRNAs and their subnetworks were highly related to drug resistance. NR_028502.1/NR_028505.1 were found differentially co-expressed with nine mRNAs, and highly correlated with better clinical outcome. NR_030725.1/NR_030726.1 co-expressed with eleven mRNAs, and were associated with poor survival in patients with lung cancer. Our work comprehensively identified expression signature of resistance-associated lncRNAs and their inter-regulated mRNAs in lung cancer.

Construction of an oesophageal cancer-specific ceRNA network based on miRNA, lncRNA, and mRNA expression data

AIM To explore the expression profiles of microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and mRNAs in oesophageal squamous cell carcinoma (ESCC) in order to construct an oesophageal cancer-specific competing endogenous RNA (ceRNA) network. METHODS In this work, the expression data of miRNAs, lncRNAs, and mRNAs in ESCC were obtained. An oesophageal cancer-specific ceRNA network was then constructed and investigated. RESULTS CeRNAs have the ability to reduce the targeting activity of miRNAs, leading to the de-repression of specific mRNAs with common miRNA response elements. CeRNA interactions have a critical effect in gene regulation and cancer development. CONCLUSION This study suggests a novel perspective on potential oesophageal cancer mechanisms as well as novel pathways for modulating ceRNA networks for treating cancers.

Clinical Significance of Retinoic Acid Receptor Beta Promoter Methylation in Prostate Cancer: A Meta-Analysis

Background/Aims: Retinoic acid receptor beta (RAR beta) is a retinoic acid receptor gene that has been shown to play key roles during multiple cancer processes, including cell proliferation, apoptosis, migration and invasion. Numerous studies have found that methylation of the RAR beta promoter contributed to the occurrence and development of malignant tumors. However, the connection between RAR beta promoter methylation and prostate cancer (PCa) remains unknown. This meta-analysis evaluated the clinical significance of RAR beta promoter methylation in PCa. Materials and Methods: We searched all published records relevant to RAR beta and PCa in a series of databases, including PubMed, Embase, Cochrane Library, ISI Web of Science and CNKI. The rates of RAR beta promoter methylation in the PCa and control groups (including benign prostatic hyperplasia and normal prostate tissues) were summarized. In addition, we evaluated the source region of available samples and the methods used to detect methylation. To compare the incidence and variation in RAR beta promoter methylation in PCa and non-PCa tissues, the odds ratio (OR) and 95% confidence interval (CI) were calculated accordingly. All the data were analyzed with the statistical software STATA 12.0. Results: Based on the inclusion and exclusion criteria, 15 articles assessing 1,339 samples were further analyzed. These data showed that the RAR beta promoter methylation rates in PCa tissues were significantly higher than the rates in the non-PCa group (OR=21.65, 95% CI: 9.27-50.57). Subgroup analysis according to the source region of samples showed that heterogeneity in Asia was small (I2=0.0%, P=0.430). Additional subgroup analysis based on the method used to detect RAR beta promoter methylation showed that the heterogeneity detected by MSP (methylation-specific PCR) was relatively small (I2=11.3%, P=0.343). Conclusion: Although studies reported different rates for RAR beta promoter methylation in PCa tissues, the total analysis demonstrated that RAR beta promoter methylation may be correlated with PCa carcinogenesis and that the RAR beta gene is particularly susceptible. Additional studies with sufficient data are essential to further evaluate the clinical features and prognostic utility of RAR beta promoter methylation in PCa.

Unique Features of Pancreatic-Resident Regulatory T Cells in Autoimmune Type 1 Diabetes

Recent progress in regulatory T cells (Tregs) biology emphasizes the importance of understanding tissue-resident Tregs in response to tissue-specific environment. Now, emerging evidence suggests that pancreatic-resident forkhead box P3+ Tregs have distinguishable effects on the suppression of over-exuberant immune responses in autoimmune type 1 diabetes (T1D). Thus, there is growing interest in elucidating the role of pancreatic-resident Tregs that function and evolve in the local environment. In this review, we discuss the phenotype and function of Tregs residing in pancreatic tissues and pancreatic lymph nodes, with emphasis on the unique subpopulations of Tregs that control the disease progression in the context of T1D. Specifically, we discuss known and possible modulators that influence the survival, migration, and maintenance of pancreatic Tregs.

Identification of an early diagnostic biomarker of lung adenocarcinoma based on co-expression similarity and construction of a diagnostic model

BackgroundThe purpose of this study was to achieve early and accurate diagnosis of lung cancer and long-term monitoring of the therapeutic response.MethodsWe downloaded GSE20189 from GEO database as analysis data. We also downloaded human lung adenocarcinoma RNA-seq transcriptome expression data from the TCGA database as validation data. Finally, the expression of all of the genes underwent z test normalization. We used ANOVA to identify differentially expressed genes specific to each stage, as well as the intersection between them. Two methods, correlation analysis and co-expression network analysis, were used to compare the expression patterns and topological properties of each stage. Using the functional quantification algorithm, we evaluated the functional level of each significantly enriched biological function under different stages. A machine-learning algorithm was used to screen out significant functions as features and to establish an early diagnosis model. Finally, survival analysis was used to verify the correlation between the outcome and the biomarkers that we found.ResultsWe screened 12 significant biomarkers that could distinguish lung cancer patients with diverse risks. Patients carrying variations in these 12 genes also presented a poor outcome in terms of survival status compared with patients without variations.ConclusionsWe propose a new molecular-based noninvasive detection method. According to the expression of the stage-specific gene set in the peripheral blood of patients with lung cancer, the difference in the functional level is quantified to realize the early diagnosis and prediction of lung cancer.