Publications by authors named "Guangshun Li"

6 Publications

  • Page 1 of 1

MicroRNA-217 inhibits the proliferation and invasion, and promotes apoptosis of non-small cell lung cancer cells by targeting sirtuin 1.

Oncol Lett 2021 May 17;21(5):386. Epub 2021 Mar 17.

Department of Thoracic, Xi'an Central Hospital, Xi'an, Shaanxi 710003, P.R. China.

Non-small cell lung cancer (NSCLC) is a common malignancy worldwide. MicroRNA (miR)-217 and sirtuin 1 (SIRT1) have been reported to play significant roles in different types of cancer, such as osteosarcoma and prostate cancer; however, the association between miR-217 and SIRT1 in the cell proliferation, apoptosis and invasion of NSCLC remain unknown. Thus, the present study aimed to investigate the roles of miR-217 and SIRT1 in NSCLC. The expression levels of miR-217 and SIRT1 were detected via reverse transcription-quantitative (RT-q)PCR and western blot analyses. The effect of miR-217 on A549 and H1299 cell proliferation, apoptosis and invasion was assessed via the Cell Counting Kit-8, flow cytometry and Transwell assays, respectively. In addition, the association between SIRT1 and miR-217 was predicted using the TargetScan database, and verified via the dual-luciferase reporter assay, and RT-qPCR and western blot analyses. The results demonstrated that miR-217 expression was significantly downregulated, while SIRT1 expression was significantly upregulated in A549 and H1299 cells compared with the human bronchial epithelial cells. Furthermore, transfection with miR-217 mimic significantly inhibited A549 and H1299 cell proliferation and invasion, and induced A549 and H1299 cell apoptosis. The results of the dual-luciferase reporter assay and western blot analysis confirmed that SIRT1 is a target gene of miR-217. In addition, miR-217 inhibited the activation of AMP-activated protein kinase (AMPK) and mTOR signaling. Taken together, the results of the present study suggest that miR-217 inhibits A549 and H1299 cell proliferation and invasion, and induces A549 and H1299 cell apoptosis by targeting SIRT1 and inactivating the SIRT1-mediated AMPK/mTOR signaling pathway. Thus, miR-217 may be used as a potential therapeutic target for the treatment of patients with NSCLC.
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http://dx.doi.org/10.3892/ol.2021.12647DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988702PMC
May 2021

Chemoprotective effect of atorvastatin against benzo(a)pyrene-induced lung cancer via the inhibition of oxidative stress and inflammatory parameters.

Ann Transl Med 2021 Feb;9(4):355

Department of Respiratory, Affiliated Xi'an Central Hospital, The Medical School of Xi'an Jiaotong University, Xi'an, China.

Background: Lung cancer affects approximately 9% of women and 17% of men worldwide, and has a mortality rate of 17%. Previously published studies have suggested that oxidative stress expansion can lead to lung cancer. The aim of the current study was to analyze the possible inhibitory pathway of atorvastatin against lung cancer cells in an model.

Methods: The cytotoxic effects of atorvastatin on lung cancer cell lines H460 and A549 were analyzed, as well as cell cycle arrest and cell morphology. Benzo(a)pyrene (BaP) was used for the induction of lung cancer in experimental rats, and atorvastatin (5, 10, and 20 mg/kg body weight) was used for treatment in a dose-dependent manner. Body weight and lung tumors were calculated at regular intervals. Antioxidants, pro-inflammatory cytokines, phase I and II antioxidant enzymes, polyamine enzymes, and apoptosis markers were determined at end of the experimental study.

Results: Cell cycle arrest occurred at the G2/M phase after atorvastatin treatment. Atorvastatin increased cytochrome C expression and caspase activity in a dose-dependent manner, and increased the activity of antioxidative enzymes, such as GPx, SOD, GST, reduced glutathione, and catalase, and reduced the level of nitrate and LPO. It also altered the xanthine oxidase (XO), Lactic Acid Dehydrogenase (LDH), quinone reductase (QR), UDP-glucuronosyltransferase (UDP-GT), adenosine deaminase (ADA), Aryl hydrocarbon hydroxylase (AHH), 5'-nucleotidase, cytochrome P450, cytochrome B5 and NADPH cytochrome C reductase levels. Atorvastatin was found to modulate polyamine enzyme levels, such as histamine, spermine, spermidine, and putrescine, and significantly (P<0.001) reduced the pro-inflammatory cytokine levels, such as tumor necrosis factor-α. Interleukin (IL)-6 and interleukin-1β (IL-1β) increased caspase-3 and caspase-9 levels in a dose-dependent manner.

Conclusions: Our findings indicate that atorvastatin can inhibit lung cancer through apoptosis.
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http://dx.doi.org/10.21037/atm-20-7770DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7944302PMC
February 2021

Noniterative Sparse LS-SVM Based on Globally Representative Point Selection.

IEEE Trans Neural Netw Learn Syst 2021 Feb 4;32(2):788-798. Epub 2021 Feb 4.

A least squares support vector machine (LS-SVM) offers performance comparable to that of SVMs for classification and regression. The main limitation of LS-SVM is that it lacks sparsity compared with SVMs, making LS-SVM unsuitable for handling large-scale data due to computation and memory costs. To obtain sparse LS-SVM, several pruning methods based on an iterative strategy were recently proposed but did not consider the quantity constraint on the number of reserved support vectors, as widely used in real-life applications. In this article, a noniterative algorithm is proposed based on the selection of globally representative points (global-representation-based sparse least squares support vector machine, GRS-LSSVM) to improve the performance of sparse LS-SVM. For the first time, we present a model of sparse LS-SVM with a quantity constraint. In solving the optimal solution of the model, we find that using globally representative points to construct the reserved support vector set produces a better solution than other methods. We design an indicator based on point density and point dispersion to evaluate the global representation of points in feature space. Using the indicator, the top globally representative points are selected in one step from all points to construct the reserved support vector set of sparse LS-SVM. After obtaining the set, the decision hyperplane of sparse LS-SVM is directly computed using an algebraic formula. This algorithm only consumes O(N2) in computational complexity and O(N) in memory cost which makes it suitable for large-scale data sets. The experimental results show that the proposed algorithm has higher sparsity, greater stability, and lower computational complexity than the traditional iterative algorithms.
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http://dx.doi.org/10.1109/TNNLS.2020.2979466DOI Listing
February 2021

Circ_0076305 regulates cisplatin resistance of non-small cell lung cancer via positively modulating STAT3 by sponging miR-296-5p.

Life Sci 2019 Dec 21;239:116984. Epub 2019 Oct 21.

Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710004, PR China. Electronic address:

Aims: Circular RNAs (circRNAs) acted as key regulators in the development of various human tumors. Our present study aimed to investigate the role and molecular mechanism of circ_0076305 in regulating cisplatin (DDP) resistance of non-small cell lung cancer (NSCLC).

Main Methods: Using RT-qPCR, the expressions of circ_0076305 in NSCLC tissues and cells (A549, H1650, A549/DDP, H1650/DDP) were measured. Through loss-of-function and overexpression experiments, the role of circ_0076305 in DDP resistance of NSCLC was verified. Inhibitory rate and IC50 for DDP were detected using MTT method after DDP treatment. Western blotting was performed to evaluate protein levels of P-gp and MRP1. The bindings between circ_0076305 and miR-296-5p, as well as miR-296-5p and STAT3 were validated by bioinformatics, CircRIP, Pearson's correlation analysis and luciferase report vector assays.

Key Findings: Circ_0076305 was upregulated in NSCLC, and more significantly elevated in DDP-resistant NSCLC tissues and cells. Further experiments discovered that circ_0076305 could regulate DDP resistance of NSCLC cells via binding to miR-296-5p. Directly targeted by miR-296-5p, STAT3 hindered the miR-296-5p-induced suppression on DDP resistance. Finally, the expression of circ_0076305 was found to have positive correlation with STAT3, and circ_0076305 was validated to regulate STAT3 via targeting miR-296-5p.

Significance: Our present study illustrated that circ_0076305 regulated STAT3 expression and DDP resistance of NSCLC cells via sponging miR-296-5p. These results suggested knockdown of circ_0076305 might provide an effective approach for NSCLC treatment strategy.
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http://dx.doi.org/10.1016/j.lfs.2019.116984DOI Listing
December 2019

Methods of Resource Scheduling Based on Optimized Fuzzy Clustering in Fog Computing.

Sensors (Basel) 2019 May 8;19(9). Epub 2019 May 8.

School of Information Science and Engineering, Qufu Normal University, Rizhao 276800, China.

Cloud computing technology is widely used at present. However, cloud computing servers are far from terminal users, which may lead to high service request delays and low user satisfaction. As a new computing architecture, fog computing is an extension of cloud computing that can effectively solve the aforementioned problems. Resource scheduling is one of the key technologies in fog computing. We propose a resource scheduling method for fog computing in this paper. First, we standardize and normalize the resource attributes. Second, we combine the methods of fuzzy clustering with particle swarm optimization to divide the resources, and the scale of the resource search is reduced. Finally, we propose a new resource scheduling algorithm based on optimized fuzzy clustering. The experimental results show that our method can improve user satisfaction and the efficiency of resource scheduling.
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http://dx.doi.org/10.3390/s19092122DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6539192PMC
May 2019

ACCBN: ant-Colony-clustering-based bipartite network method for predicting long non-coding RNA-protein interactions.

BMC Bioinformatics 2019 Jan 9;20(1):16. Epub 2019 Jan 9.

School of Information Science and Engineering, Central South University, Changsha, 410083, China.

Background: Long non-coding RNA (lncRNA) studies play an important role in the development, invasion, and metastasis of the tumor. The analysis and screening of the differential expression of lncRNAs in cancer and corresponding paracancerous tissues provides new clues for finding new cancer diagnostic indicators and improving the treatment. Predicting lncRNA-protein interactions is very important in the analysis of lncRNAs. This article proposes an Ant-Colony-Clustering-Based Bipartite Network (ACCBN) method and predicts lncRNA-protein interactions. The ACCBN method combines ant colony clustering and bipartite network inference to predict lncRNA-protein interactions.

Results: A five-fold cross-validation method was used in the experimental test. The results show that the values of the evaluation indicators of ACCBN on the test set are significantly better after comparing the predictive ability of ACCBN with RWR, ProCF, LPIHN, and LPBNI method.

Conclusions: With the continuous development of biology, besides the research on the cellular process, the research on the interaction function between proteins becomes a new key topic of biology. The studies on protein-protein interactions had important implications for bioinformatics, clinical medicine, and pharmacology. However, there are many kinds of proteins, and their functions of interactions are complicated. Moreover, the experimental methods require time to be confirmed because it is difficult to estimate. Therefore, a viable solution is to predict protein-protein interactions efficiently with computers. The ACCBN method has a good effect on the prediction of protein-protein interactions in terms of sensitivity, precision, accuracy, and F1-score.
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http://dx.doi.org/10.1186/s12859-018-2586-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6327428PMC
January 2019
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