Publications by authors named "Su Cui"

19 Publications

  • Page 1 of 1

Benzo[a]pyrene diol epoxide-induced transformed cells identify the significance of hsa_circ_0051488, a ERCC1-derived circular RNA in pulmonary squamous cell carcinoma.

Mol Carcinog 2021 10 28;60(10):684-701. Epub 2021 Jul 28.

Department of Toxicology, School of Public Health, China Medical University, Shenyang, Liaoning, China.

ERCC1 is a gene for repairing DNA damage whose function is related to carcinogenic-induced tumorigenesis and the effectiveness of platinum therapies. Circular RNAs (circRNAs) are products of posttranscriptional regulation with pleiotropic effects on the pathogenesis of lung cancer. We aim to identify that specific circRNAs derived from ERCC1 can regulate key biological processes involved in the development of lung cancer. We performed bioinformatics analysis, in vitro experiments, and analyzed clinical samples, to determine the biological features of a certain ERCC1-derived circRNA termed as hsa_circ_0051488 in benzo[a]pyrene diol epoxide-induced malignant transformed cell and lung cancer cell. The well-established model of transformed cells provided an ideal platform for analyzing the molecular characteristics of this circRNA in the malignant transformation of lung epithelial cell, which supports that hsa_circ_0051488 functions in the onset and growth of lung squamous cell carcinoma (LUSC). Further analysis indicates that the absence of hsa_circ_0051488 promoted the proliferation of cells with the malignant phenotype. Extensive experiments confirm that hsa_circ_0051488 is present in the cytoplasm and functioned as a competing endogenous RNA. In particular, hsa_circ_0051488 binds to mir-6717-5p, thereby modulating the expression of SATB2 gene, a lung cancer suppressor. Furthermore, our in silico experiments indicate that SATB2 can inhibit multiple tumor pathways and its expression positively correlated with the tumor suppressor gene CRMP1. These findings suggest a possible regulatory mechanism of hsa_circ_0051488 in LUSC, and that the newly discovered hsa_circ_0051488/miR-6717-5p/SATB2 axis may be a potential route for therapeutic intervention of LUSC.
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http://dx.doi.org/10.1002/mc.23335DOI Listing
October 2021

LncRNA EWSAT1 Regulates the Tumorigenesis of NSCLC as a ceRNA by Modulating miR-330-5p/ITGA5 Axis.

Biochem Genet 2021 Apr 29. Epub 2021 Apr 29.

Department of Thorax, The First Affiliated Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning, 110001, People's Republic of China.

The aim of the study is to investigate how lncRNA EWSAT1 regulates the tumorigenesis of non-small cell lung cancer (NSCLC) as a ceRNA by modulating miR-330-5p/ITGA5 axis. qRT-PCR was conducted to evaluate the expression of EWSAT1 in NSCLC tissue. Then, A549 cells were selected and divided into Blank shScramble, shEWSAT1, miR-330-5p inhibitor, shEWSAT1 + miR-330-5p inhibitor, and siITGA5 and miR-330-5p inhibitor + siITGA5 groups. Besides, a series of in-vitro experiments were carried out to determine the changes in cell proliferation, apoptosis, invasion, and migration in each group. In addition, xenograft models were also constructed on nude mice to detect the tumor volume and weight, and the expression of Ki67 and apoptosis in xenograft tumor were evaluated. In NSCLC tissue and cell, EWSAT1 was upregulated significantly, demonstrating a correlation with tumor diameter, differentiation, lymph node metastasis, and TNM stage. Dual luciferase reporter gene assay confirmed targeting relationships among miR-330-5p, EWSAT1, and ITGA5. In comparison with the Blank group, the number of cell clones in the shEWSAT1 group and siITGA5 decreased, with declined invasion and migration but increased apoptotic rate. Meanwhile, ITGA5, MMP-2, and MMP-9 were downregulated with upregulated cleaved caspase-3. However, the changes above were totally reversed in the miR-330-5p inhibitor group, and miR-330-5p inhibitor transfection abolished the effect of shEWSAT1. In addition, subcutaneous xenotransplantation showed that the tumor growth in shEWSAT1 group retarded significantly, with downregulation of Ki67 and increase apoptotic rate. Silencing EWSAT1 could inhibit the expression of ITGA5 via upregulating miR-330-5p, thus, resulting in the inhibition of NSCLC cell growth.
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http://dx.doi.org/10.1007/s10528-021-10069-4DOI Listing
April 2021

CABEAN: a software for the control of asynchronous Boolean networks.

Authors:
Cui Su Jun Pang

Bioinformatics 2021 05;37(6):879-881

Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, 4365 Esch-sur-Alzette, Luxembourg.

Summary: Direct cell reprogramming, also called transdifferentiation, has great potential for tissue engineering and regenerative medicine. Boolean networks, a popular modelling framework for gene regulatory networks, make it possible to identify intervention targets for direct cell reprogramming with computational methods. In this work, we present our software, CABEAN, for the control of asynchronous Boolean networks. CABEAN identifies efficacious nodes, whose perturbations can drive the dynamics of a network from a source attractor (the initial cell type) to a target attractor (the desired cell type). CABEAN provides several control methods integrating practical constraints. Thus, it has the ability to provide a rich set of control sets, such that biologists can select suitable ones for validation based on specific experimental settings.

Availability And Implementation: The executable binary and the user guide of the software are publicly available at https://satoss.uni.lu/software/CABEAN/.
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http://dx.doi.org/10.1093/bioinformatics/btaa752DOI Listing
May 2021

Controlling large Boolean networks with single-step perturbations.

Bioinformatics 2019 07;35(14):i558-i567

Faculty of Science, Technology and Communication, University of Luxembourg, Esch-sur-Alzette, Luxembourg.

Motivation: The control of Boolean networks has traditionally focussed on strategies where the perturbations are applied to the nodes of the network for an extended period of time. In this work, we study if and how a Boolean network can be controlled by perturbing a minimal set of nodes for a single-step and letting the system evolve afterwards according to its original dynamics. More precisely, given a Boolean network (BN), we compute a minimal subset Cmin of the nodes such that BN can be driven from any initial state in an attractor to another 'desired' attractor by perturbing some or all of the nodes of Cmin for a single-step. Such kind of control is attractive for biological systems because they are less time consuming than the traditional strategies for control while also being financially more viable. However, due to the phenomenon of state-space explosion, computing such a minimal subset is computationally inefficient and an approach that deals with the entire network in one-go, does not scale well for large networks.

Results: We develop a 'divide-and-conquer' approach by decomposing the network into smaller partitions, computing the minimal control on the projection of the attractors to these partitions and then composing the results to obtain Cmin for the whole network. We implement our method and test it on various real-life biological networks to demonstrate its applicability and efficiency.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btz371DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612811PMC
July 2019

Crystallization Kinetics of Poly(ethylene oxide) under Confinement in Nanoporous Alumina Studied by in Situ X-ray Scattering and Simulation.

Langmuir 2019 Sep 26;35(36):11799-11808. Epub 2019 Aug 26.

Beijing National Laboratory for Molecular Sciences (BNLMS), CAS Key Laboratory of Engineering Plastics, CAS Research/Education Center for Excellence in Molecular Sciences , Institute of Chemistry, Chinese Academy of Sciences , Beijing 100190 , P. R. China.

While a relatively complete understanding of the nucleation and orientation of polymers under confinement in one-dimensional nanochannels has been achieved, crystallization kinetics investigation of confined polymers is still rare. In this work, we investigated the crystallization kinetics of poly(ethylene oxide) confined in anodic alumina oxide templates with different pore sizes using in situ wide-angle X-ray scattering (WAXS). The crystallization kinetics results were fitted with the Avrami equation. The Avrami index was determined by both "isothermal step crystallization" and in situ WAXS. The crystallization process of polymers under one-dimensional nanopore confinement was simulated by a "one-dimensional lattice model". Based on this model, it is shown that homogeneous nucleation with the simultaneous growth of multiple crystal planes with drastically different growth rates could result in Avrami indexes lower than 1.
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http://dx.doi.org/10.1021/acs.langmuir.9b01968DOI Listing
September 2019

AC138128.1 an Intronic lncRNA originating from ERCC1 Implies a Potential Application in Lung Cancer Treatment.

J Cancer 2019 9;10(16):3608-3617. Epub 2019 Jun 9.

Dept. of Toxicology, School of Public Health, China Medical University, Shenyang, P.R. China.

Lung cancer is one of the most devastating tumors with a high incidence and mortality worldwide. Polymorphisms and expression of commonly predicted the occurrence and prognosis of lung cancer. However, few studies have focused on long non-coding RNAs related to though some studies reminded the importance of its post-transcriptional regulation. In the present study, an intronic lncRNA AC138128.1 originated from was firstly identified in microarray chip and database, and its possibility as a novel biomarker to predict lung cancer treatment was further discussed. Firstly, the qRT-PCR data showed that AC138128.1 expression was much lower in lung cancer comparing with its para-cancer tissues, which further analyzed by ROC curve. Similarly, the difference was also verified in 16HBE, A549 and LK cells. Then AC138128.1 expression was found to have an increasing trend in a dose or time-dependent manner after cisplatin treatment. Finally, the subcellular distribution of AC138128.1 reminded that AC138128.1 was mainly expressed in the nucleus. Interestingly a positive relationship between AC138128.1 and expression was only found in cancer tissues, which reminded AC138128.1 may be involved in the regulation of ERCC1. Therefore, as a preliminary exploration of the lncRNA originated from , the present study suggested AC138128.1 is of potential value in predicting platinum analogue benefit in lung cancer.
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http://dx.doi.org/10.7150/jca.31832DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636308PMC
June 2019

An Efficient Approach Towards the Source-Target Control of Boolean Networks.

IEEE/ACM Trans Comput Biol Bioinform 2020 Nov-Dec;17(6):1932-1945. Epub 2020 Dec 8.

We study the problem of computing a minimal subset of nodes of a given asynchronous Boolean network that need to be perturbed in a single-step to drive its dynamics from an initial state to a target steady state (or attractor), which we call the source-target control of Boolean networks. Due to the phenomenon of state-space explosion, a simple global approach that performs computations on the entire network may not scale well for large networks. We believe that efficient algorithms for such networks must exploit the structure of the networks together with their dynamics. Taking this view, we derive a decomposition-based solution to the minimal source-target control problem which can be significantly faster than the existing approaches on large networks. We then show that the solution can be further optimized if we take into account appropriate information about the source state. We apply our solutions to both real-life biological networks and randomly generated networks, demonstrating the efficiency and efficacy of our approach.
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http://dx.doi.org/10.1109/TCBB.2019.2915081DOI Listing
December 2020

Algorithms for the Sequential Reprogramming of Boolean Networks.

IEEE/ACM Trans Comput Biol Bioinform 2019 Sep-Oct;16(5):1610-1619. Epub 2019 May 2.

Cellular reprogramming, a technique that opens huge opportunities in modern and regenerative medicine, heavily relies on identifying key genes to perturb. Most of the existing computational methods for controlling which attractor (steady state) the cell will reach focus on finding mutations to apply to the initial state. However, it has been shown, and is proved in this article, that waiting between perturbations so that the update dynamics of the system prepares the ground, allows for new reprogramming strategies. To identify such sequential perturbations, we consider a qualitative model of regulatory networks, and rely on Binary Decision Diagrams to model their dynamics and the putative perturbations. Our method establishes a set identification of sequential perturbations, whether permanent (mutations) or only temporary, to achieve the existential or inevitable reachability of an arbitrary state of the system. We apply an implementation for temporary perturbations on models from the literature, illustrating that we are able to derive sequential perturbations to achieve trans-differentiation.
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http://dx.doi.org/10.1109/TCBB.2019.2914383DOI Listing
March 2020

Towards Optimal Decomposition of Boolean Networks.

IEEE/ACM Trans Comput Biol Bioinform 2019 Apr 30. Epub 2019 Apr 30.

In recent years, great efforts have been made to analyse biological systems to understand the long-run behaviours. As a well-established formalism for modelling real-life biological systems, Boolean networks (BNs) allow their representation and analysis using formal reasoning and tools. Most biological systems are robust - they can withstand the loss of links and cope with external environmental perturbations. Hence, the BNs used to model such systems are necessarily large and dense, and yet modular. However, existing analysis methods only work well on networks of moderate size. Thus, there is a great need for efficient methods that can handle large-scale BNs and for doing so it is inevitable to exploit both the structural and dynamic properties of the networks. In this paper, we propose a method towards the optimal decomposition of BNs to balance the relation between the structure and dynamics of a network. We show that our method can greatly improve the existing decomposition-based attractor detection by analysing a number of large real-life biological networks.
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http://dx.doi.org/10.1109/TCBB.2019.2914051DOI Listing
April 2019

Rs3212986 polymorphism, a possible biomarker to predict smoking-related lung cancer, alters DNA repair capacity via regulating ERCC1 expression.

Cancer Med 2018 12 19;7(12):6317-6330. Epub 2018 Nov 19.

Department of Toxicology, School of Public Health, China Medical University, Shenyang, China.

Single nucleotide polymorphisms (SNPs) in 3'UTR of key DNA repair enzyme genes are associated with inter-individual differences of DNA repair capacity (DRC) and susceptibility to a variety of human malignancies such as lung cancer. In this study, seven candidate SNPs in 3'UTR of DRC-related genes including ERCC1 (rs3212986, rs2336219, and rs735482), OGG1 (rs1052133), MLH3 (rs108621), CD3EAP (rs1007616), and PPP1R13L (rs6966) were analyzed in 300 lung cancer patients and controls from the northeast of China. Furthermore, we introduced ERCC1 (CDS+3'UTR) or CD3EAP (CDS) cDNA clone to transfect HEK293T and 16HBE cells. Cell viability between different genotypes of transfected cells exposed to BPDE was detected by CCK-8 assay, while DNA damage was visualized using γH2AX immunofluorescence and the modified comet assay. We found that minor A-allele of rs3212986 could reflect a linkage with increasing risk of NSCLC. Compared with CC genotype, AA genotype of ERCC1 rs3212986 was a high-risk factor for NSCLC (OR = 3.246; 95%CI: 1.375-7.663). Particularly stratified by smoking status in cases and controls, A allele of ERCC1 rs3212986 also exhibited an enhanced risk to develop lung cancer in smokers only (P < 0.05). Interestingly, reduced repair efficiency of DNA damage was observed in 293T ERCC1(AA) and 16HBE ERCC1(AA), while no significant difference was appeared in two genotypes of CD3EAP (3' adjacent gene of ERCC1) overexpressed cells. Our findings suggest that rs3212986 polymorphism in 3'UTR of ERCC1 overlapped with CD3EAP may affect the repair of the damage induced by BPDE mainly via regulating ERCC1 expression and become a potential biomarker to predict smoking-related lung cancer.
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http://dx.doi.org/10.1002/cam4.1842DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308093PMC
December 2018

The lncRNA RHPN1-AS1 downregulation promotes gefitinib resistance by targeting miR-299-3p/TNFSF12 pathway in NSCLC.

Cell Cycle 2018 2;17(14):1772-1783. Epub 2018 Aug 2.

a Department of Thoracic Surgery , the First Hospital of China Medical University , Shenyang City , P.R. China.

Although epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) gefitinib has exhibited notable clinical efficacy in non-small cell lung cancer (NSCLC) patients. However, its therapeutic efficacy is ultimately limited by the development of gefitinib resistance. The present study aimed to investigate the effects of the long non-coding RNA, RHPN1-AS1 on gefitinib resistance in NSCLC and explore the underlying mechanisms. In this study, RHPN1-AS1 was observed to be downregulated in gefitinib resistant patients and NSCLC cell lines. Besides, decreased expression of RHPN1-AS1 was found to be associated with poor prognosis of NSCLC patients. RHPN1-AS1 knockdown conferred gefitinib resistance to gefitinib sensitive NSCLC cells, whereas the overexpression of RHPN1-AS1 sensitized gefitinib resistant NSCLC cells to gefitinib treatment. Mechanistically, RHPN1-AS1 was found to positively regulate the expression of TNFSF12 by directly interacting with miR-299-3p. Collectively, RHPN1-AS1 modulates gefitinib resistance through miR-299-3p/TNFSF12 pathway in NSCLC. Our findings indicate that RHPN1-AS1 may serve as not only a prognostic biomarker for gefitinib resistance but also as a promising therapeutic biomarker and target for the treatment of NSCLC patients.
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http://dx.doi.org/10.1080/15384101.2018.1496745DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133316PMC
November 2019

ASSA-PBN: A Toolbox for Probabilistic Boolean Networks.

IEEE/ACM Trans Comput Biol Bioinform 2018 Jul-Aug;15(4):1203-1216. Epub 2017 Nov 14.

As a well-established computational framework, probabilistic Boolean networks (PBNs) are widely used for modelling, simulation, and analysis of biological systems. To analyze the steady-state dynamics of PBNs is of crucial importance to explore the characteristics of biological systems. However, the analysis of large PBNs, which often arise in systems biology, is prone to the infamous state-space explosion problem. Therefore, the employment of statistical methods often remains the only feasible solution. We present ${\mathsf{ASSA-PBN}}$ , a software toolbox for modelling, simulation, and analysis of PBNs. ${\mathsf{ASSA-PBN}}$ provides efficient statistical methods with three parallel techniques to speed up the computation of steady-state probabilities. Moreover, particle swarm optimisation (PSO) and differential evolution (DE) are implemented for the estimation of PBN parameters. Additionally, we implement in-depth analyses of PBNs, including long-run influence analysis, long-run sensitivity analysis, computation of one-parameter profile likelihoods, and the visualization of one-parameter profile likelihoods. A PBN model of apoptosis is used as a case study to illustrate the main functionalities of ${\mathsf{ASSA-PBN}}$ and to demonstrate the capabilities of ${\mathsf{ASSA-PBN}}$ to effectively analyse biological systems modelled as PBNs.
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http://dx.doi.org/10.1109/TCBB.2017.2773477DOI Listing
May 2019

Complexity Analysis of Carbon Market Using the Modified Multi-Scale Entropy.

Entropy (Basel) 2018 Jun 5;20(6). Epub 2018 Jun 5.

Center for Energy Development and Environmental Protection Strategy Research, Jiangsu University, Zhenjiang 212013, China.

Carbon markets provide a market-based way to reduce climate pollution. Subject to general market regulations, the major existing emission trading markets present complex characteristics. This paper analyzes the complexity of carbon market by using the multi-scale entropy. Pilot carbon markets in China are taken as the example. Moving average is adopted to extract the scales due to the short length of the data set. Results show a low-level complexity inferring that China's pilot carbon markets are quite immature in lack of market efficiency. However, the complexity varies in different time scales. China's carbon markets (except for the Chongqing pilot) are more complex in the short period than in the long term. Furthermore, complexity level in most pilot markets increases as the markets developed, showing an improvement in market efficiency. All these results demonstrate that an effective carbon market is required for the full function of emission trading.
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http://dx.doi.org/10.3390/e20060434DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512953PMC
June 2018

Different splicing isoforms of ERCC1 affect the expression of its overlapping genes CD3EAP and PPP1R13L, and indicate a potential application in non-small cell lung cancer treatment.

Int J Oncol 2018 Jun 29;52(6):2155-2165. Epub 2018 Mar 29.

Department of Toxicology, School of Public Health, China Medical University, Shenyang, Liaoning 110122, P.R. China.

Numerous genes are arranged in complex overlapping and interlaced patterns, and such arrangements potentially contribute to the regulation of gene expression. Previous studies have demonstrated that a region in chromosome 19q13.2-3 encompassing the overlapping genes excision repair cross-complementation group 1 (ERCC1), CD3e molecule associated protein (CD3EAP) and protein phosphatase 1 regulatory subunit 13 like (PPP1R13L) was found to be associated with the risk and prognosis of non-small cell lung cancer (NSCLC). The present study confirmed the hypothesis that there are co-expression patterns among these overlapping genes. The suggestive bioinformatic evidence of The Cancer Genome Atlas was verified by quantitative polymerase chain reaction (qPCR) analysis of NSCLC tissue samples. In addition, a cisplatin-induced DNA damage cell model was assessed by microarray analysis, qPCR and 3' rapid amplification of cDNA ends (3'RACE) to verify and quantify the expression levels of co-expressed alternative splicing isoforms in the NSCLC tissues, as well as in cancer A549 and normal 16HBE cells. The expression of CD3EAP exon 1 was demonstrated to be significantly associated with PPP1R13L exon 1, while CD3EAP exon 3 was significantly associated with ERCC1 exon 11 in normal and NSCLC tissues. It was observed that short transcripts of ERCC1, CD3EAP and PPP1R13L are co-expressed in A549 cells and full-length transcripts are co-expressed in 16HBE cells. Furthermore, a novel transcriptional regulation pattern was described based on the positional associations of overlapping genes. The region encompassing the overlapping genes ERCC1, CD3EAP and PPP1R13L may be involved in linking the upstream and downstream genes, while the different splicing isoforms of ERCC1 affect the expression of its overlapping genes, suggesting potential application in cisplatin resistance in NSCLC treatment.
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http://dx.doi.org/10.3892/ijo.2018.4347DOI Listing
June 2018

In situ synthesis of bilayered gradient poly(vinyl alcohol)/hydroxyapatite composite hydrogel by directional freezing-thawing and electrophoresis method.

Mater Sci Eng C Mater Biol Appl 2017 Aug 18;77:76-83. Epub 2017 Mar 18.

Beijing National Laboratory for Molecular Sciences, Key Laboratory of Engineering Plastics, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China.

Bilayered poly(vinyl alcohol) (PVA)/hydroxyapatite (HA) composite hydrogels with anisotropic and gradient mechanical properties were prepared by the combination of directional freezing-thawing (DFT) and electrophoresis method. Firstly, PVA hydrogels with aligned channel structure were prepared by the DFT method. Then, HA nanoparticles were in situ synthesized within the PVA hydrogels via electrophoresis. By controlling the time of the electrophoresis process, a bilayered gradient hydrogel containing HA particles in only half of the gel region was obtained. The PVA/HA composite hydrogel exhibited gradient mechanical strength depending on the distance to the cathode. The gradient initial tensile modulus ranging from 0.18MPa to 0.27MPa and the gradient initial compressive modulus from 0.33MPa to 0.51MPa were achieved. The binding strength of the two regions was relatively high and no apparent internal stress or defect was observed at the boundary. The two regions of the bilayered hydrogel also showed different osteoblast cell adhesion properties.
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http://dx.doi.org/10.1016/j.msec.2017.03.136DOI Listing
August 2017

The Long Non-Coding RNA XIST Controls Non-Small Cell Lung Cancer Proliferation and Invasion by Modulating miR-186-5p.

Cell Physiol Biochem 2017 25;41(6):2221-2229. Epub 2017 Apr 25.

Background/aims: Long non-coding RNAs (lncRNAs) are key players in the development and progression of human cancers. The lncRNA XIST (X-inactive specific transcript) has been shown to be upregulated in human non-small cell lung cancer (NSCLC); however, its role and molecular mechanisms in NSCLC cell progression remain unclear.

Methods: qRT-PCR was conducted to assess the expression of XIST and miR-186. Cell proliferation was detected using MTT assay. Cell invasion and migration were evaluated using transwell assay. Cell cycle distribution and apoptosis rates were analyzed by flow cytometry. Luciferase reporter assay was used to identify the direct regulation of XIST and miR-186. A RNA immunoprecipitation was used to analyze whether XIST was associated with the RNA-induced silencing complex (RISC).

Results: We confirmed that XIST was upregulated in NSCLC cell lines and tissues. Functionally, XIST knockdown inhibited cancer cell proliferation and invasion, and induced apoptosis in vitro, and suppressed subcutaneous tumor growth in vivo. Mechanistic investigations revealed a reciprocal repressive interaction between XIST and miR-186-5p. Furthermore, we showed that miR-186-5p has a binding site for XIST. Our data also indicated that XIST and miR-186-5p are likely in the same RNA induced silencing complex.

Conclusion: Together, our data revealed that XIST knockdown confers suppressive function in NSCLC and XIST may be a novel therapeutic marker in this disease.
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http://dx.doi.org/10.1159/000475637DOI Listing
July 2017

A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring.

PLoS One 2016 10;11(10):e0164104. Epub 2016 Oct 10.

Department of Electrical, Electronic and Information Engineering, University of Bologna, Viale Risorgimento 2, Bologna, l40136, Italy.

Objective: Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared.

Methods: Six MSPE algorithms-derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis-were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures.

Results: CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness.

Conclusions: MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect changes. CG-based multiscale permutation entropies may fail to describe the characteristics of EEG at high decomposition scales.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0164104PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5056744PMC
April 2017

The ERCC2/XPD Lys751Gln polymorphism affects DNA repair of benzo[a]pyrene induced damage, tested in an in vitro model.

Toxicol In Vitro 2016 Aug 29;34:300-308. Epub 2016 Apr 29.

Dept. Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands.

Nucleotide excision repair (NER) is an important defense mechanism of the body to exogenous carcinogens and mutagens, such as benzo[a]pyrene (B[a]P). Genetic polymorphisms in ERCC2/XPD, a critical element in NER, are thought to be associated with individual's cancer susceptibility. Although ERCC2/XPD Lys751Gln (rs13181) is the most studied polymorphism, the impact of this polymorphism on DNA repair capacity to carcinogen remains unclear. In the present study, cDNA clones carrying different genotypes of ERCC2/XPD (Lys751Gln) were introduced into an ERCC2/XPD deficient cell line (UV5) in a well-controlled biological system. After B[a]P treatment, cell growth inhibition rates and DNA damage levels in all cells were detected respectively. As expected, we found that the DNA repair capacity in UV5 cells was restored to levels similar to wildtype parent AA8 cells upon introduction of the cDNA clone of ERCC2/XPD (Lys751). Interestingly, after B[a]P treatment, transfected cells expressing variant ERCC2/XPD (751Gln) showed an enhanced cellular sensitivity and a diminished DNA repair capacity. The wildtype genotype AA (Lys) was found to be associated with a higher DNA repair capacity as compared to its polymorphic genotype CC (Gln). These data indicate that ERCC2/XPD Lys751Gln polymorphism affects DNA repair capacity after exposure to environmental carcinogens such as B[a]P in this well-controlled in vitro system and could act as a biomarker to increase the predictive value to develop cancer.
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http://dx.doi.org/10.1016/j.tiv.2016.04.015DOI Listing
August 2016

A Pharmacokinetics-Neural Mass Model (PK-NMM) for the Simulation of EEG Activity during Propofol Anesthesia.

PLoS One 2015 31;10(12):e0145959. Epub 2015 Dec 31.

State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.

Modeling the effects of anesthetic drugs on brain activity is very helpful in understanding anesthesia mechanisms. The aim of this study was to set up a combined model to relate actual drug levels to EEG dynamics and behavioral states during propofol-induced anesthesia. We proposed a new combined theoretical model based on a pharmacokinetics (PK) model and a neural mass model (NMM), which we termed PK-NMM--with the aim of simulating electroencephalogram (EEG) activity during propofol-induced general anesthesia. The PK model was used to derive propofol effect-site drug concentrations (C(eff)) based on the actual drug infusion regimen. The NMM model took C(eff) as the control parameter to produce simulated EEG-like (sEEG) data. For comparison, we used real prefrontal EEG (rEEG) data of nine volunteers undergoing propofol anesthesia from a previous experiment. To see how well the sEEG could describe the dynamic changes of neural activity during anesthesia, the rEEG data and the sEEG data were compared with respect to: power-frequency plots; nonlinear exponent (permutation entropy (PE)); and bispectral SynchFastSlow (SFS) parameters. We found that the PK-NMM model was able to reproduce anesthesia EEG-like signals based on the estimated drug concentration and patients' condition. The frequency spectrum indicated that the frequency power peak of the sEEG moved towards the low frequency band as anesthesia deepened. Different anesthetic states could be differentiated by the PE index. The correlation coefficient of PE was 0.80 ± 0.13 (mean ± standard deviation) between rEEG and sEEG for all subjects. Additionally, SFS could track the depth of anesthesia and the SFS of rEEG and sEEG were highly correlated with a correlation coefficient of 0.77 ± 0.13. The PK-NMM model could simulate EEG activity and might be a useful tool for understanding the action of propofol on brain activity.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0145959PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4697853PMC
June 2016
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