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Han W, Yu F, Guan W. Oncogenic roles of lncRNA BLACAT1 and its related mechanisms in human cancers. Biomed Pharmacother 2020; 130:110632. [PMID: 34321169 DOI: 10.1016/j.biopha.2020.110632] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 07/30/2020] [Accepted: 08/02/2020] [Indexed: 02/07/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) play indispensable roles in mediating regulation of epigenetics, and their dysregulation is strongly associated with the initiation and progression of human cancers. Recently, lncRNA bladder cancer-associated transcript 1 (BLACAT1) has been observed to exert oncogenic effects on cancers, including glioma, breast cancer, lung cancer, hepatocellular carcinoma, gastric cancer, colorectal cancer, ovarian cancer, cervical cancer and osteosarcoma. Additional mechanical analyses have uncovered that lncRNA BLACAT1 is positively correlated with tumor stage, lymph node metastasis and distant metastasis of primary tumors via involvement with various cellular activities, thus leading to poor overall survival and progression-free survival (PFS). In this review, we generalize the oncogenic roles of BLACAT1 in multiple human cancers through correlation with clinical implications and cellular activities. Moreover, we forecast its potential clinical application as a novel biomarker and a promising therapeutic target for cancers.
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Affiliation(s)
- Wei Han
- Department of Neurosurgery, The Third Affiliated Hospital of Soochow University, Changzhou, China; Modern Medical Research Center, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Fan Yu
- Department of Endocrinology, The Third Affiliated Hospital of Soochow University, Changzhou, China; Modern Medical Research Center, The Third Affiliated Hospital of Soochow University, Changzhou, China
| | - Wei Guan
- Department of Neurosurgery, The Third Affiliated Hospital of Soochow University, Changzhou, China.
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Yamagata K, Suzuki S, Tagami M. Docosahexaenoic acid prevented tumor necrosis factor alpha-induced endothelial dysfunction and senescence. Prostaglandins Leukot Essent Fatty Acids 2016; 104:11-8. [PMID: 26802937 DOI: 10.1016/j.plefa.2015.10.006] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2015] [Revised: 09/26/2015] [Accepted: 10/02/2015] [Indexed: 01/22/2023]
Abstract
We investigated how docosahexaenoic acid (DHA) regulated tumor necrosis factor-alpha (TNF-α)-induced senescence and dysfunction in endothelial cells (EC). We used RT-PCR to examine the expression of several genes related to senescence and dysfunction in EC. TNF-α-induced p21 protein levels were investigated by Western blot (WB) and fluorescence antibody techniques. TNF-α induced the senescence marker β-galactosidase and the expression of several senescence and endothelial dysfunction-related genes, e.g., CDKN1A, SHC1 and GLB1. DHA attenuated TNF-α-induced senescence-related gene expression and p21 protein expression. DHA attenuated TNF-α-induced gene expression related to dysfunction of EC, such as plasminogen activator inhibitor 1 (SERPINE1), lectin-like oxidized low-density lipoprotein receptor-1 (OLR1), thromboxane A2 receptor (TXA2R) and p38 MAPK (MAPK14). DHA reversed the TNF-α-mediated reduction of endothelial nitric oxide synthase (NOS3) gene expression. TNF-α-mediated upregulation of these genes was inhibited by allopurinol and apocynin. These results indicated that DHA regulated the expression of several genes that are associated with senescence and dysfunction of EC.
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Affiliation(s)
- Kazuo Yamagata
- Department of Food Bioscience and Biotechnology, College of Bioresource Sciences, Nihon University (NUBS), Fujisawa, Japan.
| | - Sayaka Suzuki
- Department of Food Bioscience and Biotechnology, College of Bioresource Sciences, Nihon University (NUBS), Fujisawa, Japan
| | - Motoki Tagami
- Department of Internal Medicine, Sanraku Hospital, Chiyoda-Ku, Tokyo, Japan
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Mikheenko A, Saveliev V, Gurevich A. MetaQUAST: evaluation of metagenome assemblies. Bioinformatics 2015; 32:1088-90. [PMID: 26614127 DOI: 10.1093/bioinformatics/btv697] [Citation(s) in RCA: 310] [Impact Index Per Article: 34.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2015] [Accepted: 11/23/2015] [Indexed: 12/12/2022] Open
Abstract
UNLABELLED During the past years we have witnessed the rapid development of new metagenome assembly methods. Although there are many benchmark utilities designed for single-genome assemblies, there is no well-recognized evaluation and comparison tool for metagenomic-specific analogues. In this article, we present MetaQUAST, a modification of QUAST, the state-of-the-art tool for genome assembly evaluation based on alignment of contigs to a reference. MetaQUAST addresses such metagenome datasets features as (i) unknown species content by detecting and downloading reference sequences, (ii) huge diversity by giving comprehensive reports for multiple genomes and (iii) presence of highly relative species by detecting chimeric contigs. We demonstrate MetaQUAST performance by comparing several leading assemblers on one simulated and two real datasets. AVAILABILITY AND IMPLEMENTATION http://bioinf.spbau.ru/metaquast CONTACT aleksey.gurevich@spbu.ru SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg 199034, Russia
| | - Vladislav Saveliev
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg 199034, Russia
| | - Alexey Gurevich
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg 199034, Russia
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Raznikova MO, Raznikov VV. Probabilistic calculations of biomolecule charge states that generate mass spectra of multiply charged ions. Mol Biol 2015. [DOI: 10.1134/s0026893315050143] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Vasilinetc I, Prjibelski AD, Gurevich A, Korobeynikov A, Pevzner PA. Assembling short reads from jumping libraries with large insert sizes. Bioinformatics 2015; 31:3262-8. [PMID: 26040456 DOI: 10.1093/bioinformatics/btv337] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2015] [Accepted: 05/26/2015] [Indexed: 11/13/2022] Open
Abstract
MOTIVATION Advances in Next-Generation Sequencing technologies and sample preparation recently enabled generation of high-quality jumping libraries that have a potential to significantly improve short read assemblies. However, assembly algorithms have to catch up with experimental innovations to benefit from them and to produce high-quality assemblies. RESULTS We present a new algorithm that extends recently described exSPAnder universal repeat resolution approach to enable its applications to several challenging data types, including jumping libraries generated by the recently developed Illumina Nextera Mate Pair protocol. We demonstrate that, with these improvements, bacterial genomes often can be assembled in a few contigs using only a single Nextera Mate Pair library of short reads. AVAILABILITY AND IMPLEMENTATION Described algorithms are implemented in C++ as a part of SPAdes genome assembler, which is freely available at bioinf.spbau.ru/en/spades. CONTACT ap@bioinf.spbau.ru SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Irina Vasilinetc
- Algorithmic Biology Lab, St. Petersburg Academic University 194021
| | - Andrey D Prjibelski
- Algorithmic Biology Lab, St. Petersburg Academic University 194021, Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St.Petersburg State University, 199004
| | - Alexey Gurevich
- Algorithmic Biology Lab, St. Petersburg Academic University 194021, Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St.Petersburg State University, 199004
| | - Anton Korobeynikov
- Algorithmic Biology Lab, St. Petersburg Academic University 194021, Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St.Petersburg State University, 199004, Department of Mathematics and Mechanics, St. Petersburg State University, St. Petersburg, 198504, Russia and
| | - Pavel A Pevzner
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St.Petersburg State University, 199004, Department of Computer Science and Engineering, University of California, San Diego, CA 92093-0404, USA
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Abstract
Dysregulated homeostasis of epithelial cells resulting in disruption of mucosal barrier function is an important pathogenic mechanism in inflammatory bowel diseases (IBD). We have characterized a novel gastric protein, Antrum Mucosal Protein (AMP)-18, that has pleiotropic properties; it is mitogenic, anti-apoptotic and can stimulate formation of tight junctions. A 21-mer synthetic peptide derived from AMP-18 exhibits the same biological functions as the full-length protein and is an effective therapeutic agent in mouse models of IBD. In this study we set out to characterize therapeutic mechanisms and identify molecular targets by which AMP-18 maintains and restores disrupted epithelial homeostasis in cultured intestinal epithelial cells and a mouse model of IBD. Tumor necrosis factor (TNF)-α, a pro-inflammatory cytokine known to mediate gastrointestinal (GI) mucosal injury in IBD, was used to induce intestinal epithelial cell injury, and study the effects of AMP-18 on apoptosis and the cell cycle. An apoptosis array used to search for targets of AMP-18 in cells exposed to TNF-α identified the cyclin-dependent kinase inhibitor p21WAF1/CIP1. Treatment with AMP-18 blunted increases in p21 expression and apoptosis, while reversing disturbed cell cycle kinetics induced by TNF-α. AMP-18 appears to act through PI3K/AKT pathways to increase p21 phosphorylation, thereby reducing its nuclear accumulation to overcome the antiproliferative effects of TNF-α. In vitamin D receptor-deficient mice with TNBS-induced IBD, the observed increase in p21 expression in colonic epithelial cells was suppressed by treatment with AMP peptide. The results indicate that AMP-18 can maintain and/or restore the homeostatic balance between proliferation and apoptosis in intestinal epithelial cells to protect and repair mucosal barrier homeostasis and function, suggesting a therapeutic role in IBD.
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Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis. Sci Rep 2015; 5:9283. [PMID: 25788156 PMCID: PMC4365388 DOI: 10.1038/srep09283] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Accepted: 02/20/2015] [Indexed: 12/16/2022] Open
Abstract
The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.
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TimeXNet: identifying active gene sub-networks using time-course gene expression profiles. BMC SYSTEMS BIOLOGY 2014; 8 Suppl 4:S2. [PMID: 25522063 PMCID: PMC4290689 DOI: 10.1186/1752-0509-8-s4-s2] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Background Time-course gene expression profiles are frequently used to provide insight into the changes in cellular state over time and to infer the molecular pathways involved. When combined with large-scale molecular interaction networks, such data can provide information about the dynamics of cellular response to stimulus. However, few tools are currently available to predict a single active gene sub-network from time-course gene expression profiles. Results We introduce a tool, TimeXNet, which identifies active gene sub-networks with temporal paths using time-course gene expression profiles in the context of a weighted gene regulatory and protein-protein interaction network. TimeXNet uses a specialized form of the network flow optimization approach to identify the most probable paths connecting the genes with significant changes in expression at consecutive time intervals. TimeXNet has been extensively evaluated for its ability to predict novel regulators and their associated pathways within active gene sub-networks in the mouse innate immune response and the yeast osmotic stress response. Compared to other similar methods, TimeXNet identified up to 50% more novel regulators from independent experimental datasets. It predicted paths within a greater number of known pathways with longer overlaps (up to 7 consecutive edges) within these pathways. TimeXNet was also shown to be robust in the presence of varying amounts of noise in the molecular interaction network. Conclusions TimeXNet is a reliable tool that can be used to study cellular response to stimuli through the identification of time-dependent active gene sub-networks in diverse biological systems. It is significantly better than other similar tools. TimeXNet is implemented in Java as a stand-alone application and supported on Linux, MS Windows and Macintosh. The output of TimeXNet can be directly viewed in Cytoscape. TimeXNet is freely available for non-commercial users.
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Prjibelski AD, Vasilinetc I, Bankevich A, Gurevich A, Krivosheeva T, Nurk S, Pham S, Korobeynikov A, Lapidus A, Pevzner PA. ExSPAnder: a universal repeat resolver for DNA fragment assembly. Bioinformatics 2014; 30:i293-301. [PMID: 24931996 PMCID: PMC4058921 DOI: 10.1093/bioinformatics/btu266] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
UNLABELLED Next-generation sequencing (NGS) technologies have raised a challenging de novo genome assembly problem that is further amplified in recently emerged single-cell sequencing projects. While various NGS assemblers can use information from several libraries of read-pairs, most of them were originally developed for a single library and do not fully benefit from multiple libraries. Moreover, most assemblers assume uniform read coverage, condition that does not hold for single-cell projects where utilization of read-pairs is even more challenging. We have developed an exSPAnder algorithm that accurately resolves repeats in the case of both single and multiple libraries of read-pairs in both standard and single-cell assembly projects. AVAILABILITY AND IMPLEMENTATION http://bioinf.spbau.ru/en/spades
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Affiliation(s)
- Andrey D Prjibelski
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USA
| | - Irina Vasilinetc
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USA
| | - Anton Bankevich
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USA
| | - Alexey Gurevich
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USA
| | - Tatiana Krivosheeva
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USA
| | - Sergey Nurk
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USA
| | - Son Pham
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USA
| | - Anton Korobeynikov
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USAAlgorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USA
| | - Alla Lapidus
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USAAlgorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USA
| | - Pavel A Pevzner
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USAAlgorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia, Department of Mathematics and Mechanics, Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia and Department of Computer Science and Engineering, University of California, San Diego, USA
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Li S, Zhang B. Traditional Chinese medicine network pharmacology: theory, methodology and application. Chin J Nat Med 2014; 11:110-20. [PMID: 23787177 DOI: 10.1016/s1875-5364(13)60037-0] [Citation(s) in RCA: 567] [Impact Index Per Article: 56.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2013] [Indexed: 02/06/2023]
Abstract
Traditional Chinese medicine (TCM) has a long history of viewing an individual or patient as a system with different statuses, and has accumulated numerous herbal formulae. The holistic philosophy of TCM shares much with the key ideas of emerging network pharmacology and network biology, and meets the requirements of overcoming complex diseases, such as cancer, in a systematic manner. To discover TCM from a systems perspective and at the molecular level, a novel TCM network pharmacology approach was established by updating the research paradigm from the current "one target, one drug" mode to a new "network target, multi-components" mode. Subsequently, a set of TCM network pharmacology methods were created to prioritize disease-associated genes, to predict the target profiles and pharmacological actions of herbal compounds, to reveal drug-gene-disease co-module associations, to screen synergistic multi-compounds from herbal formulae in a high-throughput manner, and to interpret the combinatorial rules and network regulation effects of herbal formulae. The effectiveness of the network-based methods was demonstrated for the discovery of bioactive compounds and for the elucidation of the mechanisms of action of herbal formulae, such as Qing-Luo-Yin and the Liu-Wei-Di-Huang pill. The studies suggest that the TCM network pharmacology approach provides a new research paradigm for translating TCM from an experience-based medicine to an evidence-based medicine system, which will accelerate TCM drug discovery, and also improve current drug discovery strategies.
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Affiliation(s)
- Shao Li
- Bioinformatics Division and Center for Synthetic and Systems Biology, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.
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Patil A, Kumagai Y, Liang KC, Suzuki Y, Nakai K. Linking transcriptional changes over time in stimulated dendritic cells to identify gene networks activated during the innate immune response. PLoS Comput Biol 2013; 9:e1003323. [PMID: 24244133 PMCID: PMC3820512 DOI: 10.1371/journal.pcbi.1003323] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2013] [Accepted: 09/21/2013] [Indexed: 01/09/2023] Open
Abstract
The innate immune response is primarily mediated by the Toll-like receptors functioning through the MyD88-dependent and TRIF-dependent pathways. Despite being widely studied, it is not yet completely understood and systems-level analyses have been lacking. In this study, we identified a high-probability network of genes activated during the innate immune response using a novel approach to analyze time-course gene expression profiles of activated immune cells in combination with a large gene regulatory and protein-protein interaction network. We classified the immune response into three consecutive time-dependent stages and identified the most probable paths between genes showing a significant change in expression at each stage. The resultant network contained several novel and known regulators of the innate immune response, many of which did not show any observable change in expression at the sampled time points. The response network shows the dominance of genes from specific functional classes during different stages of the immune response. It also suggests a role for the protein phosphatase 2a catalytic subunit α in the regulation of the immunoproteasome during the late phase of the response. In order to clarify the differences between the MyD88-dependent and TRIF-dependent pathways in the innate immune response, time-course gene expression profiles from MyD88-knockout and TRIF-knockout dendritic cells were analyzed. Their response networks suggest the dominance of the MyD88-dependent pathway in the innate immune response, and an association of the circadian regulators and immunoproteasomal degradation with the TRIF-dependent pathway. The response network presented here provides the most probable associations between genes expressed in the early and the late phases of the innate immune response, while taking into account the intermediate regulators. We propose that the method described here can also be used in the identification of time-dependent gene sub-networks in other biological systems.
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Affiliation(s)
- Ashwini Patil
- The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Yutaro Kumagai
- WPI Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Kuo-ching Liang
- The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Yutaka Suzuki
- Department of Medical Genome Sciences, The University of Tokyo, Tokyo, Japan
| | - Kenta Nakai
- The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- * E-mail:
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Abstract
OBJECTIVE This study aimed to investigate the effect of serum taken from patients with severe acute pancreatitis (SAP) on vascular endothelial permeability. METHODS The monolayer permeability of endothelial cells (ECs) was assessed. Morphological changes in ECs, induced by serum from patients with SAP were assessed. Expressions of RhoA, myosin light chain (MLC) phosphorylation, and VE-cadherin protein were detected by Western blot. RESULTS Compared with the control group, 20% SAP serum significantly increased endothelial monolayer permeability (P < 0.01), markedly induced transcellular F-actin redistribution with stress fiber formation and VE-cadherin derangement with fragmentations located at the cell borders, and increased gaps between ECs. Furthermore, Western blotting showed that SAP serum induced rapid activation of Rho protein, and markedly increased the level of phosphorylated MLC. However, pretreatment with Y-27632 (an inhibitor for Rho kinase) significantly inhibited endothelial hyperpermeability and the morphological changes of F-actin rearrangement and VE-cadherin redistribution. This was associated with a down-regulation of Rho protein expression and a reduction in the level of MLC phosphorylation. CONCLUSIONS The SAP serum induces the loss of vascular endothelial monolayer integrity, with endothelial F-actin stress fiber formation and VE-cadherin redistribution. One of the mechanisms for this process involves the activation of the Rho/Rho kinase signaling pathway.
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Chen J, Pande M, Huang YJ, Wei C, Amos CI, Talseth-Palmer BA, Meldrum CJ, Chen WV, Gorlov IP, Lynch PM, Scott RJ, Frazier ML. Cell cycle-related genes as modifiers of age of onset of colorectal cancer in Lynch syndrome: a large-scale study in non-Hispanic white patients. Carcinogenesis 2012; 34:299-306. [PMID: 23125224 DOI: 10.1093/carcin/bgs344] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Heterogeneity in age of onset of colorectal cancer in individuals with mutations in DNA mismatch repair genes (Lynch syndrome) suggests the influence of other lifestyle and genetic modifiers. We hypothesized that genes regulating the cell cycle influence the observed heterogeneity as cell cycle-related genes respond to DNA damage by arresting the cell cycle to provide time for repair and induce transcription of genes that facilitate repair. We examined the association of 1456 single nucleotide polymorphisms (SNPs) in 128 cell cycle-related genes and 31 DNA repair-related genes in 485 non-Hispanic white participants with Lynch syndrome to determine whether there are SNPs associated with age of onset of colorectal cancer. Genotyping was performed on an Illumina GoldenGate platform, and data were analyzed using Kaplan-Meier survival analysis, Cox regression analysis and classification and regression tree (CART) methods. Ten SNPs were independently significant in a multivariable Cox proportional hazards regression model after correcting for multiple comparisons (P < 5 × 10(-4)). Furthermore, risk modeling using CART analysis defined combinations of genotypes for these SNPs with which subjects could be classified into low-risk, moderate-risk and high-risk groups that had median ages of colorectal cancer onset of 63, 50 and 42 years, respectively. The age-associated risk of colorectal cancer in the high-risk group was more than four times the risk in the low-risk group (hazard ratio = 4.67, 95% CI = 3.16-6.92). The additional genetic markers identified may help in refining risk groups for more tailored screening and follow-up of non-Hispanic white patients with Lynch syndrome.
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Affiliation(s)
- Jinyun Chen
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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