5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Xanthatin Selectively Targets Retinoblastoma by Inhibiting the PLK1-Mediated Cell Cycle

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Purpose

          Retinoblastoma is the most common primary intraocular malignant tumor in children. Although intra-arterial chemotherapy and conventional chemotherapy have become promising therapeutic approaches for advanced intraocular retinoblastoma, the side effects threaten health and are unavoidable, making the development of targeted therapy an urgent need. Therefore, we intended to find a potential drug for human retinoblastoma by screening an in-house compound library that included 89 purified and well-characterized natural products.

          Methods

          We screened a panel of 89 natural products in retinoblastoma cell lines to find the inhibitor. The inhibition of the identified inhibitor xanthatin on cell growth was detected through half-maximal inhibitory concentration (IC 50), flow cytometry assay, and zebrafish model system. RNA-seq further selected the target gene PLK1.

          Results

          We reported the discovery of xanthatin as an effective inhibitor of retinoblastoma. Mechanistically, xanthatin selectively inhibited the proliferation of retinoblastoma cells by inducing cell cycle arrest and promoting apoptosis. Interestingly, xanthatin targeted PLK1-mediated cell cycle progression. The efficacy of xanthatin was further confirmed in zebrafish models.

          Conclusions

          Collectively, our data suggested that xanthatin significantly inhibited tumor growth in vitro and in vivo, and xanthatin could be a potential drug treatment for retinoblastoma.

          Related collections

          Most cited references61

          • Record: found
          • Abstract: found
          • Article: not found

          StringTie enables improved reconstruction of a transcriptome from RNA-seq reads.

          Methods used to sequence the transcriptome often produce more than 200 million short sequences. We introduce StringTie, a computational method that applies a network flow algorithm originally developed in optimization theory, together with optional de novo assembly, to assemble these complex data sets into transcripts. When used to analyze both simulated and real data sets, StringTie produces more complete and accurate reconstructions of genes and better estimates of expression levels, compared with other leading transcript assembly programs including Cufflinks, IsoLasso, Scripture and Traph. For example, on 90 million reads from human blood, StringTie correctly assembled 10,990 transcripts, whereas the next best assembly was of 7,187 transcripts by Cufflinks, which is a 53% increase in transcripts assembled. On a simulated data set, StringTie correctly assembled 7,559 transcripts, which is 20% more than the 6,310 assembled by Cufflinks. As well as producing a more complete transcriptome assembly, StringTie runs faster on all data sets tested to date compared with other assembly software, including Cufflinks.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Differential expression analysis for sequence count data

            High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. We propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, DESeq, as an R/Bioconductor package.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              NGS QC Toolkit: A Toolkit for Quality Control of Next Generation Sequencing Data

              Next generation sequencing (NGS) technologies provide a high-throughput means to generate large amount of sequence data. However, quality control (QC) of sequence data generated from these technologies is extremely important for meaningful downstream analysis. Further, highly efficient and fast processing tools are required to handle the large volume of datasets. Here, we have developed an application, NGS QC Toolkit, for quality check and filtering of high-quality data. This toolkit is a standalone and open source application freely available at http://www.nipgr.res.in/ngsqctoolkit.html. All the tools in the application have been implemented in Perl programming language. The toolkit is comprised of user-friendly tools for QC of sequencing data generated using Roche 454 and Illumina platforms, and additional tools to aid QC (sequence format converter and trimming tools) and analysis (statistics tools). A variety of options have been provided to facilitate the QC at user-defined parameters. The toolkit is expected to be very useful for the QC of NGS data to facilitate better downstream analysis.
                Bookmark

                Author and article information

                Journal
                Invest Ophthalmol Vis Sci
                Invest Ophthalmol Vis Sci
                IOVS
                Investigative Ophthalmology & Visual Science
                The Association for Research in Vision and Ophthalmology
                0146-0404
                1552-5783
                13 December 2021
                December 2021
                : 62
                : 15
                : 11
                Affiliations
                [1 ]Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
                [2 ]Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
                [3 ]National Research Center for Translational Medicine, State Key Laboratory of Medical Genomics, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
                [4 ]Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
                Author notes
                Correspondence: Renbing Jia, Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639, Zhizaoju Road, Huangpu District, Shanghai 200001, China; renbingjia@ 123456sjtu.edu.cn .
                Jiayan Fan, Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 12, Lane 833, Zhizaoju Road, Shanghai 200001, China; fanjiayan1118@ 123456126.com .
                Jianming Zhang, National Research Center for Translational Medicine, State Key Laboratory of Medical Genomics, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 20025, China; jzuc@ 123456shsmu.edu.cn .
                [*]

                JY and YL contributed equally to this work.

                [#]

                JF, JZ and RJ are co-corresponding authors of this work.

                Article
                IOVS-21-32724
                10.1167/iovs.62.15.11
                8684308
                34901994
                d5583efa-b976-4a27-bd31-c41656a7a22d
                Copyright 2021 The Authors

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

                History
                : 12 November 2021
                : 06 April 2021
                Page count
                Pages: 13
                Categories
                Retina
                Retina

                xanthatin,retinoblastoma,cell cycle,plk1
                xanthatin, retinoblastoma, cell cycle, plk1

                Comments

                Comment on this article