Inviting an author to review:
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Bromodomain inhibitor i-BET858 triggers a unique transcriptional response coupled to enhanced DNA damage, cell cycle arrest and apoptosis in high-grade ovarian carcinoma cells

      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

          Background

          Ovarian cancer has a specific unmet clinical need, with a persistently poor 5-year survival rate observed in women with advanced stage disease warranting continued efforts to develop new treatment options. The amplification of BRD4 in a significant subset of high-grade serous ovarian carcinomas (HGSC) has led to the development of BET inhibitors (BETi) as promising antitumour agents that have subsequently been evaluated in phase I/II clinical trials. Here, we describe the molecular effects and ex vivo preclinical activities of i-BET858, a bivalent pan-BET inhibitor with proven in vivo BRD inhibitory activity.

          Results

          i-BET858 demonstrates enhanced cytotoxic activity compared with earlier generation BETis both in cell lines and primary cells derived from clinical samples of HGSC. At molecular level, i-BET858 triggered a bipartite transcriptional response, comprised of a ‘core’ network of genes commonly associated with BET inhibition in solid tumours, together with a unique i-BET858 gene signature. Mechanistically, i-BET858 elicited enhanced DNA damage, cell cycle arrest and apoptotic cell death compared to its predecessor i-BET151.

          Conclusions

          Overall, our ex vivo and in vitro studies indicate that i-BET858 represents an optimal candidate to pursue further clinical validation for the treatment of HGSC.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13148-023-01477-x.

          Related collections

          Most cited references65

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Fast gapped-read alignment with Bowtie 2.

              As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
                Bookmark

                Author and article information

                Contributors
                l.francis@swansea.ac.uk
                Journal
                Clin Epigenetics
                Clin Epigenetics
                Clinical Epigenetics
                BioMed Central (London )
                1868-7075
                1868-7083
                15 April 2023
                15 April 2023
                2023
                : 15
                : 63
                Affiliations
                [1 ]GRID grid.4827.9, ISNI 0000 0001 0658 8800, Swansea University Medical School, Swansea University, ; Singleton Park, Swansea, SA2 8PP UK
                [2 ]GRID grid.418236.a, ISNI 0000 0001 2162 0389, Immunology Research Unit, GlaxoSmithKline, Medicines Research Centre, ; Stevenage, SG1 2NY UK
                [3 ]GRID grid.419728.1, ISNI 0000 0000 8959 0182, Swansea Bay University Health Board, ; Swansea, SA12 7BR UK
                [4 ]Cwm Taf Morgannwg University Health Board, Swansea, SA2 8QA UK
                [5 ]Porvair Sciences Ltd, Wrexham, LL13 9XS UK
                Article
                1477
                10.1186/s13148-023-01477-x
                10105475
                37060086
                b2aaea31-8704-4a81-964e-cfaf156e523e
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 8 June 2022
                : 29 March 2023
                Funding
                Funded by: Welsh Government and European Regional Development Fund
                Award ID: 2017/COL/004
                Award ID: 2017/COL/004
                Award ID: 2017/COL/004
                Award ID: 2017/COL/001
                Award ID: 2017/COL/004
                Award ID: 2017/COL/001
                Award ID: 2017/COL/004
                Award ID: 2017/COL/004
                Award ID: 2017/COL/004
                Award ID: 2017/COL/004
                Award ID: 2017/COL/004
                Award ID: 2017/COL/004
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2023

                Genetics
                ovarian cancer,beti,advanced therapeutics,drug development,i-bet858
                Genetics
                ovarian cancer, beti, advanced therapeutics, drug development, i-bet858

                Comments

                Comment on this article