Blog
About

6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Mitochondrial uncoupling reveals a novel therapeutic opportunity for p53-defective cancers

      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

          There are considerable challenges in directly targeting the mutant p53 protein, given the large heterogeneity of p53 mutations in the clinic. An alternative approach is to exploit the altered fitness of cells imposed by loss-of-wild-type p53. Here we identify niclosamide through a HTS screen for compounds selectively killing p53-deficient cells. Niclosamide impairs the growth of p53-deficient cells and of p53 mutant patient-derived ovarian xenografts. Metabolome profiling reveals that niclosamide induces mitochondrial uncoupling, which renders mutant p53 cells susceptible to mitochondrial-dependent apoptosis through preferential accumulation of arachidonic acid (AA), and represents a first-in-class inhibitor of p53 mutant tumors. Wild-type p53 evades the cytotoxicity by promoting the transcriptional induction of two key lipid oxygenation genes, ALOX5 and ALOX12B, which catalyzes the dioxygenation and breakdown of AA. Therefore, we propose a new paradigm for targeting cancers defective in the p53 pathway, by exploiting their vulnerability to niclosamide-induced mitochondrial uncoupling.

          Abstract

          Several challenges are involved in direct targeting of mutant p53, while targeting altered fitness of cells with loss of wild type p53 is an alternative approach. Here they identify niclosamide to be selectively toxic to p53 deficient cells through a previously unknown mitochondrial uncoupling mechanism.

          Related collections

          Most cited references 54

          • 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

            In vivo activation of the p53 pathway by small-molecule antagonists of MDM2.

            MDM2 binds the p53 tumor suppressor protein with high affinity and negatively modulates its transcriptional activity and stability. Overexpression of MDM2, found in many human tumors, effectively impairs p53 function. Inhibition of MDM2-p53 interaction can stabilize p53 and may offer a novel strategy for cancer therapy. Here, we identify potent and selective small-molecule antagonists of MDM2 and confirm their mode of action through the crystal structures of complexes. These compounds bind MDM2 in the p53-binding pocket and activate the p53 pathway in cancer cells, leading to cell cycle arrest, apoptosis, and growth inhibition of human tumor xenografts in nude mice.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification.

              Metabolite profiling in biomarker discovery, enzyme substrate assignment, drug activity/specificity determination, and basic metabolic research requires new data preprocessing approaches to correlate specific metabolites to their biological origin. Here we introduce an LC/MS-based data analysis approach, XCMS, which incorporates novel nonlinear retention time alignment, matched filtration, peak detection, and peak matching. Without using internal standards, the method dynamically identifies hundreds of endogenous metabolites for use as standards, calculating a nonlinear retention time correction profile for each sample. Following retention time correction, the relative metabolite ion intensities are directly compared to identify changes in specific endogenous metabolites, such as potential biomarkers. The software is demonstrated using data sets from a previously reported enzyme knockout study and a large-scale study of plasma samples. XCMS is freely available under an open-source license at http://metlin.scripps.edu/download/.
                Bookmark

                Author and article information

                Contributors
                cheokcf@imcb.a-star.edu.sg
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                26 September 2018
                26 September 2018
                2018
                : 9
                Affiliations
                [1 ]IFOM-p53Lab Joint Research Laboratory, IFOM, Milan, 20139 Italy
                [2 ]ISNI 0000 0004 0385 0924, GRID grid.428397.3, Duke–NUS Graduate Medical School, ; 8 College Road, Singapore, 169857 Singapore
                [3 ]ISNI 0000 0004 0637 0221, GRID grid.185448.4, p53 Laboratory, Agency for Science Technology and Research, ; Singapore, 138648 Singapore
                [4 ]ISNI 0000 0004 0637 0221, GRID grid.185448.4, Institute of Molecular and Cell Biology, , Agency for Science Technology and Research, ; Singapore, 138673 Singapore
                [5 ]ISNI 0000 0001 2180 6431, GRID grid.4280.e, Cancer Science Institute of Singapore, , National University of Singapore, ; Singapore, 117599 Singapore
                [6 ]ISNI 0000 0004 0637 0221, GRID grid.185448.4, Bioprocessing Technology Institute, , Agency for Science Technology and Research, ; Singapore, 138668 Singapore
                [7 ]ISNI 0000 0001 2180 6431, GRID grid.4280.e, Department of Pathology, Yong Loo Lin School of Medicine, , National University of Singapore, ; Singapore, 119074 Singapore
                [8 ]ISNI 0000 0004 0637 0221, GRID grid.185448.4, Skin Research Institute of Singapore, , Agency for Science Technology and Research, ; Singapore, 138648 Singapore
                [9 ]ISNI 0000 0000 8958 3388, GRID grid.414963.d, Department of Gynaecological Oncology, , KK Women’s and Children’s Hospital, ; Singapore, 229899 Singapore
                [10 ]ISNI 0000 0000 8958 3388, GRID grid.414963.d, Department of Pathology and Laboratory Medicine, , KK Women’s and Children’s Hospital, ; Singapore, 229899 Singapore
                [11 ]ISNI 0000 0004 0620 9745, GRID grid.410724.4, Laboratory of Molecular Endocrinology, , National Cancer Centre Singapore, ; Singapore, 169610 Singapore
                [12 ]ISNI 0000 0001 2180 6431, GRID grid.4280.e, Department of Pharmacology, Yong Loo Lin School of Medicine, , National University of Singapore, ; Singapore, 117600 Singapore
                [13 ]GRID grid.440782.d, National University Cancer Institute, ; Singapore, 119074 Singapore
                [14 ]ISNI 0000 0001 2180 6431, GRID grid.4280.e, Department of Biochemistry, Yong Loo Lin School of Medicine, , National University of Singapore, ; Singapore, 117596 Singapore
                Article
                5805
                10.1038/s41467-018-05805-1
                6158291
                30258081
                © The Author(s) 2018

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                Categories
                Article
                Custom metadata
                © The Author(s) 2018

                Uncategorized

                Comments

                Comment on this article