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      Shieldin complex promotes DNA end-joining and counters homologous recombination in BRCA1-null cells

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          Abstract

          BRCA1 deficiencies cause breast, ovarian, prostate and other cancers, and render tumours hypersensitive to PARP inhibitors. To understand resistance mechanisms, we conducted whole-genome CRISPR-Cas9 synthetic-viability/resistance screens in BRCA1-deficient breast cancer cells treated with PARP inhibitors. We identified two previously uncharacterized proteins, C20orf196 and FAM35A, whose inactivation confers strong PARP-inhibitor resistance. Mechanistically, we show C20orf196 and FAM35A form a complex, “Shieldin” (SHLD1/2), with FAM35A interacting with single-stranded DNA via its C-terminal OB fold region. We establish that Shieldin acts as the downstream effector of 53BP1/RIF1/MAD2L2 to promote DNA double-strand break (DSB) end-joining through restricting DSB resection and counteract homologous recombination by antagonising BRCA2/RAD51 loading in BRCA1-deficient cells. Notably, Shieldin inactivation further sensitises BRCA1-deficient cells to cisplatin, suggesting how defining the SHLD1/2 status of BRCA1-deficient tumours might aid patient stratification and yield new treatment opportunities. Highlighting this potential, we document reduced SHLD1/2 expression in human breast cancers displaying intrinsic or acquired PARP-inhibitor resistance.

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          Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.

          Quantitative proteomics has traditionally been performed by two-dimensional gel electrophoresis, but recently, mass spectrometric methods based on stable isotope quantitation have shown great promise for the simultaneous and automated identification and quantitation of complex protein mixtures. Here we describe a method, termed SILAC, for stable isotope labeling by amino acids in cell culture, for the in vivo incorporation of specific amino acids into all mammalian proteins. Mammalian cell lines are grown in media lacking a standard essential amino acid but supplemented with a non-radioactive, isotopically labeled form of that amino acid, in this case deuterated leucine (Leu-d3). We find that growth of cells maintained in these media is no different from growth in normal media as evidenced by cell morphology, doubling time, and ability to differentiate. Complete incorporation of Leu-d3 occurred after five doublings in the cell lines and proteins studied. Protein populations from experimental and control samples are mixed directly after harvesting, and mass spectrometric identification is straightforward as every leucine-containing peptide incorporates either all normal leucine or all Leu-d3. We have applied this technique to the relative quantitation of changes in protein expression during the process of muscle cell differentiation. Proteins that were found to be up-regulated during this process include glyceraldehyde-3-phosphate dehydrogenase, fibronectin, and pyruvate kinase M2. SILAC is a simple, inexpensive, and accurate procedure that can be used as a quantitative proteomic approach in any cell culture system.
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            Is Open Access

            featureCounts: An efficient general-purpose program for assigning sequence reads to genomic features

            , , (2013)
            Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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              A new method for gray-level picture thresholding using the entropy of the histogram

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                Author and article information

                Journal
                100890575
                21417
                Nat Cell Biol
                Nat. Cell Biol.
                Nature cell biology
                1465-7392
                1476-4679
                14 September 2018
                18 July 2018
                August 2018
                18 January 2019
                : 20
                : 8
                : 954-965
                Affiliations
                [1 ]The Wellcome Trust/Cancer Research UK Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge CB2 1QN, UK
                [2 ]Academic Urology Group, Department of Surgery, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke’s Hospital, Hills Road, Cambridge CB2 0QQ, UK
                [3 ]Genome Integrity, Immunity and Cancer Unit, Department of Immunology, Department of Genomes and Genetics, Institut Pasteur, 75015 Paris, France
                [4 ]Division of Oncogenomics, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
                [5 ]Department of Oncology and Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge CB2 0RE, UK
                [6 ]Institute of Molecular Biology (IMB), 55128 Mainz, Germany
                [7 ]Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA, UK
                [8 ]Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
                [9 ]AstraZeneca, Waltham, Massachusetts, 02451, USA
                [10 ]Vall d'Hebron Institute of Oncology, Barcelona, Spain
                [11 ]Astrazeneca, 1 Francis Crick Ave, Cambridge CB2 0RE, UK
                Author notes
                Article
                EMS78112
                10.1038/s41556-018-0140-1
                6145444
                30022119
                82b9e563-89d3-45a0-a124-b3465d3805d4

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                Cell biology
                Cell biology

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