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      Multi-chaperone function modulation and association with cytoskeletal proteins are key features of the function of AIP in the pituitary gland

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          Abstract

          Despite the well-recognized role of loss-of-function mutations of the aryl hydrocarbon receptor interacting protein gene ( AIP) predisposing to pituitary adenomas, the pituitary-specific function of this tumor suppressor remains an enigma. To determine the repertoire of interacting partners for the AIP protein in somatotroph cells, wild-type and variant AIP proteins were used for pull-down/quantitative mass spectrometry experiments against lysates of rat somatotropinoma-derived cells; relevant findings were validated by co-immunoprecipitation and co-localization. Global gene expression was studied in AIP mutation positive and negative pituitary adenomas via RNA microarrays. Direct interaction with AIP was confirmed for three known and six novel partner proteins. Novel interactions with HSPA5 and HSPA9, together with known interactions with HSP90AA1, HSP90AB1 and HSPA8, indicate that the function/stability of multiple chaperone client proteins could be perturbed by a deficient AIP co-chaperone function. Interactions with TUBB, TUBB2A, NME1 and SOD1 were also identified. The AIP variants p.R304* and p.R304Q showed impaired interactions with HSPA8, HSP90AB1, NME1 and SOD1; p.R304* also displayed reduced binding to TUBB and TUBB2A, and AIP-mutated tumors showed reduced TUBB2A expression. Our findings suggest that cytoskeletal organization, cell motility/adhesion, as well as oxidative stress responses, are functions that are likely to be involved in the tumor suppressor activity of AIP.

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          Most cited references 137

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          The basics of epithelial-mesenchymal transition.

          The origins of the mesenchymal cells participating in tissue repair and pathological processes, notably tissue fibrosis, tumor invasiveness, and metastasis, are poorly understood. However, emerging evidence suggests that epithelial-mesenchymal transitions (EMTs) represent one important source of these cells. As we discuss here, processes similar to the EMTs associated with embryo implantation, embryogenesis, and organ development are appropriated and subverted by chronically inflamed tissues and neoplasias. The identification of the signaling pathways that lead to activation of EMT programs during these disease processes is providing new insights into the plasticity of cellular phenotypes and possible therapeutic interventions.
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            UniProt: a hub for protein information

            UniProt is an important collection of protein sequences and their annotations, which has doubled in size to 80 million sequences during the past year. This growth in sequences has prompted an extension of UniProt accession number space from 6 to 10 characters. An increasing fraction of new sequences are identical to a sequence that already exists in the database with the majority of sequences coming from genome sequencing projects. We have created a new proteome identifier that uniquely identifies a particular assembly of a species and strain or subspecies to help users track the provenance of sequences. We present a new website that has been designed using a user-experience design process. We have introduced an annotation score for all entries in UniProt to represent the relative amount of knowledge known about each protein. These scores will be helpful in identifying which proteins are the best characterized and most informative for comparative analysis. All UniProt data is provided freely and is available on the web at http://www.uniprot.org/.
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              Probability-based protein identification by searching sequence databases using mass spectrometry data

              Several algorithms have been described in the literature for protein identification by searching a sequence database using mass spectrometry data. In some approaches, the experimental data are peptide molecular weights from the digestion of a protein by an enzyme. Other approaches use tandem mass spectrometry (MS/MS) data from one or more peptides. Still others combine mass data with amino acid sequence data. We present results from a new computer program, Mascot, which integrates all three types of search. The scoring algorithm is probability based, which has a number of advantages: (i) A simple rule can be used to judge whether a result is significant or not. This is particularly useful in guarding against false positives. (ii) Scores can be compared with those from other types of search, such as sequence homology. (iii) Search parameters can be readily optimised by iteration. The strengths and limitations of probability-based scoring are discussed, particularly in the context of high throughput, fully automated protein identification.
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                Author and article information

                Journal
                Oncotarget
                Oncotarget
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                6 February 2018
                11 January 2018
                : 9
                : 10
                : 9177-9198
                Affiliations
                1 Centre for Endocrinology, Barts and The London School of Medicine, Queen Mary University of London, London, EC1M 6BQ, UK
                2 Genome Damage and Stability Centre, University of Sussex, Brighton, Falmer, BN1 9RQ, UK
                3 Centre for Microvascular Research, Barts and The London School of Medicine, Queen Mary University of London, London, EC1M 6BQ, UK
                4 Present address: Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, MD 20892-1862, USA
                5 Present address: Protein Crystallography Facility, Centre for Structural Biology, Flowers Building, Department of Life Sciences, Imperial College London, London, SW7 2AZ, UK
                Author notes
                Correspondence to: Márta Korbonits, m.korbonits@ 123456qmul.ac.uk
                Article
                24183
                10.18632/oncotarget.24183
                5823669
                29507682
                Copyright: © 2018 Hernández-Ramírez et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Categories
                Research Paper

                Oncology & Radiotherapy

                aip, co-chaperone, quantitative mass spectrometry, acromegaly, fipa

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