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Comprehensive Identification and Characterization of Human Secretome Based on Integrative Proteomic and Transcriptomic Data.
Chen, Geng; Chen, Jiwei; Liu, Huanlong; Chen, Shuangguan; Zhang, Yang; Li, Peng; Thierry-Mieg, Danielle; Thierry-Mieg, Jean; Mattes, William; Ning, Baitang; Shi, Tieliu.
Afiliação
  • Chen G; The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
  • Chen J; The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
  • Liu H; The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
  • Chen S; The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
  • Zhang Y; The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
  • Li P; The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
  • Thierry-Mieg D; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, United States.
  • Thierry-Mieg J; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, United States.
  • Mattes W; National Center for Toxicological Research, Food and Drug Administration, Jefferson City, AR, United States.
  • Ning B; National Center for Toxicological Research, Food and Drug Administration, Jefferson City, AR, United States.
  • Shi T; The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.
Front Cell Dev Biol ; 7: 299, 2019.
Article em En | MEDLINE | ID: mdl-31824949
Secreted proteins (SPs) play important roles in diverse important biological processes; however, a comprehensive and high-quality list of human SPs is still lacking. Here we identified 6,943 high-confidence human SPs (3,522 of them are novel) based on 330,427 human proteins derived from databases of UniProt, Ensembl, AceView, and RefSeq. Notably, 6,267 of 6,943 (90.3%) SPs have the supporting evidences from a large amount of mass spectrometry (MS) and RNA-seq data. We found that the SPs were broadly expressed in diverse tissues as well as human body fluid, and a significant portion of them exhibited tissue-specific expression. Moreover, 14 cancer-specific SPs that their expression levels were significantly associated with the patients' survival of eight different tumors were identified, which could be potential prognostic biomarkers. Strikingly, 89.21% of 6,943 SPs (2,927 novel SPs) contain known protein domains. Those novel SPs we mainly enriched with the known domains regarding immunity, such as Immunoglobulin V-set and C1-set domain. Specifically, we constructed a user-friendly and freely accessible database, SPRomeDB (www.unimd.org/SPRomeDB), to catalog those SPs. Our comprehensive SP identification and characterization gain insights into human secretome and provide valuable resource for future researches.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Front Cell Dev Biol Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Front Cell Dev Biol Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China