期刊
JOURNAL OF CYSTIC FIBROSIS
卷 14, 期 6, 页码 687-699出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jcf.2015.09.006
关键词
Cystic fibrosis; Protein folding; Chaperones; Proteostasis; System biology; Bioinformatics; High-content microscopy; High-throughput screening; Mass spectrometry; Genomics; Proteomics; Epigenetics; Epiproteomics
资金
- FCT/MCTES/PIDDAC, Portugal [PTDC/SAU-GMG/122299/2010]
- center grant from FCT/MCTES, Portugal [PEst-OE/BIA/UI4046/2011]
- Cystic Fibrosis Foundation, USA
- Tobacco-Related Disease Research Program [TRDRP 23RT-0012]
- National Institute of Health (NTH) [HL079442, GM42336, DK785483]
- Cystic Fibrosis Foundation (CFF)
- Fundação para a Ciência e a Tecnologia [PTDC/SAU-GMG/122299/2010] Funding Source: FCT
The cystic fibrosis (CF) transmembrane conductance regulator (CFTR) protein does not operate in isolation, rather in a dynamic network of interacting components that impact its synthesis, folding, stability, intracellular location and function, referred to herein as the 'CFTR Functional Landscape (CFFL)'. For the prominent F508del mutation, many of these interactors are deeply connected to a protein fold management system, the proteostasis network (PN). However, CF encompasses an additional 2000 CFTR variants distributed along its entire coding sequence (referred to as CFTR2), and each variant contributes a differential liability to PN management of CFTR and to a protein 'social network' (SN) that directs the probability of the (patho)physiologic events that impact ion transport in each cell, tissue and patient in health and disease. Recognition of the importance of the PN and SN in driving the unique patient CFFL leading to disease highlights the importance of precision medicine in therapeutic management of disease progression. We take the view herein that it is not CFTR, rather the PN/SN, and their impact on the CFFL, that are the key physiologic forces driving onset and clinical progression of CF. We posit that a deep understanding of each patients PN/SN gained by merging genomic, proteomic (mass spectrometry (MS)), and high-content microscopy (HCM) technologies in the ccintext of novel network learning algorithms will lead to a paradigm shift in CF clinical management. This should allow for generation of new classes of patient specific PN/SN directed therapeutics for personalized management of the CFFL in the clinic. (C) 2015 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.
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