Chapter title |
Proteostasis
|
---|---|
Chapter number | 2 |
Book title |
Proteostasis
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3756-1_2 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3754-7, 978-1-4939-3756-1
|
Authors |
Carvalho, Ana Sofia, Rodríguez, Manuel S, Matthiesen, Rune, Ana Sofia Carvalho, Manuel S. Rodríguez, Rune Matthiesen |
Editors |
Rune Matthiesen |
Abstract |
Automatic analysis of increasingly growing literature repositories including data integration to other databases is a powerful tool to propose hypothesis that can be used to plan experiments to validate or disprove the hypothesis. Furthermore, it provides means to evaluate the redundancy of research line in comparison to the published literature. This is potentially beneficial for those developing research in a specific disease which are interested in exploring a particular pathway or set of genes/proteins. In the scope of the integrating book a case will be made addressing proteostasis factors in cancer. The maintenance of proteome homeostasis, known as proteostasis, is a process by which cells regulate protein translation, degradation, subcellular localization, and protein folding and consists of an integrated network of proteins. The ubiquitin-proteasome system plays a key role in essential biological processes such as cell cycle, DNA damage repair, membrane trafficking, and maintaining protein homeostasis. Cells maintain proteostasis by regulating protein translation, degradation, subcellular localization, and protein folding. Aberrant proteostasis leads to loss-of-function diseases (cystic fibrosis) and gain-of-toxic-function diseases (Alzheimer's, Parkinson's, and Huntington's disease). Cancer therapy on the other hand explores inhibition of proteostasis factors to trigger endoplasmic reticulum stress with subsequent apoptosis. Alternatively therapies target deubiquitinases and thereby regulate tumor promoters or suppressors. Furthermore, mutations in specific proteostasis factors are associated with higher risk for specific cancers, e.g., BRCA mutations in breast cancer. This chapter discusses proteostasis protein factors' association with cancer from a literature mining perspective. |
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