Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText.
Kick-your-searchterm to multiple Engines kick-your-query now !>
A dictionary by aggregated review articles of nephrology, medicine and the life sciences
Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

suck abstract from ncbi


10.1186/s13073-016-0311-2

http://scihub22266oqcxt.onion/10.1186/s13073-016-0311-2
suck pdf from google scholar
C4864925!4864925!27175787
unlimited free pdf from europmc27175787    free
PDF from PMC    free
html from PMC    free

suck abstract from ncbi


Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
pmid27175787      Genome+Med 2016 ; 8 (ä): ä
Nephropedia Template TP

gab.com Text

Twit Text FOAVip

Twit Text #

English Wikipedia


  • Frequent mutations in acetylation and ubiquitination sites suggest novel driver mechanisms of cancer #MMPMID27175787
  • Narayan S; Bader GD; Reimand J
  • Genome Med 2016[]; 8 (ä): ä PMID27175787show ga
  • Background: Discovery of cancer drivers is a major goal of cancer research. Driver genes and pathways are often predicted using mutation frequency, assuming that statistically significant recurrence of specific somatic mutations across independent samples indicates their importance in cancer. However, many mutations, including known cancer drivers, are not observed at high frequency. Fortunately, abundant information is available about functional ?active sites? in proteins that can be integrated with mutations to predict cancer driver genes, even based on low frequency mutations. Further, considering active site information predicts detailed biochemical mechanisms impacted by the mutations. Post-translational modifications (PTMs) are active sites that are regulatory switches in proteins and pathways. We analyzed acetylation and ubiquitination, two important PTM types often involved in chromatin organization and protein degradation, to find proteins that are significantly affected by tumor somatic mutations. Methods: We performed computational analyses of acetylation and ubiquitination sites in a pan-cancer dataset of 3200 tumor samples from The Cancer Genome Atlas (TCGA). These analyses were targeted at different levels of biological organization including individual genes, pathway annotated gene sets, and protein-protein interaction networks. Results: Acetylation and ubiquitination site mutations are enriched in cancer with significantly stronger evolutionary conservation and accumulation in protein domains. Gene-focused analysis with the ActiveDriver method reveals significant co-occurrences of acetylation and ubiquitination PTMs and mutation hotspots in known oncoproteins (TP53, AKT1, IDH1) and highlights candidate cancer driver genes with PTM-related mechanisms (e.g. several histone proteins and the splicing factor SF3B1). Pathway analysis shows that PTM mutations in acetylation and ubiquitination sites accumulate in cancer-related processes such as cell cycle, apoptosis, chromatin regulation, and metabolism. Integrated mutation analysis of clinical information and protein interaction networks suggests that many PTM-specific mutations associate with decreased patient survival. Conclusions: Mutation analysis of acetylation and ubiquitination PTM sites reveals their importance in cancer. As PTM networks are increasingly mapped and related enzymes are often druggable, deeper investigation of specific associated mutations may lead to the discovery of treatment-relevant cellular mechanisms. Electronic supplementary material: The online version of this article (doi:10.1186/s13073-016-0311-2) contains supplementary material, which is available to authorized users.
  • ä


  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    Linkout box