Pathway: Paradoxical activation of RAF signaling by kinase inactive BRAF
Reactions in pathway: Paradoxical activation of RAF signaling by kinase inactive BRAF :
Paradoxical activation of RAF signaling by kinase inactive BRAF
While BRAF-specific inhibitors inhibit MAPK/ERK activation in the presence of the BRAF V600E mutant, paradoxical activation of ERK signaling has been observed after treatment of cells with inhibitor in the presence of WT BRAF (Wan et al, 2004; Garnett et al, 2005; Heidorn et al, 2010; Hazivassiliou et al, 2010; Poulikakos et al, 2010). This paradoxical ERK activation is also seen in cells expressing kinase-dead or impaired versions of BRAF such as D594V, which occur with low frequency in some cancers (Wan et al, 2004; Heidorn et al, 2010). Unlike BRAF V600E, which occurs exclusively of activating RAS mutations, kinase-impaired versions of BRAF are coincident with RAS mutations in human cancers, and indeed, paradoxical activation of ERK signaling in the presence of inactive BRAF is enhanced in the presence of oncogenic RAS (Heidorn et al, 2010; reviewed in Holderfield et al, 2014). Although the details remain to be worked out, paradoxical ERK activation in the presence of inactive BRAF appears to rely on enhanced dimerization with and transactivation of CRAF (Heidorn et al, 2010; Hazivassiliou et al, 2010; Poulikakos et al, 2010; Roring et al, 2012; Rajakulendran et al, 2009; Holderfield et al, 2013; Freeman et al, 2013; reviewed in Roskoski, 2010; Samatar and Poulikakos, 2014; Lavoie and Therrien, 2015). RAF inhibitors can promote association of RAF-RAS interaction and enhanced RAF dimerization through disruption of intramolecular interactions between the kinase domain and its N-terminal regulatory region. Moreover, specific BRAF inhibitors can only occupy one protomer within the transcactivated BRAF dimer due to negative co-operativity leading to paradoxical ERK activation. (Karoulia et al, 2016; Jin et al, 2017, reviewed in Karoulia et al, 2017).
Signaling processes are central to human physiology (e.g., Pires-da Silva & Sommer 2003), and their disruption by either germ-line and somatic mutation can lead to serious disease. Here, the molecular consequences of mutations affecting visual signal transduction and signaling by diverse growth factors are annotated.
Biological processes are captured in Reactome by identifying the molecules (DNA, RNA, protein, small molecules) involved in them and describing the details of their interactions. From this molecular viewpoint, human disease pathways have three mechanistic causes: the inclusion of microbially-expressed proteins, altered functions of human proteins, or changed expression levels of otherwise functionally normal human proteins.
The first group encompasses the infectious diseases such as influenza, tuberculosis and HIV infection. The second group involves human proteins modified either by a mutation or by an abnormal post-translational event that produces an aberrant protein with a novel function. Examples include somatic mutations of EGFR and FGFR (epidermal and fibroblast growth factor receptor) genes, which encode constitutively active receptors that signal even in the absence of their ligands, or the somatic mutation of IDH1 (isocitrate dehydrogenase 1) that leads to an enzyme active on 2-oxoglutarate rather than isocitrate, or the abnormal protein aggregations of amyloidosis which lead to diseases such as Alzheimer's.
Infectious diseases are represented in Reactome as microbial-human protein interactions and the consequent events. The existence of variant proteins and their association with disease-specific biological processes is represented by inclusion of the modified protein in a new or variant reaction, an extension to the 'normal' pathway. Diseases which result from proteins performing their normal functions but at abnormal rates can also be captured, though less directly. Many mutant alleles encode proteins that retain their normal functions but have abnormal stabilities or catalytic efficiencies, leading to normal reactions that proceed to abnormal extents. The phenotypes of such diseases can be revealed when pathway annotations are combined with expression or rate data from other sources.
Depending on the biological pathway/process immediately affected by disease-causing gene variants, non-infectious diseases in Reactome are organized into diseases of signal transduction by growth factore receptors and second messengers, diseases of mitotic cell cycle, diseases of cellular response to stress, diseases of programmed cell death, diseases of DNA repair, disorders of transmembrane transporters, diseases of metabolism, diseases of immune system, diseases of neuronal system, disorders of developmental biology, disorders of extracellular matrix organization, and diseases of hemostatis.
