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Kinome-wide decoding of network-attacking mutations rewiring cancer signaling.

Creixell P, Schoof EM, Simpson CD, Longden J, Miller CJ, Lou HJ, Perryman L, Cox TR, Zivanovic N, Palmeri A, Wesolowska-Andersen A, Helmer-Citterich M, Ferkinghoff-Borg J, Itamochi H, Bodenmiller B, Erler JT, Turk BE, Linding R - Cell (2015)

Bottom Line: However, global analysis of these events is currently limited.Here, we identify six types of network-attacking mutations (NAMs), including changes in kinase and SH2 modulation, network rewiring, and the genesis and extinction of phosphorylation sites.We identified and experimentally validated several NAMs, including PKCγ M501I and PKD1 D665N, which encode specificity switches analogous to the appearance of kinases de novo within the kinome.

View Article: PubMed Central - PubMed

Affiliation: Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark.

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Related in: MedlinePlus

Evidence and Model for Functional Mutations and Tumor-Specific Network Medicine(A) The functional mutations found in this study are clear examples of single amino acid mutations that can severely perturb signaling networks.(B) Our study shows how non-recurrent cancer mutations on non-conserved residues can be functionally important and that functional recurrent (orange) and non-recurrent (red) NAMs can converge at the signaling network level. We also identified a case where a functional mutation in a low-abundant protein is accompanied by its overexpression.(C) The deployment of tools like ReKINect should enable the proposition of more refined signaling mechanisms underlying cellular cancer phenotypes and identification of driver and therapeutically relevant mutations.
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fig7: Evidence and Model for Functional Mutations and Tumor-Specific Network Medicine(A) The functional mutations found in this study are clear examples of single amino acid mutations that can severely perturb signaling networks.(B) Our study shows how non-recurrent cancer mutations on non-conserved residues can be functionally important and that functional recurrent (orange) and non-recurrent (red) NAMs can converge at the signaling network level. We also identified a case where a functional mutation in a low-abundant protein is accompanied by its overexpression.(C) The deployment of tools like ReKINect should enable the proposition of more refined signaling mechanisms underlying cellular cancer phenotypes and identification of driver and therapeutically relevant mutations.

Mentions: While a large fraction of recurrent and/or conserved mutations can directly or indirectly be considered NAMs as they typically perturb signaling networks (as exemplified here with BRAF V600E) and they typically operate as functional driver mutations, in this study we have demonstrated that non-recurrent and non-conserved mutations also can be functional NAMs (Figure 7B). This may be most evident from the observation that downstream rewiring mutations can lead to a switch of specificity of a comparable magnitude to the specificity difference between two distinct kinases in the human kinome. Thus, despite the fact that previous studies of cancer mutations, including some on kinase domains, have disregarded non-recurrent variants as being non-functional passenger mutations (Greenman et al., 2007), our results suggest that many of these do indeed have a functional role. Still, pinning down the actual contribution of these less frequent yet functional mutations, or combinations thereof, and under which context they drive oncogenesis will require a concerted research effort by both the genomics and signaling communities. If we move from a perception of oncogenes and tumor-suppressors operating in isolation to drive oncogenesis, toward a new paradigm, where numerous mutations play a driving role under specific cellular contexts (e.g., when appearing in combination with other mutations) (Creixell et al., 2012a, Wu et al., 2010), it will be important to acknowledge that it is likely that several of these functional NAMs drive cancer in a concerted fashion.


Kinome-wide decoding of network-attacking mutations rewiring cancer signaling.

Creixell P, Schoof EM, Simpson CD, Longden J, Miller CJ, Lou HJ, Perryman L, Cox TR, Zivanovic N, Palmeri A, Wesolowska-Andersen A, Helmer-Citterich M, Ferkinghoff-Borg J, Itamochi H, Bodenmiller B, Erler JT, Turk BE, Linding R - Cell (2015)

Evidence and Model for Functional Mutations and Tumor-Specific Network Medicine(A) The functional mutations found in this study are clear examples of single amino acid mutations that can severely perturb signaling networks.(B) Our study shows how non-recurrent cancer mutations on non-conserved residues can be functionally important and that functional recurrent (orange) and non-recurrent (red) NAMs can converge at the signaling network level. We also identified a case where a functional mutation in a low-abundant protein is accompanied by its overexpression.(C) The deployment of tools like ReKINect should enable the proposition of more refined signaling mechanisms underlying cellular cancer phenotypes and identification of driver and therapeutically relevant mutations.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4644236&req=5

fig7: Evidence and Model for Functional Mutations and Tumor-Specific Network Medicine(A) The functional mutations found in this study are clear examples of single amino acid mutations that can severely perturb signaling networks.(B) Our study shows how non-recurrent cancer mutations on non-conserved residues can be functionally important and that functional recurrent (orange) and non-recurrent (red) NAMs can converge at the signaling network level. We also identified a case where a functional mutation in a low-abundant protein is accompanied by its overexpression.(C) The deployment of tools like ReKINect should enable the proposition of more refined signaling mechanisms underlying cellular cancer phenotypes and identification of driver and therapeutically relevant mutations.
Mentions: While a large fraction of recurrent and/or conserved mutations can directly or indirectly be considered NAMs as they typically perturb signaling networks (as exemplified here with BRAF V600E) and they typically operate as functional driver mutations, in this study we have demonstrated that non-recurrent and non-conserved mutations also can be functional NAMs (Figure 7B). This may be most evident from the observation that downstream rewiring mutations can lead to a switch of specificity of a comparable magnitude to the specificity difference between two distinct kinases in the human kinome. Thus, despite the fact that previous studies of cancer mutations, including some on kinase domains, have disregarded non-recurrent variants as being non-functional passenger mutations (Greenman et al., 2007), our results suggest that many of these do indeed have a functional role. Still, pinning down the actual contribution of these less frequent yet functional mutations, or combinations thereof, and under which context they drive oncogenesis will require a concerted research effort by both the genomics and signaling communities. If we move from a perception of oncogenes and tumor-suppressors operating in isolation to drive oncogenesis, toward a new paradigm, where numerous mutations play a driving role under specific cellular contexts (e.g., when appearing in combination with other mutations) (Creixell et al., 2012a, Wu et al., 2010), it will be important to acknowledge that it is likely that several of these functional NAMs drive cancer in a concerted fashion.

Bottom Line: However, global analysis of these events is currently limited.Here, we identify six types of network-attacking mutations (NAMs), including changes in kinase and SH2 modulation, network rewiring, and the genesis and extinction of phosphorylation sites.We identified and experimentally validated several NAMs, including PKCγ M501I and PKD1 D665N, which encode specificity switches analogous to the appearance of kinases de novo within the kinome.

View Article: PubMed Central - PubMed

Affiliation: Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark.

Show MeSH
Related in: MedlinePlus