Abstract
The identification of biologically significant variants in cancer genomes is critical to therapeutic discovery, but it is limited by the statistical power needed to discern driver from passenger. Independent biological data can be used to filter cancer exomes and increase statistical power. Large genetic databases for inherited diseases are uniquely suited to this task because they contain specific amino acid alterations with known pathogenicity and molecular mechanisms. However, no rigorous method to overlay this information onto the cancer exome exists. Here, we present a computational methodology that overlays any variant database onto the somatic mutations in all cancer exomes. We validate the computation experimentally and identify novel associations in a re-analysis of 7362 cancer exomes. This analysis identified activating SOS1 mutations associated with Noonan syndrome as significantly altered in melanoma and the first kinase-activating mutations in ACVR1 associated with adult tumors. Beyond a filter, significant variants found in both rare cancers and rare inherited diseases increase the unmet medical need for therapeutics that target these variants and may bootstrap drug discovery efforts in orphan indications.
| Original language | English (US) |
|---|---|
| Article number | e1006081 |
| Journal | PLoS genetics |
| Volume | 12 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 2016 |
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All Science Journal Classification (ASJC) codes
- Ecology, Evolution, Behavior and Systematics
- Molecular Biology
- Genetics
- Genetics(clinical)
- Cancer Research
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Inherited Disease Genetics Improves the Identification of Cancer-Associated Genes. / Zhao, Boyang; Pritchard, Justin R.
In: PLoS genetics, Vol. 12, No. 6, e1006081, 06.2016.Research output: Contribution to journal › Article
TY - JOUR
T1 - Inherited Disease Genetics Improves the Identification of Cancer-Associated Genes
AU - Zhao, Boyang
AU - Pritchard, Justin R.
PY - 2016/6
Y1 - 2016/6
N2 - The identification of biologically significant variants in cancer genomes is critical to therapeutic discovery, but it is limited by the statistical power needed to discern driver from passenger. Independent biological data can be used to filter cancer exomes and increase statistical power. Large genetic databases for inherited diseases are uniquely suited to this task because they contain specific amino acid alterations with known pathogenicity and molecular mechanisms. However, no rigorous method to overlay this information onto the cancer exome exists. Here, we present a computational methodology that overlays any variant database onto the somatic mutations in all cancer exomes. We validate the computation experimentally and identify novel associations in a re-analysis of 7362 cancer exomes. This analysis identified activating SOS1 mutations associated with Noonan syndrome as significantly altered in melanoma and the first kinase-activating mutations in ACVR1 associated with adult tumors. Beyond a filter, significant variants found in both rare cancers and rare inherited diseases increase the unmet medical need for therapeutics that target these variants and may bootstrap drug discovery efforts in orphan indications.
AB - The identification of biologically significant variants in cancer genomes is critical to therapeutic discovery, but it is limited by the statistical power needed to discern driver from passenger. Independent biological data can be used to filter cancer exomes and increase statistical power. Large genetic databases for inherited diseases are uniquely suited to this task because they contain specific amino acid alterations with known pathogenicity and molecular mechanisms. However, no rigorous method to overlay this information onto the cancer exome exists. Here, we present a computational methodology that overlays any variant database onto the somatic mutations in all cancer exomes. We validate the computation experimentally and identify novel associations in a re-analysis of 7362 cancer exomes. This analysis identified activating SOS1 mutations associated with Noonan syndrome as significantly altered in melanoma and the first kinase-activating mutations in ACVR1 associated with adult tumors. Beyond a filter, significant variants found in both rare cancers and rare inherited diseases increase the unmet medical need for therapeutics that target these variants and may bootstrap drug discovery efforts in orphan indications.
UR - http://www.scopus.com/inward/record.url?scp=84977516398&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84977516398&partnerID=8YFLogxK
U2 - 10.1371/journal.pgen.1006081
DO - 10.1371/journal.pgen.1006081
M3 - Article
C2 - 27304678
AN - SCOPUS:84977516398
VL - 12
JO - PLoS Genetics
JF - PLoS Genetics
SN - 1553-7390
IS - 6
M1 - e1006081
ER -