Aims: The p53 regulatory network is crucial in directing the suppression of cancer formation and mediating the response to commonly used cancer therapies. Functional genetic variants in the genes comprising this network could help identify individuals at greater risk for cancer and patients with poorer responses to therapies, but few such variants have been identified as yet. Methods: We first develop and apply three different screens that utilize known characteristics of functional single nucleotide polymorphisms (SNPs) in the p53 network to search for variants that associate with allelic differences in (i) recent natural selection, (ii) chemosensitivity profiles, and (iii) the gender- and age- dependent incidence of soft-tissue sarcoma. Secondly, we study and explore the functional mechanisms associated with the identified variants. Results: We identify SNPs in the PPP2R5E, CD44, YWHAQ and ESR1 genes that associate with allelic differences in the age of tumour diagnosis (up to 32.5 years, p=0.031), cancer risk (up to 8.1 odds ratio, p=0.004) and overall survival (up to 2.85 relative risk, p=0.011) in sarcomas, ovarian and pancreatic cancers, and exhibit allelic differences in the cellular responses to cytotoxic chemotherapeutic agents (up to 5.4-fold, p=5.6x10<sup>-47</sup>). Lastly, we identify candidate causal SNPs in those genes and describe the regulatory mechanisms by which they might affect human cancer. Conclusions: Together, our work suggests that the inherited genetics of the p53 pathway have a great potential to further define populations in their abilities to react to stress, suppress tumor formation and respond to therapies.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:558392 |
| Date | January 2011 |
| Creators | Grochola, Lukasz Filip |
| Contributors | Bond, Gareth |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:aacc7084-81a8-4e97-b1ac-024d9bed106e |
Page generated in 0.0027 seconds