Genome wide in silico SNP-tumor association analysis.
BACKGROUND
Carcinogenesis occurs, at least in part, due to the accumulation of mutations in critical genes that control the mechanisms of cell proliferation, differentiation and death. Publicly accessible databases contain millions of expressed sequence tag (EST) and single nucleotide polymorphism (SNP) records, which have the potential to assist in the identification of SNPs overrepresented in tumor tissue.


METHODS
An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106).


RESULTS
A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigation


CONCLUSIONS
This novel in silico approach can assist in prioritization of genes and SNPs in the effort to elucidate the genetic mechanisms underlying the development of cancer.
Bioinformatics Group and Discovery Technology Department at Schering-Plough Research Institute, 2015 Galloping Hill Road, Kenilworth, New Jersey 07033, USA. ping.qiu@spcorp.com
Ping
P
Qiu
Luquan
L
Wang
Mitch
M
Kostich
Wei
W
Ding
Jason S
JS
Simon
Jonathan R
JR
Greene
D030541:Databases, Genetic; D020224:Expressed Sequence Tags; D005787:Gene Frequency; D009317:National Library of Medicine (U.S.); D009369:Neoplasms / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D014481:United States