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BMC Syst Biol. 2013;7 Suppl 1:S2. doi: 10.1186/1752-0509-7-S1-S2. Epub 2013 Aug 12.

Identification of genetic markers with synergistic survival effect in cancer.

Abstract

BACKGROUND:

Cancers are complex diseases arising from accumulated genetic mutations that disrupt intracellular signaling networks. While several predisposing genetic mutations have been found, these individual mutations account only for a small fraction of cancer incidence and mortality. With large-scale measurement technologies, such as single nucleotide polymorphism (SNP) microarrays, it is now possible to identify combinatorial effects that have significant impact on cancer patient survival.

RESULTS:

The identification of synergetic functioning SNPs on genome-scale is a computationally daunting task and requires advanced algorithms. We introduce a novel algorithm, Geninter, to identify SNPs that have synergetic effect on survival of cancer patients. Using a large breast cancer cohort we generate a simulator that allows assessing reliability and accuracy of Geninter and logrank test, which is a standard statistical method to integrate genetic and survival data.

CONCLUSIONS:

Our results show that Geninter outperforms the logrank test and is able to identify SNP-pairs with synergetic impact on survival.

PMID:
24267921
PMCID:
PMC3750540
DOI:
10.1186/1752-0509-7-S1-S2
[Indexed for MEDLINE]
Free PMC Article
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