Identification of genetic markers with synergistic survival effect in cancer

Abstract

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

Synergistic markers based on inter-covariate association estimate treatment option with lower propensity to covariates

“…It avoids the curse of dimensionality and overfitting problem caused by parametric model. In the training process, the original treatment option is replaced by the synergistic markers’ estimate that can impose the genuine treatment effect in the outcome prediction model ( 10 ).…”

InCoB2013 introduces Systems Biology as a major conference theme

“…Two literature mining contributions introduced new tools in support of understanding pathway and disease relationships. PathNER [ 6 ] detects pathway names mentioned in the literature in context of a particular disease [ 7 ] whereas GenoMesh [ 8 ] predicts microbial gene relationships and genome-wide networks using similarity and dissimilarity functions [ 9 ]. The utility and impact of PathNER garnered the authors the InCoB Best Paper Award among manuscripts accepted for this supplement issue.…”