Identification of Genetic Markers with Synergistic Survival Effect in Cancer

Riku Louhimo; Marko Laakso; Tuomas Heikkinen; Susanna Laitinen; Pekka Manninen; Vladimir Rogojin; Minna Miettinen; Carl Blomqvist; Jianjun Liu; Heli Nevanlinna; Sampsa Hautaniemi

doi:10.1186/1752-0509-7-S1-S2

Identification of Genetic Markers with Synergistic Survival Effect in Cancer

Riku Louhimo, Marko Laakso, Tuomas Heikkinen, Susanna Laitinen, Pekka Manninen, Vladimir Rogojin, Minna Miettinen, Carl Blomqvist, Jianjun Liu, Heli Nevanlinna, Sampsa Hautaniemi

Research output: Contribution to journal › Article › Scientific › peer-review

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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.

Original language	Undefined/Unknown
Pages (from-to)	–
Journal	BMC Systems Biology
Volume	7
Issue number	1
DOIs	https://doi.org/10.1186/1752-0509-7-S1-S2
Publication status	Published - 2013
MoE publication type	A1 Journal article-refereed

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10.1186/1752-0509-7-S1-S2

Cite this

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title = "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.",

author = "Riku Louhimo and Marko Laakso and Tuomas Heikkinen and Susanna Laitinen and Pekka Manninen and Vladimir Rogojin and Minna Miettinen and Carl Blomqvist and Jianjun Liu and Heli Nevanlinna and Sampsa Hautaniemi",

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TY - JOUR

T1 - Identification of Genetic Markers with Synergistic Survival Effect in Cancer

AU - Louhimo, Riku

AU - Laakso, Marko

AU - Heikkinen, Tuomas

AU - Laitinen, Susanna

AU - Manninen, Pekka

AU - Rogojin, Vladimir

AU - Miettinen, Minna

AU - Blomqvist, Carl

AU - Liu, Jianjun

AU - Nevanlinna, Heli

AU - Hautaniemi, Sampsa

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

U2 - 10.1186/1752-0509-7-S1-S2

DO - 10.1186/1752-0509-7-S1-S2

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SN - 1752-0509

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