Ferkingstad Egil, Frigessi Arnoldo, Lyng Heidi
Department of Biostatistics and (sfi) Statistics for Innovation, University of Oslo, Gaustadalleen, Oslo, NO-0314, Norway.
Genome Biol. 2008;9(3):R58. doi: 10.1186/gb-2008-9-3-r58. Epub 2008 Mar 22.
In cancer, genes may have indirect effects on patient survival, mediated through interactions with other genes. Methods to study the indirect effects that contribute significantly to survival are not available. We propose a novel methodology to detect and quantify indirect effects from gene expression data. We discover indirect effects through several target genes of transcription factors in cancer microarray data, pointing to genetic interactions that play a significant role in tumor progression.
在癌症中,基因可能通过与其他基因的相互作用对患者生存产生间接影响。目前尚无研究对生存有显著贡献的间接影响的方法。我们提出了一种新方法,用于从基因表达数据中检测和量化间接影响。我们通过癌症微阵列数据中转录因子的几个靶基因发现了间接影响,这表明基因相互作用在肿瘤进展中发挥着重要作用。