J Integr Bioinform - Integrating protein-protein interaction networks with gene-gene co-expression networks improves gene signatures for classifying breast cancer metastasis.

Tópicos

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Resumo

Multiple studies have illustrated that gene expression profiling of primary breast cancers throughout the final stages of tumor development can provide valuable markers for risk prediction of metastasis and disease sub typing. However, the identification of a biologically interpretable and universally shared set of markers proved to be difficult. Here, we propose a method for de novo grouping of genes by dissecting the protein-protein interaction network into disjoint sub networks using pair wise gene expression correlation measures. We show that the obtained sub networks are functionally coherent and are consistently identified when applied on a compendium composed of six different breast cancer studies. Application of the proposed method using different integration approaches underlines the robustness of the identified sub network related to cell cycle and identifies putative new sub network markers for metastasis related to cell-cell adhesion, the proteasome complex and JUN-FOS signalling. Although gene selection with the proposed method does not directly improve upon previously reported cross study classification performances, it shows great promises for applications in data integration and result interpretation.

Resumo Limpo

multipl studi illustr gene express profil primari breast cancer throughout final stage tumor develop can provid valuabl marker risk predict metastasi diseas sub type howev identif biolog interpret univers share set marker prove difficult propos method de novo group gene dissect proteinprotein interact network disjoint sub network use pair wise gene express correl measur show obtain sub network function coher consist identifi appli compendium compos six differ breast cancer studi applic propos method use differ integr approach underlin robust identifi sub network relat cell cycl identifi putat new sub network marker metastasi relat cellcel adhes proteasom complex junfo signal although gene select propos method direct improv upon previous report cross studi classif perform show great promis applic data integr result interpret

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