title: A DNA methylation network interaction measure, and detection of network oncomarkers.
abstract: Epigenetic processes--including DNA methylation--are increasingly seen as having a fundamental role in chronic diseases like cancer. DNA methylation patterns offer a route to develop prognostic measures based directly on DNA measurements, rather than less-stable RNA measurements. A novel DNA methylation-based measure of the co-ordinated interactive behaviour of genes is developed, in a network context. It is shown that this measure reflects well the co-regulatory behaviour linked to gene expression (at the mRNA level) over the same network interactions. This measure, defined for pairs of genes in a single patient/sample, associates with overall survival outcome independent of known prognostic clinical features, in several independent data sets relating to different cancer types. In total, more than half a billion CpGs in over 1600 samples, taken from nine different cancer entities, are analysed. It is found that groups of gene-pair interactions which associate significantly with survival identify statistically significant subnetwork modules. Many of these subnetwork modules are shown to be biologically relevant by strong correlation with pre-defined gene sets, such as immune function, wound healing, mitochondrial function and MAP-kinase signalling. In particular, the wound healing module corresponds to an increase in co-ordinated interactive behaviour between genes for worse prognosis, and the immune module corresponds to a decrease in co-ordinated interactive behaviour between genes for worse prognosis. This measure has great potential for defining DNA-based cancer biomarkers. Such biomarkers could naturally be developed further, by drawing on the rapidly expanding knowledge base of network science.
authors.affiliation: Department of Mathematics, University College London, London, United Kingdom ; CoMPLEX, University College London, London, United Kingdom.
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Bartlett
authors.affiliation: Department of Statistical Science, University College London, London, United Kingdom ; CoMPLEX, University College London, London, United Kingdom.
authors.forename: Sofia C
authors.initials: SC
authors.lastname: Olhede
authors.affiliation: Department of Mathematics, University College London, London, United Kingdom.
authors.forename: Alexey
authors.initials: A
authors.lastname: Zaikin
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics*; D019295:Computational Biology / Q000379:methods; D019175:DNA Methylation; D004843:Epistasis, Genetic; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000235:genetics / Q000401:mortality; D011379:Prognosis
chemical_list: D014408:Biomarkers, Tumor