SIMULATION STUDY OF NONLINEAR PLASMA MASER

Plasma maser is a new nonlinear process in plasma turbulence which coexists with the quasilinear process between electrons and the resonant mode. Since the prediction of the process [1], it attracted much attention because multi-modes turbulence which contains enhanced high frequency fluctuations in addition to low frequency turbulence are quite often observed in laboratory and astropysical plasma

Network-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression

Motivation: A rapid progression of esophageal squamous cell carcinoma (ESCC) causes a high mortality rate because of the propensity for metastasis driven by genetic and epigenetic alterations. The identification of prognostic biomarkers would help prevent or control metastatic progression. Expression analyses have been used to find such markers, but do not always validate in separate cohorts. Epigenetic marks, such as DNA methylation, are a potential source of more reliable and stable biomarkers. Importantly, the integration of both expression and epigenetic alterations is more likely to identify relevant biomarkers. Results: We present a new analysis framework, using ESCC progression-associated gene regulatory network (GRN(escc)), to identify differentially methylated CpG sites prognostic of ESCC progression. From the CpG loci differentially methylated in 50 tumor–normal pairs, we selected 44 CpG loci most highly associated with survival and located in the promoters of genes more likely to belong to GRN(escc). Using an independent ESCC cohort, we confirmed that 8/10 of CpG loci in the promoter of GRN(escc) genes significantly correlated with patient survival. In contrast, 0/10 CpG loci in the promoter genes outside the GRN(escc) were correlated with patient survival. We further characterized the GRN(escc) network topology and observed that the genes with methylated CpG loci associated with survival deviated from the center of mass and were less likely to be hubs in the GRN(escc). We postulate that our analysis framework improves the identification of bona fide prognostic biomarkers from DNA methylation studies, especially with partial genome coverage. Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online