Multi-omics analysis identifies novels genes involved in glioma prognosis.

ABSTRACT: Gliomas have highly variable clinical outcomes that are not adequately predicted on the basis of histologic class nor genetic markers. We performed a comprehensive analysis that integrated multi-omics datasets to elucidate factors influencing glioma prognosis. We detected 17 grade-related genes different in expression between LGG and GBM cohorts. By combining multi-layer information including genetic markers, DNA methylation and gene expression, we constructed two gene networks of relations from the grade-related genes. From the networks, we identified 178 prognostic genes whose activity states, in terms of DNA methylation and gene expression level, are relevant to prognostic outcomes of gliomas, with low activity associated with better outcomes. The efficacy of these 178 genes' activity s

SUBMITTER: Li Y 

PROVIDER: S-EPMC11833133 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature