Multi-omics analysis identifies novels genes involved in glioma prognosis

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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 states as prognostic factors beyond genetic markers, i.e. IDH1 or PTEN gene mutations, was validated externally. Among the 178 prognostic genes, we validated roles in gliomas for 121 genes from previous literature, and more importantly, we identified 67 novel candidate genes for glioma research. Expression of these 178 genes was particularly pronounced during fetal development in various brain regions. Our findings provide clues for understanding glioma prognosis and highlight some novel glioma-associated genes that warrant further investigation.
Funding Information
  • National Natural Science Foundation of China (32070661)

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