Genomics and Prognosis Analysis of Epithelial-Mesenchymal Transition in Glioma

Frontiers in Oncology
Chuming TaoXingen Zhu

Abstract

Background: Epithelial-mesenchymal transition (EMT) is regulated by induction factors, transcription factor families and an array of signaling pathways genes, and has been implicated in the invasion and progression of gliomas. Methods: We obtained the Clinicopathological data sets from Chinese Glioma Genome Atlas (CGGA). The "limma" package was used to analyze the expression of EMT-related genes in gliomas with different pathological characteristics. We used the "ConsensusClusterPlus" package to divide gliomas into two groups to study their correlation with glioma malignancy. The least absolute shrinkage and selection operator (LASSO) Cox regression was applied to select seven prognosis-associated genes to build the risk signature, and the coefficients obtained from the LASSO algorithm were used to calculate the risk score which we applied to determine the prognostic value of the risk signature. Univariate and multivariate Cox regression analyses were used to determine whether the risk signature is an independent prognostic indicator. Results: We analyzed the differentially expressed 22 common epithelial-mesenchymal transition-associated genes in 508 gliomas graded by different clinicopathological features. Two glioma subgroups...Continue Reading

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Citations

Nov 27, 2020·Frontiers in Cell and Developmental Biology·Shengchao XuZhixiong Liu
Nov 17, 2020·Frontiers in Endocrinology·Sarah WhitbyEvdokia Dimitriadis
May 4, 2021·Journal of Oncology·Anna Maria ReussNicolai Savaskan
Jun 3, 2021·International Journal of Molecular Sciences·Anna Maria ReussNicolai Savaskan
Sep 7, 2021·Frontiers in Bioengineering and Biotechnology·Ke XueJian Wan

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Methods Mentioned

BETA
PCA

Software Mentioned

Oncomine
LASSO
R
Prism
SPSS
R package
GSEA
GraphPad
ConsensusClusterPlus

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