What question did this study set out to answer?

To systematically analyze proneural-to-mesenchymal transition (PMT) in glioma and establish a prognostic long non-coding RNA (lncRNA) risk signature.

October 7, 2020Journal of Translational MedicineOpen Access

Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma

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Authors

QLQingyu LiangSoochow University GGGefei GuanFirst Hospital of China Medical University XLXue LiNorth Sichuan Medical University

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Overview

Transcriptomic analysis reveals a 10-lncRNA signature linked to proneural-to-mesenchymal transition in glioma, suggesting its utility in predicting patient survival and immunosuppression.

Key Points

To systematically analyze proneural-to-mesenchymal transition (PMT) in glioma and establish a prognostic long non-coding RNA (lncRNA) risk signature.
Extracted gene expression profiles and clinical data from TCGA, CGGA, GSE16011, and Rembrandt cohorts.
Identified candidate PMT-associated lncRNAs using weighted gene co-expression network analysis (WGCNA) and built a prognostic model using LASSO and Cox regression analyses.
Identified 149 PMT-associated lncRNAs and derived a 10-lncRNA prognostic signature (including CRNDE, SNHG18, and TP73-AS1) that effectively stratified glioma cases into high- and low-risk survival groups.
Demonstrated that the 10-lncRNA signature acts as an independent prognostic factor for high-grade glioma, with high-risk status correlating with mesenchymal subtype immunosuppression and competing endogenous RNA activity.

Cite This Study

Liang et al. (2020) studied this question.

synapsesocial.com/papers/6a826b29fc3df235bc877c76 https://doi.org/10.1186/s12967-020-02552-0

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October 7, 2020Journal of Translational MedicineOpen Access

Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma

View Full Paper

Ask AI

Bookmark

Authors

QLQingyu LiangSoochow University GGGefei GuanFirst Hospital of China Medical University XLXue LiNorth Sichuan Medical University

Discussion

Member takes

Overview

Transcriptomic analysis reveals a 10-lncRNA signature linked to proneural-to-mesenchymal transition in glioma, suggesting its utility in predicting patient survival and immunosuppression.

Key Points

To systematically analyze proneural-to-mesenchymal transition (PMT) in glioma and establish a prognostic long non-coding RNA (lncRNA) risk signature.
Extracted gene expression profiles and clinical data from TCGA, CGGA, GSE16011, and Rembrandt cohorts.
Identified candidate PMT-associated lncRNAs using weighted gene co-expression network analysis (WGCNA) and built a prognostic model using LASSO and Cox regression analyses.
Identified 149 PMT-associated lncRNAs and derived a 10-lncRNA prognostic signature (including CRNDE, SNHG18, and TP73-AS1) that effectively stratified glioma cases into high- and low-risk survival groups.
Demonstrated that the 10-lncRNA signature acts as an independent prognostic factor for high-grade glioma, with high-risk status correlating with mesenchymal subtype immunosuppression and competing endogenous RNA activity.

Cite This Study

Liang et al. (2020) studied this question.

synapsesocial.com/papers/6a826b29fc3df235bc877c76 https://doi.org/10.1186/s12967-020-02552-0

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