TCGA-LGG

TCGA-LGG analyzes the prognostic significance of Engrailed 1 (EN1) overexpression in lower grade glioma (LGG) by integrating TCGA and GEO (GSE16011) datasets to correlate EN1 expression with patient survival and clinicopathological features.

Key Features:

• Data Sources: Integrates 530 LGG cases from TCGA and 273 glioma cases from GSE16011 (GEO).
• Classification: Classifies LGG patients by histopathological subtype, IDH1 mutation status, and 1p19q co-deletion status.
• Statistical Analysis: Applies Cox regression across 13 cancer types with a focused analysis on LGG to evaluate the impact of EN1 expression on survival.
• Survival Analysis: Generates Kaplan-Meier survival curves to correlate EN1 expression levels with clinicopathological characteristics and overall survival (OS) times.

Scientific Applications:

• Prognostic Marker Identification: High EN1 expression is associated with significantly shorter 5-, 10-, and 15-year overall survival (OS) in LGG patients irrespective of IDH1 mutation or 1p19q co-deletion status.
• Subtype Analysis: Identifies the astrocytoma subgroup as exhibiting the highest EN1 expression and the shortest survival times compared to oligoastrocytoma and oligodendroglioma.

Methodology:

Data mining using OncoLnc for initial coefficient analysis; bioinformatic analyses via R2 and the UCSC Xena browser; Cox regression and Kaplan-Meier survival analysis; statistical significance assessed with false discovery rate (FDR) correction.