Identification of Gender-Specific Molecular Differences in Glioblastoma (GBM) and Low-Grade Glioma (LGG) by the Analysis of Large Transcriptomic and Epigenomic Datasets

Differences in the incidence and outcome of glioma between males and females are well known, being more striking for glioblastoma (GB) than low-grade glioma (LGG). The extensive and well-annotated data in publicly available databases enable us to analyze the molecular basis of these differences at a global level. Here, we have analyzed The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases to identify molecular indicators for these gender-based differences by different methods. Based on the nature of data available/accessible, the transcriptomic profile was studied in TCGA by using DeSeq2 and in CGGA by T-test, after correction based. Only IDH1 wild-type tumors were studied in CGGA. Using weighted gene co-expression network analysis (WGCNA), network analysis was done, followed by the assessment of modular differential connectivity. Differentially affected signaling pathways were identified. The gender-based effects of differentially expressed genes on survival were determined. DNA methylation was studied as an indicator of gender-based epigenetic differences. The results clearly showed gender-based differences in both GB and LGG, whatever method or database was used. While there were differences in the results obtained between databases and methods used, some major signaling pathways such as Wnt signaling and pathways involved in immune processes and the adaptive immune response were common to different assessments. There was also a differential gende...
Source: Frontiers in Oncology - Category: Cancer & Oncology Source Type: research