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Updated: Oct 4, 2025
Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
Bioinformatics analysis of immune infiltration in glioblastoma multiforme based on data using a methylation chip in
Song-Zhou Du1, Cheng Chen2, Lu Qin3
1Department of Neurosurgery, Jingzhou Hospital of Traditional Chinese Medicine, The Third Clinical Medical College, Yangtze University, Jingzhou, China.
Background:
Glioblastoma multiforme (GBM) is the most aggressive and malignant tumor of the central nervous system. The study was to obtain the data of immune cell infiltration based on the data of a methylation chip in the GEO, and to clarify its prognostic significance for GBM.
Methods:
The methylation data of glioblastoma was obtained by using the Illumina human methylation 450k BeadChip. The corrected expression was obtained by using edge R. Limma was used to correct the expression amount of the samples, and EpiDISH was used to translate the methylation expression data, so that the expression amount was transformed into the expression matrix of immune cells. The immune cells were then co-expressed, and the proportion and correlation of related immune cells was determined. The results of the cells in each of two groups were analyzed by enrichment and PCA mapping to establish the relevant differences.
Results:
The data of GBM patients were obtained from the methylation chip of the GEO database. Patients were divided into a long-term (SNU-LTS) (21 cases), and short-term survival group (SNU-STS) (12 cases). There were 73 genes with significant individual differences between the two groups (P<0.05). EpiDISH was used to translate the methylation expression data into the expression matrix of immune cells, which showed that the highest proportion of cells in groups were mono cells, while Gran cells and CD8T appeared in a very small number of samples. The positive correlation between mono and B cells was the strongest, while the negative correlation between mono and Gran cells was the strongest. A violin chart shows that there was no significant difference in the infiltration degree of six kinds of immune cells between the two groups. Principal component analysis (PCA) showed that there was individual difference between the two groups, but the overall consistency was high.
Conclusions:
Data on tumor immune cell infiltration can be obtained by using a methylation chip in the GEO database. This not only extends the application abilities of methylation chips but provides obvious individual differences. The study of tumor immune infiltrating cells may pave the way for targeted therapy in the treatment of GBM.
