Tumor Heterogeneity and Molecular Characteristics of Glioblastoma Revealed by Single-Cell RNA-Seq Data Analysis.
Dhanusha YesudhasS Akila Parvathy DharshiniY-H TaguchiM Michael GromihaPublished in: Genes (2022)
Glioblastoma multiforme (GBM) is the most common infiltrating lethal tumor of the brain. Tumor heterogeneity and the precise characterization of GBM remain challenging, and the disease-specific and effective biomarkers are not available at present. To understand GBM heterogeneity and the disease prognosis mechanism, we carried out a single-cell transcriptome data analysis of 3389 cells from four primary IDH-WT (isocitrate dehydrogenase wild type) glioblastoma patients and compared the characteristic features of the tumor and periphery cells. We observed that the marker gene expression profiles of different cell types and the copy number variations (CNVs) are heterogeneous in the GBM samples. Further, we have identified 94 differentially expressed genes (DEGs) between tumor and periphery cells. We constructed a tissue-specific co-expression network and protein-protein interaction network for the DEGs and identified several hub genes, including CX3CR1, GAPDH, FN1, PDGFRA, HTRA1, ANXA2 THBS1, GFAP, PTN, TNC , and VIM . The DEGs were significantly enriched with proliferation and migration pathways related to glioblastoma. Additionally, we were able to identify the differentiation state of microglia and changes in the transcriptome in the presence of glioblastoma that might support tumor growth. This study provides insights into GBM heterogeneity and suggests novel potential disease-specific biomarkers which could help to identify the therapeutic targets in GBM.
Keyphrases
- single cell
- rna seq
- copy number
- genome wide
- high throughput
- wild type
- data analysis
- induced apoptosis
- protein protein
- end stage renal disease
- mitochondrial dna
- chronic kidney disease
- dna methylation
- ejection fraction
- small molecule
- poor prognosis
- newly diagnosed
- gene expression
- oxidative stress
- prognostic factors
- spinal cord injury
- cell proliferation
- stem cells
- inflammatory response
- big data
- climate change
- patient reported outcomes
- low grade
- network analysis
- endoplasmic reticulum stress
- peritoneal dialysis