Identification and characterization of sex-dependent gene expression profile in glioblastoma.
Shangyao QinYimin YuanHong LiuYingyan PuKefu ChenYulong WuZhida SuPublished in: Neuropathology : official journal of the Japanese Society of Neuropathology (2022)
Glioblastoma (GBM) is the most lethal primary tumor in the human brain and lacks favorable treatment options. Sex differences in the outcome of GBM are broadly acknowledged, but the underlying molecular mechanisms remain largely unknown. To identify the sex-dependent critical genes in the progression of GBM, raw data from several microarray datasets with the same array platform were downloaded from the Gene Expression Omnibus (GEO) database. These datasets included tumorous and normal tissue from patients with GBM and crucial sex features. Then, the differentially expressed genes (DEGs) in female and male tumors were identified via bioinformatics analysis, respectively. Functional signatures of the identified DEGs were further annotated by Gene Ontology (GO) and pathway enrichment analyses. Venn diagram and functional protein-protein interaction (PPI) network analyses were performed to screen out the sex-specific DEGs. Survival analysis of patients with differences in the expression level of selected genes was then carried out using the data from The Cancer Genome Atlas (TCGA). Here, we showed that ECT2, AURKA, TYMS, CDK1, NCAPH, CENPU, OIP5, KIF14, ASPM, FBXO5, SGOL2, CASC5, SHCBP1, FN1, LOX, IGFBP3, CSPG4, and CD44 were enriched in female tumor samples, whereas TNFSF13B, CXCL10, CXCL8, CXCR4, TLR2, CCL2, and FCGR2A were enriched in male tumor samples. Among these key genes, interestingly, ECT2 was associated with increased an survival rate for female patients, whileTNFSF13B could be regarded as a potential marker of poor prognosis in male patients. These results suggested that sex differences in patients may be attributed to the heterogeneous gene activity, which might influence the oncogenesis and the outcomes of GBM.
Keyphrases
- poor prognosis
- bioinformatics analysis
- gene expression
- end stage renal disease
- genome wide
- ejection fraction
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- dna methylation
- long non coding rna
- prognostic factors
- emergency department
- high throughput
- risk assessment
- squamous cell carcinoma
- skeletal muscle
- transcription factor
- immune response
- inflammatory response
- lymph node metastasis
- weight loss
- high resolution
- artificial intelligence
- climate change
- genome wide analysis
- cell cycle
- liver fibrosis
- free survival
- big data
- low density lipoprotein
- papillary thyroid
- childhood cancer