Screening for genes and subnetworks associated with atypical teratoid/rhabdoid tumors using bioinformatics analysis

Abstract

Objectives: Atypical teratoid/rhabdoid tumors (AT/RTs) are rare, fast-growing lesions of central nervous system and their prognosis is poor. Nowadays, multimodal managements, including surgery, chemotherapy and radiation therapy are advocated; however, low survival rate and severe neurocognitive toxicity of chemotherapy as well as the irreversible long-term sequelae of irradiation in infants and young children with AT/RTs are alarming. The aim of our study is to provide valid biological information for more tailored advance therapy for these lesions.

Methods: Gene expression profile of GSE94349 was downloaded from GEO database and was analyzed using limma R package. Function and enrichment analyses of DEGs were performed based on DAVID database. PPI network construction, hub gene selection and module analysis were conducted in Cytoscape software.

Results: In this study, 224 up-regulated genes and 572 down-regulated genes were selected as DEGs. The up-regulated genes were mainly enriched in molecular function and cell component, which mainly included protein binding and nucleus, respectively. The down-regulated DEGs were significantly involved in cell component such as plasma membrane and integral component of membrane. Cell cycle and retrograde endocannabinoid signaling were the main KEGG pathway of up and down DEGs, respectively. CDK1, CCNA2, CDC20, TOP2A were identified as hub genes and two significant network modules were also obtained.

Conclusions: Our study may help to further understand the molecular characteristics and provide more tailored targets for future treatment of AT/RTs. Hub genes CDK1, CCNA2, CDC20, TOP2A as well as cell cycle signaling pathway may be new more tailored targets for future treatment of AT/RTs.

Keywords:

• AT/RTs
• CDK1
• CCNA2
• CDC20
• TOP2A

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Data availability statement

These data were derived from the following resources available in the public domain: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE94349.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant 81772693.