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Risk Score Prediction Model of Prognosis in GC Patients by Age and Gender Combined With m6A Modification Genes FTO and RBM15.
Yue, Limin; Zhang, Rongguang; Chen, Shuaiyin; Duan, Guangcai.
Affiliation
  • Yue L; Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Zhang R; Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Chen S; Department of Epidemiology, College of Public Health, Hainan Medical University, Haikou, China.
  • Duan G; Department of Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, China.
Front Cell Dev Biol ; 10: 710708, 2022.
Article in En | MEDLINE | ID: mdl-35433701
ABSTRACT

Background:

Gastric cancer (GC) has a high mortality rate. N6-methyladenosine (m6A) is involved in the development of GC. Age and gender are associated with GC incidence and survival. This study aimed to explore the risk score prediction model of prognosis in GC patients by age and gender combined with m6A modification genes.

Methods:

Data on m6A modification gene expression and clinical information downloaded from the Cancer Genome Atlas (TCGA) database were used to construct the risk score prediction model. Cox and least absolute shrinkage and selection operator (LASSO) regression were performed to identify clinical characteristics and m6A modification genes associated with prognosis. A risk score prediction model was established based on multivariate Cox regression analysis. The Gene Expression Omnibus (GEO) database was used to validate this model.

Results:

Most of the m6A modification genes were upregulated in GC tumor tissues compared with that in normal tissues and were correlated with clinical characteristics including grade, stage status, and T status. The risk score prediction model was established based on age, gender, FTO, and RBM15. GC patients were divided into high- or low-risk groups based on the median risk score. Patients with a high risk score had poor prognosis. Multivariate Cox regression indicated that risk score was an independent prognostic factor for GC patients. The data from GSE84437 verified the predictive value of this model.

Conclusion:

The risk score prediction model based on age and gender combined with m6A modification genes FTO and RBM15 was an independent prognostic factor for GC patients.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Aspects: Determinantes_sociais_saude Language: En Journal: Front Cell Dev Biol Year: 2022 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Aspects: Determinantes_sociais_saude Language: En Journal: Front Cell Dev Biol Year: 2022 Document type: Article Affiliation country: China
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