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Updated: Sep 2, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
A prognostic Risk Score model for oral squamous cell carcinoma constructed by 6 glycolysis-immune-related genes
Yi Liu1, Tong Wang2, Ronghua Li2
1Department of Stomatology, Tianjin First Central Hospital, Nankai District, No.24 Fukang Road, Tianjin, 300192, People's Republic of China. 13821075639@163.com.
Background:
Oral squamous cell carcinoma (OSCC) is the most frequent tumor of the head and neck. The glycolysis-related genes and immune-related genes have been proven prognostic values in various cancers. Our study aimed to test the prognostic value of glycolysis-immune-related genes in OSCC.
Methods:
Data of OSCC patients were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Enrichment analysis was applied to the glycolysis- and immune-related genes screened by differential expression analysis. Univariate Cox and LASSO Cox analyses were used to filtrate the genes related to the prognosis of OSCC and to construct Risk Score model.
Results:
A Risk Score model was constructed by six glycolysis-immune-related genes (including ALDOC, VEGFA, HRG, PADI3, IGSF11 and MIPOL1). High risk OSCC patients (Risk Score >-0.3075) had significantly worse overall survival than that of low risk patients (Risk Score <-0.3075).
Conclusions:
The Risk Score model constructed basing on 6 glycolysis-immune-related genes was reliable in stratifying OSCC patients with different prognosis.
