| Popis: |
Background: Oral cancer (OC) is one of the malignant diseases with high morbidity and mortality worldwide. The prognosis of OC patients has not improved with the development of technology, and treatment outcomes are still particularly poor. Therefore, we screened immune-related genes (IRGs) to construct a risk model for the prognosis of OC patients.Methods: We downloaded and analyzed the clinical materials and gene coexpression network of a total of 321 OC samples from The Cancer Genome Atlas (TCGA) OC dataset. Stromal and immune scores and tumor purity were calculated based on Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data. In addition, CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA) were applied to analyze the immune infiltration in each TCGA-OC cohort. Then we used the R package NbClust to divide the samples into two immune subtypes (S1 and S2). The control group was S2, and the treatment group was S1. Differences in genetic screening conditions were | a fold change | > 2 and FDR < 0.01. We obtained and analyzed 1111 IRGs from the two immune subtypes based on the ImmPort database. Then, 18 IRGs were selected from the 1111 IRGs for further analysis through the least absolute shrinkage and selection operator (LASSO) and univariate Cox regression analysis. Next, CCL22, CCL21, CD79A, CTLA4, MS4A2 and MS4A1 were screened out through the multivariate Cox regression analysis to develop a precise IRG prognosis risk model (IRGPRM) with area under curves (AUCs) of 0.639, 0.620 and 0.586 after 1, 3and 5 years, respectively. We divided the samples into high-risk and low-risk groups using the IRGPRM. Kaplan-Meier analysis was used to determine the survival rate of the two subtypes. The expression data of head and neck squamous cell carcinoma samples were downloaded from Gene Expression Omnibus (GEO) database to test the prognosis capability of the IRGPRM.Results: A six IRGPRM was established. Based on the model, TCGA-OC cohorts and testing sets were divided into high-risk and low-risk groups. The Kaplan-Meier analysis indicated poor overall survival (OS) in the high-risk group. Furthermore, the TIMMER analysis demonstrated that the expression of CCL22, CCL21, CD79A, CTLA4, MS4A2 and MS4A1 was positively correlated with the immune infiltration level based on the Tumor Immune Estimation Resource (TIMER) database. In addition, a nomogram based on risk score and clinical stage showed good calibration and moderate discrimination.Conclusions: Our findings suggest that this model can be a prognostic indicator for OC patients. |
