| Popis: |
BackgroundThe malignant progression and treatment resistance of head and neck squamous cell carcinoma are closely related to the tumor immune microenvironment. Long non-coding RNA (lncRNA) plays a regulatory role in this process and may be exploited as new signatures for head and neck squamous cell carcinoma(HNSCC) diagnosis, prognosis, and treatment.MethodsHNSCC transcriptome data was abstracted from the Cancer Genome Atlas (TCGA) data resource, and uncovered immune-linked lncRNA through co-expression analysis. Besides, univariate along with Lasso penalty regression were employed to determine immune-linked lncRNA pairs with different expressions. We then compared area under the curve, calculated the Akaike information criterion (AIC) value of the receiver operating characteristic curve for 5 years, determined cutoff points, and established an optimal predictive model for identifying high- and low-risk HNSCC patients. Then, we evaluated these patients with high- and low-risk HNSCC in terms of survival, clinic-pathological characteristics, tumor-infiltrating immune cells, chemotherapeutic efficacy, and immunosuppressed biomarkers.ResultsThis study included 545 samples. By co-expression analysis of known immune-linked genes and lncRNAs, a total of 809 immune-related lncRNAs were collected. 77 differentially expressed immune-related lncRNAs were identified (logFC>2,FDR |
