Cuproptosis is considered a novel copper-induced cell death model regulated by targeting lipoylated TCA cycle proteins. In this study, we established a novel signature based on cuproptosis-related lncRNAs (crlncRNAs) to predict the prognosis and immune landscape of head and neck squamous cell carcinoma.
RNA-seq matrix, somatic mutation files, and clinical data were obtained from The Cancer Genome Atlas database. After dividing patients into two sets, a crlncRNA signature was established based on survival related crlncRNAs, which were selected by the univariate Cox analysis and least absolute shrinkage and selection operator Cox regression. To evaluate the model, Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) were utilized, and a nomogram was established for survival prediction. Immune landscape analysis, drug sensitivity, cluster analysis, tumor mutation burden (TMB) and ceRNA network analysis were conducted subsequently.
A crlncRNA related prognosis signature was finally constructed with 12 crlncRNAs. The areas under the ROC curves (AUCs) were 0.719, 0.705 and 0.693 respectively for 1, 3, and 5-year’s overall survival (OS). Patients in the low-risk group behaved a better prognosis, lower TMB, higher immune function activity and scores. In addition, patients from cluster 2 were more sensitive to chemotherapy and immunotherapy.
In this study, we constructed a novel crlncRNA risk model to predict the survival of HNSCC patients. This reliable and acceptable prognostic signature may guide and promote the progress of novel treatment strategies for HNSCC patients.