Immune-Related lncRNA to Construct Novel Signature and Predict the Immune Landscape of in Head and Neck Squamous Cell Carcinoma

Abstract

Background: Head and neck squamous cell carcinoma (HNSCC) are head and neck cancers. On the other hand, the antitumor immune responses affect the outcome of radiotherapy against HNSCC. Method: We used a novel signature algorithm, paring, and iteration to build a multi-lncRNA signature, which did not need any particular expression lncRNA levels. Results: We identified 21 differently expressed immune-related lncRNAs associated with prognosis of HNSCC. Kaplan-Meier analyses revealed the high-risk lncRNAs signature associated with poor prognosis of HNSCC. Moreover, the AUC of the lncRNAs signature was 0.840, underscoring their utility in prediction HNSCC prognosis. Indeed, our risk assessment model was superior to traditional clinicopathological features in predicting HNSCC prognosis. GSEA revealed the immune and cancer-related pathways in the risk group individuals. The top 30 driver genes with the highest alteration frequency of TP53, TTN, FAT1, CDKN1A, PIK3CA, NOTCH1, MUC16, CASM3, and CASP8 was significantly different among the high and low-risk groups. We found a substantial difference in the expression of PDCD-1 (PD-1), CTLA4, GGT1, TIGIT among others, between the two groups of patients. Conclusion: This study suggests that novel features constructed by irlncRNAs without the need to predict lncRNA expression levels can predict prognosis in HNSCC patients. Funding Statement: This work is not supported by grants. Declaration of Interests: The authors declare that they have no competing interests. Ethics Approval Statement: Not applicable.