Abstract
Background: Our investigation sought to uncover the intrinsic features of Head and Neck Squamous Cell Carcinoma (HNSCC), particularly the role of long non-coding RNAs implicated in disulfidptosis (DRLs). Materials and methods: We carried out lncRNA-mRNA RNA-Seq studies on HNSCC cells and harnessed the data from The Cancer Genome Atlas (TCGA), which includes 522 HNSCC tumors and 44 normal specimens. Bioinformatics evaluations aided in recognizing DRLs and estimating their prognostic value. Furthermore, we built a predictive model related to the chosen DRLs to scrutinize its linkage with the patients' prognosis. We also dug into tumor mutation loads and responses to chemotherapy. Results: Our study identified three key DRLs (LINC02434, AC245041.2, and LINC02762) with considerable correlation to HNSCC prognosis. The risk model, utilizing these DRLs, successfully categorized patients into high-risk and low-risk clusters, uncovering differential survival trajectories. Moreover, the same risk model conveyed unique prognostic potential in HNSCC. Surveying the tumor microenvironment unfolded disparities between the groups, hinting toward potential implications for tactics in immunotherapy. We recognized distinct chemotherapeutic drugs with fluctuating responses across the risk clusters and molecular categories. Conclusion: This investigation not only sheds light on prospective therapeutic pathways but also enhances our grasp of the molecular intricacies of HNSCC.