头颈部鳞状细胞癌的预后预测：铜死亡相关长非编码 RNA 特征的构建。

BACKGROUND: Recently, a new type of programmed cell death, cuproptosis, has been identified to play important role in the progression of tumors. We constructed a cuproptosis-related long non-coding RNA (lncRNA) signature to predict the prognostic significance for head and neck squamous cell carcinoma (HNSCC). METHODS: The risk model was developed based on differentially expressed lncRNAs associated with cuproptosis. Principal component analysis was used to assess the validity. The Kaplan-Meier curves were analyzed to compare the overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) values. The multivariate and univariate Cox regression analyses were used to evaluate the prognostic efficiency. Furthermore, the functional enrichment, immune cell infiltration, tumor mutation burden (TMB), and sensitivity toward chemotherapy were also explored. RESULTS: Six cuproptosis-related lncRNAs (AL109936.2, CDKN2A-DT, AC090587.1, KLF3-AS1, AL133395.1, and LINC01063) were identified to construct the independent prognostic predictor for HNSCC. The area under the curve and C-index values obtained using the risk model were higher than the values corresponding to the clinical factors. Analysis of Kaplan-Meier curves indicated that the OS, PFS, and DSS time recorded for the patients in the low-risk group were higher than the corresponding values recorded for the patients belonging to the high-risk group. By functional enrichment analysis, we observed that differentially expressed genes were enriched in the immune response and tumor-associated pathways. The patients characterized by a low-risk score exhibited better immune cell infiltration than the patients belonging to the other group. We also observed that the sensitivity of the individuals belonging to the low-risk group to chemotherapeutic agents (cisplatin, docetaxel, and paclitaxel) was higher than the sensitivity of those in the other group. CONCLUSIONS: A cuproptosis-related lncRNA-based signature that functioned as an independent prognosis predictor for HNSCC patients was constructed. The chemosensitivity of individual patients can be potentially predicted using this signature.

背景：最近，一种新的细胞程序性死亡方式——铜死亡，被发现与肿瘤的发展密切相关。我们构建了一个铜死亡相关的长非编码 RNA（lncRNA）特征模型，以预测头颈部鳞状细胞癌（HNSCC）的预后意义。

方法：该风险模型是基于与铜死亡相关的差异表达 lncRNA 构建的。采用主成分分析评估其有效性。通过 Kaplan-Meier 曲线比较总生存期（OS）、疾病特异性生存期（DSS）和无进展生存期（PFS）。采用多变量和单变量 Cox 回归分析评估预后效率。此外，还探讨了功能富集、免疫细胞浸润、肿瘤突变负荷（TMB）以及对化疗的敏感性。

结果：鉴定出 6 个与铜死亡相关的 lncRNA（AL109936.2、CDKN2A-DT、AC090587.1、KLF3-AS1、AL133395.1 和 LINC01063），用于构建 HNSCC 的独立预后预测因子。使用风险模型获得的曲线下面积和 C 指数值高于临床因素对应的数值。Kaplan-Meier 曲线分析表明，低风险组患者的 OS、PFS 和 DSS 时间高于高风险组患者。通过功能富集分析，观察到差异表达基因富集在免疫反应和肿瘤相关途径中。低风险评分患者的免疫细胞浸润优于其他组患者。还观察到低风险组患者对化疗药物（顺铂、多西他赛和紫杉醇）的敏感性高于其他组患者。

结论：构建了一个基于铜死亡相关 lncRNA 的模型，作为 HNSCC 患者的独立预后预测因子。该模型可以潜在预测个体患者的化疗敏感性。