Head and neck squamous carcinoma (HNSCC), characterized by immunosuppression, is a group of highly heterogeneous cancers. Although immunotherapy exerts a promising influence on HNSCC, the response rate remains low and varies in assorted primary sites. Immunological mechanisms underlying HNSCC pathogenesis and treatment response are not fully understood. This study aimed to develop a differentially expressed genes (DEGs)–based risk model to predict immunotherapy efficacy and stratify prognosis of HNSCC patients.

The expression profiles of HNSCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The tumor microenvironment and immune response were estimated by cell type identification via estimating relative subset of known RNA transcripts (CIBERSORT) and immunophenoscore (IPS). The differential expression pattern based on human papillomavirus status was identified. A DEGs-based prognostic risk model was developed and validated. All statistical analyses were performed with R software (version 3.6.3).

By using the TCGA database, we identified DKK1, HBEGF, RNASE7, TNFRSF12A, INHBA, and IPIK3R3 as DEGs that were associated with patients’ overall survival (OS). Patients were stratified into the high- and low-risk subgroups according to a DEGs-based prognostic risk model. Significant difference in OS was found between the high- and low-risk patients (1.64 vs. 2.18 years, P = 0.0017). In multivariate Cox analysis, the risk model was an independent prognostic factor for OS (hazard radio = 1.06, 95% confidence interval [1.02–1.10], P = 0.004). More CD8⁺ T cells and regulatory T cells were observed in the low-risk group and associated with a favorable prognosis. The IPS analysis suggested that the low-risk patients possessed a higher IPS score and a higher immunoreactivity phenotype, which were correlated with better immunotherapy response.

Collectively, we established a reliable DEGs-based risk model with potential prognostic value and capacity to predict the immunophenotype of HNSCC patients.

以免疫抑制为特征的头颈部鳞状细胞癌 (HNSCC) 是一组高度异质性的癌症。尽管免疫疗法对 HNSCC 产生了有希望的影响，但反应率仍然很低，并且在各种原发部位有所不同。HNSCC 发病机制和治疗反应的免疫机制尚不完全清楚。本研究旨在开发一种基于差异表达基因 (DEG) 的风险模型，以预测 HNSCC 患者的免疫治疗效果和预后分层。

HNSCC 患者的表达谱从癌症基因组图谱（TCGA）数据库下载。通过估计已知 RNA 转录物 (CIBERSORT) 和免疫表观评分 (IPS) 的相对子集，通过细胞类型鉴定来估计肿瘤微环境和免疫反应。确定了基于人乳头瘤病毒状态的差异表达模式。开发并验证了基于 DEG 的预后风险模型。所有统计分析均使用 R 软件（版本 3.6.3）进行。

通过使用 TCGA 数据库，我们发现丹麦克朗1,HBEGF,核糖核酸酶7,TNFRSF12A,INHBA， 和IPIK3R3作为与患者总生存期（OS）相关的DEG。根据基于 DEG 的预后风险模型，将患者分为高风险和低风险亚组。高风险和低风险患者的 OS 存在显着差异（1.64 年 vs. 2.18 年，磷= 0.0017)。在多变量 Cox 分析中，风险模型是 OS 的独立预后因素（危险无线电 = 1.06，95% 置信区间 [1.02–1.10]，磷= 0.004)。在低风险组中观察到更多的 CD8 ⁺ T 细胞和调节性 T 细胞，并且与良好的预后相关。IPS 分析表明，低风险患者具有更高的 IPS 评分和更高的免疫反应表型，这与更好的免疫治疗反应相关。

总的来说，我们建立了一个可靠的基于 DEGs 的风险模型，具有潜在的预后价值和预测 HNSCC 患者免疫表型的能力。