Department of Stomatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Pediatric Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Oral Dis. 2023 Jan;29(1):138-153. doi: 10.1111/odi.13889. Epub 2021 May 13.
The aim of this study was to identify prognostic autophagy-related genes and lncRNAs to predict clinical outcomes in head and neck squamous cell carcinoma (HNSCC).
Differentially expressed autophagy-related genes and autophagy-related lncRNAs were identified by comparing pare-carcinoma and carcinoma samples of HNSCC. And then, we constructed an ARG and an AR-lncRNA signature risk score. Receiver operating characteristic (ROC) curve analyses were performed to assess the prognostic prediction capacity. Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) functional annotation were used to analysis the functions of ARGs and AR-lncRNAs.
Six ARGs and thirteen AR-lncRNAs were identified in the ARG and AR-lncRNA signatures, and overall survival (OS) in the high-risk group was significantly shorter than the low-risk group. ROC analysis showed the ARG and AR-lncRNA signatures have excellent ability of predicting the total OS of patients with HNSCC. What's more, GSEA and GO functional annotation proved that autophagy-related pathways are mainly enriched in the high-risk group.
These findings indicated that our ARG signature and AR-lncRNA signature could be considered to predict the prognosis of patients with HNSCC and provide a deep understanding of the biological mechanisms of autophagy in HNSCC.
本研究旨在鉴定与自噬相关的预后基因和 lncRNA，以预测头颈部鳞状细胞癌（HNSCC）的临床结局。
通过比较 HNSCC 的癌旁和癌组织，鉴定出差异表达的自噬相关基因和自噬相关 lncRNA。然后，构建了一个 ARG 和一个 AR-lncRNA 特征风险评分。通过接受者操作特征（ROC）曲线分析来评估预后预测能力。基因集富集分析（GSEA）和基因本体论（GO）功能注释用于分析 ARGs 和 AR-lncRNAs 的功能。
在 ARG 和 AR-lncRNA 特征中鉴定出了 6 个 ARG 和 13 个 AR-lncRNA，高风险组的总体生存率（OS）明显短于低风险组。ROC 分析表明，ARG 和 AR-lncRNA 特征具有预测 HNSCC 患者总 OS 的优异能力。此外，GSEA 和 GO 功能注释表明，自噬相关途径主要富集在高风险组。
这些发现表明，我们的 ARG 特征和 AR-lncRNA 特征可以考虑用于预测 HNSCC 患者的预后，并深入了解 HNSCC 中自噬的生物学机制。
