School of Stomatology, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Shandong University, Wenhua West Road No. 44, Jinan, 250014, Shandong, China.
Department of Orthodontics, State Key Laboratory Oral Disease, Sichuan University, West China Hospital Stomatology, Chengdu, 610041, Sichuan, China.
J Cancer Res Clin Oncol. 2020 Mar;146(3):621-630. doi: 10.1007/s00432-020-03155-4. Epub 2020 Feb 17.
Head and neck squamous cell carcinoma (HNSCC) is a common cancer with high mortality and poor prognosis partially owing to lack of application of predictive markers. Increasing evidence has suggested that metabolic dysregulation plays an important part in tumorigenesis. We aim to identify a prognostic metabolic pathway (MP) signature in HNSCC.
Single sample gene-set enrichment analysis (ssGSEA) was used in metabolic gene sets to develop a metabolism-based prognostic risk score (MPRS) for HNSCC using Cox regression analysis (univariate, LASSO, and stepwise multiple cox analysis), which was then validated in different subgroups, and association with clinical and mutational features was analyzed.
Seventy-two dysregulated metabolic pathways were identified, and a six-MP signature (6MPS) was constructed which can effectively distinguish between the high- and low-risk patients in both training and testing sets, accompanied with high sensitivity and specificity (AUC = 0.7) in prognosis prediction. 6MPS was also applicable to patients of different subgroups. Furthermore, 6MPS is not only an independent prognostic predictor but also associated with clinicopathological and mutational features. Higher tumor stage and tumor mutation burden (TMB) have a higher MPRS.
6MPS functions not only as a promising predictor of prognosis and survival but also as potential marker for therapeutic schedule monitoring.
头颈部鳞状细胞癌（HNSCC）是一种常见的癌症，死亡率和预后较差，部分原因是缺乏预测标志物的应用。越来越多的证据表明，代谢失调在肿瘤发生中起着重要作用。我们旨在确定 HNSCC 中的预后代谢途径（MP）特征。
使用单样本基因集富集分析（ssGSEA）对代谢基因集进行分析，采用 Cox 回归分析（单因素、LASSO 和逐步多 Cox 分析）建立基于代谢的 HNSCC 预后风险评分（MPRS），并在不同亚组中进行验证，并分析与临床和突变特征的相关性。
确定了 72 个失调的代谢途径，构建了一个六代谢途径（6MPS） signature，可以有效地在训练集和测试集中区分高风险和低风险患者，具有较高的敏感性和特异性（AUC=0.7）在预后预测中。6MPS 也适用于不同亚组的患者。此外，6MPS 不仅是独立的预后预测因子，还与临床病理和突变特征相关。较高的肿瘤分期和肿瘤突变负荷（TMB）具有更高的 MPRS。
6MPS 不仅可以作为预后和生存的有前途的预测因子，也可以作为治疗方案监测的潜在标志物。
