Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia; Faculty of Medicine, University of Queensland, Brisbane, Australia.
Dermatology Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD 4102, Australia.
Oral Oncol. 2021 Feb;113:105136. doi: 10.1016/j.oraloncology.2020.105136. Epub 2021 Jan 7.
The major cause of mucosal squamous cell carcinomas of the head and neck (HNSCCs) has been attributed to human papillomavirus (HPV) infection. Here we investigate if microRNA expression in HNSCC can be used as a prognostic tool with or without HPV status.
We performed a discovery miRNA microarray (miRBase v.21) profiling of 52 tonsillar SCCs with TaqMan real-time PCR validation of 228 HNSCCs. Patients had a histologically confirmed primary SCC of the oropharynx, oral cavity, hypopharynx or larynx. Logistic regression models were used to estimate the magnitude of the effect of association with clinical factors and miRNAs associated with HPV status. For recurrence and survival analysis, we used unadjusted and multivariable adjusted Cox proportional hazard regression models.
Seventeen miRNAs were significantly associated with better prognosis in the discovery phase and were validated in the extended dataset. The best fitting model (AUC = 0.92) for HPV status included age, smoking, and miRNAs: miR-15b, miR-20b, miR-29a, miR-29c, miR-142, miR-146a and miR-205. Using Cox regression model for recurrence, miR-29a was associated with 49% increased risk of recurrence while miR-30e and miR-342 were associated with decreased risk of recurrence with HRs 0.92 (95% CI 0.85-0.99) and 0.84 (95% CI 0.73-0.98), respectively. Our best fitting model for survival included age, gender, alcohol consumption, N stage, recurrence, HPV status, together with miRNAs-20b, 29a, and 342.
miRNAs show potential to serve as usual biomarkers to predict the clinical course of patients with mucosal HNSCC.
头颈部（HNSCC）黏膜鳞状细胞癌的主要病因归因于人类乳头瘤病毒（HPV）感染。在此，我们研究 HNSCC 中的 microRNA 表达是否可以作为一种预测工具，无论 HPV 状态如何。
我们对 52 例扁桃体鳞状细胞癌（SCC）进行了 miRNA 微阵列（miRBase v.21）谱分析，并对 228 例 HNSCC 进行了 TaqMan 实时 PCR 验证。患者的病理检查均为口咽、口腔、下咽或喉的原发性 SCC。采用逻辑回归模型估计关联临床因素和与 HPV 状态相关的 microRNAs 的关联程度。对于复发和生存分析，我们使用未经调整和多变量调整的 Cox 比例风险回归模型。
在发现阶段，有 17 个 microRNAs 与更好的预后显著相关，并在扩展数据集得到验证。HPV 状态的最佳拟合模型（AUC=0.92）包括年龄、吸烟和 microRNAs：miR-15b、miR-20b、miR-29a、miR-29c、miR-142、miR-146a 和 miR-205。使用 Cox 回归模型进行复发分析，miR-29a 与复发风险增加 49%相关，HR 为 0.92（95%CI 0.85-0.99），miR-30e 和 miR-342 与复发风险降低相关，HR 分别为 0.92（95%CI 0.85-0.99）和 0.84（95%CI 0.73-0.98）。我们的生存最佳拟合模型包括年龄、性别、饮酒、N 期、复发、HPV 状态，以及 microRNAs-20b、29a 和 342。
microRNAs 显示出作为预测黏膜 HNSCC 患者临床病程的常规生物标志物的潜力。
