A seven-gene prognostic signature for rapid determination of head and neck squamous cell carcinoma survival

作者：Shen, Sipeng; Bai, Jianling; Wei, Yongyue; Wang, Guanrong; Li, Qingya; Zhang, Ruyang; Duan, Weiwei; Yang, Sheng; Du, Mulong; Zhao, Yang; Christiani, David C.; Chen, Feng^*

来源：Oncology Reports, 2017, 38(6): 3403-3411.

DOI：10.3892/or.2017.6057

• head and neck squamous cell carcinoma
• overall survival
• gene expression
• prognostic signature

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer and displays divergent clinical outcomes. Prognostic biomarkers might improve risk stratification and survival prediction. We aimed to investigate the prognostic genes associated with overall survival. A two-step gene selection method was used to develop a seven-gene-based prognostic model based on the training set collected from The Cancer Genome Atlas (TCGA). In addition, the prognostic model was validated in an independent testing set from Gene Expression Omnibus (GEO). The score based on the model successfully distinguished HNSCC survival into high-risk and low-risk groups in the training set (HR, 2.79; 95% CI, 1.98-3.92; P=4.05x10(-9)) and the testing set (HR, 2.05; 95% CI, 1.35-3.11; P=7.98x10(-4)). In addition, the score could significantly predict 5-year survival by ROC curves (AUCs for training set, 0.73; testing set, 0.66). Combining risk scores with clinical characteristics improved the AUCs beyond using clinical characteristics alone (training set, from 0.57 to 0.75; testing set, from 0.63 to 0.72). A subgroup sensitivity analysis with HPV status and tumor sites revealed that the risk score was significant in all subgroups except oral cavity tumors of the testing set. Furthermore, HPV-positive status improves survival in oropharyngeal HNSCC but not non-oropharyngeal HNSCC. In conclusion, the seven-gene prognostic signature is a reliable and practical prognostic tool for HNSCC. This approach can add prognostic value to clinical characteristics and provides a new possibility for individualized treatment.

• 出版日期2017-12
• 单位南京医科大学; 江苏省计划生育科学技术研究所