Bangjie Chen: College & Hospital of Stomatology, Key Lab. of Oral Diseases Research of Anhui Province, Anhui Medical University, Hefei, China.
Yanxun Han: The First Affiliated Hospital (First Clinical Medical College), Anhui Medical University, Hefei, China.
Shuyan Sheng: The First Affiliated Hospital (First Clinical Medical College), Anhui Medical University, Hefei, China.
Jianyi Deng: The First Affiliated Hospital (First Clinical Medical College), Anhui Medical University, Hefei, China.
Emely Vasquez: CUNY School of Medicine, New York, USA.
Vicky Yau: Division of Oral and Maxillofacial Surgery, NewYork Presbyterian (Columbia Irving Medical Center), New York, USA.
Muzi Meng: UK Program Site, American University of the Caribbean School of Medicine, Preston, UK.
Chenyu Sun: The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Tao Wang: The Affiliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, China.
Yu Wang: The Affiliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, China.
Mengfei Sheng: College & Hospital of Stomatology, Key Lab. of Oral Diseases Research of Anhui Province, Anhui Medical University, Hefei, China.
Tiangang Wu: College & Hospital of Stomatology, Key Lab. of Oral Diseases Research of Anhui Province, Anhui Medical University, Hefei, China.
Xinyi Wang: The First Affiliated Hospital (First Clinical Medical College), Anhui Medical University, Hefei, China.
Yuchen Liu: The First Affiliated Hospital (First Clinical Medical College), Anhui Medical University, Hefei, China.
Ning Lin: The Affiliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, China. lin2007512@vip.163.com.
Lei Zhang: College & Hospital of Stomatology, Key Lab. of Oral Diseases Research of Anhui Province, Anhui Medical University, Hefei, China. zhanglei6551@126.com.
Wei Shao: College & Hospital of Stomatology, Key Lab. of Oral Diseases Research of Anhui Province, Anhui Medical University, Hefei, China. shaowei@ahmu.edu.cn.
OBJECTIVES: To develop a model that can assist in the diagnosis and prediction of prognosis for head and neck squamous cell carcinoma (HNSCC). MATERIALS AND METHODS: Data from TCGA and GEO databases were used to generate normalized gene expression data. Consensus Cluster Plus was used for cluster analysis and the relationship between angiogenesis-associated gene (AAG) expression patterns, clinical characteristics and survival was examined. Support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) analyzes and multiple logistic regression analyzes were performed to determine the diagnostic model, and a prognostic nomogram was constructed using univariate and multivariate Cox regression analyses. ESTIMATE, XCELL, TIMER, QUANTISEQ, MCPCOUNTER, EPIC, CIBERSORT-ABS, CIBERSORT algorithms were used to assess the immune microenvironment of HNSCC patients. In addition, gene set enrichment analysis, treatment sensitivity analysis, and AAGs mutation studies were performed. Finally, we also performed immunohistochemistry (IHC) staining in the tissue samples. RESULTS: We classified HNSCC patients into subtypes based on differences in AAG expression from TCGA and GEO databases. There are differences in clinical features, TME, and immune-related gene expression between two subgroups. We constructed a HNSCC diagnostic model based on nine AAGs, which has good sensitivity and specificity. After further screening, we constructed a prognostic risk signature for HNSCC based on six AAGs. The constructed risk score had a good independent prognostic significance, and it was further constructed into a prognostic nomogram together with age and stage. Different prognostic risk groups have differences in immune microenvironment, drug sensitivity, gene enrichment and gene mutation. CONCLUSION: We have constructed a diagnostic and prognostic model for HNSCC based on AAG, which has good performance. The constructed prognostic risk score is closely related to tumor immune microenvironment and immunotherapy response.
