Prognostic Value of a Ten-Gene Signature in HNSCC Patients Based on Tumor-Associated Macrophages Expression Profiling

Zhaoyi Lu; Xiaoli Deng; Hui Li

doi:10.3389/fonc.2020.569002

Prognostic Value of a Ten-Gene Signature in HNSCC Patients Based on Tumor-Associated Macrophages Expression Profiling

Front Oncol. 2020 Nov 18:10:569002. doi: 10.3389/fonc.2020.569002. eCollection 2020.

Authors

Zhaoyi Lu^{1

2}, Xiaoli Deng^{3

4}, Hui Li²

Affiliations

¹ Department of Otolaryngology, Head and Neck Surgery, Xiangya Hospital, Central South University, Changsha, China.
² Department of Otolaryngology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
³ Textile College, Changzhou Vocational Institute of Textile and Garment, Changzhou, China.
⁴ Key Laboratory of Xinjiang Phytomedicine Resource and Utilization, Ministry of Education, Shihezi University, Shihezi, China.

Abstract

Tumor-associated macrophages (TAMs) are regarded as the most abundantly infiltrating immune cells around the tumor microenvironment (TME) in head and neck squamous cell carcinoma (HNSCC), which plays an essential role in immunosuppression and tumorigenesis. In the TCGA HNSCC cohort, 500 patients with clinical-pathological information and RNA sequence expression were randomly assigned to training for lasso regression and validation for verification, respectively. A TAM-based ten-gene signature (TBGs) was constructed, which divided the patients into high-risk and low-risk groups, could predict overall survival (OS) of HNSCC patients in the training dataset (p = 3.527e^-05) and validation dataset (p = 3.785e^-02). The result of Cox univariate and multivariate regression analyses showed that the risk score of TBGs could be an independent prognostic factor in HNSCC. ROC curve confirmed that the risk score of TBGs has good sensitivity and specificity for prognosis prediction (AUC = 0.659) and was also verified by the validation dataset (AUC = 0.621). We obtained key risk transcription factors (TFs)-EHF and SNAI2-by correlation analysis with TBGs. Moreover, we ran a gene set enrichment analysis (GSEA) to speculate that TBGs act on interstitial remodeling, tumor killing, metabolic reprogramming, and tumor immune-related pathways. Finally, we combined clinical-pathological features and risk score of TBGs to establish clinical nomograms, and calibration curves verified the accuracy of long-term clinical prognosis in the two datasets (C-index of 5-year OS = 0.721 and 0.716). In general, the TBGs we obtained may accurately predict the prognosis of HNSCC patients to provide personalized treatment.

Keywords: gene signature; head and neck squamous cell carcinoma; prognostic value; transcription factors; tumor-associated macrophages.