Int J Med Sci 2021; 18(1):226-238. doi:10.7150/ijms.51064 This issue

Research Paper

Tumor Mutation Burden, Immune Cell Infiltration, and Construction of Immune-Related Genes Prognostic Model in Head and Neck Cancer

Ai-Min Jiang#, Meng-Di Ren#, Na Liu, Huan Gao, Jing-Jing Wang, Xiao-Qiang Zheng, Xiao Fu, Xuan Liang, Zhi-Ping Ruan, Tao Tian, Yu Yao

Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.
#These authors contributed equally to this work.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Citation:
Jiang AM, Ren MD, Liu N, Gao H, Wang JJ, Zheng XQ, Fu X, Liang X, Ruan ZP, Tian T, Yao Y. Tumor Mutation Burden, Immune Cell Infiltration, and Construction of Immune-Related Genes Prognostic Model in Head and Neck Cancer. Int J Med Sci 2021; 18(1):226-238. doi:10.7150/ijms.51064. Available from https://www.medsci.org/v18p0226.htm

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Abstract

Background: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide, and the prognosis of HNSCC remains bleak. Numerous studies revealed that the tumor mutation burden (TMB) could predict the survival outcomes of a variety of tumors.

Objectives: This study aimed to investigate the TMB and immune cell infiltration in these patients and construct an immune-related genes (IRGs) prognostic model.

Methods: The expression data of 546 HNSCC patients were obtained from The Cancer Genome Atlas (TCGA) database. All patients were divided into high- and low- TMB groups, and the relationship between TMB and clinical relevance was further analyzed. The differentially expressed genes (DEGs) were identified using the R software package, limma. Functional enrichment analyses were conducted to identify the significantly enriched pathways between two groups. CIBERSORT algorithm was adopted to calculate the abundance of 22 leukocyte subtypes. The IRGs prognostic model was constructed via the multivariate Cox regression analysis.

Results: Missense mutation and single nucleotide variants (SNV) were the most predominant mutation types in HNSCC. TP53, TTN, and FAT1 were the most frequently mutated genes. Patients with high TMB were observed with worse survival outcomes. The functional analysis of TMB associated DEGs showed that the identified DEGs mainly involved in spliceosome, RNA degradation, proteasome, and RNA polymerase pathways. We observed that macrophages, T cells CD8, and T cells CD4 memory were the most commonly infiltrated subtypes of immune cells in HNSCC. Finally, an IRGs prognostic model was constructed, and the AUC of the ROC curve was 0.635.

Conclusions: Our results suggest that high TMB is associated with poor prognosis in HNSCC patients. The constructed model has potential prognostic value for the prognosis of these individuals, and it needs to be further validated in large-scale and prospective studies.

Keywords: Head and neck squamous cell carcinoma (HNSCC), Tumor mutation burden (TMB), Immune cell infiltration, Immune-related genes (IRGs), TCGA