A novel metabolic-related gene signature for predicting clinical prognosis and immune microenvironment in head and neck squamous cell carcinoma

Yongxin Cao; Zili Dai; Guofeng Xie; Guihong Liu; Liyi Guo; Jian Zhang

doi:10.1016/j.yexcr.2023.113628

A novel metabolic-related gene signature for predicting clinical prognosis and immune microenvironment in head and neck squamous cell carcinoma

Exp Cell Res. 2023 Jul 15;428(2):113628. doi: 10.1016/j.yexcr.2023.113628. Epub 2023 May 4.

Authors

Yongxin Cao¹, Zili Dai², Guofeng Xie², Guihong Liu³, Liyi Guo⁴, Jian Zhang⁵

Affiliations

¹ Department of Oncology, Dongguan Songshan Lake Tungwah Hospital, Dongguan, China.
² Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China.
³ Department of Radiation Oncology, Dongguan Tungwah Hospital, Dongguan, China.
⁴ Department of Oncology and Hematology, The Six People's Hospital of Huizhou City, Huiyang Hospital Affiliated to Southern Medical University, Huizhou, China. Electronic address: 13802869551@139.com.
⁵ Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China; Guangzhou Medical University, Guangzhou, China. Electronic address: zhangjian@gzhmu.edu.cn.

PMID: 37149080
DOI: 10.1016/j.yexcr.2023.113628

Abstract

Objectives: Metabolic reprogramming is not only an essential hallmark in the progression of head and neck squamous cell carcinoma (HNSCC), but also an important regulator of cancer cell adaptation to tumor microenvironment (TME). However, the potential mechanism of metabolic reprogramming in TME of HNSCC is still unknown.

Methods: The head and neck squamous cell carcinoma with survival information were obtained the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The metabolic-related genes were identified by differential analysis and survival analysis. Univariate and multivariate Cox regression analyses were applied to determine an overall estimate of metabolic-related risk signature and related clinical parameters. The sensitivity and specificity of the risk signature were evaluated by time-dependent receiver operation characteristic (ROC) curves. TME immune cell infiltration mediated by metabolic-related genes was explored by gene set enrichment analysis (GSEA) and correlation analysis.

Results: Seven metabolic-related genes (SMS, MTHFD2, HPRT1, DNMT1, PYGL, ADA, and P4HA1) were identified to develop a metabolic-related risk signature. The low-risk group had a better overall survival compared to that of the high-risk group in the TCGA and GSE65858 cohorts. The AUCs for 1-, 3-, and 5-year overall survival were 0.646 vs. 0.673, 0.694 vs. 0.639, and 0.673 vs. 0.573, respectively. The AUC vale of risk score was 0.727 vs. 0.673. The low-risk group was associated with immune cell infiltration in the TME.

Conclusions: The metabolic-related risk signature were constructed and validated, which could involve in regulating the immune cell infiltration in the TME and act as an independent biomarker that predicted the prognosis of HNSCC.

Keywords: Head and neck squamous cell carcinoma; Metabolic; Prognosis; Risk signature; Tumor microenvironment.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Head and Neck Neoplasms* / genetics
Humans
Hypoxanthine Phosphoribosyltransferase*
Risk Factors
Squamous Cell Carcinoma of Head and Neck / genetics
Tumor Microenvironment / genetics

Substances

Hypoxanthine Phosphoribosyltransferase