Development and Validation of a Necroptosis-Related Prognostic Model in Head and Neck Squamous Cell Carcinoma

Abstract

Necroptosis is a new regulated cell-death mechanism that plays a critical role in various cancers. However, few studies have considered necroptosis-related genes (NRGs) as prognostic indexes for cancer. As one of the most common cancers in the world, head and neck squamous cell carcinoma (HNSCC) lacks effective diagnostic strategies at present. Hence, a series of novel prognostic indexes are required to support clinical diagnosis. Recently, many studies have confirmed that necroptosis was a key regulated mechanism in HNSCC, but no systematic study has ever studied the correlation between necroptosis-related signatures and the prognosis of HNSCC. Thus, in the current study, we aimed to construct a risk model of necroptosis-related signatures for HNSCC. We acquired 159 NRGs from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and compared them with samples of normal tissue downloaded from The Cancer Genome Atlas (TCGA), ultimately screening 38 differentially expressed NRGs (DE-NRGs). Then, by Cox regression analysis, we successfully identified 7 NRGs as prognostic factors. We next separated patients into high- and low-risk groups via the prognostic model consisting of 7 NRGs. Individuals in the high-risk group had much shorter overall survival (OS) times than their counterparts. Furthermore, using Cox regression analysis, we confirmed the necroptosis-related prognostic model to be an independent prognostic factor for HNSCC. Receiver operating characteristic (ROC) curve analysis proved the predictive ability of this model. Finally, Gene Expression Omnibus (GEO) data sets (GSE65858, GSE4163) were used as independent databases to verify the model’s predictive ability, and similar results obtained from two data sets confirmed our conclusion. Collectively, in this study, we first referred to necroptosis-related signatures as an independent prognostic model for cancer via bioinformatics measures, and the necroptosis-related prognostic model we constructed could precisely forecast the OS time of patients with HNSCC. Utilizing the model may significantly improve the diagnostic rate and provide a series of new targets for treatment in the future.

Construction of an abnormal glycosylation risk model and its application in predicting the prognosis of patients with head and neck cancer

“…Ultimately, a LASSO linear regression method was employed to screen and select 16 prognostic marker genes, which were utilized to construct a prognostic model. Furthermore, the clinical and expression data for GSE65858 and GSE41613 were obtained from the Gene Expression Omnibus (GEO) database ( https://www.ncbi.nlm.nih.gov/geo/ ) to serve as the validation set for the risk model 8 .…”

Immune infiltration and a necroptosis-related gene signature for predicting the prognosis of patients with cervical cancer

“…We identified 651 genes associated with necrotizing apoptosis via GeneCards. A published study proposed 159 genes (Zhang et al, 2022). After removing the duplicated genes involved in the above GO terms, we had a total of 749 NRGs for the downstream analysis.…”

A novel necroptosis-related model predicts the prognosis and immunocompetence of head and neck squamous cell carcinoma

“…About 50% of necrosis in HNSCC is caused by necroptosis and suggested that necroptosis can release damage-associated molecular patterns (DAMPs) to promote cancer metastasis and cancer progression (11). The necroptosis-related prognostic risk model established by Zhang Z et al for HNSCC included 7 necroptosis-related genes (NRGs) that were significantly associated with the prognosis of HNSCC (12). However, after extracting the expression levels of 7 NRGs from the RNA-seq of HNSCC patients in the TCGA database, we found that there was no significant difference in the expression levels of VDAC1 and CHMP3 between HNSCC tissues and normal tissues, and the expression level of TRAF5 was relatively low.…”