Frontiers in Genetics (Sep 2022)

Development of a prognostic prediction model based on a combined multi-omics analysis of head and neck squamous cell carcinoma cell pyroptosis-related genes

  • Bin Chen,
  • Bin Chen,
  • Bin Chen,
  • Yuanbo Luo,
  • Yuanbo Luo,
  • Yuanbo Luo,
  • Xueran Kang,
  • Xueran Kang,
  • Xueran Kang,
  • Yuxing Sun,
  • Yuxing Sun,
  • Yuxing Sun,
  • Chenyan Jiang,
  • Chenyan Jiang,
  • Chenyan Jiang,
  • Bin Yi,
  • Bin Yi,
  • Bin Yi,
  • Xiaojun Yan,
  • Xiaojun Yan,
  • Xiaojun Yan,
  • Yisheng Chen,
  • Runjie Shi,
  • Runjie Shi,
  • Runjie Shi

DOI
https://doi.org/10.3389/fgene.2022.981222
Journal volume & issue
Vol. 13

Abstract

Read online

This study aimed to understand the prognosis of patients with head and neck squamous cell carcinoma (HNSCC) and to develop and validate a prognostic model for HNSCC based on pyroptosis-associated genes (PAGs) in nasopharyngeal carcinoma. The Cancer Genome Atlas database was used to identify differentially expressed PAGs. These genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes functional annotation analyses and Gene Ontology analyses. The NLR family pyrin domain containing 1 (NLRP1) gene, charged multivesicular body protein 7 (CHMP7) gene, and cytochrome C (CYCS) gene were used to create a prognostic model for HNSCC. The results of the Kaplan-Meier (K-M) and Cox regression analyses indicated that the developed model served as an independent risk factor for HNSCC. According to the K-M analysis, the overall survival of high-risk patients was lower than that of low-risk patients. The hazard ratios corresponding to the risk scores determined using the multivariate and univariate Cox regression analyses were 1.646 (95% confidence interval (CI): 1.189–2.278) and 1.724 (95% CI: 1.294–2.298), respectively, and the area under the receiver operator characteristic curve was 0.621. The potential mechanisms associated with the functions of the identified genes were then identified, and the tumor microenvironment and levels of immune cell infiltration achieved were analyzed. The immune infiltration analysis revealed differences in the distribution of Th cells, tumor-infiltrating lymphocytes, regulatory T cells, follicular helper T cells, adipose-derived cells, interdigitating dendritic cells, CD8+ T cells, and B cells. However, validating bioinformatics analyses through biological experiments is still recommended. This study developed a prognostic model for HNSCC that included NLRP1, CHMP7, and CYCS.

Keywords