Glycolysis related gene expression signature in predicting prognosis of laryngeal squamous cell carcinoma

Bioengineered. 2021 Dec;12(1):8738-8752. doi: 10.1080/21655979.2021.1980177.

Abstract

Researches have suggested that aerobic glycolysis can reflect the development and progression of most carcinomas. We aimed to investigate whether glycolysis-related genes (GRGs) are associated with overall survival in laryngeal squamous cell carcinoma (LSCC). Here, we identified differentially expressed GRGs in TCGA dataset and microarray sample of GSE27020 from GEO database. A set of two glycolytic gene signatures, including DDIT4 and PLOD2 was screened through Cox and Lasso regression. The risk score was calculated using the gene expression of the two GRGs. The high-risk group presented a poor prognosis through Kaplan-Meier method. The ROC curve indicated good prediction performance in survival based on the validation of four cohorts. Univariate and multivariate Cox regression analyses suggested that two-gene signature could be an independent risk factor in LSCC. A total of 17 LSCC patients were enrolled to clarify the genetic expression through using reverse transcription-polymerase chain reaction (RT-PCR). A visualized nomogram was then constructed to predict 1-, 3-, and 5-year overall survival. Taken together, two novel glycolytic gene signatures were discovered and validated, providing a potential therapeutic and overall survival (OS)-prediction biomarker for LSCC.

Keywords: GEO; Laryngeal squamous cell carcinoma; TCGA; gene signature; prognosis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / metabolism*
  • Carcinoma, Squamous Cell / genetics
  • Carcinoma, Squamous Cell / metabolism
  • Carcinoma, Squamous Cell / pathology
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic*
  • Glycolysis*
  • Humans
  • Laryngeal Neoplasms / genetics
  • Laryngeal Neoplasms / metabolism
  • Laryngeal Neoplasms / pathology*
  • Nomograms*
  • Prognosis
  • ROC Curve
  • Survival Rate
  • Transcriptome*

Substances

  • Biomarkers, Tumor

Grants and funding

This study was supported by the National Natural Science Foundation of China (Grant No. 81972529), the Science and Technology Commission of Shanghai Municipality (Grant No. 19411961300).