ArticleJournal of thoracic disease2023
A novel pyroptosis-related model for prognostic prediction in esophageal squamous cell carcinoma: a bioinformatics analysis.
Article in Journal of thoracic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- PCBP2 mediates MTUS1 degradation through 3'-UTR binding to restrict pyroptosis and augment malignant progression in esophageal squamous cell carcinoma.Esophagus : official journal of the Japan Esophageal Society · 2026Article
- Complex biological systems analysis and deep learning for prognostic prediction of esophageal squamous cell carcinoma.iScience · 2026Article
- Progress of arylacetamide deacetylase research in metabolic diseases.Frontiers in oncology · 2025Review
- Epigenetics Meets CAR-T-Cell Therapy to Fight Cancer.Cancers · 2024Article
- Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Esophageal squamous cell carcinoma (ESCC) has a poor prognosis, and the 5-year survival rate is less than 30%. Better differentiation of patients at high risk of recurrence or metastasis could guide clinical treatment. The close relationship between pyroptosis and ESCC has been recently reported. Herein, we aimed to identify genes associated with pyroptosis in ESCC and construct a prognostic risk model. Methods: RNA-seq data of ESCC was obtained from the The Cancer Genome Atlas (TCGA) database. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were used to calculate the pyroptosis-related pathway score (Pys). Weighted gene co-expression network analysis (WGCNA) and univariate Cox regression were used to screen for pyroptotic genes associated with prognosis, and Lasso regression was used to establish a risk score. Finally, the T test was used to compare the relationship between the model and tumor-node-metastasis (TNM) stage. Furthermore, we compared the difference of immune infiltrating cells and immune checkpoints between the low- and high-risk groups. Results: Using WGCNA, 283 genes were significantly associated with N staging and Pys. Among them, univariate Cox analysis suggested that 83 genes were associated with prognosis of ESCC patients. After that, Conclusions: Our study identified 3 prognosis pyroptosis-related genes in the ESCC and successfully build a prognostic model.
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