A novel pyroptosis-related gene signature for predicting the prognosis of cervical cancer

Although morbidity has decreased in developed regions, cervical cancer (CC) continues to have the highest incidence of all gynecological malignancies. The burden of morbidity and mortality in developing regions is also rising quickly, especially for advanced CC. Along with apoptosis, iron death, and other forms of programmed cell death, pyroptosis is a significant inflammatory process. Its connection to the malignancy mechanism has been verified. The expression of genes linked to pyroptosis in CC tissue and its relationship to prognosis, however, remain poorly understood. Using The Cancer Genome Atlas, we first discovered 13 differentially expressed pyroptosis-related genes (DE-PRGs) in the study (TCGA). Based on DE-PRGs, CC patients were divided into four subtypes. The 4 parts’ times showed large variations according to the K-M curve. Then, using the least absolute shrinkage and selection operator (LASSO) Cox regression method, we created a mod el for predicting CC based on pyroptosis-associated genes. There were significant differences in overall survival (OS) times involving the high-risk and low-risk groups for all CC patients in the TCGA group, who were divided into low-risk and high-risk groups (p equals 0.0441). The risk score status as an independent prognostic factor for CC was confirmed by independent prognostic predictor validation. The analyses of single-sample gene set and enrichment analysis (ssGSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) all revealed significant differences in immune cells and immune pathways involving high- and low-risk groups (p less than 0.001), indicating a weakened immune status in high-risk groups. In conclusion, pyroptosis-associated genes are involved in tumor immunity and can help determine a patient’s prognosis for CC. As a result, we have created and validated a signature that is related to pyroptosis and predicts CC prognosis, which may aid in early diagnosis, prognostic analysis, and immunotherapy.