Establishing a Novel Pyroptosis-Related Gene Signature and Predicting Chemical Drugs for Papillary Thyroid Cancer

Background: The present study aimed to construct a novel pyroptosis-related gene signature to predict the prognosis of papillary thyroid cancer (PTC).

Methods: The gene expression level and survival and prognosis information of PTC were obtained from TCGA. The differentially expressed pyroptosis-related genes (DEPs) between cancer and control groups were selected, followed by subtype analysis. A prognostic model was built using LASSO regression analysis. The samples were then divided into high- and low-risk groups, and the differences in immune cell distribution in different risk groups were compared. The chemical drugs associated with genes in the prognostic model were extracted from the Comparative Toxicogenomics Database.

Results: A total of 31 DEPs were selected, and 3 different subtypes were obtained. A prognostic model based on 6 pyroptosis-related genes was constructed. The risk grouping was significantly correlated with the actual prognosis, and the model was found to be an independent prognostic factor. Six immune cells with significant differences in distribution in different risk groups were screened. CGP52608 could target four genes in the prognostic model, including GSDMB, NLRC4, IL1A, and IL6.

Conclusion: The present study constructed a pyroptosis-related gene signature that could predict the prognosis of PTC. Additionally, this signature was correlated with tumor immunity.