A Novel Pyroptotic and Inflammatory Gene Signature Predicts the Prognosis of Cutaneous Melanoma and the Effect of Anticancer Therapies - Xu, Yujian; Chen, Youbai; Niu, Zehao; Xing, Jiahua; Yang, Zheng; Yin, Xiangye; Guo, Lingli; Zhang, Qixu; Qiu, Haixia; Han, Yan (Frontiers in Medicine, 2022)
Purpose: The purpose of this study was to construct a gene signature comprising genes related to both inflammation and pyroptosis (GRIPs) to predict the prognosis of cutaneous melanoma (CM) patients and the efficacy of immunotherapy, chemotherapy, and targeted therapy in these patients. Methods: WGCNA was performed to identify GRIPs. Multivariate Cox regression further identified genes to construct a risk score. Areas under the ROC curves (AUCs) were calculated and Kaplan-Meier analyses were performed for the two groups, following validation in an external cohort from GEO. Multivariable Cox regression identified independent predictors. A nomogram including the GRIP signature and clinicopathological characteristics was developed for clinical use. Gene set enrichment analyses (GSEA) illustrated differentially-enriched pathways. Differences in the tumor microenvironment (TME) between the two groups were assessed. The efficacies of immune checkpoint inhibitors (ICIs), chemotherapeutic agents, and targeted agents were predicted for both groups. Immunohistochemical analyses of the GRIPs between the normal and CM tissues were performed using the Human Protein Atlas (HPA) data. Results: A novel gene signature comprising 9 GRIPs (TLR1, CCL8, EMP3, IFNGR2, CCL25, IL15, RTP4, and NLRP6) was constructed. The signature had AUCs of 0.714 and 0.670 for predicting 3-year OS in the TCGA, and GEO cohorts, respectively. Kaplan-Meier analyses revealed that the high-risk group had poorer prognosis. The nomogram showed good accuracy and reliability in predicting 3-year OS (AUC = 0.810). GSEA and TME analysis showed that the high-risk group had lower levels of pyroptosis, inflammation, and immune response such as lower levels of CD8+ T-cell infiltration, CD4+ memory-activated T-cell infiltration, and immune checkpoint activation. In addition, low-risk patients whose disease expressed PD-1 or CTLA-4 were likely to respond better to ICIs, and several chemotherapeutic and targeted agents. Immunohistochemical analysis confirmed the distinct expression of 5 out of the 8 GRIPs between normal and CM tissues. Conclusion: Our novel 8-GRIP signature can accurately predict the prognosis of CM patients and the efficacies of multiple anticancer therapies. These GRIPs might be potential prognostic biomarkers and therapeutic targets for CM.