皮肤黑色素瘤（SKCM）是最具侵袭性的皮肤癌，占皮肤相关癌症死亡率的 75% 以上。作为一种新发现的程序性细胞死亡，焦亡已被发现与肿瘤进展密切相关。然而，SKCM 中焦亡的预后意义仍然难以捉摸。从癌症基因组图谱 (TCGA) 和基因型组织表达 (GTEx) 数据库中获得了总共 469 个 SKCM 样本和 812 个正常样本。首先，鉴定了正常样本和SKCM样本之间差异表达的细胞焦亡相关基因（PRG）。其次，我们建立了基于单变量 Cox 和 LASSO Cox 回归分析的预后模型，该模型在 GSE65904 的测试队列中得到了验证。第三，使用列线图来预测 SKCM 患者的生存概率。 R 包“pRRophetic”用于识别低风险组和高风险组之间的药物敏感性。使用“immuneeconv”R 包评估肿瘤免疫浸润。最后，探讨了 GSDMD 和 SB525334 在 A375 和 A2058 细胞中的功能。基于单变量 Cox 和 LASSO 回归分析，我们建立了一个预后模型，确定了 8 个 PRG（AIM2、CASP3、GSDMA、GSDMC、GSDMD、IL18、NLRP3 和NOD2），这在测试队列中得到了验证。根据风险评分中位数将 SKCM 患者分为低风险组和高风险组。 Kaplan-Meier 生存分析显示，高危患者的总生存期短于低危患者。此外，时间依赖性 ROC 曲线验证了风险模型预测 SKCM 预后的准确性。更重要的是，鉴定出4种小分子化合物（SB525334、SR8278、吉西他滨、AT13387），它们可能是不同风险组患者的潜在药物。最后，GSDMD 的过表达和 SB525334 治疗抑制 SKCM 细胞的增殖、迁移和侵袭。在本研究中，我们构建了基于 PRG 的预后模型，并将 GSDMD 确定为潜在的治疗靶点，这为 SKCM 治疗提供了新的见解。© 2023。作者。

Skin cutaneous melanoma (SKCM) is the most aggressive skin cancer, accounting for more than 75% mortality rate of skin-related cancers. As a newly identified programmed cell death, pyroptosis has been found to be closely associated with tumor progression. Nevertheless, the prognostic significance of pyroptosis in SKCM remains elusive.A total of 469 SKCM samples and 812 normal samples were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Firstly, differentially expressed pyroptosis-related genes (PRGs) between normal samples and SKCM samples were identified. Secondly, we established a prognostic model based on univariate Cox and LASSO Cox regression analyses, which was validated in the test cohort from GSE65904. Thirdly, a nomogram was used to predict the survival probability of SKCM patients. The R package "pRRophetic" was utilized to identify the drug sensitivity between the low- and high-risk groups. Tumor immune infiltration was evaluated using "immuneeconv" R package. Finally, the function of GSDMD and SB525334 was explored in A375 and A2058 cells.Based on univariate Cox and LASSO regression analyses, we established a prognostic model with identified eight PRGs (AIM2, CASP3, GSDMA, GSDMC, GSDMD, IL18, NLRP3, and NOD2), which was validated in the test cohort. SKCM patients were divided into low- and high-risk groups based on the median of risk score. Kaplan-Meier survival analysis showed that high-risk patients had shorter overall survival than low-risk patients. Additionally, time-dependent ROC curves validated the accuracy of the risk model in predicting the prognosis of SKCM. More importantly, 4 small molecular compounds (SB525334, SR8278, Gemcitabine, AT13387) were identified, which might be potential drugs for patients in different risk groups. Finally, overexpression of GSDMD and SB525334 treatment inhibit the proliferation, migration, and invasion of SKCM cells.In this study, we constructed a prognostic model based on PRGs and identified GSDMD as a potential therapeutic target, which provide new insights into SKCM treatment.© 2023. The Author(s).