卵巢癌（OC）是一种威胁女性健康的肿瘤，其高死亡率和不良预后引起了严重关注。热原性细胞凋亡（pyroptosis）作为一种程序性细胞死亡形式，对于决定患者的癌症预后具有重要意义，可能成为一种新的治疗靶点。然而，目前对热原性细胞凋亡相关基因（PRGs）对预后的影响的研究还不充分。本研究利用OC中PRGs的生物信息学分析，构建了预后模型。在OC中，我们发现了18个上调或下调的热原性调节因子。通过分析预后，我们建立了一个基于9个基因的预后模型。每个OC患者都得到一个风险评分，可以将其分为高风险和/或低生存几率的亚组以及低风险和/或高生存几率的亚组。功能富集和免疫浸润分析表明，高风险组中免疫通路的低表达可能是导致生存几率降低的原因。多变量Cox回归研究发现，年龄、临床分期和预后模型是影响OC预后的独立因素。为了预测OC患者的生存情况，我们开发了一个预测性判分卡（nomogram）。此外，我们发现预测性PRGs与临床分期之间存在相关性，表明AIM2、CASP3、ZBP1和CASP8可能在OC肿瘤生长中起到某种作用。经过详细和完整的生物信息学分析，我们在OC中鉴定了lncRNA RP11-186B7.4/hsa-miR-449a/CASP8/AIM2/ZBP1的调控轴。我们的研究可能为OC的预后生物标志物和治疗靶点提供一种新的方法。版权所有 © 2023 Elsevier Ltd. 保留所有权利。

Ovarian cancer (OC), is a tumor that poses a serious threat to women's health due to its high mortality rate and bleak prognosis. Pyroptosis, a type of programmed cell death, is important for determining the prognosis of a patient's prognosis for cancer and may represent a novel target for treatment. However, research into how prognosis is impacted by pyroptosis-related genes (PRGs) is poorly understood. In this study, a prognostic model was created using bioinformatic analysis of PRGs in OC. In OC, we discovered 18 pyroptosis regulators that were either up- or down-regulated. By analyzing prognoses, we developed a 9-genes based prognostic model. Each OC patient received a risk score that could be used to categorize them into two subgroups: those with high risk and/or low chance of survival and those with low risk and/or high chance of survival. Functional enrichment and immunoinfiltration analysis indicated that low expression of immune pathways in high-risk group may account for the decrease of survival possibility. In Multivariable cox regression studies, age, clinical stage and the prognostic model were discovered to be independent factors impacting the prognosis for OC. To forecast OC patient survival, a predictive nomogram was developed. Furthermore, we found a correlation between predictive PRGs and clinical stage, indicating that AIM2, CASP3, ZBP1 and CASP8 may play a role in the growth of tumor in OC. After detailed and complete bioinformatics analysis, the lncRNA RP11-186B7.4/hsa-miR-449a/CASP8/AIM2/ZBP1 regulatory axis was identified in OC. Our study may provide a novel approach for prognostic biomarkers and therapeutic targets of OC.Copyright © 2023 Elsevier Ltd. All rights reserved.