Medical Faculty of Ludwig-Maximilians-University of Munich, University Hospital of LMU Munich, Munich, Germany.
Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Dis Markers. 2022 May 29;2022:9141117. doi: 10.1155/2022/9141117. eCollection 2022.
The importance of pyroptosis in tumorigenesis and cancer progression is becoming increasingly apparent. However, the efficacy of using pyroptosis-related genes (PRGs) in predicting the prognosis of pancreatic adenocarcinoma (PAAD) patients is unknown.
This investigation used two databases to obtain expression data for PAAD patients. Differentially expressed PRGs (DEPRGs) were identified between PAAD and control samples. Several bioinformatic approaches were used to analyze the biological functions of DEPRGs and to identify prognostic DERPGs. A miRNA-prognostic DEPRG-transcription factor (TF) regulatory network was created via the miRNet online tool. A risk score model was created after each patient's risk score was calculated. The microenvironments of the low- and high-risk groups were assessed using xCell, the expression of immune checkpoints was determined, and gene set variation analysis (GSVA) was performed. Finally, the efficacy of certain potential drugs was predicted using the pRRophetic algorithm, and the results in the high- and low-risk groups were compared.
A total of 13 DEPRGs were identified between PAAD and control samples. Functional enrichment analysis showed that the DEPRGs had a close relationship with inflammation. In univariate and multivariate Cox regression analyses, GSDMC, IRF1, and PLCG1 were identified as prognostic biomarkers in PAAD. The results of the miRNA-prognostic DEPRG-TF regulatory network showed that GSDMC, IRF1, and PLCG1 were regulated by both specific and common miRNAs and TFs. Based on the risk score and other independent prognostic indicators, a nomogram with a good ability to predict the survival of PAAD patients was developed. By evaluating the tumor microenvironment, we observed that the immune and metabolic microenvironments of the two groups were substantially different. In addition, individuals in the low-risk group were more susceptible to axitinib and camptothecin, whereas lapatinib might be preferred for patients in the high-risk group.
Our study revealed the prognostic value of PRGs in PAAD and created a reliable model for predicting the prognosis of PAAD patients. Our findings will benefit the prognostication and treatment of PAAD patients.
细胞焦亡在肿瘤发生和癌症进展中的重要性日益明显。然而，利用细胞焦亡相关基因（PRGs）预测胰腺导管腺癌（PAAD）患者预后的效果尚不清楚。
本研究使用两个数据库获取 PAAD 患者的表达数据。比较 PAAD 样本和对照样本之间差异表达的 PRGs（DEPRGs）。采用多种生物信息学方法分析 DEPRGs 的生物学功能，并鉴定预后 DEPRGs。通过 miRNet 在线工具构建 miRNA-预后 DEPRG-转录因子（TF）调控网络。计算每位患者的风险评分后，建立风险评分模型。使用 xCell 评估低风险组和高风险组的微环境，测定免疫检查点的表达，并进行基因集变异分析（GSVA）。最后，使用 pRRophetic 算法预测某些潜在药物的疗效，并比较高低风险组的结果。
在 PAAD 样本和对照样本之间共鉴定出 13 个 DEPRGs。功能富集分析表明，DEPRGs 与炎症密切相关。在单因素和多因素 Cox 回归分析中，GSDMC、IRF1 和 PLCG1 被鉴定为 PAAD 的预后生物标志物。miRNA-预后 DEPRG-TF 调控网络的结果表明，GSDMC、IRF1 和 PLCG1 受到特异性和共同 miRNA 和 TF 的调控。基于风险评分和其他独立的预后指标，构建了一个具有良好预测 PAAD 患者生存能力的列线图。通过评估肿瘤微环境，我们观察到两组的免疫和代谢微环境存在显著差异。此外，低风险组的个体对阿昔替尼和喜树碱更敏感，而拉帕替尼可能更适合高风险组的患者。
本研究揭示了 PRGs 在 PAAD 中的预后价值，并建立了一个可靠的模型来预测 PAAD 患者的预后。我们的研究结果将有助于 PAAD 患者的预后和治疗。
