Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China.
Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Sci Rep. 2023 Oct 16;13(1):17577. doi: 10.1038/s41598-023-43036-7.
Pancreatic cancer (PC) is known for its high degree of heterogeneity and exceptionally adverse outcome. While disulfidptosis is the most recently identified form of cell death, the predictive and therapeutic value of disulfidptosis-related genes (DRGs) for PC remains unknown. RNA sequencing data with the follow-up information, were retrieved from the TCGA and ICGC databases. Consensus clustering analysis was conducted on patient data using R software. Subsequently, the LASSO regression analysis was conducted to create a prognostic signature for foreseeing the outcome of PC. Differences in relevant pathways, mutational landscape, and tumor immune microenvironment were compared between PC samples with different risk levels. Finally, we experimentally confirmed the impact of DSG3 on the invasion and migration abilities of PC cells. All twenty DRGs were found to be hyperexpressed in PC tissues, and fourteen of them significantly associated with PC survival. Using consensus clustering analysis based on these DRGs, four DRclusters were identified. Additionally, altogether 223 differential genes were evaluated between clusters, indicating potential biological differences between them. Four gene clusters (geneClusters) were recognized according to these genes, and a 10-gene prognostic signature was created. High-risk patients were found to be primarily enriched in signaling pathways related to the cell cycle and p53. Furthermore, the rate of mutations was markedly higher in high-risk patients, besides important variations were present in terms of immune microenvironment and chemotherapy sensitivity among patients with different risk levels. DSG3 could appreciably enhance the invasion and migration of PC cells. This work, based on disulfidoptosis-related genes (DRGs), holds the promise of classifying PC patients and predicting their prognosis, mutational landscape, immune microenvironment, and drug therapy. These insights could boost an improvement in a better comprehension of the role of DRGs in PC as well as provide new opportunities for prognostic prediction and more effective treatment strategies.
胰腺癌（PC）以高度异质性和极差的预后而闻名。虽然二硫键凋亡是最近发现的细胞死亡形式，但二硫键凋亡相关基因（DRGs）对 PC 的预测和治疗价值仍不清楚。从 TCGA 和 ICGC 数据库中检索到具有随访信息的 RNA 测序数据。使用 R 软件对患者数据进行共识聚类分析。随后，进行 LASSO 回归分析，为预测 PC 结局创建预后特征。比较不同风险水平的 PC 样本之间相关通路、突变景观和肿瘤免疫微环境的差异。最后，我们通过实验证实了 DSG3 对 PC 细胞侵袭和迁移能力的影响。所有 20 个 DRGs 在 PC 组织中均高表达，其中 14 个与 PC 生存显著相关。基于这些 DRGs 的共识聚类分析，确定了四个 DRclusters。此外，在聚类之间评估了总共 223 个差异基因，表明它们之间存在潜在的生物学差异。根据这些基因，识别出四个基因簇（geneClusters），并创建了一个 10 基因预后特征。高风险患者主要富集在与细胞周期和 p53 相关的信号通路中。此外，高风险患者的突变率明显更高，不同风险水平患者的免疫微环境和化疗敏感性也存在重要差异。DSG3 可显著增强 PC 细胞的侵袭和迁移能力。这项基于二硫键凋亡相关基因（DRGs）的工作有望对 PC 患者进行分类并预测其预后、突变景观、免疫微环境和药物治疗。这些发现可以提高对 DRGs 在 PC 中的作用的更好理解，并为预后预测和更有效的治疗策略提供新的机会。
