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<p>Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a five-year survival rate below 10%. Regulatory cell death (RCD) plays a critical role in tumor progression and therapy response, yet its prognostic implications in PDAC remain underexplored. In this study, we systematically investigated RCD-related genes using bulk RNAseq and single-cell RNAseq cohorts. By integrating 101 machine learning algorithm combinations, we developed a prognostic signature named the RCD index (RCDI), which demonstrated robust performance in predicting overall survival and clinical outcomes of PDAC patients. Furthermore, we explored the immune heterogeneity associated with different RCDI scores, including immune cell infiltration profiles, immune-related functional pathways, and immunotherapy-related biomarkers. Our results revealed that RCDI is significantly correlated with the tumor immune microenvironment and may serve as a potential indicator for stratifying PDAC patients who could benefit from immune checkpoint blockade therapy. Overall, this study provides a novel tool for risk stratification and individualized treatment in PDAC patients.</p>

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Elucidating the pathway activity and prognostic significance of diverse regulatory cell death patterns in pancreatic ductal adenocarcinoma

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月27日

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  • Lingling Jin,
  • Yanwen Chen,
  • Jiazheng Sun,
  • Honglu Yu

摘要

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a five-year survival rate below 10%. Regulatory cell death (RCD) plays a critical role in tumor progression and therapy response, yet its prognostic implications in PDAC remain underexplored. In this study, we systematically investigated RCD-related genes using bulk RNAseq and single-cell RNAseq cohorts. By integrating 101 machine learning algorithm combinations, we developed a prognostic signature named the RCD index (RCDI), which demonstrated robust performance in predicting overall survival and clinical outcomes of PDAC patients. Furthermore, we explored the immune heterogeneity associated with different RCDI scores, including immune cell infiltration profiles, immune-related functional pathways, and immunotherapy-related biomarkers. Our results revealed that RCDI is significantly correlated with the tumor immune microenvironment and may serve as a potential indicator for stratifying PDAC patients who could benefit from immune checkpoint blockade therapy. Overall, this study provides a novel tool for risk stratification and individualized treatment in PDAC patients.