本研究基于 19 个 PANoptosis 相关基因特征对胆道癌患者进行分子分型。通过共识聚类，将患者分为 A 和 B 两个亚型。通过整合多组学数据和不同队列的临床信息，我们阐明了胆道癌不同亚型与患者预后的相关性，与患者的免疫浸润特征相关。对19个基因特征进行LASSO回归分析，构建并验证了9个基因风险评分预后模型，该模型可以准确预测胆道癌的预后。不同胆道癌患者的总生存率。此外，我们还开发了一个预测列线图，展示了我们模型的临床实用性和稳健性。对基于风险评分的免疫景观的进一步分析强调了与免疫细胞浸润、化疗和免疫治疗反应的潜在关联。我们的研究为胆道癌的个性化治疗策略提供了宝贵的见解，这对于改善患者预后和指导治疗决策至关重要在临床实践中。© 2024。作者。

This study conducted molecular subtyping of biliary tract cancer patients based on 19 PANoptosis-related gene signatures.Through consensus clustering, patients were categorized into two subtypes, A and B. By integrating multi-omics data and clinical information from different cohorts, we elucidated the association between different subtypes of biliary tract cancer and patient prognosis, which correlated with the immune infiltration characteristics of patients.LASSO regression analysis was performed on the 19 gene signatures, and we constructed and validated a 9-gene risk score prognostic model that accurately predicts the overall survival rate of different biliary tract cancer patients. Additionally, we developed a predictive nomogram demonstrating the clinical utility and robustness of our model. Further analysis of the risk score-based immune landscape highlighted potential associations with immune cell infiltration, chemotherapy, and immune therapy response.Our study provides valuable insights into personalized treatment strategies for biliary tract cancer, which are crucial for improving patient prognosis and guiding treatment decisions in clinical practice.© 2024. The Author(s).