PDF(Pubmed)
Abstract：
Pancreatic cancer (PAC) is one of the most malignant cancer types and immunotherapy has emerged as a promising treatment option. PAC cells undergo metabolic reprogramming, which is thought to modulate the tumor microenvironment (TME) and affect immunotherapy outcomes. However, the metabolic landscape of PAC and its association with the TME remains largely unexplored.
We characterized the metabolic landscape of PAC based on 112 metabolic pathways and constructed a novel metabolism-related signature (MBS) using data from 1,188 patients with PAC. We evaluated the predictive performance of MBS for immunotherapy outcomes in 11 immunotherapy cohorts from both bulk-RNA and single-cell perspectives. We validated our results using immunohistochemistry, western blotting, colony-formation assays, and an in-house cohort.
MBS was found to be negatively associated with antitumor immunity, while positively correlated with cancer stemness, intratumoral heterogeneity, and immune resistant pathways. Notably, MBS outperformed other acknowledged signatures for predicting immunotherapy response in multiple immunotherapy cohorts. Additionally, MBS was a powerful and robust biomarker for predicting prognosis compared with 66 published signatures. Further, we identified dasatinib and epothilone B as potential therapeutic options for MBS-high patients, which were validated through experiments.
Our study provides insights into the mechanisms of immunotherapy resistance in PAC and introduces MBS as a robust metabolism-based indicator for predicting response to immunotherapy and prognosis in patients with PAC. These findings have significant implications for the development of personalized treatment strategies in patients with PAC and highlight the importance of considering metabolic pathways and immune infiltration in TME regulation.
We characterized the metabolic landscape of PAC based on 112 metabolic pathways and constructed a novel metabolism-related signature (MBS) using data from 1,188 patients with PAC. We evaluated the predictive performance of MBS for immunotherapy outcomes in 11 immunotherapy cohorts from both bulk-RNA and single-cell perspectives. We validated our results using immunohistochemistry, western blotting, colony-formation assays, and an in-house cohort.
MBS was found to be negatively associated with antitumor immunity, while positively correlated with cancer stemness, intratumoral heterogeneity, and immune resistant pathways. Notably, MBS outperformed other acknowledged signatures for predicting immunotherapy response in multiple immunotherapy cohorts. Additionally, MBS was a powerful and robust biomarker for predicting prognosis compared with 66 published signatures. Further, we identified dasatinib and epothilone B as potential therapeutic options for MBS-high patients, which were validated through experiments.
Our study provides insights into the mechanisms of immunotherapy resistance in PAC and introduces MBS as a robust metabolism-based indicator for predicting response to immunotherapy and prognosis in patients with PAC. These findings have significant implications for the development of personalized treatment strategies in patients with PAC and highlight the importance of considering metabolic pathways and immune infiltration in TME regulation.
摘要：
背景：胰腺癌（PAC）是最恶性的癌症类型之一，免疫疗法已成为有希望的治疗选择。PAC细胞经历代谢重编程，被认为可以调节肿瘤微环境（TME）并影响免疫治疗结果。然而,PAC的代谢景观及其与TME的关联在很大程度上仍未被探索。
方法：我们基于112个代谢途径对PAC的代谢景观进行了表征，并使用来自1,188名PAC患者的数据构建了新的代谢相关特征（MBS）。我们从bulk-RNA和单细胞角度评估了11个免疫治疗队列中MBS对免疫治疗结果的预测性能。我们用免疫组织化学验证了我们的结果，西方印迹,集落形成试验,和一个内部队列。
结果：发现MBS与抗肿瘤免疫呈负相关，虽然与癌症干性呈正相关，肿瘤内异质性，和免疫抗性途径。值得注意的是,MBS在预测多个免疫治疗队列中的免疫治疗反应方面优于其他公认的特征。此外,与66个已发表的标记相比，MBS是预测预后的强大而强大的生物标志物。Further,我们确定达沙替尼和埃坡霉素B是MBS高患者的潜在治疗选择，通过实验验证。
结论：我们的研究提供了对PAC免疫治疗耐药机制的见解，并将MBS作为一个可靠的基于代谢的指标，用于预测PAC患者对免疫治疗的反应和预后。这些发现对PAC患者个性化治疗策略的发展具有重要意义，并强调了在TME调节中考虑代谢途径和免疫浸润的重要性。
方法：我们基于112个代谢途径对PAC的代谢景观进行了表征，并使用来自1,188名PAC患者的数据构建了新的代谢相关特征（MBS）。我们从bulk-RNA和单细胞角度评估了11个免疫治疗队列中MBS对免疫治疗结果的预测性能。我们用免疫组织化学验证了我们的结果，西方印迹,集落形成试验,和一个内部队列。
结果：发现MBS与抗肿瘤免疫呈负相关，虽然与癌症干性呈正相关，肿瘤内异质性，和免疫抗性途径。值得注意的是,MBS在预测多个免疫治疗队列中的免疫治疗反应方面优于其他公认的特征。此外,与66个已发表的标记相比，MBS是预测预后的强大而强大的生物标志物。Further,我们确定达沙替尼和埃坡霉素B是MBS高患者的潜在治疗选择，通过实验验证。
结论：我们的研究提供了对PAC免疫治疗耐药机制的见解，并将MBS作为一个可靠的基于代谢的指标，用于预测PAC患者对免疫治疗的反应和预后。这些发现对PAC患者个性化治疗策略的发展具有重要意义，并强调了在TME调节中考虑代谢途径和免疫浸润的重要性。
