基于机器学习的整合方法开发了一种基于代谢的共识模型,用于改善胰腺癌的免疫治疗。
Machine learning-based integration develops a metabolism-derived consensus model for improving immunotherapy in pancreatic cancer.
发表日期:2023 Sep
作者:
Yongdong Guo, Ronglin Wang, Jingjie Shi, Cheng Yang, Peixiang Ma, Jie Min, Ting Zhao, Lei Hua, Yang Song, Junqiang Li, Haichuan Su
来源:
Journal for ImmunoTherapy of Cancer
摘要:
胰腺癌(PAC)是最恶性的癌症类型之一,并且免疫疗法已经成为一种有希望的治疗选择。PAC细胞经历代谢重编程,被认为会调节肿瘤微环境(TME)并影响免疫疗法的结果。然而,PAC的代谢景观及其与TME的关联仍然未被广泛探索。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患者的数据构建了一个新的代谢相关标记(MBS)。我们从批量RNA和单细胞的角度评估了MBS对11个免疫疗法队列的预测性能。我们通过免疫组织化学、免疫印迹、集落形成实验和内部队列验证了我们的结果。我们发现MBS与抗肿瘤免疫呈负相关,同时与癌症干细胞性、肿瘤内多样性和免疫抵抗途径呈正相关。值得注意的是,MBS在多个免疫疗法队列中的预测免疫疗法反应的性能优于其他公认的标记。此外,与已发表的66个标记相比,MBS是一种强有力且稳健的预测生存的生物标记。此外,我们通过实验确定了达沙替尼和埃泼托啉B作为高MBS患者的潜在治疗选择,并进行了验证。我们的研究揭示了PAC免疫疗法抗性机制,并引入MBS作为预测PAC患者对免疫疗法反应和预后的稳健基于代谢的指标。这些发现对于开发个体化治疗策略有重要意义,并强调在TME调控中考虑代谢途径和免疫浸润的重要性。© 作者(或其雇主)2023。根据CC BY-NC许可,允许重新使用。由BMJ出版。
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.© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.