Systems biology analysis of vaccine-induced immunity to infectious diseases in cancer patients

传染病对全球健康构成重大威胁，2019年在全球造成200多万人死亡。虽然许多关于传染病的研究主要集中在分析其他健康个体的免疫力，但患有癌症等既往疾病的患者往往最容易受到影响。癌症及其治疗与免疫系统失调有关，癌症患者极易感染(如流感、SARS-CoV-2)。重要的是，癌症患者接种疫苗的反应往往很差。癌症患者免疫失调和免疫低下的分子和细胞机制是多方面的，在不同的患者/情况下是不同的，目前还不清楚。深入了解这些机制对于确定预防传染病的新战略和开发个性化治疗方法至关重要。在这个项目中，我将填补这一知识空白，并确定1)癌症如何操纵免疫系统，导致调节失调和疫苗反应不良；2)疫苗如何反过来长期影响调节失调的免疫系统。为了实现这一目标，我将使用多组学系统生物学方法，分析接种疫苗前后癌症患者的血液样本。我的研究利用了高分辨率免疫图谱技术，包括质量细胞术、单细胞转录组分析和表观基因组学分析。我将这些实验工具与机器学习驱动的、集成的、多层次的数据分析和功能验证分析相结合。最近，我成功地应用这种方法来确定人类感染SARS-CoV-2期间的免疫失调，并表明流感疫苗通过表观基因组机制对一系列病毒病原体提供了广泛的、非特异性的保护。这里提出的项目将为癌症患者有效接种疫苗提供1)可操作的免疫学目标，2)识别疫苗反应不良风险的生物标记物候选，以及3)深入了解疫苗对癌症患者免疫系统的持久、非特异性影响。这些见解将启发为癌症患者量身定做的新型疫苗和干预策略，以恢复免疫系统调节失调患者的有效免疫。从长远来看，我的愿景是开发协同方法，通过优化疫苗和癌症治疗之间的相互作用来提高对病原体和肿瘤的免疫力。艾美诺特项目的资金和支持网络将是实现这一愿景的关键。

Infectious diseases constitute a significant threat to global health and caused more than 2 million deaths worldwide in 2019. While much of the research on infectious diseases focuses primarily on analyzing immunity in otherwise healthy individuals, patients with preexisting medical conditions like cancer often suffer most. Cancer and its treatments are associated with dysregulated immune systems, and cancer patients are highly susceptible to infections (e.g., influenza, SARS-CoV-2). Importantly, cancer patients often respond poorly to vaccination. The molecular and cellular mechanisms underlying immune dysregulation and poor immunity in cancer patients are manifold, variable among individual patients/conditions, and currently not well understood. An in-depth understanding of these mechanisms is essential to identifying novel strategies to prevent infectious diseases and developing individualized therapies. In this project, I will fill this knowledge gap and determine 1) how cancer manipulates the immune system to cause dysregulation and poor vaccine responses and 2) how vaccines, in turn, affect the dysregulated immune system in the long term. To achieve this goal, I will use a multi-omics systems biology approach and analyze blood samples from cancer patients collected before and after vaccination. My research exploits high-resolution immune profiling technologies, including mass cytometry, single-cell transcriptomics, and epigenomics analyses. I combine these experimental tools with machine learning-driven, integrated, multilevel data analysis and functional validation assays. Recently, I applied this approach successfully to determine immune dysregulation during SARS-CoV-2 infection in humans and to show that influenza vaccines provide broad, nonspecific protection against a range of viral pathogens via epigenomic mechanisms. The project proposed here will provide 1) actionable, immunological targets for effective vaccination in cancer patients, 2) biomarker candidates identifying patients at risk of poor vaccine response, and 3) insights into the lasting, nonspecific impact of vaccines on cancer patients' immune systems. These insights will inspire novel vaccines tailored to cancer patients and intervention strategies to restore effective immunity in patients with dysregulated immune systems. In the longer term, my vision is to develop synergistic approaches that boost immunity against pathogens and tumors by, for instance, optimizing the interplay between vaccines and cancer treatments. The Emmy Noether program's funding and support network will be essential in realizing this vision.