An engineered platform to establish the role of interferon signaling in dormancy and chemoresistance

尽管护理标准有所改善，但卵巢癌患者的总体治愈率仍徘徊在40%左右，使其成为最致命的妇科恶性肿瘤。虽然大多数患者最初对化疗表现出一定的反应性，但20-30%的卵巢癌患者在完成治疗后6个月内复发。目前，没有方法在开始治疗之前预测患者对化疗的反应。有一种罕见的癌细胞亚群，可以在强烈的外部刺激下转变为暂时的休眠状态，从而逃避化疗。这些细胞可以在治疗结束后重新唤醒并发展成转移性疾病。该项目的主要目标是利用一种新型硅基材料来研究指导细胞进入休眠的信号机制，然后利用这些知识开发一种临床工具来识别化疗耐药风险增加的患者。该项目的结果可用于开发针对休眠癌细胞的更有效的治疗方法。除了科学探索，该项目还旨在通过促进与双子城地区代表性不足的K-12学生的接触来提高工程的多样性，公平性和包容性。该推广活动将包括各种工程主题的教育演讲和实践经验，包括癌症生物工程。一个新的，动手细胞封装活动也将开发和整合到现有的介绍组织工程外展模块提供多次通过科学与工程UMN学院每年夏天。该项目的主要目标是利用一个新的平台来确定干扰素信号传导在细胞休眠的诱导、维持和唤醒中的作用。具有休眠能力的癌细胞可以以暂时的非增殖状态存在，使它们能够逃避许多常见的化疗药物。干扰素是具有抗病毒和免疫调节功能的有效信号分子。最近，已经假设癌细胞中升高的干扰素信号传导有助于增加化学抗性。具有休眠能力的癌细胞也显示出显著的干扰素信号传导激活的证据。本项目的第一个目标是利用一种新的封装平台，以确定精确的干扰素刺激的信号轴促进休眠。基因敲除将用于评估特定干扰素刺激的转录调节因子对休眠诱导和化学抗性的贡献。该项目的第二个目标是开发一种预后工具，可用于预测患者对化疗的反应。先前的工作表明，硅胶中的固定选择了癌细胞的化学抗性亚群。将对卵巢癌患者进行一项回顾性研究，以评估硅胶固定作为识别化疗耐药风险患者的方法的预后潜力。同时，将利用机制研究的结果，结合机器学习技术，从患者肿瘤的单细胞测序数据中生成干扰素相关的预后基因特征。这些结果将促进对癌细胞休眠的理解，并为卵巢癌患者的分层制定新的策略，为治疗决策提供信息。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Despite improvements to the standard of care, the overall cure rate for ovarian cancer patients has stagnated at around 40%, making it the most lethal gynecologic malignancy. While most patients initially show some responsiveness to chemotherapy, 20-30% of ovarian cancer patients experience recurrence within 6 months of the completion of treatment. Currently, there is no method to predict a patient’s response to chemotherapy prior to initiating treatment. There is a rare subpopulation of cancer cells that can transition into a temporary dormant state in response to harsh external cues, allowing them to evade chemotherapy. These cells can then reawaken after treatment has concluded and develop into metastatic disease. The main goals of this project are to utilize a novel silica-based material to investigate the signaling mechanisms directing cells to enter dormancy, and then use this knowledge to develop a clinical tool to identify patients at increased risk for chemoresistance. The results from this project could be used to inform the development of more effective therapeutics to target dormant cancer cells. Beyond scientific exploration, this project also aims to improve diversity, equity, and inclusion in engineering by promoting engagement with underrepresented K-12 students in the Twin Cities area. This outreach will include educational presentations and hands-on experiences on various engineering topics, including cancer bioengineering. A new, hands-on cell encapsulation activity will also be developed and integrated into an existing Introduction to Tissue Engineering outreach module offered multiple times each summer through the UMN College of Science and Engineering. The main goal of this project is to leverage a novel platform to determine the role of interferon signaling on the induction of, sustenance of, and awakening from cellular dormancy. Dormancy-capable cancer cells can exist in a temporary, non-proliferative state, allowing them to evade many common chemotherapeutics. Interferons are potent signaling molecules with known antiviral and immunomodulatory functions. Recently, elevated interferon signaling in cancer cells has been hypothesized to contribute to increased chemoresistance. Dormancy-capable cancer cells also show evidence of significant interferon signaling activation. The first objective of this project is to utilize a novel encapsulation platform to identify the precise interferon-stimulated signaling axes promoting dormancy. Genetic knockdowns will be used to evaluate the contribution to dormancy induction and chemoresistance of specific interferon-stimulated transcriptional regulators. The second objective of this project is to develop a prognostic tool that could be used to predict a patient’s response to chemotherapy. Previous work has shown that immobilization in silica gel selects for a chemoresistant subpopulation of cancer cells. A retrospective study of ovarian cancer patients will be performed to assess the prognostic potential of silica gel immobilization as a method for identifying patients at risk of chemoresistance. In parallel, results from the mechanistic investigation will be leveraged, in conjunction with machine learning techniques, to generate an interferon-related prognostic gene signature from single cell sequencing data of patient tumors. These results will advance the understanding of cancer cell dormancy and develop new strategies for stratifying ovarian cancer patients to inform treatment decisions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.