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

尽管护理标准有所提高，但卵巢癌患者的总体治愈率仍停留在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有一定的反应，但20%-30%的卵巢癌患者在完成治疗后6个月内复发。目前，还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，可以在恶劣的外部信号下转变为临时休眠状态，从而使它们能够逃避化疗。这些细胞可以在治疗结束后重新唤醒，并发展为转移性疾病。该项目的主要目标是利用一种新型的硅基材料来研究引导细胞进入休眠的信号机制，然后利用这一知识开发一种临床工具来识别化疗耐药风险增加的患者。该项目的结果可能被用来为开发更有效的针对休眠癌细胞的治疗方法提供信息。除了科学探索，该项目还旨在通过促进双子城地区代表不足的K-12学生的参与来提高多样性、公平性和工程学包容性。这一推广活动将包括各种工程主题的教育报告和实践经验，包括癌症生物工程。还将开发一项新的动手细胞封装活动，并将其整合到每年夏天通过密歇根大学科学与工程学院多次提供的现有组织工程导论扩展模块中。这个项目的主要目标是利用一个新的平台来确定干扰素信号在细胞休眠的诱导、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、非增殖的状态存在，使它们能够逃避许多常见的化疗药物。干扰素是一种强大的信号分子，具有已知的抗病毒和免疫调节功能。最近，肿瘤细胞中干扰素信号的升高被认为是导致化疗耐药性增加的原因。能够休眠的癌细胞也显示出显著的干扰素信号激活的证据。该项目的第一个目标是利用一种新的封装平台来识别促进休眠的干扰素刺激的精确信号轴。基因敲除将被用来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可用于预测患者对化疗反应的预后工具。以前的工作表明，硅胶中的固定化选择了对化疗耐药的癌细胞亚群。将对卵巢癌患者进行一项回顾性研究，以评估硅胶固定化作为一种识别化疗耐药风险患者的方法的预后潜力。同时，机械研究的结果将与机器学习技术相结合，从患者肿瘤的单细胞测序数据中产生与干扰素相关的预后基因签名。这些结果将促进对癌细胞休眠的理解，并开发新的策略来对卵巢癌患者进行分层，以便为治疗决策提供信息。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.